Multimodal signal acquisition synchronized by a universal clock

Abstract

On multimodal signal acquisition synchronized by a universal clock. [Solution] [0003] Embodiments described herein relate to a process for multimodal signal acquisition, for example from a charged particle device or other scientific instrument, based on universal clock synchronization of various multimodal signals. The system may include a memory that stores computer-executable components and a processor that executes the computer-executable components stored in the memory, the computer-executable components including an identification component that identifies a set of inputs and outputs of the scientific instrument, and a parameterization component that tracks the set of inputs and outputs based on a universal clock common to the set of inputs and outputs.

Description

[Technical Field]

[0001] The present invention relates to multimodal signal acquisition synchronized by a universal clock. [Background technology]

[0002] Scientific experiments can involve acquiring input and output signals based on various timelines and other tracking methods, e.g., based on location in two-dimensional or three-dimensional space. Analysis of these various signals, including, for example, comparing signals using different timelines and / or tracking methods, can be a challenging process due to gaps in the data, jumps in tracking methods due to environmental disturbances, and / or a lack of relationships between tracking methods. As a result, the aggregated signal acquisition set can resemble a complex tangle of data, where relationships can be difficult and / or impossible to determine. [Brief explanation of the drawings]

[0003] Embodiments will be readily understood from the following detailed description taken in conjunction with the accompanying drawings, in which: To facilitate this description, like reference numerals refer to like structural elements; and Embodiments are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings. [Figure 1] 1 illustrates a block diagram of an example scientific instrument for performing one or more operations according to one or more embodiments described herein. [Figure 2] 2 illustrates a flow diagram of an example method of performing operations using the scientific instrument of FIG. 1 according to one or more embodiments described herein. [Figure 3] 1 illustrates a graphical user interface (GUI) that can be used in performing one or more of the methods described herein, according to one or more embodiments described herein. [Figure 4]1 illustrates a block diagram of an example computing device capable of performing one or more of the methods disclosed herein, in accordance with one or more embodiments described herein. [Figure 5] 1 illustrates a block diagram of an example non-limiting system that can facilitate a process for tracking input and output signal acquisition in accordance with one or more embodiments described herein. [Figure 6] 1 illustrates a block diagram of another exemplary non-limiting system that can facilitate a process for tracking input and output signal acquisition in accordance with one or more embodiments described herein. [Figure 7] 7 illustrates a flow diagram of a signal acquisition workflow that may be obtained by the non-limiting system of FIG. 6, according to one or more embodiments described herein. [Figure 8] 7 illustrates a flow diagram of a signal acquisition and tracking workflow that may be performed by the non-limiting system of FIG. 6 according to one or more embodiments described herein. [Figure 9] 7 illustrates another flow diagram of a signal acquisition and tracking workflow that may be performed by the non-limiting system of FIG. 6 according to one or more embodiments described herein. [Figure 10] 6 illustrates a flow diagram of one or more processes that may be performed by the signal tracking system of FIG. 5 according to one or more embodiments described herein. [Figure 11] 7 illustrates another flow diagram of one or more processes that may be performed by the signal tracking system of FIG. 6 according to one or more embodiments described herein. [Figure 12] 12 illustrates a continuation of the flow diagram of FIG. 11 of one or more processes that may be performed by the signal tracking system of FIG. 6 according to one or more embodiments described herein. [Figure 13] 1 illustrates a block diagram of an example scientific instrument system capable of performing one or more of the methods described herein, according to one or more embodiments described herein. [Figure 14] 1 illustrates a block diagram of an exemplary operating environment into which embodiments of the subject matter described herein may be incorporated. [Figure 15] 1 illustrates an exemplary schematic block diagram of a computing environment with which the subject matter described herein can at least partially interact and / or be implemented. DETAILED DESCRIPTION OF THE INVENTION

[0004] overview The following presents a summary to provide a basic understanding of one or more embodiments described herein. This summary is not intended to identify key or critical elements and / or delineate the scope of particular embodiments or the claims. Its sole purpose is to present concepts in a simplified form as a prelude to the more detailed description that is presented later. In one or more embodiments, the systems, computer-implemented methods, apparatuses, and / or computer program products described herein can provide a plug-and-play process for generating identifiers and / or updating a library data store with such identifiers based at least in part on an annotation ranking schema.

[0005] According to one embodiment, a system may include a memory that stores computer-executable components and a processor that executes the computer-executable components stored in the memory, the computer-executable components including an identification component that identifies a set of inputs and outputs of a scientific instrument, and a parameterization component that tracks the set of inputs and outputs based on a universal clock that is common to the set of inputs and outputs.

[0006] According to another embodiment, a computer-implemented method may include identifying, by a system operably coupled to a processor, a set of inputs and outputs of a scientific instrument; and tracking, by the system, the inputs and outputs of the set based on a universal clock that is common to the inputs and outputs of the set.

[0007] According to yet another embodiment, a computer program product facilitates a process for tracking inputs and outputs of a scientific device, the computer program product comprising a computer-readable storage medium having program instructions embodied thereon, the program instructions being executable by a processor to cause the processor to identify, by the processor, a set of inputs and outputs of the scientific instrument, and to cause the processor to track, by the processor, the inputs and outputs of the set based on a universal clock common to the inputs and outputs of the set.

[0008] One or more embodiments described herein may be implemented within, in association with, and / or coupled to a scientific imaging device or other scientific instrument, such as a charged particle device.

[0009] One or more embodiments described herein can be employed with a variety of (e.g., multimodal) signal types, including, but not limited to, stimulation, detection, scanning, optical, magnetic, electrical phase transition, and / or dynamic excitation. Each of these signal types can employ a universal clock, thus allowing the inputs and / or outputs of these signal types to be tracked and analyzed relative to one another without data loss, time conversion, etc. Furthermore, environmental disturbances that cause changes in XY position due to, for example, physical instability, bumps, vibrations, etc., do not alter such a clock because the universal clock is not based solely on XY position.

[0010] As a result, the parameters can be easily ordered relative to one another, thus enabling identification of one or more interference frequencies in the environment that perturb another signal, such as an image output signal, and isolation of such one or more interference frequencies.

[0011] In one or more cases, based on one or more embodiments described herein, one or more experiment types can be performed that cannot be performed using existing frameworks. For example, simultaneous measurements and critical dose measurements can benefit from the signal comparison provided by using a common universal clock and the lack of signal tracking loss (e.g., from tracking continuously acquired signals using XY position, as in existing frameworks).

[0012] In one or more cases, based on using one or more embodiments described herein, reduced storage space and bandwidth can be employed for storing and recording signals due to the ability to omit recording XY position outputs corresponding to beam blanking.

[0013] One or more embodiments described herein can be applied on a plug-and-play basis to various architectures of existing scientific instruments, signal acquisition equipment, etc. For example, areas / fields of catalysis, metallurgy, ceramics, magnetic phase transitions, electrical phase transitions, optical stimulation, and / or liquid cell research are among those that can benefit from a process for tracking the inputs and outputs of scientific devices against a common universal clock.

[0014] Detailed Description The following detailed description is merely illustrative and is not intended to limit the embodiments and / or their application or uses. Furthermore, there is no intention to be bound by any expressed or implied information presented in the Summary of the Invention section or the Detailed Description section above. One or more embodiments will now be described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a more thorough understanding of one or more embodiments. It will be apparent, however, that in various instances, one or more embodiments may be practiced without these specific details.

[0015] Various operations may be described sequentially as multiple discrete actions or operations in a manner that is most helpful for understanding the subject matter disclosed herein. However, the order of description should not be construed as implying that these operations are necessarily order dependent. In particular, these operations may be performed in an order different from the order presented. Operations described may be performed in an order different from the described embodiment. Various additional operations may be performed and / or described operations may be omitted in additional embodiments.

[0016] Turning now to the general subject of signal acquisition, such processes may be performed in multiple experimental, information gathering, monitoring, industrial, manufacturing, and / or other scientific processes. Often, it is desirable to acquire multiple different signal types at least partially in parallel with one another. Such signal types may include, but are not limited to, stimulus, detection, scanning, optical, magnetic, electric phase transition, and / or dynamic excitation signals. These signals may be analyzed offline (e.g., separate from the performance of the respective process, experiment, etc.) and / or online (e.g., during the performance of the respective process, experiment, etc.).

[0017] Part of such analysis may include a desired comparison of different signals occurring simultaneously for the same location. This analysis may be difficult due to signal loss, signal jumps, and / or incomparable reference points (e.g., timelines and other tracking methods). For example, different tracking methods, and even different timelines, may have unknown time jumps, tracking jumps, data loss, etc. In one or more cases, environmental disturbances, such as vibrations, bumps, etc., may affect signal acquisition, causing changes in the acquired signal and / or the reference tracking employed. These occurrences may make comparisons between different signal types difficult, if not outright impossible, and may require undesirable amounts of bandwidth, time, power, and / or effort.

[0018] One such example is a scanning transmission electron microscope. This can include image acquisition using a transmission electron microscope (STEM) or other scientific imaging device. Operation of such a STEM device can include acquiring signals related to stimulation, detection, scanning, optics, etc., based on different timelines, XY positions, and / or other tracking methods. These signal types can be acquired at least partially simultaneously with one another. However, various signal sets may be asynchronous and unlinked. Therefore, event documentation may be difficult due to the above-mentioned deficiencies. For example, vibration may cause movement of X position, Y position, or XY position (e.g., either or both X and Y positions). Therefore, one signal type may be based on XY position, and another may be based on consecutive time point acquisition. As a result, data ordering based on the acquired signals may be difficult due to the time-invariant but unstable XY positions. Furthermore, correlation errors may be introduced into artifact compensation and / or dynamic behavior analysis based on the signals / data obtained therefrom.

[0019] These correlation errors can be difficult to distinguish and / or filter out. In one or more cases, such correlation errors can go unrecognized and result in inaccurate data. In one or more cases, such correlation errors can cause lost data, inconsistent signal / data correlation, and / or an inability to align signals / data with one another. In one or more cases, such correlation errors can contribute to an undesirable amount of bandwidth, time, power, and / or effort associated with event documentation and / or dynamic experiment setup. Indeed, such correlation errors can make such dynamic experiments difficult to reproduce.

[0020] Another such example may involve dynamic excitation via a laser, where a holder or other device positioned in the electron beamline may employ a clock separate from the excitation clock employed to monitor excitation and monitor variations in stimulus parameters in time. Phase-locked experiments may be impossible due to the unlinking of the respective timelines. As a result, events on the illumination side of such an experiment are not linked in time with events on the detection side of the experiment.

[0021] In other words, a STEM scanning experiment can involve sequential acquisition of visited scan points and sequential acquisition in space and time by accessing the scan points at a series of time points. This can mean that at least the XY positions are different from other dynamically changing optical aspects (e.g., deflectors, blankers, stimuli, etc.), and therefore the detected signals may not be linked. As a result, it may be impossible or undesirably difficult to time-stamp the data obtained from the signals with events. To enable such time-stamping, the various signals must be synchronized into an event stream. This can result in sequencing parameters that can change due to environmental disturbances to the experiment and / or the system operating the experiment.

[0022] To address one or more deficiencies in such existing frameworks, one or more embodiments are described herein that can provide improved accuracy and / or efficiency of data correlation based on various types of multimodal signal acquisition. The various signals may be based on various timelines, clocks, and / or other tracking methods, but may be synchronized to a single or common universal clock by one or more embodiments described herein.

[0023] That is, a STEM scanning experiment addressed by one or more embodiments described herein can include sequential acquisition of visited scan points and sequential acquisition in space and time by accessing scan points at a series of time points. Based on the use of a common universal clock and not using XY positions as a tracking method, XY positions can be time-stamped with events, as can other dynamically changing optical aspects (e.g., deflectors, blankers, stimuli, etc.). To enable such stamping, various signals can be synchronized into an event stream based on a common universal clock. This can include stamping XY positions (e.g., parameterizing XY positions) with timestamps similar to signals from detectors, active blankers, and / or ultrafast cavity components. As a result, ordering parameters can be employed that are time-invariant and therefore invariant to environmental disturbances like traditional XY positions, which may differ due to their instability.

[0024] In one or more cases, five-dimensional (5D) space can be generated in static experiments for beam X position or beam Y position by time-stamping every event. The 5D space in static experiments can further include an energy-dispersive X-ray energy loss spectrum (e.g., about 0-40 keV) or an electron energy loss spectrum (e.g., about 0-40 keV), expressed as dE. The 5D space in static experiments can further include electrons detected below the sample at different scattering angles kx and ky, such as within a range of 0-300 milliradian half angles. Additionally and / or alternatively, the dimensionality of the stamped space can be increased by detecting backscattered and / or secondary electrons and cathodoluminescence signals above the sample. Additionally and / or alternatively, a seventh-dimensional space can be generated, including electron-without-electron and stimulus dynamics in non-static experiments.

[0025] One or more benefits may include better software and / or hardware instability compensation of multimodal signals, with or without the use of artificial intelligence analysis. As used herein, the term "multimodal" refers to having various types of signals or other tracked data, also referred to herein as signals. Examples may include, but are not limited to, stimulation, optical, scanning, detection and / or excitation signals and / or XY position.

[0026] For example, in connection with better software instability compensation, having the time axis as a reference for the signal of a STEM image or a map of a spectral signal may enable searching for environmental interference frequencies that perturb the image, allowing separation of such interference frequencies from the desired signal. Environmental disturbances and / or interference frequencies may include, but are not limited to, drift in time of the energy axis (EELS), drift, vibration, and / or fixed frequencies in real space (e.g., X & position artifacts). Frequencies in energy space can be found back in real space, and correlation may allow better frequencies to be identified for software compensation, taking into account one or more embodiments described herein.

[0027] As another example, in connection with better hardware instability compensation, when scanning at the highest speed of the scanning unit, the dwell time per pixel can be defined by how often the pixel is accessed. The time series of signals within a pixel, when analyzed, can provide information about damage and / or scanning artifacts. Note that when using a variable dwell time, only one time point is provided, making this analysis impossible. Using existing frameworks, compensation can be performed for the entire frame, which can compensate for drift but not frequency (flagging) or sample degradation (damage). In contrast, using one or more embodiments described herein and using the fastest dwell time to distribute energy more evenly, this can be addressed by synchronous tracking. Additionally and / or alternatively, temperature gradients, damaging electron (charging) gradients, and / or scanning artifacts can be addressed by synchronous tracking.

[0028] Additionally and / or alternatively, one or more other benefits may include the ability to correlate a variety of different types of signals (e.g., correlate multimodal signals), lack of impact of environmental disturbances on acquired signals, the ability to easily isolate undesired frequencies, the ability to employ new types of dynamic experiments, the ability to employ the systems described herein with a variety of signal acquisition frameworks (e.g., a variety of different hardware, software, and / or firmware), applying one or more embodiments described herein to multiple different industries, and / or a reduction in the time, energy, memory, and / or bandwidth employed in signal acquisition due to non-recording of signals / data points corresponding to beam blanking.

[0029] The discussion now turns to a general discussion of one or more scientific instrument systems, and associated methods, computing devices, and / or computer-readable media disclosed herein. For example, in one or more embodiments, a system may include a memory that stores computer-executable components and a processor that executes the computer-executable components stored in the memory, the computer-executable components including an identification component that identifies a set of inputs and outputs of the scientific instrument, and a parameterization component that tracks the set of inputs and outputs based on a universal clock that is common to the set of inputs and outputs.

[0030] One or more embodiments disclosed herein, as described above, can achieve improved performance compared to existing approaches. For example, based on the application of a common universal clock to track XY position and other acquired signals (e.g., acquired multimodal signals), this can allow the inputs and / or outputs of these signal types to be tracked and analyzed relative to one another without data loss, time conversion, etc. Furthermore, environmental disturbances that cause changes in XY position due to, for example, physical instability, bumps, vibrations, etc., do not alter the universal clock because such clock is not based solely on XY position.

[0031] Thus, embodiments disclosed herein can provide improvements in scientific instrument technology (e.g., improvements in the computer technology supporting such scientific instrumentation, among other improvements), which can be employed in sample analysis in a variety of fields, including, but not limited to, optics, signal processing, spectroscopy (e.g., electron energy loss spectroscopy, mass spectroscopy, or electron spectroscopy), microscopy (e.g., electron microscopy, transmission electron microscopy, or scanning transmission electron microscopy), and / or nuclear magnetic resonance (NMR). Other applicable fields can include, but are not limited to, those related to catalysis, metallurgy, ceramics, magnetic phase transitions, electrical phase transitions, optical stimulation, and / or liquid cell research.

[0032] Various embodiments disclosed herein may improve upon existing techniques to achieve the technical advantage of high-information and / or accurate information analysis based on multimodal signal acquisition capable of obtaining such information. That is, one or more embodiments described herein may provide for parameterization of various signal inputs and / or outputs of the same experiment, operation, and / or process, allowing for the identification of one or more interference frequencies in the environment that perturb another signal, such as an image output signal, and the isolation of such one or more interference frequencies.

[0033] In one or more cases, based on one or more embodiments described herein, one or more experiment types can be performed that cannot be performed using existing frameworks. For example, simultaneous measurements and critical dose measurements can benefit from the signal comparison provided by using a common universal clock and the lack of signal tracking loss (e.g., from tracking continuously acquired signals using XY position, as in existing frameworks).

[0034] In one or more cases, based on using one or more embodiments described herein, reduced storage space and bandwidth can be employed for storing and recording signals due to the ability to omit recording XY position outputs corresponding to beam blanking.

[0035] One or more embodiments described herein may be applied on a plug-and-play basis to a variety of architectures of existing scientific instruments, signal acquisition equipment, and the like.

[0036] These may be useful applications and / or processes for a variety of industries employing materials analysis, product manufacturing, quality control, etc. Accordingly, embodiments disclosed herein may provide improvements to scientific instrumentation technology (e.g., improvements to the computer technology supporting such scientific instrumentation, among other improvements).

[0037] Such technical advantages, as described above, are not achievable by routine and existing techniques, and all user entities of a system including such embodiments can benefit from these advantages (e.g., by assisting the user entities in performing technical tasks, such as cross-modal information analysis based on multimodal signal acquisition).

[0038] Thus, the technical features of the embodiments disclosed herein (e.g., application of a common universal clock, time stamping according to the common universal clock, identification of interference frequencies, etc.), as well as combinations of the features of the embodiments disclosed herein, are clearly unconventional in signal acquisition for the general field of materials analysis, in addition to, but not limited to, the fields of optics, signal processing, spectroscopy, and / or NMR.

[0039] As discussed further herein, various aspects of the embodiments disclosed herein can improve the functionality of the computer itself. That is, the computational and / or user interface features disclosed herein do not solely involve the collection and / or comparison of information, but instead can apply new analytical and technological techniques to modify the operation of computer analysis of material compounds. For example, when a common universal clock is employed, it can become more efficient and accurate over time to enable the generation and application of timestamps that can be correlated with each other without variance due to environmental influences, comparisons to determine relationships between acquired signals, event determination based on multimodal signals, etc., as may be performed by classical computers and / or one or more artificial intelligences employing the results of one or more embodiments described herein. That is, when signals are acquired and synchronized according to a common universal clock, without using variable XY positions as a synchronization element, but rather by synchronizing XY positions along with other inputs and outputs, greater and more accurate comparative data is generated for use in exploration, querying, event determination, signal comparison, and other analyses performed on various multimodal signals synchronized in one or more embodiments described herein. Thus, one or more of the non-limiting systems described herein, including the signal tracking system, may be self-improving, as described herein.

[0040] Thus, the present disclosure introduces functionality that neither existing computing devices nor humans can perform. Rather, such existing computing devices are ineffective at analyzing multimodal acquired signal data and / or synchronizing multimodal signals, including continuous tracking of XY position, without having to consider XY position variance and / or environmental disturbance data, as one or more embodiments described herein can provide for this process. Given the associated time, energy, and / or data loss, it is impractical to operate within existing approaches.

[0041] Accordingly, embodiments of the present disclosure may serve any of a number of technical purposes, such as controlling a particular technical system or process, determining how to control machinery from measurements, digital audio, image, or video augmentation or analysis, separating material sources in mixed signals, generating data for reliable and / or efficient transmission or storage, providing estimates and confidence intervals for material samples, or providing faster processing of sensor data. In particular, the present disclosure provides technical solutions to technical problems, including but not limited to, hologram correction, image / signal blurring, applying combined blurring techniques, and / or subsequent image reconstruction, resulting in faster, more complete, and / or more efficient processing of the generated image and, therefore, the imaged material sample or other target composition.

[0042] Accordingly, the embodiments disclosed herein provide improvements in materials analysis techniques (eg, improvements in computer techniques supporting materials analysis, among other improvements).

[0043] As used herein, the phrase "based on" should be understood to mean "based at least in part on," unless otherwise specified.

[0044] As used herein, the term "component" can refer to an atomic element, a molecular element, a phase of an atomic or molecular element, or a combination thereof.

[0045] As used herein, the term "data" can include metadata.

[0046] As used herein, the terms “entity,” “requesting entity,” and “user entity” may refer to a machine, device, component, hardware, software, smart device, party, organization, individual, and / or human being.

[0047] As used herein, the term "sample" can refer to a single material, multiple materials, a composition, a compound, a solution, a product, and the like.

[0048] As used herein, the term "signal" may refer to input and / or output communication, transmission, reading, etc., provided in any suitable form, including, but not limited to, digital data, electrical, fiber optic, magnetic, optical, light, audible, sound, vibratory, and / or tactile.

[0049] One or more embodiments will now be described with reference to the drawings, wherein like reference numerals are used to refer to like drawing elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a more thorough understanding of one or more embodiments. It will be apparent, however, that in various instances, one or more embodiments may be practiced without these specific details.

[0050] Furthermore, it should be understood that the embodiments depicted in one or more figures described herein are for illustrative purposes only, and thus the architecture of the embodiments is not limited to the systems, devices, and / or components depicted herein, nor to any particular ordering, connection, and / or coupling of the systems, devices, and / or components depicted herein.

[0051] Referring now particularly to one or more figures, initially to FIG. 1 , a block diagram of a scientific instrument module 100 for performing material analysis operations using a signal tracking process is illustrated, according to various embodiments described herein. The scientific instrument module 100 may be implemented by circuitry (e.g., including electrical and / or optical components) such as a programmed computing device. The logic of the scientific instrument module 100 may be contained in a single computing device or may be distributed across multiple computing devices that communicate with each other as needed. An example of a computing device in which the scientific instrument module 100, alone or in combination, may be implemented is discussed herein with reference to the computing device 400 of FIG. 4 , and an example of a system of interconnected computing devices in which the scientific instrument module 100 may be implemented across one or more of the computing devices is discussed herein with reference to the scientific instrument system 1300 of FIG. 13 .

[0052] The scientific instrument module 100 may include first logic 102, second logic 104, third logic 106, and fourth logic 108. As used herein, the term "logic" may include an apparatus that performs a set of operations associated with the logic. For example, any of the logic elements included in the module 100 may be implemented by one or more computing devices programmed with instructions to cause one or more processing devices of the computing devices to perform a set of operations associated with the computing devices. In particular embodiments, a logic element may include one or more non-transitory computer-readable media having instructions that, when executed by one or more processing devices of the one or more computing devices, cause the one or more computing devices to perform a set of operations associated with the computing devices. As used herein, the term "module" may refer to a collection of one or more logic elements that together perform a function associated with the module. Different logic elements within a module may take the same form or different forms. For example, some logic within a module may be implemented by a programmed general-purpose processing device, while other logic within the module may be implemented by an application-specific integrated circuit (ASIC). In another example, different ones of the logic elements in a module may be associated with different sets of instructions executed by one or more processing devices. A module may omit one or more of the logic elements depicted in the associated figure, but, for example, a module may include a subset of the logic elements depicted in the associated figure if the module performs a subset of the operations discussed herein with reference to that module.

[0053] The first logic 102 may receive, discover, locate, download, request, measure, and / or otherwise determine a set of signals and, therefore, a set of inputs and outputs (e.g., data and / or metadata) corresponding to the set of signals, i.e., the first logic 102 may obtain data to be processed and for later use in generating timestamps and / or performing signal comparisons.

[0054] The second logic 104 may generally perform a data time stamping process by time stamping inputs and outputs with timestamps based on data output from a universal clock, i.e., the second logic 104 may employ the output of the first logic 102 as a trigger for the second logic 104.

[0055] Specifically, the third logic 106 can track the inputs and outputs according to the universal clock and based on the timestamps output from the second logic 104 by filtering out interfering frequencies among the inputs and outputs that correspond to the interfering outputs. That is, the third logic 106 can employ the output of the second logic 104 to execute the third logic 106.

[0056] The fourth logic 108 can analyze the data output from the universal clock and, among other things, synchronize another clock to the universal clock.

[0057] 2 illustrates a flow diagram of a method 200 of performing operations by a scientific instrument module 100, according to various embodiments. The operations of method 200 may be illustrated with reference to particular embodiments disclosed herein (e.g., the scientific instrument module 100 discussed herein with reference to FIG. 1 , the GUI 300 discussed herein with reference to FIG. 3 , the computing device 400 discussed herein with reference to FIG. 4 , and / or the scientific instrument system 1300 discussed herein with reference to FIG. 13 ), but method 200 may be used in any suitable configuration to perform any suitable operations. Although the operations are illustrated in FIG. 2 once each and in a particular order, the operations may be reordered and / or repeated as desired and appropriate (e.g., different operations performed may be performed in parallel when suitable).

[0058] A first operation may be performed at 202. For example, the first logic 102 of the module 100 may perform the first operation 202. The first operation 202 may include receiving, discovering, locating, downloading, requesting, measuring, and / or otherwise determining a set of signals and, therefore, a set of inputs and outputs (e.g., data and / or metadata) corresponding to the set of signals.

[0059] A second operation may be performed at 204. For example, the second logic 104 of the module 100 may perform the second operation 204. The second operation 204 may include using data output from the universal clock compared to metadata associated with the inputs and outputs to generate and apply timestamps to the inputs and outputs according to the universal clock.

[0060] A third operation may be performed at 206. For example, the third logic 106 of the module 100 may perform the third operation 206. The third operation 206 may include analyzing the input and output according to the timestamps to determine interference frequency outputs corresponding to interference that at least partially overlaps with the imaging output, and filtering out undesired interference frequency outputs.

[0061] A fourth operation may be performed at 208. For example, the fourth logic 108 of the module 100 may perform the fourth operation 208. The fourth operation 208 may include analyzing data output from the universal clock to synchronize another clock, such as an excitation clock, to the universal clock.

[0062] Scientific instrument methods disclosed herein can include interactions with a user entity (e.g., via a user local computing device 1320, discussed herein with reference to Figure 13). These interactions can include providing information to the user entity (e.g., information regarding the operation of a scientific instrument such as the scientific instrument 1310 of Figure 13, information regarding a sample being analyzed or other tests or measurements performed by the scientific instrument, information obtained from a local or remote database, or other information), or providing options for the user entity to enter commands (e.g., to control the operation of a scientific instrument such as the scientific instrument 1310 of Figure 13 or to control the analysis of data generated by the scientific instrument), queries (e.g., to a local or remote database), or other information. In some embodiments, these interactions may be performed through a graphical user interface (GUI) that includes a visual display on a display device (e.g., display device 410, discussed herein with reference to FIG. 4 ) that provides output to a user entity and / or prompts the user entity to provide input (e.g., via one or more input devices, such as a keyboard, mouse, trackpad, or touchscreen included in other I / O devices 412, discussed herein with reference to FIG. 4 ). The scientific instrument system 1300 disclosed herein may include any suitable GUI for interaction with a user entity.

[0063] 3, an exemplary GUI 300 is depicted that may be used in performing one or more of the methods described herein, according to various embodiments described herein. As noted above, the GUI 300 may be provided on a display device (e.g., the display device 410 discussed herein with reference to FIG. 4) of a computing device (e.g., the computing device 400 discussed herein with reference to FIG. 4) of a scientific instrument system (e.g., the scientific instrument system 1300 discussed herein with reference to FIG. 13), and a user entity may interact with the GUI 300 using any suitable input device (e.g., any of the input devices included in the other I / O devices 412 discussed herein with reference to FIG. 4) and input technique (e.g., cursor movement, motion capture, facial recognition, gesture detection, voice recognition, button actuation, etc.).

[0064] GUI 300 can include a data display area 302, a data analysis area 304, a scientific instrument control area 306, and a settings area 308. The particular number and arrangement of areas depicted in Figure 3 is merely illustrative, and any number and arrangement of areas containing any desired features can be included in GUI 300.

[0065] The data display area 302 may display data generated by a scientific instrument (e.g., the scientific instrument 1310 discussed herein with reference to FIG. 13). For example, the data display area 302 may display one or more output results, which may include, but are not limited to, one or more of timing, signal frequency, input, output, timestamp, etc.

[0066] The data analysis area 304 can display the results of a data analysis (e.g., the results of analyzing the data illustrated in the data display area 302 and / or other data). For example, the data analysis area 304 can display one or more analyses comparing pairs of signals based on their respective timestamps. In one or more embodiments, the data display area 302 and the data analysis area 304 can be combined in the GUI 300 (e.g., to include data output from scientific instruments and several analyses of the data in a common graph or area).

[0067] The scientific instrument control area 306 may include options that allow a user entity to control a scientific instrument (e.g., the scientific instrument 1310 discussed herein with reference to FIG. 13). For example, the scientific instrument control area 306 may include one or more controls for customizing the amount of data that is analyzed (e.g., the number of signals, the range of frequencies, the time range of the signals, etc.).

[0068] Settings area 308 may include options that enable a user entity to control features and functionality of GUI 300 (and / or other GUIs) and / or perform common computing operations related to data display area 302 and data analysis area 304 (e.g., saving data on a storage device such as storage device 404 discussed herein with reference to FIG. 4 , transmitting data to another user entity, labeling data with a timestamp, etc.). For example, settings area 308 may include one or more options for changing the color, fill, or format of an illustrative diagram, such as an illustrative diagram of one or more signals acquired and tracked.

[0069] As noted above, the scientific instrument module 100 can be implemented by one or more computing devices. Accordingly, considering now FIG. 4, FIG. 4 illustrates a block diagram of a computing device 400 capable of performing some or all of the scientific instrument methods disclosed herein, according to various embodiments. In one or more embodiments, the scientific instrument module 100 can be implemented by a single computing device 400 or by multiple computing devices 400. Furthermore, as discussed below, the computing device 400 (or multiple computing devices 400) implementing the scientific instrument module 100 can be part of one or more of the scientific instrument 1310, user local computing device 1320, service local computing device 1330, or remote computing device 1340 of FIG. 13.

[0070] 4 is illustrated as having several components, any one or more of which may be omitted or duplicated as suitable for the application and configuration. As illustrated, these components may include one or more of a processor 402, a storage device 404, an interface device 406, a battery / power circuitry 408, a display device 410, and other input / output (I / O) devices 412, as described below.

[0071] In one or more embodiments, one or more of the components included in computing device 400 may be mounted on one or more motherboards and housed within a housing (e.g., comprising plastic, metal, and / or other materials). In one or more embodiments, some of these components may be fabricated on a single system-on-a-chip (SoC) (e.g., an SoC may include one or more processors 402 and one or more storage devices 404). Additionally, in one or more embodiments, computing device 400 may omit one or more of the components illustrated in FIG. 4. In one or more embodiments, computing device 400 may include interface circuitry (not shown) for coupling to one or more components using any suitable interface (e.g., a Universal Serial Bus (USB) interface, a High-Definition Multimedia Interface (HDMI®) interface, a Controller Area Network (CAN) interface, a Serial Peripheral Interface (SPI) interface, an Ethernet interface, a wireless interface, or any other suitable interface). For example, computing device 400 may omit display device 410 but may include display device interface circuitry (eg, connector and driver circuitry) to which display device 410 can be coupled.

[0072] Computing device 400 may include a processor 402 (e.g., one or more processing devices). As used herein, the term "processing device" may refer to any device or portion of a device that processes electronic data from registers and / or memory and converts the electronic data into other electronic data that can be stored in registers and / or memory. Processor 402 may include one or more digital signal processors (DSPs), application specific integrated circuits (ASICs), central processing units (CPUs), graphics processing units (GSMUs), or other processors. This may include a graphics processing unit (GPU), a cryptographic processor (a dedicated processor that executes cryptographic algorithms in hardware), a server processor, or any other suitable processing device.

[0073] The computing device 400 may include a storage device 404 (e.g., one or more storage devices). The storage device 404 may include random access memory (RAM) (e.g., static RAM). The storage device 404 may include one or more memory devices, such as static RAM (SRAM) devices, magnetic RAM (MRAM) devices, dynamic RAM (DRAM) devices, resistive RAM (RRAM) devices, or conductive-bridging RAM (CBRAM) devices, hard-drive-based memory devices, solid-state memory devices, network drives, cloud drives, or any combination of memory devices. In one or more embodiments, the storage device 404 may include memory sharing a die with the processor 402. In one such embodiment, the memory may be used as cache memory and may include, for example, embedded dynamic random-access memory (eDRAM) or spin transfer torque magnetic random-access memory (STT-MRAM). In one or more embodiments, the storage device 404 may include a non-transitory computer-readable medium having instructions thereon that, when executed by one or more processing devices (e.g., processor 402), cause the computing device 400 to perform any suitable ones of the methods or portions of those methods disclosed herein.

[0074] Computing device 400 may include interface device 406 (e.g., one or more interface devices 406). Interface device 406 may include one or more communication chips, connectors, and / or other hardware and software to manage communications between computing device 400 and other computing devices. For example, interface device 406 may include circuitry for managing wireless communications for transferring data to and from computing device 400. The term "wireless" and its derivatives may be used to describe circuits, devices, systems, methods, techniques, communication channels, etc. that can communicate data through the use of modulated electromagnetic radiation over a non-solid medium. This term does not imply that the associated devices do not include any wiring, although in one or more embodiments, the associated devices may not include any wiring. The circuitry included in interface device 406 for managing wireless communications may implement any of a number of wireless standards or protocols, including, but not limited to, Wi-Fi (IEEE 802.11 family), Institute for Electrical and Electronic Engineers (IEEE) standards including the IEEE 802.16 standard (e.g., the IEEE 802.16-2005 Amendment), the Long-Term Evolution (LTE) project (e.g., the Advanced LTE project, the Ultra Mobile Broadband (UMB) project (also referred to as "3GPP®2"), etc.) with any amendments, updates, and / or revisions.In one or more embodiments, the circuitry included in the interface device 406 for managing wireless communications may be compatible with any of the following wireless communication standards: Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Universal Mobile Telecommunications System (UMTS), High Speed ​​Packet Access (HSPA), Evolved HSPA (Evolved HSPA), and the like. In one or more embodiments, the interface device 406 may operate in accordance with a HSPA, E-HSPA, or LTE network. In one or more embodiments, the interface device 406 may include circuitry for managing wireless communications that may operate in accordance with a GSM Evolution (EDGE) network, a GSM EDGE Radio Access Network (GERAN), a Universal Terrestrial Radio Access Network (UTRAN), or an Evolved UTRAN (E-UTRAN). In one or more embodiments, the interface device 406 may include circuitry for managing wireless communications that may operate in accordance with a Code Division Multiple Access (CDMA), a Time Division Multiple Access (TDMA), or an LTE network. Division Multiple Access (TDMA), Digital Enhanced Cordless Communications (Digital Enhanced Cordless Telecommunications (DECT), Evolution-Data Optimization EV-DO (Echo Optimized, EV-DO), and derivatives thereof, as well as any other wireless protocols designated as 3G, 4G, 5G, and beyond. In one or more embodiments, interface device 406 may include one or more antennas (e.g., one or more antenna arrays) for receiving and / or transmitting wireless communications.

[0075] In one or more embodiments, interface device 406 may include circuitry for managing wired communications, such as electrical, optical, or any other suitable communications protocol. For example, interface device 406 may include circuitry supporting communications according to Ethernet technology. In one or more embodiments, interface device 406 may support both wireless and wired communications and / or may support multiple wired and / or wireless communications protocols. For example, a first set of circuits in interface device 406 may be dedicated to short-range wireless communications, such as Wi-Fi or Bluetooth, while a second set of circuits in interface device 406 may be dedicated to long-range wireless communications, such as global positioning system (GPS), EDGE, GPRS, CDMA, WiMAX, LTE, EV-DO, or others. In one or more embodiments, a first set of circuits in interface device 406 may be dedicated to wireless communications, while a second set of circuits in interface device 406 may be dedicated to wired communications.

[0076] Computing device 400 may include battery / power circuitry 408. Battery / power circuitry 408 may include one or more energy storage devices (e.g., batteries or capacitors) and / or circuitry for coupling components of computing device 400 to an energy source (e.g., AC line power) separate from computing device 400.

[0077] Computing device 400 may include a display device 410 (e.g., multiple display devices). Display device 410 may include any visual indicator, such as a heads-up display, a computer monitor, a projector, a touchscreen display, a liquid crystal display (LCD), a light-emitting diode display, or a flat panel display.

[0078] Computing device 400 may include other input / output (I / O) devices 412, such as, for example, one or more audio output devices (e.g., speakers, headsets, earphones, alarms, etc.), one or more audio input devices (e.g., microphones or microphone arrays), a location device (e.g., a GPS device that communicates with a satellite-based system to receive the location of computing device 400, as is known in the art), an audio codec, a video codec, a printer, sensors (e.g., thermocouples or other temperature sensors, humidity sensors, pressure sensors, vibration sensors, accelerometers, gyroscopes, etc.), an image data capture device such as a camera, a keyboard, a cursor control device (e.g., a mouse, stylus, trackball, or touchpad), a barcode reader, a Quick Response (QR) code reader, or a radio frequency identification (RFID) device. RFID (Radio Frequency Identification) readers may be mentioned.

[0079] Computing device 400 may have any suitable form factor for its application and configuration, such as a handheld or mobile computing device (e.g., a cell phone, a smartphone, a mobile Internet device, a tablet computer, a laptop computer, a netbook computer, an ultrabook computer, a personal digital assistant (PDA), an ultra-mobile personal computer, etc.), a desktop or server computing device, or other network computing component.

[0080] 5 and 6, in one or more embodiments, the non-limiting systems 500 and / or 600 illustrated in Figures 5 and 6, and / or the systems may further comprise one or more computers and / or computing-based elements described herein with reference to a computing environment, such as computing environment 1500 illustrated in Figure 15. In one or more described embodiments, the computers and / or computing-based elements may be used in connection with implementing one or more of the systems, devices, components, and / or computer-implemented operations shown and / or described in connection with Figures 5 and / or 6 and / or other figures described herein.

[0081] 5, the figure illustrates a block diagram of an exemplary non-limiting system 500 that may comprise a signal tracking system 502. The signal tracking system 502 may facilitate synchronization and tracking of multi-modal signals, such as those typically associated with scientific instruments.

[0082] In one or more embodiments, the signal tracking system 502 may be configured, at least in part, by the computing device 400 .

[0083] It should be noted that signal tracking system 502 is merely briefly detailed to provide an introduction to a more complex and / or more extensive signal tracking system 602 as illustrated in Figure 6. That is, further details regarding processes that may be performed by one or more embodiments described herein are provided below in connection with the non-limiting system 600 of Figure 6.

[0084] 5, signal tracking system 502 can include at least memory 504, bus 505, processor 506, identification component 510, and / or parameterization component 514. Processor 506 can be the same as, included in, or different from processor 402. Memory 504 can be the same as, included in, or different from storage device 404.

[0085] Using the above components, the signal tracking system 502 can facilitate the process of tracking multi-modal signals being acquired for the scientific instrument 501.

[0086] In general, the identification component 510 can identify a multimodal set of signals 530 and can further identify a set of inputs and outputs 532 that correspond to, are constructed by, and / or are generated from the data / metadata of the multimodal set of signals 530. The set of signals 530 can be, for example, acquired by the signal tracking system 502 and / or by a scientific instrument 501. The set of signals 530 can be output by the scientific instrument 501 or by another scientific instrument 501. For example, the scientific instrument 501 that can output the multimodal set of signals 530 can be an imaging device, such as a charged particle device.

[0087] Stated another way, the identification component 510 may generally identify the set of inputs and outputs 532 of the scientific instrument 501 .

[0088] The identification component 510 may generally determine whether each signal type in the multimodal set of signals 530 has been identified to be synchronized with one another, i.e., the identification component 510 may compare the sets of signals 530 against one another to determine differences therebetween, for example, to determine the individual types of the set of multimodal types in the multimodal set of signals 530.

[0089] Additionally, the parameterization component 514 may track the inputs and outputs 532 of the set 532 based on a universal clock 538 that is generally common to the inputs and outputs 532 of the set. That is, the parameterization component 514 may execute one or more processes to analyze the inputs and outputs 532 of the set according to synchronization (e.g., timestamps and / or other parameters) applied to the inputs and outputs 532 of the set, enabling linkage and / or correlation between the sets of signals 530.

[0090] As a result of these components, various multimodal signals 530 can be compared to one another to determine, for example, how the signals contributed to events occurring in one or more signals, which may be based on various types of signals, the position of the sample, the energy applied to the sample, etc.

[0091] The identification component 510 and / or the parameterization component 514 may be operatively coupled to a processor 506, which may be operatively coupled to the memory 504. A bus 505 may provide the operative coupling. The processor 506 may facilitate execution of the identification component 510 and / or the parameterization component 514. The identification component 510 and / or the parameterization component 514 may be stored in the memory 504.

[0092] In general, the non-limiting system 500 may employ any suitable communication method (e.g., electronic, telecommunications, internet, infrared, fiber, etc.) to provide communication between the signal tracking system 502, the library data store, and / or any devices associated with the user entity.

[0093] As an overview of the components and their functionality described above, reference is now made very briefly to Figure 10, which illustrates a flow diagram of an exemplary, non-limiting method 1000 that can facilitate a process for multimodal signal tracking. Although the non-limiting method 1000 is described with respect to the non-limiting system 500 of Figure 5, the non-limiting method 1000 may also be applicable to other systems described herein, such as the non-limiting system 600 of Figure 6. Repeated descriptions of similar elements and / or processes used in each embodiment are omitted for the sake of brevity.

[0094] At 1002, the non-limiting method 1000 may include identifying, by a system (e.g., identification component 510) operably coupled to a processor, a set of inputs and outputs (e.g., set of inputs and outputs 532) of a scientific instrument (e.g., scientific instrument 501).

[0095] At 1004, the non-limiting method 1000 may include determining, by the system (e.g., the identification component 510), whether each signal type of the multimodal set of signals (e.g., the multimodal set of signals 530) has been identified to be synchronized with one another. If no, the non-limiting method 1000 may return to step 1002. If yes, the non-limiting method may proceed to step 1006.

[0096] At 1006, the non-limiting method 1000 may include tracking, by the system (e.g., parameterization component 516), the inputs and outputs of the set based on a universal clock (e.g., universal clock 538) that is common to the inputs and outputs of the set.

[0097] Referring now to Figure 6, a non-limiting system 600 is illustrated that may include a signal tracking system 602, a scientific instrument 601, and a library datastore (DS) 644. Repeated descriptions of similar elements and / or processes used in each embodiment are omitted for brevity. Descriptions of an embodiment of Figure 5 may be applicable to an embodiment of Figure 6. Similarly, descriptions of an embodiment of Figure 6 may be applicable to an embodiment of Figure 5.

[0098] In general, the signal tracking system 602 can facilitate the process of tracking the multi-modal signals 630 being acquired for the scientific instrument 601 .

[0099] In one or more embodiments, the signal tracking system 602 may be configured, at least in part, by the computing device 400 .

[0100] One or more communications between one or more components of the non-limiting system 600 may be provided by wired and / or wireless means, including, but not limited to, using a cellular network, a wide area network (WAN) (e.g., the Internet), and / or a local area network (LAN). Suitable wired or wireless technologies for supporting communications include, but are not limited to, wireless fidelity (Wi-Fi), global mobile telecommunications (GMT), and the like. system for mobile communication (GSM), universal system for mobile communication Mobile Telecommunications System (UMTS), WiMAX (worldwide Interoperability for microwave access (WiMAX), enhanced general packet radio service (enhanced GPRS), third generation partnership project (3GPP) long term evolution (LTE), third generation partnership project 2 (3GPP2) ultra-mobile broadband (UMB), high speed packet access (high High-speed packet access (HSPA), Zigbee and other 802.XX wireless technologies and / or legacy telecommunications technologies, BLUETOOTH®, Session Initiation Protocol (SIP), ZIGBEE®, RF4CE protocol, WirelessHART protocol, 6LoWPAN (IPv6 over Low Power Wireless Area Networks), Z-Wave, advanced and / or adaptive network technology (ANT), ultra-wideband (UWB) standard protocols and / or other proprietary and / or non-proprietary communication protocols.

[0101] The signal tracking system 602 may be associated with (eg, accessible via) a cloud computing environment, such as the cloud computing environment 1500 of FIG.

[0102] The signal tracking system 602 may comprise multiple components, which may include a memory 604, a processor 606, a bus 605, an identification component 610, a stamping component 612, a parameterization component 614, a filtering component 616, a synchronization component 618, an evaluation component 620, and / or a recording component 622. Using these components, the signal tracking system 602 may facilitate the process of tracking the multimodal signals 630 being acquired for the scientific instruments 601, for example, by collectively synchronizing the multimodal signals 630 to a common universal clock 638.

[0103] The processor 606, memory 604, and bus 605 of the signal tracking system 602 will now be described. For example, in one or more embodiments, the signal tracking system 602 may comprise a processor 606 (e.g., a computer processing unit, a microprocessor, a classical processor, and / or the like). In one or more embodiments, the components associated with the signal tracking system 602 may include one or more computer- and / or machine-readable, writable, and / or executable components and / or instructions, as described herein with or without reference to one or more figures of one or more embodiments, that may be executed by the processor 606 to provide for the performance of one or more processes defined by such components and / or instructions. In one or more embodiments, the processor 606 may comprise an identification component 610, a stamping component 612, a parameterization component 614, a filtering component 616, a synchronization component 618, an evaluation component 620, and / or a recording component 622.

[0104] In one or more embodiments, signal tracking system 602 may comprise a computer-readable memory 604 that may be operatively coupled to processor 606. Memory 604 may store computer-executable instructions that, when executed by processor 606, may cause processor 606 and / or one or more other components of signal tracking system 602 (e.g., identification component 610, stamping component 612, parameterization component 614, filtering component 616, synchronization component 618, evaluation component 620, and / or recording component 622) to perform one or more operations. In one or more embodiments, memory 604 may store computer-executable components (e.g., identification component 610, stamping component 612, parameterization component 614, filtering component 616, synchronization component 618, evaluation component 620, and / or recording component 622).

[0105] The signal tracking system 602 and / or its components described herein may be communicatively coupled to each other electrically, operatively, optically, and / or otherwise via a bus 605. The bus 605 may include one or more of a memory bus, a memory controller, a peripheral bus, an external bus, a local bus, and / or another type of bus that may use one or more bus architectures. One or more of these examples of the bus 605 may be used.

[0106] In one or more embodiments, the signal tracking system 602 may be coupled (e.g., communicatively, electrically, operatively, optically, and / or similarly) to one or more external systems (e.g., an electrical output generating system, one or more output targets, and / or an output target controller, not illustrated), sources, and / or devices (e.g., computing devices, communication devices, and / or similar devices), e.g., via a network. In one or more embodiments, the signal tracking system 602 and / or one or more of the components of the non-limiting system 600 may reside in the cloud and / or may reside locally (e.g., at a designated location) within a local computing environment.

[0107] In addition to the processor 606 and / or memory 604 described above, the signal tracking system 602 may comprise one or more computer- and / or machine-readable, writable, and / or executable components and / or instructions that, when executed by the processor 606, may provide for the performance of one or more operations defined by such components and / or instructions.

[0108] Additional components of signal tracking system 602 will now be described (e.g., identification component 610, stamping component 612, parameterization component 614, filtering component 616, synchronization component 618, evaluation component 620, and / or recording component 622). Generally, signal tracking system 602 may perform a set of processes that may be separated into various steps, including, but not limited to, identifying a set of inputs and outputs 632, time-stamping the inputs and outputs 632, tracking the inputs and outputs 632, which may include interference filtering, recording, evaluation, analysis, identifying time delays, etc., and synchronizing a universal clock 638 to another clock associated with one or more of the inputs and outputs of set of inputs and outputs 632.

[0109] First, it should be noted that in one or more embodiments, the identification component 610, the stamping component 612, the parameterization component 614, the filtering component 616, the synchronization component 618, the evaluation component 620, and / or the recording component 622 can be implemented independently without one or more other components of the identification component 610, the stamping component 612, the parameterization component 614, the filtering component 616, the synchronization component 618, the evaluation component 620, and / or the recording component 622. Additionally and / or alternatively, the identification component 610, the stamping component 612, the parameterization component 614, the filtering component 616, the synchronization component 618, the evaluation component 620, and / or the recording component 622 may be configured by the high-level analysis component 603, and one or more of the below-described functions of the identification component 610, the stamping component 612, the parameterization component 614, the filtering component 616, the synchronization component 618, the evaluation component 620, and / or the recording component 622 may be configured by the high-level analysis component 603. and / or the identification component 610, stamping component 612, parameterization component 614, filtering component 616, synchronization component 618, evaluation component 620, and / or recording component 622 can be omitted with the high-level monitoring component 603 performing one or more of the below-described functions of one or more of the omitted identification component 610, stamping component 612, parameterization component 614, filtering component 616, synchronization component 618, evaluation component 620, and / or recording component 622.

[0110] Referring first to the identification component 610, this component may generally identify a multimodal set of signals 630 and may further identify a set of inputs and outputs 632 that correspond to, are constructed by, and / or are generated from the data / metadata of the multimodal set of signals 630. Turning briefly to FIG. 9 in addition to FIG. 6, steps 902 and 904 may be performed by the identification component 610.

[0111] The set of signals 630 may be, for example, acquired by the signal tracking system 602 and / or by the scientific instrument 601. The set of signals 630 may be output by the scientific instrument 601 or by another scientific instrument 601. For example, the scientific instrument 601 that may output the multimodal set of signals 630 may be an imaging device such as a charged particle device, a scanning electron microscope (SEM), a scanning transmission electron microscope (STEM), etc.

[0112] Stated another way, the identification component 610 may generally identify a set 632 of inputs and outputs of the charged particle device 601. More specifically, the identification component 610 may scan one or more frequencies, communications, signal paths, communication packets, action logs, etc., corresponding to the scientific instrument 601 to identify a multimodal set 630 of signals, which may include the set 632 of inputs and outputs. A determination between an input of the set 632 and an output of the set 632 may be based on the identification component 610 tracking the occurrence of a signal in the set 630 (e.g., whether the signal was generated / transmitted by the scientific instrument 601 or received / obtained by the scientific instrument 601, for example).

[0113] In one or more embodiments, the identification component 610 may generally determine whether each signal type of the multimodal set of signals 630 has been identified to be synchronized with one another, i.e., the identification component 610 may compare and contrast the signals of the set of signals 630 against one another to determine differences therebetween, for example, to determine the individual types of the set of multimodal types of the multimodal set of signals 630.

[0114] For example, with brief reference to FIG. 7 , one or more signal types are illustrated, but are not limited to these. More or fewer signal types than those listed in the context workflow 700 may be employed by the scientific instrument 601 and, therefore, may be identified by the identification component 610. Examples may include, among others, interference frequency data 732F, imaging data 740, excitation data 732G, XY position data 732A, stimulus data 732B, detection data 732C, scan data 732D, and / or optical data 732E (described below). As illustrated, each may employ individual tracking methods, such as an independent clock 732, excitation clock 742, and / or XY position tracking 744. As a result, linking and / or synchronization between different data types (e.g., corresponding to each signal type) may be difficult, if not impossible. This may create challenges in understanding events that occurred during an experiment. For example, this may make it difficult for artificial intelligence to correlate various data resulting from an experiment.

[0115] 6 and 9, the stamping component 612 can generally generate one or more timestamps 634 for the inputs and outputs based on the data output from the universal clock 638, where the timestamps 634 are not affected by changes in the XY position outputs of the outputs (set 632). That is, in step 906, the stamping component 612 can determine the data output 636 from the universal clock 638. Based thereon, the stamping component 612 can compare the serial count of the universal clock 638 with the metadata of the inputs and outputs of the set of inputs and outputs 632. Based on the comparison, the stamping component 612 can generate metadata defining a timestamp 634 for each point of data in the set 632 that has been obtained (e.g., identified by the identification component 610).

[0116] In one or more embodiments, this generation and application of timestamp 634 may be performed dynamically, for example, in parallel with and / or immediately prior to data acquisition of the signal by identification component 610. In one or more other embodiments, this generation and application of timestamp 634 may be applied some time after data is acquired, such as after an experiment has begun. Regardless, metadata associated with the inputs and outputs of set 632 may be employed to compare the inputs and / or outputs to the data output 636 of universal clock 638. This may include comparing XY positional traces 744 along the timeline of universal clock 638.

[0117] In one or more embodiments, the timestamp 634 may be stored in the memory 604 , the library data store 644 , and / or any other suitable location communicatively accessible to the signal tracking system 602 .

[0118] Referring briefly to universal clock 638, such clock may be a component of processor 606 or any other processor communicatively accessible to signal tracking system 602. Universal clock 638 may provide a continuous (e.g., serial) count of time in any suitable unit increments.

[0119] In step 908, the parameterization component 614 may track the inputs and outputs 632 of the set 632 based on a universal clock 638 that is generally common to the set's inputs and outputs 632. That is, a single universal clock 638, and therefore a single timing, may be employed for the multimodal set 630 of signals and, therefore, for the set 632 of inputs and outputs constituted by the multimodal set 630 of signals.

[0120] Based thereon, the parameterization component 614 may perform one or more processes to analyze the set of inputs and outputs 632 according to synchronization (e.g., timestamps and / or other parameters) applied to the set of inputs and outputs 632 to enable linkage and / or correlation between the set of signals 630.

[0121] This tracking may include, but is not limited to, interference filtering, recording, evaluation, analysis, time delay identification, and the like.

[0122] It is understood that, based at least on the processes performed by stamping component 612 and parameterization component 614, universal clock 638 can be employed without any adjustment of universal clock 638 based on environmental disturbances 660 to the scientific instrument (e.g., without any adjustment of any clock for tracking signal set 630). For example, environmental disturbances 660 may cause variance, drift, stoppages, and / or jumps in signal outputs and / or inputs to the experiment. In one example, environmental disturbances 660 may cause XY position vibrations, bumps, etc., thus causing variance in XY position outputs (of input and output set 632). Accordingly, such variances can be similarly accounted for in XY position tracking 744. As another example, experiment outputs can be used to discover environmental interference frequencies within energy axis instabilities, and that understanding can be applied to correct one or more instabilities in XY position, or vice versa.

[0123] Without one or more embodiments described herein, clock timing invariance may be difficult and / or impossible to compare with variable XY position tracking 744. For example, timing precision may increase to femtosecond or attosecond precision in ultrafast experiments involving, for example, cavity or laser excitation of illumination, in one embodiment, where multiple clock phase shifts between tracks may occur, which may be undesirably difficult to compensate for later. Indeed, it may be time-consuming if multiple input / output clocks are to be synchronized after the experiment, and undesirably, in existing cases where universal time stamping is not performed online, it may be difficult or impossible to process live data. That is, for experiments where scanning speeds may be on the order of nanoseconds per pixel, this may require nanosecond precision of XY position tracking synchronized with input / output signals.

[0124] Alternatively, based on one or more processes of the stamping component 612 and / or parameterization component 614 employing the timing of the universal clock 638, an ordering parameter (e.g., time corresponding to the universal clock 638) may be employed that does not change with environmental disturbances 660 like conventional XY position tracking 744. This may be because while time is invariant, XY position tracking 744 may be variable due to instabilities such as physical instabilities.

[0125] For example, and briefly referring to FIG. 8, as illustrated in solution workflow 800, each of the various data types (corresponding to the respective signal types) can employ a single, common tracking method based on a universal clock 638.

[0126] Referring again to Figures 6 and 9, based on instructions (e.g., communications, signals, etc.) from the parameterization component 614, various additional components of the signal tracking system 602 can perform various respective processes 908A-908D.

[0127] For example, in step 908B, filtering component 616 may filter out interference frequency output 732F of output 632, which is affecting imaging output 740 of output 632. This may be accomplished by scanning for interference frequencies corresponding to interference frequency output 732F according to universal clock 638. Such a process cannot be performed using existing frameworks due to the lack of synchronization between different signal types acquired from scientific instrument 601.

[0128] As another example, in step 908C, the evaluation component 620 can identify time delays 640 between different combinations of inputs, outputs, or both, among the set of inputs and outputs 632 according to the universal clock 638. That is, a gap in data can be associated with a first signal in the set 630 but not with other signals in the set 630. This gap can be accounted for based on a process performed by the stamping component 612 and / or the parameterization component 614. Such a process cannot be performed using existing frameworks due to the lack of synchronization between different signal types obtained from the scientific instrument 601.

[0129] As another example, in step 908A, the recording component 622 can record a set of XY position outputs 732A-NB from the outputs 632 from the scientific instrument 601, where the recording component 622 omits recording of the XY position outputs 732A-B corresponding to beam blanking. That is, using a high-speed beam blanker during a scan by the scientific instrument 601 can generate a sparse XY pattern. Conventionally, all empty XY positions are recorded. By using the timing of the universal clock 638 as a reference, only such unblanked associated signals / data (e.g., XY position outputs 732A-NB) can be recorded when the beam is unblanked. Conversely, omitting the recording of each blanked associated signal / data (e.g., XY position outputs 732A-B) can result in a significant reduction in bandwidth, power, time, storage space, memory, and / or data employed. Such a process cannot be performed using existing frameworks due to the lack of synchronization between different signal types acquired from the scientific instrument 601.

[0130] Recording by recording component 622 may include a write action (eg, including update 642) to suitable storage, such as library data store (DS) 644, or any other suitable action.

[0131] As another example, various comparisons between signal types 631 may be performed in step 908D, not specifically defined herein, i.e., the process and / or results of using signal tracking system 602 are not limited to only those explicitly described herein.

[0132] Further, in step 910, based on the data output 636 of the universal clock 638, the synchronization component 618 can determine a second timing of the excitation clock 742 to be employed for dynamic excitation by the scientific instrument 601. In response, the synchronization component 618 can synchronize the first timing of the universal clock 638 to the second timing of the excitation clock 742, or vice versa.

[0133] For example, in dynamic experiments, time zero can be defined as the point at which excitation is applied. The corresponding response of the sample can be measured in time to study decay times in irreversible experiments. In a stroboscopic setup, periodic pulsed illumination can be synchronized with periodic excitation of the sample to monitor reversible processes. The phase shift between two weak signals can be summed (e.g., in ultrafast experiments), and the temporal response can be measured by measuring the phase shift between excitation and illumination. In one or more cases, the phase shift can be detected by time-stamping the sample excitation event and the detection of the signal at the sensor using a time-resolved detector. Unlike existing frameworks, which only employ single-shot pulsing of the beam or stroboscopic excitation synchronized with the sample excitation time, one or more embodiments described herein can provide for simultaneous synchronization of beam scanning, source, and detection events with the sample excitation time.

[0134] Indeed, in one or more other embodiments, the universal clock 638 may be set based on (eg, in parallel with) the corresponding output data of any other independent clocks 738 .

[0135] As a result of the various components 610-622 discussed above, the various multimodal signals 630 can be compared to one another to determine, for example, how the multiple signals may have contributed to an event occurring in / defined by one or more signals. Such an event may be based on the various types 631 of signals, the XY position 732A of the sample, the energy applied to the sample, etc.

[0136] In one or more embodiments, artificial intelligence Intelligence (AI) analysis can be employed to determine compensation for artifacts resulting from experiments on the scientific instrument 601, which may be possible because the time reference is always undisturbed (e.g., unchanging).

[0137] In one or more embodiments, one or more experiment types that cannot be performed using existing frameworks can be performed based on one or more embodiments described herein. For example, simultaneous measurements and / or critical dose measurements can benefit from the signal comparison provided by using a common universal clock 638 and the lack of signal tracking loss (e.g., from tracking continuously acquired signals using XY position 732A, as in existing frameworks). By way of another example, such new experiments can include easy integration of new dynamic third-party components, such as holders, lasers, and / or high-speed detectors, based on the processes described above, as may be performed by at least identification component 610, stamping component 612, and parameterization component 614.

[0138] Furthermore, as an additional and / or alternative result of the use of one or more embodiments described herein, one or more of the following benefits may be provided, but are not limited to: easy and reproducible setup of dynamic experimental workflows, accurate event documentation for offline analysis, increased time resolution down to nanoseconds, improved accuracy of correlation of multimodal data via time stamping, and / or improved drift correction accuracy in dynamic experiments via maximum scan speeds.

[0139] With the above-described components and their functionality now summarized, reference is now made to Figures 11 and 12, which illustrate a flow diagram of an exemplary, non-limiting method 1100 that can facilitate a process for multimodal signal tracking according to one or more embodiments described herein, such as the non-limiting system 600 of Figure 6. Although the non-limiting method 1100 is described with respect to the non-limiting system 600 of Figure 6, the non-limiting method 1100 may also be applicable to other systems described herein, such as the non-limiting system 500 of Figure 5. Repeated descriptions of similar elements and / or processes used in each embodiment are omitted for the sake of brevity.

[0140] At 1102, the non-limiting method 1100 may include identifying, by a system (e.g., identification component 610), a set of inputs and outputs (e.g., set of inputs and outputs 632) of a scientific instrument (e.g., scientific instrument 601).

[0141] At 1104, the non-limiting method 1100 may include determining, by the system (e.g., the identification component 610), whether each signal type (e.g., signal type 631) of the multimodal set of signals (e.g., the multimodal set of signals 630) has been identified to be synchronized with one another. If no, the non-limiting method 1100 may return to step 1102. If yes, the non-limiting method may proceed to step 1106.

[0142] At 1106, the non-limiting method 1100 may include the system (e.g., stamping component 612) timestamping the input and output with a timestamp (e.g., timestamp 634) based on a data output (e.g., data output 636) from a universal clock (e.g., universal clock 638).

[0143] At 1108, the non-limiting method 1100 can include employing a universal clock by the system (e.g., stamping component 612) without adjusting the universal clock based on an environmental disturbance (e.g., environmental disturbance 660) to the scientific instrument, including a change in an XY position output (e.g., XY position output 732A) among the outputs.

[0144] At 1110, the non-limiting method 1100 may include tracking, by the system (e.g., parameterization component 614), the set of inputs and outputs based on a universal clock that is common to the set of inputs and outputs.

[0145] At 1112, the non-limiting method 1100 may include filtering out an interference frequency output (e.g., interference frequency output 732F) among the outputs that is affecting an imaging output (e.g., imaging output 740) among the outputs by scanning, by a system (e.g., filtering component 616), for an interference frequency corresponding to the interference frequency output according to a universal clock.

[0146] At 1114, the non-limiting method 1100 may include determining, by the system (e.g., synchronization component 618), a second timing of an excitation clock (e.g., excitation clock 742) employed for dynamic excitation by the scientific instrument.

[0147] At 1116, the non-limiting method 1100 may include synchronizing, by the system (eg, synchronization component 618), a first timing of the universal clock to a second timing of the excitation clock.

[0148] At 1118, the non-limiting method 1100 may include identifying, by the system (e.g., evaluation component 620), time delays (e.g., time delays 640) between different combinations of inputs, outputs, or both, among the set of inputs and outputs according to a universal clock.

[0149] At 1120, the non-limiting method 1100 can include recording, by a system (eg, recording component 622), a set of XY position outputs from the scientific instrument.

[0150] At 1122, the non-limiting method 1100 can include omitting, by the system (e.g., recording component 622), recording of XY position outputs (e.g., XY position outputs 732A-B) corresponding to beam blanking.

[0151] Additional Overview For ease of explanation, computer-implemented and non-computer-implemented methodologies provided herein are depicted and / or described as a series of acts. It should be understood that the present invention is not limited by the illustrated acts and / or by the order of the acts; for example, acts may be performed in one or more orders and / or simultaneously, as well as with other acts not presented and described herein. Furthermore, not all illustrated acts may be utilized to implement computer-implemented and non-computer-implemented methodologies in accordance with the described subject matter. Additionally, computer-implemented and non-computer-implemented methodologies may alternatively be represented as a series of interrelated states via state diagrams or events. Additionally, the computer-implemented methodologies described below and throughout this specification may be stored on an article of manufacture for transmission and transfer of the computer-implemented methodology to a computer. The term article of manufacture, as used herein, is intended to encompass a computer program accessible from any computer-readable device or storage medium.

[0152] Systems and / or devices are (and / or further) described herein with respect to interactions between one or more components. Such systems and / or components may include components or subcomponents specified herein, one or more of the specified components and / or subcomponents, and / or additional components. Subcomponents may be implemented as components communicatively coupled to other components rather than being included within a parent component. One or more components and / or subcomponents may be combined into a single component that provides aggregate functionality. Components may interact with one or more other components not specifically described herein for the sake of brevity, but known by those skilled in the art.

[0153] In summary, one or more systems, computer program products, and / or computer-implemented methods provided herein relate to a process for multimodal signal acquisition, for example, from a charged particle device or other scientific instrument, based on universal clock synchronization of various multimodal signals. The system may include a memory that stores computer-executable components and a processor that executes the computer-executable components stored in the memory, where the computer-executable components include an identification component that identifies a set of inputs and outputs of the scientific instrument, and a parameterization component that tracks the set of inputs and outputs based on a universal clock common to the set of inputs and outputs.

[0154] One or more embodiments described herein may employ a novel system that can be employed with a variety of (e.g., multi-modal) signal types, including, but not limited to, stimulation, detection, scanning, optical, magnetic, electrical phase transition, and / or dynamic excitation. Each of these signal types may employ a universal clock, thus allowing the inputs and / or outputs of these signal types to be tracked and analyzed relative to one another without data loss, time conversion, etc. Furthermore, environmental disturbances that cause changes in XY position due, for example, to physical instability, bumps, vibrations, etc., do not alter such a clock because the universal clock is not based solely on XY position.

[0155] Indeed, in view of one or more embodiments described herein, a practical application of one or more systems, computer-implemented methods, and / or computer program products described herein may be the ability to easily order parameters based on multimodal signal acquisition relative to one another, thus enabling identification of one or more interference frequencies in the environment that perturb another signal, such as an image output signal, and enabling isolation of such one or more interference frequencies. These are useful and practical applications of computers, thus providing enhanced (e.g., improved and / or optimized) compound analysis and / or image analysis. Overall, such computerized tools may constitute a concrete and tangible technological improvement in the field of materials analysis, and more particularly, in materials analysis based on multimodal signal acquisition.

[0156] Furthermore, one or more embodiments described herein can be used in real-world systems based on the disclosed teachings. For example, one or more embodiments described herein can provide for parameterization of various signal inputs and / or outputs of the same experiment, operation, and / or process, allowing for identification of one or more interference frequencies in the environment that perturb another signal, such as an image output signal, and for isolating such one or more interference frequencies.

[0157] In one or more cases, based on one or more embodiments described herein, one or more experiment types can be performed that cannot be performed using existing frameworks. For example, simultaneous measurements and critical dose measurements can benefit from the signal comparison provided by using a common universal clock and the lack of signal tracking loss (e.g., from tracking continuously acquired signals using XY position, as in existing frameworks).

[0158] In one or more cases, based on using one or more embodiments described herein, reduced storage space and bandwidth can be employed for storing and recording signals due to the ability to omit recording XY position outputs corresponding to beam blanking.

[0159] One or more embodiments described herein may be applied on a plug-and-play basis to a variety of architectures of existing scientific instruments, signal acquisition equipment, and the like.

[0160] These can be useful processes for a variety of industries employing materials analysis, product manufacturing, quality control, etc. Accordingly, embodiments disclosed herein can provide improvements to scientific instrumentation technology (e.g., improvements to the computer technology supporting such scientific instrumentation, among other improvements).

[0161] Furthermore, in one or more cases, the embodiments described herein may be self-improving. Indeed, when a common universal clock is employed, it may become more efficient and accurate over time to enable the generation and application of timestamps that can be correlated to one another without variance due to environmental influences, comparisons to determine relationships between acquired signals, event determination based on multimodal signals, etc., as may be performed by classical computers and / or one or more artificial intelligences employing the results of one or more embodiments described herein. That is, when signals are acquired and synchronized according to a common universal clock without using variable XY positions as a synchronization element, but rather by synchronizing XY positions along with other inputs and outputs, larger and more accurate comparative data is generated for use in exploration, querying, event determination, signal comparison, and other analyses performed on various multimodal signals synchronized with one or more embodiments described herein. Thus, one or more non-limiting systems described herein, including signal tracking systems, may be self-improving, as described herein.

[0162] Furthermore, one or more embodiments described herein may achieve a level of operational scale, for example, two or more different signals may be synchronized and tracked using timestamp generation and application for the same experiment and / or process at least partially contemporaneously with one another, and / or the same may be performed for two or more different experiments and / or processes at least partially contemporaneously with one another.

[0163] Systems and / or devices are (and / or further) described herein with respect to interactions between one or more components. Such systems and / or components may include components or subcomponents specified herein, one or more of the specified components and / or subcomponents, and / or additional components. Subcomponents may be implemented as components communicatively coupled to other components rather than being included within a parent component. One or more components and / or subcomponents may be combined into a single component that provides aggregate functionality. Components may interact with one or more other components not specifically described herein for the sake of brevity, but known by those skilled in the art.

[0164] One or more embodiments described herein may, in one or more embodiments, be inherently and / or inseparably linked to computer technology and cannot be implemented outside of a computing environment. For example, one or more processes performed by one or more embodiments described herein may provide for more efficient and even more viable execution of programs and / or program instructions, e.g., with respect to reading, synchronizing, and / or stamping digital data corresponding to multimodal signal acquisition. Systems, computer-implemented methods, and / or computer program products that provide the performance of these processes would be highly useful in the field of materials analysis and cannot be equally practically implemented in a reasonable manner outside of a computing environment.

[0165] One or more embodiments described herein may employ hardware and / or software to solve problems that are highly technical, not abstract, and cannot be performed as a series of mental acts by a human. For example, one human, or even thousands of humans, cannot efficiently, accurately, and / or effectively read, synchronize, and / or stamp digital data corresponding to multimodal signal acquisition, as one or more embodiments described herein may provide. Furthermore, neither the human mind nor a human using pen and paper can perform one or more of these processes as performed by one or more embodiments described herein.

[0166] In one or more embodiments, one or more of the processes described herein may be executed by one or more special-purpose computers (e.g., special-purpose processing units, special-purpose classical computers, and / or other types of special-purpose computers) to perform defined tasks associated with one or more of the technologies described above. One or more embodiments described herein and / or components thereof may be used to solve new problems that arise through the use of the above-referenced technological advancements, cloud computing systems, computer architectures, and / or other technologies.

[0167] One or more embodiments described herein may be fully operational to perform one or more other functions (e.g., fully powered on, fully running, and / or another function) while performing one or more of the operations described herein.

[0168] To provide a further overview, a list of embodiments and their features is provided below.

[0169] 1. A system comprising: a memory that stores computer-executable components; and a processor that executes the computer-executable components stored in the memory, the computer-executable components comprising: an identification component that identifies a set of inputs and outputs of a scientific instrument; and a parameterization component that tracks the set of inputs and outputs based on a universal clock that is common to the set of inputs and outputs.

[0170] The system of the preceding paragraph, wherein the set of inputs and outputs includes XY position inputs and outputs, and sensing inputs and outputs.

[0171] The system of any preceding paragraph, wherein the computer-executable component further comprises a stamping component that timestamps the inputs and outputs with timestamps based on data output from a universal clock, wherein the timestamps are not affected by changes in the XY position output of the outputs.

[0172] The system of any preceding paragraph, wherein the computer-executable component further comprises a filtering component that filters out interference frequency outputs from the outputs that are affecting the imaging output from the outputs by scanning for interference frequencies corresponding to the interference frequency outputs according to the universal clock.

[0173] The system of any preceding paragraph, wherein the computer-executable component determines a second timing of an excitation clock employed for dynamic excitation by the scientific instrument, and further comprises a synchronization component that synchronizes the first timing of the universal clock to the second timing of the excitation clock.

[0174] The system of any preceding paragraph in which the universal clock is employed without adjustment of the universal clock being based on environmental disturbances to the scientific instrument, including changes in XY position output among the outputs.

[0175] The system of any preceding paragraph, wherein the computer-executable components further comprise an evaluation component that identifies, according to a universal clock, time delays between different combinations of inputs, outputs, or both, of the set of inputs and outputs.

[0176] The system of any preceding paragraph, wherein the computer-executable component further comprises a recording component that records a set of XY position outputs among the outputs from the charged particle device, and wherein the recording component omits recording of XY position outputs corresponding to beam blanking.

[0177] A computer-implemented method comprising: identifying, by a system operably coupled to a processor, a set of inputs and outputs of a charged particle device; and tracking, by the system, the inputs and outputs of the set based on a universal clock that is common to the inputs and outputs of the set.

[0178] The computer-implemented method of the preceding paragraph further comprising generating, by the system, timestamps for the inputs and outputs based on data output from the universal clock, wherein the timestamps are not affected by changes in XY position output of the outputs.

[0179] The computer-implemented method of any preceding paragraph, further including filtering out interference frequency outputs among the outputs that are affecting the imaging output among the outputs by scanning, by the system, according to the universal clock for interference frequencies that correspond to the interference frequency outputs.

[0180] The computer-implemented method of any preceding paragraph, further including determining, by the system, a first timing of an excitation clock employed for dynamic excitation by the charged particle device; and synchronizing, by the system, a second timing of the universal clock to the first timing of the excitation clock.

[0181] The computer-implemented method of any preceding paragraph, further comprising employing a universal clock by the system without adjustment of the universal clock based on environmental disturbances to the scientific instrument, including changes in XY position outputs among the outputs.

[0182] The computer-implemented method of any preceding paragraph, further comprising identifying, by the system, time delays between different combinations of inputs, outputs, or both, of the set of inputs and outputs according to a universal clock.

[0183] The computer-implemented method of any preceding paragraph, further comprising recording, by the system, a set of XY position outputs among the outputs from the charged particle device, wherein the recording comprises omitting recording of XY position outputs corresponding to beam blanking.

[0184] 1. A computer program product that facilitates a process for tracking inputs and outputs of a scientific device, the computer program product comprising a computer-readable storage medium having program instructions embodied thereon, the program instructions being executable by a processor to cause the processor to identify, by the processor, a set of inputs and outputs of a charged particle device, and to track, by the processor, the set of inputs and outputs based on a universal clock that is common to the set of inputs and outputs.

[0185] The computer program product of the preceding paragraph, wherein the program instructions are further executable by the processor to cause the processor to generate timestamps for the inputs and outputs based on data output by the processor from the universal clock, the timestamps being unaffected by changes in XY position output of the outputs.

[0186] The computer program product of any preceding paragraph, wherein the program instructions are further executable by a processor to cause the processor to filter out interference frequency outputs among the outputs that are affecting the imaging output among the outputs by scanning, by the processor, according to the universal clock, for interference frequencies corresponding to the interference frequency outputs.

[0187] The computer program product of any preceding paragraph, wherein the program instructions are further executable by the processor to cause the processor to adopt the universal clock without adjustment of the universal clock based on environmental disturbances to the scientific instrument, including changes in XY position outputs among the outputs.

[0188] The computer program product of any preceding paragraph, wherein the program instructions are further executable by a processor to cause the processor to identify, by the processor, time delays between different combinations of inputs, outputs, or both, of the set of inputs and outputs according to a universal clock.

[0189] Scientific Instrument System Description Referring now to Figure 13, a detailed description of additional context for one or more embodiments described herein in Figures 1-12 is provided. One or more computing devices implementing any of the scientific instrument modules or methods disclosed herein may be part of a scientific instrument system. Figure 13 illustrates a block diagram of an exemplary scientific instrument system 1300 capable of performing one or more of the scientific instrument methods or other methods disclosed herein, in accordance with various embodiments described herein. The scientific instrument modules and methods disclosed herein (e.g., scientific instrument module 100 of Figure 1 and method 200 of Figure 2) may be implemented by one or more of the scientific instrument 1310, user local computing device 1320, service local computing device 1330, and / or remote computing device 1340 of the scientific instrument system 1300.

[0190] Any of the scientific instrument 1310, the user local computing device 1320, the service local computing device 1330, and / or the remote computing device 1340 may include any of the embodiments of computing device 400 discussed herein with reference to FIG. 4, and any of the scientific instrument 1310, the user local computing device 1320, the service local computing device 1330, and / or the remote computing device 1340 may take the form of any suitable one or more of the embodiments of computing device 400 discussed herein with reference to FIG. 4.

[0191] One or more of the scientific instruments 1310, user local computing devices 1320, service local computing devices 1330, and / or remote computing devices 1340 may include a processing device 1302, a storage device 1304, and / or an interface device 1306. The processing device 1302 may take any suitable form, including any form of processor 402 discussed herein with reference to FIG. 4. The processing devices 1302 included in different ones of the scientific instruments 1310, user local computing devices 1320, service local computing devices 1330, and / or remote computing devices 1340 may take the same form or different forms. The storage device 1304 may take any suitable form, including any form of storage device 404 discussed herein with reference to FIG. 4. The storage devices 1304 included in different ones of the scientific instruments 1310, user local computing devices 1320, service local computing devices 1330, and / or remote computing devices 1340 may take the same form or different forms. The interface devices 1306 may take any suitable form, including any of the forms of the interface devices 406 discussed herein with reference to Figure 4. The interface devices 1306 included in different ones of the scientific instruments 1310, the user local computing device 1320, the service local computing device 1330, and / or the remote computing device 1340 may take the same or different forms.

[0192] The scientific instrument 1310, the user local computing device 1320, the service local computing device 1330, and / or the remote computing device 1340 can communicate with other elements of the scientific instrument system 1300 via communication paths 1308. As shown, the communication paths 1308 can communicatively couple the interface devices 1306 of different elements of the scientific instrument system 1300 (e.g., according to any of the communication techniques discussed herein with reference to the interface device 406 of the computing device 400 of FIG. 4 ) and can be wired or wireless communication paths. While the particular scientific instrument system 1300 depicted in FIG. 13 includes communication paths between each pair of the scientific instrument 1310, the user local computing device 1320, the service local computing device 1330, and the remote computing device 1340, this “fully connected” implementation is merely illustrative, and various embodiments can omit various ones of the communication paths 1308. For example, in one or more embodiments, the service local computing device 1330 may omit the direct communication path 1308 between its interface device 1306 and the interface device 1306 of the scientific instrument 1310, and instead may communicate with the scientific instrument 1310 via the communication path 1308 between the service local computing device 1330 and the user local computing device 1320, and / or the communication path 1308 between the user local computing device 1320 and the scientific instrument 1310.

[0193] The scientific instrument 1310 may include any suitable scientific instrument, such as a separation or MS instrument, or other instrument that facilitates material analysis.

[0194] The user local computing device 1320 may be a computing device near a user of the scientific instrument 1310 (e.g., according to any of the embodiments of the computing device 400 discussed herein). In one or more embodiments, the user local computing device 1320 may also be near the scientific instrument 1310, but need not be. For example, a user local computing device 1320 associated with a home, office, or other building associated with a user entity may be remote from but in communication with the scientific instrument 1310 such that the user entity can control and / or access data from the scientific instrument 1310 using the user local computing device 1320. In one or more embodiments, the user local computing device 1320 may be a laptop, smartphone, or tablet device. In one or more embodiments, the user local computing device 1320 may be a portable computing device. In one or more embodiments, the user local computing device 1320 may be deployed in the field.

[0195] The service local computing device 1330 may be a computing device (e.g., according to any of the embodiments of computing device 400 discussed herein) that is proximate to an entity that provides services to the scientific instrument 1310. For example, the service local computing device 1330 may be proximate to the manufacturer of the scientific instrument 1310 or a third-party service company. In one or more embodiments, the service local computing device 1330 may communicate with the scientific instrument 1310, the user local computing device 1320, and / or the remote computing device 1340 (e.g., via a direct communication path 1308 or via multiple “indirect” communication paths 1308, as discussed above) to receive data regarding the operation of the scientific instrument 1310, the user local computing device 1320, and / or the remote computing device 1340 (e.g., results of self-diagnostic tests of the scientific instrument 1310, calibration coefficients used by the scientific instrument 1310, measurements of sensors associated with the scientific instrument 1310, etc.). In one or more embodiments, the service local computing device 1330 can communicate with the scientific instrument 1310, the user local computing device 1320, and / or the remote computing device 1340 (e.g., via a direct communication path 1308 or via multiple “indirect” communication paths 1308, as discussed above) and transmit data to the scientific instrument 1310, the user local computing device 1320, and / or the remote computing device 1340 (e.g., to update programmed instructions such as firmware in the scientific instrument 1310, to initiate the execution of a test or calibration sequence in the scientific instrument 1310, to update programmed instructions such as software in the user local computing device 1320 or the remote computing device 1340, etc.).A user entity of the scientific instrument 1310 can communicate with the service local computing device 1330 to utilize the scientific instrument 1310 or the user local computing device 1320 to report problems with the scientific instrument 1310 or the user local computing device 1320, to request a technician visit to improve the operation of the scientific instrument 1310, to order consumables or replacement parts associated with the scientific instrument 1310, or for other purposes.

[0196] The remote computing device 1340 may be a computing device that is remote from the scientific instrument 1310 and / or from the user local computing device 1320 (e.g., according to any of the embodiments of the computing device 400 discussed herein). In one or more embodiments, the remote computing device 1340 may be included in a data center or other large-scale server environment. In one or more embodiments, the remote computing device 1340 may include network-attached storage (e.g., as part of the storage device 1304). The remote computing device 1340 may store data generated by the scientific instrument 1310, perform analysis of the data generated by the scientific instrument 1310 (e.g., according to programmed instructions), facilitate communications between the user local computing device 1320 and the scientific instrument 1310, and / or facilitate communications between the service local computing device 1330 and the scientific instrument 1310.

[0197] In one or more embodiments, one or more of the elements of the scientific instrument system 1300 illustrated in Figure 13 may be omitted. Furthermore, in one or more embodiments, more than one of various elements of the elements of the scientific instrument system 1300 of Figure 13 may be present. For example, the scientific instrument system 1300 may include multiple user local computing devices 1320 (e.g., different user local computing devices 1320 associated with different user entities or different locations). In another example, the scientific instrument system 1300 may include multiple scientific instruments 1310 that are all in communication with a service local computing device 1330 and / or a remote computing device 1340; in such an embodiment, the service local computing device 1330 may monitor these multiple scientific instruments 1310, and the service local computing device 1330 may cause updates or other information to be "broadcast" to the multiple scientific instruments 1310 simultaneously. Different scientific instruments 1310 in the scientific instrument system 1300 can be located near each other (e.g., in the same room) or far from each other (e.g., on different floors of a building, in different buildings, in different cities, etc.). In one or more embodiments, the scientific instruments 1310 can be connected to an Internet-of-Things (IoT) stack that enables command and control of the scientific instruments 1310 through web-based applications, virtual or augmented reality applications, mobile applications, and / or desktop applications. Any of these applications can be accessed by a user entity operating a user local computing device 1320 that is in communication with the scientific instruments 1310 through an intervening remote computing device 1340. In one or more embodiments, the scientific instruments 1310 can be sold by a manufacturer together with one or more associated user local computing devices 1320 as part of a local scientific instrument computing unit 1312.

[0198] In one or more embodiments, different ones of the scientific instruments 1310 included in the scientific instrument system 1300 may be different types of scientific instruments 1310. For example, one scientific instrument 1310 may be an EDS device and another scientific instrument 1310 may be an analytical device that analyzes the results of the EDS device. In some such embodiments, the remote computing device 1340 and / or the user local computing device 1320 may combine data from different types of scientific instruments 1310 included in the scientific instrument system 1300.

[0199] Example Operating Environment 14 is a schematic block diagram of an operating environment 1400 with which the described subject matter can interact. The operating environment 1400 includes one or more remote components 1410. The remote components 1410 can be hardware and / or software (e.g., threads, processes, computing devices). In one or more embodiments, the remote components 1410 can be a distributed computer system connected via a communications framework 1440 to local autoscaling components and / or programs that use resources of the distributed computer system. The communications framework 1440 can include wired network devices, wireless network devices, mobile devices, wearable devices, radio access network devices, gateway devices, femtocell devices, servers, etc.

[0200] The operating environment 1400 also includes one or more local components 1420. The local components 1420 can be hardware and / or software (e.g., threads, processes, computing devices). In one or more embodiments, the local components 1420 can include auto-scaling components and / or programs that communicate / use remote resources 1410 and 1420, etc., connected to a remotely located distributed computing system via a communication framework 1440.

[0201] One possible communication between the remote component 1410 and the local component 1420 can be in the form of data packets adapted to be transmitted between two or more computer processes. Another possible communication between the remote component 1410 and the local component 1420 can be in the form of circuit-switched data adapted to be transmitted between two or more computer processes in radio time slots. The operating environment 1400 includes a communication framework 1440 that can be used to facilitate communication between the remote component 1410 and the local component 1420 and can include an air interface, such as an interface for a UMTS network over an LTE network. The remote component 1410 can include a hard drive, solid-state drive, subscriber identity module (SIM) card, electronic SIM card, or other storage device that can be used to store information on the remote component 1410 side of the communication framework 1440. The local component 1420 may be operably connected to one or more remote data stores 1450, such as a SIM, eSIM, device memory, etc. Similarly, the local component 1420 may be operably connected to one or more local data stores 1430 that may be employed to store information on the local component 1420 side of the communications framework 1440.

[0202] Exemplary Computing Environment To provide additional context for the various embodiments described herein, Figure 15 and the following discussion are intended to provide a brief, general description of a suitable computing environment 1500 in which various embodiments of the embodiments discussed herein may be implemented. While the embodiments have been described above in the general context of computer-executable instructions that may be executed on one or more computers, those skilled in the art will recognize that the embodiments may also be implemented in combination with other program modules and / or as a combination of hardware and software.

[0203] Generally, program modules include routines, programs, components, data structures, etc. that perform tasks or implement abstract data types. Furthermore, the methods may be practiced with other computer system configurations, including single-processor or multi-processor computer systems, minicomputers, mainframe computers, Internet of Things (IoT) devices, distributed computing systems, and personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics, and the like, each of which may be operatively coupled to one or more associated devices.

[0204] The illustrated embodiments of the present specification may also be practiced in distributed computing environments where certain tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[0205] Although a computing device typically includes a variety of media, which may include a computer-readable storage medium, a machine-readable storage medium, and / or a communication medium, these two terms are used differently herein as follows. A computer-readable storage medium or a machine-readable storage medium may be any available storage medium that can be accessed by a computer, and includes both volatile and nonvolatile media, removable and non-removable media. By way of example and not limitation, a computer-readable storage medium or a machine-readable storage medium may be implemented in connection with any method or technology for storing information, such as computer-readable or machine-readable instructions, program modules, structured data, or unstructured data.

[0206] A computer-readable storage medium may include, but is not limited to, random access memory (RAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD ROM), digital versatile disk (DVD), Blu-ray disc (BD) or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device, solid-state drive or other solid-state storage device, or other tangible and / or non-transitory medium that can be used to store the desired information. In this regard, the terms "tangible" or "non-transitory" as applied to storage, memory, or computer-readable medium herein exclude only the propagating transitory signal itself as a modifier, and do not disclaim all standard storage, memory, or computer-readable medium that do not merely propagate the transitory signal itself.

[0207] The computer-readable storage medium can be accessed by one or more local or remote computing devices for various operations on the information stored by the medium, for example, via access requests, queries, or other data retrieval protocols.

[0208] Communication media typically embodies computer-readable instructions, data structures, program modules, or other structured or unstructured data in a data signal, such as a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery or transmission media. The term "modulated data signal" or signal refers to a signal that has one or more characteristics set or changed in such a manner as to encode information in the signal or signals. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media.

[0209] 15, an exemplary computing environment 1500 in which one or more embodiments described herein can be implemented includes a computer 1502, which includes a processing unit 1504, a system memory 1506, and a system bus 1508. The system bus 1508 couples system components, including but not limited to the system memory 1506, to the processing unit 1504. The processing unit 1504 can be any of a variety of commercially available processors. Dual microprocessors and other multi-processor architectures can also be used as the processing unit 1504.

[0210] The system bus 1508 may be any of several types of bus structures that may be further interconnected to a memory bus (with or without a memory controller), a peripheral bus, and a local bus using any of a variety of commercially available bus architectures. The system memory 1506 includes a ROM 1510 and a RAM 1512. The basic input / output system (BIOS) may be stored in non-volatile memory such as a ROM, erasable programmable read-only memory (EPROM), or EEPROM, and contains the basic routines that help to transfer information between elements within the computer 1502, such as during start-up. The RAM 1512 may also include a high-speed RAM, such as static RAM, for caching data.

[0211] The computer 1502 also includes an internal hard disk drive. The computing environment 1500 may further include an internal HDD (HDD) 1514 (e.g., EIDE, SATA), and may include one or more external storage devices 1516 (e.g., a magnetic floppy disk drive (FDD) 1516, a memory stick or flash drive reader, a memory card reader, etc.). While the internal HDD 1514 is illustrated as being located within the computer 1502, the internal HDD 1514 may also be configured for external use in a suitable chassis (not shown). Additionally, although not shown in the computing environment 1500, a solid-state drive (SSD) may be used in addition to or in place of the HDD 1514.

[0212] Other internal or external storage devices may include at least one other storage device 1520 having a storage medium 1522 (e.g., a solid-state storage device, a non-volatile memory device, and / or an optical disk drive capable of reading from removable media such as CD-ROM disks, DVDs, BDs, etc.). The external storage device 1516 may be facilitated by a networked virtual machine. The HDD 1514, the external storage device 1516, and the storage device (e.g., drive) 1520 may be connectable to the system bus 1508 by an HDD interface 1524, an external storage interface 1526, and a drive interface 1528, respectively.

[0213] The drives and their associated computer-readable storage media provide non-volatile storage of data, data structures, computer-executable instructions, etc. In the case of computer 1502, the drives and storage media accommodate the storage of any data in a suitable digital format. Although the above description of computer-readable storage media refers to each type of storage device, other types of storage media readable by a computer, whether currently existing or developed in the future, may also be used in the exemplary operating environment, and further, any such storage media may contain computer-executable instructions for performing the methods described herein.

[0214] A number of program modules, including an operating system 1530, one or more application programs 1532, other program modules 1534, and program data 1536, may be stored in the drives and RAM 1512. All or portions of the operating system, applications, modules, and / or data may also be cached in RAM 1512. The systems and methods described herein can be implemented using various commercially available operating systems or combinations of operating systems.

[0215] Computer 1502 may optionally include emulation technology. For example, a hypervisor (not shown) or other intermediary may emulate the hardware environment of operating system 1530, where the emulated hardware may optionally differ from the hardware illustrated in FIG. 15 . In one such embodiment, operating system 1530 may include one of multiple virtual machines (VMs) hosted on computer 1502. Additionally, operating system 1530 may provide a runtime environment, such as the Java Runtime Environment or the .NET Framework, for application 1532. A runtime environment is a consistent execution environment that allows application 1532 to run on any operating system that includes the runtime environment. Similarly, operating system 1530 may support containers, where application 1532 may be in the form of a container, which is a lightweight, standalone executable package of software that includes, for example, code, runtime, system tools, system libraries, and settings for the application.

[0216] Additionally, the computer 1502 may include a trusted processing module. This can be enabled with a security module such as a Trusted Platform Module (TPM). For example, with a TPM, a boot component can then hash the boot component in time and wait for the result to match a secure value before loading the next boot component. This process can occur at any layer in the code execution stack of computer 1502, and can be applied at the application execution level or the operating system (OS) kernel level, for example, thereby enabling security at any level of code execution.

[0217] A user entity can enter commands and information into the computer 1502 through one or more wired / wireless input devices, such as a keyboard 1538, a touchscreen 1540, and a pointing device such as a mouse 1542. Other input devices (not shown) can include a microphone, an infrared (IR) remote control, a radio frequency (RF) remote control, or other remote controls, a joystick, a virtual reality controller and / or headset, a gamepad, a stylus pen, an image input device such as a camera, a gesture sensor input device, a visual motion sensor input device, an emotion or face detection device, a biometric input device such as a fingerprint or iris scanner, etc. These and other input devices are often connected to the processing unit 1504 through an input device interface 1544, which can be coupled to the system bus 1508, but can also be connected by other interfaces, such as a parallel port, an IEEE 1394 serial port, a game port, a USB port, an IR interface, a BLUETOOTH interface, etc.

[0218] A monitor 1546 or other type of display device can also be connected to the system bus 1508 via an interface, such as a video adapter 1548. In addition to the monitor 1546, computers typically include other peripheral output devices (not shown), such as speakers, printers, etc.

[0219] The computer 1502 can operate in a networked environment using wired and / or wireless logical connections to one or more remote computers, such as a remote computer 1550. The remote computer 1550 may be a workstation, a server computer, a router, a personal computer, a portable computer, a microprocessor-based entertainment device, a peer device, or other common network node, and typically includes many or all of the elements described relative to the computer 1502, although for simplicity, only a memory / storage device 1552 is illustrated. The depicted logical connections include wired / wireless connections to a local area network (LAN) 1554 and / or a wide area network (e.g., a wide area network (WAN) 1556). Such LAN and WAN networking environments are commonplace in offices and businesses and facilitate enterprise-wide computer networks, such as intranets, all of which can connect to a global communications network, e.g., the Internet.

[0220] When used in a LAN networking environment, the computer 1502 can be connected to the local network 1554 via a wired and / or wireless communication network interface or adapter 1558. The adapter 1558 can facilitate wired or wireless communication to the LAN 1554, and the LAN can also include a wireless access point (AP) disposed thereon for communicating with the adapter 1558 in a wireless mode.

[0221] When used in a WAN networking environment, the computer 1502 may include a modem 1560 or may be connected to a communications server on the WAN 1556 via other means for establishing communications over the WAN 1556, such as the Internet. The modem 1560 may be internal or external, and a wired or wireless device, and may be connected to the system bus 1508 via the input device interface 1544. In a networked environment, program modules depicted relative to the computer 1502, or portions thereof, may be stored in the remote memory / storage device 1552. The network connections shown are examples, and other means of establishing a communications link between computers may be used.

[0222] When used in either a LAN or WAN networking environment, computer 1502 can access a cloud storage system or other network-based storage system in addition to, or instead of, external storage device 1516, as described above. Generally, the connection between computer 1502 and the cloud storage system can be established via LAN 1554 or WAN 1556, for example, by adapter 1558 or modem 1560, respectively. Upon connecting computer 1502 to an associated cloud storage system, external storage interface 1526, with the aid of adapter 1558 and / or modem 1560, can manage the storage provided by the cloud storage system in the same way as other types of external storage. For example, external storage interface 1526 can be configured to provide access to cloud storage sources as if those sources were physically connected to computer 1502.

[0223] The computer 1502 may be operable to communicate with any wireless device or entity operatively arranged for wireless communication, such as a printer, a scanner, a desktop and / or portable computer, a portable data assistant, a communications satellite, any equipment or location associated with a radio-detectable tag (e.g., a kiosk, a newsstand, a store shelf, etc.), and a telephone. This may include Wireless Fidelity (Wi-Fi) and BLUETOOTH® wireless technologies. Thus, communication may be in a defined structure similar to an existing network, or simply ad-hoc communication between at least two devices.

[0224] Additional Information The embodiments described herein may be directed to one or more of a system, a method, an apparatus, and / or a computer program product at any possible level of technical detail of integration. A computer program product may include a computer-readable storage medium having computer-readable program instructions for causing a processor to execute aspects of one or more embodiments described herein. A computer-readable storage medium may be a tangible device capable of holding and storing instructions for use by an instruction-execution device. A computer-readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a superconducting storage device, and / or any suitable combination thereof. A non-exhaustive list of more specific examples of computer-readable storage media may also include the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (ERM), a programmable logic device (PLC ... programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital versatile disk (DVD), memory stick, floppy disk, mechanically encoded devices such as punch cards or raised structures in grooves with instructions recorded on them, and / or any suitable combination of the foregoing. As used herein, computer-readable storage medium should not be construed as being a transitory signal per se, such as radio waves and / or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides and / or other transmission media (e.g., light pulses passing through fiber optic cables), and / or electrical signals transmitted over wires.

[0225] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device and / or to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing / processing device. The computer-readable program instructions for carrying out the operations of one or more embodiments described herein may be source code and / or object code written in any combination of one or more programming languages, including assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, integrated circuit configuration data, and / or object code written in one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, and / or procedural programming languages ​​such as the "C" programming language and / or similar programming languages. The computer-readable program instructions may execute entirely on the computer, partially on the computer, as a standalone software package, partially on the computer, and / or partially on a remote computer, or entirely on a remote computer and / or server. In the latter scenario, the remote computer may be connected to the computer via any type of network, including a local area network (LAN) and / or a wide area network (WAN), and / or may be connected to an external computer (e.g., via the Internet using an Internet Service Provider).In one or more embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGAs), and / or programmable logic arrays (PLAs), can execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry to perform aspects of one or more embodiments described herein.

[0226] Aspects of one or more embodiments described herein will be described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to one or more embodiments described herein. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, and / or other programmable data processing apparatus to generate a machine such that the instructions, executed by the processor of the computer or other programmable data processing apparatus, create means for implementing the function(s) / act(s) specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can be stored on a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and / or other device to function in a particular manner, whereby the computer-readable storage medium having instructions stored therein can include an article of manufacture containing instructions that can implement aspects of the function(s) / act(s) specified in one or more blocks of the flowchart and / or block diagram. The computer-readable program instructions may also be loaded into a computer, other programmable data processing apparatus, and / or other device to cause a series of operational acts to be executed on the computer, other programmable apparatus, and / or other device to generate a computer-executed process, whereby the instructions executing on the computer, other programmable apparatus, and / or other device implement the functions / acts specified in one or more blocks of the flowcharts and / or block diagrams.

[0227] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and / or operation of possible implementations of systems, computer-executable methods, and / or computer program products according to one or more embodiments described herein. In this regard, each block in a flowchart or block diagram may represent a module, segment, and / or portion of an instruction, which comprises one or more executable instructions for implementing the specified logical function(s). In one or more alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may be executed substantially concurrently and / or the blocks may sometimes be executed in the reverse order, depending on the functionality involved. It should also be noted that each block of the block diagrams and / or flowchart illustrations, and / or combinations of blocks in the block diagrams and / or flowchart illustrations, may be implemented by a special-purpose hardware-based system capable of performing the specified functions and / or acts and / or executing one or more combinations of special-purpose hardware and / or computer instructions.

[0228] While the subject matter has been described above in the general context of computer-executable instructions for a computer program product executed on one and / or more computers, those skilled in the art will recognize that one or more embodiments herein can also be implemented, at least in part, in parallel with one or more other program modules. Generally, program modules include routines, programs, components, and / or data structures that perform particular tasks and / or implement particular abstract data types. Furthermore, the computer-implemented methods described above can be implemented with single-processor and / or multiprocessor computer systems, minicomputing devices, mainframe computers, and other computer system configurations, including computers, handheld computing devices (e.g., PDAs, phones), and / or microprocessor-based or programmable consumer and / or industrial electronic devices. The illustrated aspects can also be practiced in distributed computing environments where tasks are performed by remote processing devices linked through a communications network. However, one or more, if not all, aspects of one or more embodiments described herein can be implemented on stand-alone computers. In a distributed computing environment, program modules can be located in both local and remote memory storage devices.

[0229] As used herein, the terms “component,” “system,” “platform,” and / or “interface” can refer to and / or include computer-related entities or entities associated with an operating machine having one or more particular functions. The entities described herein can be hardware, a combination of hardware and software, software, or software in execution. For example, a component can be, but is not limited to, a process running on a processor, a processor, an object, an executable, a thread of execution, a program, and / or a computer. By way of illustration, both an application running on a server and the server can be a component. One or more components can reside within a process and / or thread of execution, but a component can also be localized on one computer and / or distributed between two or more computers. In another example, each component can execute from various computer-readable media having various data structures stored thereon. Components may communicate via local and / or remote processes, such as according to signals comprising one or more data packets (e.g., data from a local system, another component in a distributed system, and / or one component interacting across a network such as the Internet with other systems via signals). As another example, a component may be a device having a particular functionality provided by mechanical parts operated by electrical or electronic circuits operated by software and / or firmware applications executed by a processor. In such cases, the processor may be internal and / or external to the device and may execute at least a portion of the software and / or firmware applications.As yet another example, a component may be a device that provides a particular functionality through electronic components without mechanical parts, but the electronic component may include a processor and / or other means for executing software and / or firmware that at least partially provides the functionality of the electronic component. In one aspect, a component may emulate the electronic component, for example, via a virtual machine in a cloud computing system.

[0230] Additionally, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or." That is, unless otherwise specified or clear from context, "X employs A or B" is intended to mean all natural inclusive permutations. That is, if X employs A, then X employs B, or if X employs both A and B, then "X employs A or B" is satisfied under any of the foregoing cases. Furthermore, the articles "a" and "an" as used in this specification and the accompanying drawings should generally be interpreted to mean "one or more" unless otherwise specified or clear from context to refer to the singular form. As used herein, the terms "example" and / or "exemplary" are utilized to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter described herein is not limited by such examples. Additionally, any aspect or design described herein as "example" and / or "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects or designs, and is not meant to exclude equivalent exemplary structures and techniques known to those skilled in the art.

[0231] As used herein, the term "processor" may refer to substantially any computing processing unit and / or device, including, but not limited to, a single-core processor, a single processor with software multithreading execution capabilities, a multi-core processor, a multi-core processor with software multithreading execution capabilities, a multi-core processor with hardware multithreading techniques, a parallel platform, and / or a parallel platform with distributed shared memory. Additionally, a processor may refer to an integrated circuit, an application specific integrated circuit (ASIC), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic controller (PLC), a complex programmable logic device (CPLD), discrete gate or transistor logic, discrete hardware components, and / or any combination thereof designed to perform the functions described herein. Furthermore, a processor may utilize nanoscale architectures, such as, but not limited to, molecular-based transistors, switches, and / or gates, to optimize space usage and / or enhance the performance of associated equipment. A processor may be implemented as a combination of computing processing units.

[0232] As used herein, terms such as "store," "storage," "data store," "data storage," "database," and substantially any other information storage component associated with the operation and functionality of a component are utilized to refer to a "memory component," an entity embodied in a "memory," or a component that includes a memory. The memory and / or memory components described herein may be either volatile memory or nonvolatile memory, or may include both volatile and nonvolatile memory. By way of example and not limitation, nonvolatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (Electrically Programmable ROM), and the like. programmable ROM (EPROM), electrically erasable ROM (EEPROM), flash memory, and / or non-volatile random-access memory (RAM) (e.g., ferroelectric RAM) Volatile memory can include, for example, RAM, which can act as external cache memory. By way of example, and not limitation, RAM can be synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DRAM), and so on. data rate SDRAM, DDR SDRAM, enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), direct Rambus RAM Rambus RAM, DRRAM, Direct Rambus Dynamic RAM dynamic RAM (DRDRAM), and / or Rambus dynamic RAM (Rambus dynamic RAM) Memory may be available in many forms, such as RAM, RDRAM, etc. Additionally, the memory components of the systems and / or computer-implemented methods described herein are intended to comprise, but are not limited to, these and / or any other suitable types of memory.

[0233] What has been described above includes merely example systems and computer-implemented methods. Of course, it is not possible to describe every conceivable combination of components and / or computer-implemented methods for purposes of describing one or more embodiments, but one of ordinary skill in the art will recognize that many further combinations and / or permutations of one or more embodiments are possible. Furthermore, to the extent that terms such as "includes," "has," "possesses," and the like are used in the detailed description, claims, appendices, and / or drawings, such terms are intended to be as inclusive as the term "comprising," as "comprising" is interpreted when used as a transitional term in a patent claim.

[0234] Descriptions of various embodiments may be referred to as "an embodiment," "various embodiments," "one or more embodiments," or the like. The phrases "some embodiments" and / or "some embodiments" may be used, each of which may refer to one or more of the same or different embodiments.

[0235] The descriptions of various embodiments are presented for illustrative purposes and are not intended to be exhaustive or limited to the embodiments described herein. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein has been selected to best explain the principles of the embodiments, practical applications and / or technical improvements over technology found in the market, and / or to enable those skilled in the art to understand the embodiments described herein.

Claims

1. 1. A system comprising: a memory for storing computer-executable components; a processor for executing the computer-executable components stored in the memory, the computer-executable components comprising: an identification component that identifies a set of inputs and outputs of the charged particle device; a parameterization component that tracks the inputs and outputs of the set based on a universal clock that is common to the inputs and outputs of the set.

2. The system of claim 1 , wherein the inputs and outputs of the set include XY position inputs and outputs and sensing inputs and outputs.

3. the computer-executable components: a stamping component that timestamps the inputs and outputs with timestamps based on data output from the universal clock; The system of claim 1 , wherein the timestamp is insensitive to changes in the output XY position output.

4. the computer-executable components:

10. The system of claim 1, further comprising a filtering component that filters out interference frequency outputs from the outputs that are affecting an imaging output from the outputs by scanning for interference frequencies corresponding to interference frequency outputs according to the universal clock.

5. the computer-executable components:

10. The system of claim 1, further comprising a synchronization component that determines a second timing of an excitation clock employed for dynamic excitation by a scientific instrument and synchronizes a first timing of the universal clock to the second timing of the excitation clock.

6. 10. The system of claim 1, wherein the universal clock is employed without adjustment of the universal clock being based on environmental disturbances to the scientific instrument, including changes in XY position outputs of the outputs.

7. the computer-executable components: The system of claim 1 , further comprising an evaluation component that identifies time delays between different combinations of inputs, outputs, or both, among the set of inputs and outputs according to the universal clock.

8. the computer-executable components: a recording component configured to record a set of XY position outputs from the scientific instrument; The system of claim 1 , wherein the recording component omits recording XY position outputs corresponding to beam blanking.

9. 1. A computer-implemented method comprising: identifying, by a system operatively coupled to the processor, a set of inputs and outputs of the scientific instrument; and tracking, by the system, the inputs and outputs of the set based on a universal clock common to the inputs and outputs of the set.

10. 10. The computer-implemented method of claim 9, further comprising generating, by the system, timestamps for the inputs and outputs based on data output from the universal clock, wherein the timestamps are not affected by changes in XY position outputs of the outputs.

11. 10. The computer-implemented method of claim 9, further comprising filtering out interference frequency outputs of the outputs that are affecting an imaging output of the outputs by scanning, by the system, for interference frequencies corresponding to interference frequency outputs according to the universal clock.

12. determining, by the system, a first timing of an excitation clock employed for dynamic excitation by the scientific instrument; 10. The computer-implemented method of claim 9, further comprising: synchronizing, by the system, a second timing of the universal clock to the first timing of the excitation clock.

13. 10. The computer-implemented method of claim 9, further comprising employing the universal clock by the system without adjustment of the universal clock based on environmental disturbances to the scientific instrument, including changes in XY position outputs of the outputs.

14. 10. The computer-implemented method of claim 9, further comprising identifying, by the system, time delays between different combinations of inputs, outputs, or both, among the set of inputs and outputs according to the universal clock.

15. recording, by the system, a set of XY position outputs from the scientific instrument; 10. The computer-implemented method of claim 9, wherein said recording comprises omitting recording of XY position outputs corresponding to beam blanking.

16. 1. A computer program that facilitates a process for tracking inputs and outputs of a scientific device, the computer program being included in a computer-readable storage medium having program instructions embodied thereon, the program instructions being executable by a processor, the processor causing the processor to identify a set of scientific instrument inputs and outputs; and A computer program causing the processor to track the inputs and outputs of the set based on a universal clock common to the inputs and outputs of the set.

17. The program instructions are further executable by the processor to cause the processor to:

17. The computer program of claim 16, wherein the processor generates timestamps for the inputs and outputs based on data output from the universal clock, and the timestamps are not affected by changes in XY position outputs among the outputs.

18. The program instructions are further executable by the processor to cause the processor to:

17. The computer program product of claim 16, further comprising causing the processor to filter out interference frequency outputs from the outputs that are affecting an imaging output from the outputs by scanning for interference frequencies corresponding to interference frequency outputs according to the universal clock.

19. The program instructions are further executable by the processor to cause the processor to:

17. The computer program product of claim 16, causing the processor to adopt the universal clock without adjustment of the universal clock based on environmental disturbances to the scientific instrument, including changes in XY position outputs of the outputs.

20. The program instructions are further executable by the processor to cause the processor to:

17. The computer program product of claim 16, further comprising causing the processor to identify time delays between different combinations of inputs, outputs, or both, of the set of inputs and outputs according to the universal clock.

Images