Multi-modal signal acquisition through universal clock synchronization

Abstract

The invention relates to multi-modal signal acquisition synchronized by a universal clock. Embodiments described herein relate to a process for multi-modal signal acquisition, such as from charged particle devices or other scientific instruments based on universal clock synchronization of various multi-modal signals. A system may include a memory storing computer executable components; and a processor executing the computer executable component stored in the memory, where the computer executable component includes an identification component that identifies a set of inputs and outputs of a scientific instrument; and a parameterization component that tracks the inputs and outputs in the set based on a common clock that is common to the inputs and outputs in the set.

Description

Background Technology

[0001] Scientific experiments may involve acquiring input and output signals based on different timelines and other tracking methods (such as based on location in two-dimensional or three-dimensional space). Analyzing these different signals (such as comparing signals using different timelines and / or tracking methods) can be a difficult process due to gaps in the data, jumps in tracking methods caused by environmental interference, and / or a lack of correlation between tracking methods. Therefore, aggregated sets of signal acquisitions may resemble complex data tangles, making it difficult and / or impossible to determine the relationships within them. Brief description of the attached figures

[0002] The various embodiments will be readily understood from the following detailed description taken in conjunction with the accompanying drawings. For ease of description, the same reference numerals indicate the same structural elements. The various embodiments are shown in the drawings in an exemplary and non-limiting manner.

[0003] Figure 1 A block diagram of an exemplary scientific instrument for performing one or more operations according to one or more embodiments described herein is shown.

[0004] Figure 2 The use of one or more embodiments described herein is demonstrated. Figure 1 A flowchart illustrating an exemplary method for performing operations on scientific instruments.

[0005] Figure 3 A graphical user interface (GUI) is shown that can be used to perform one or more of the methods described herein, according to one or more embodiments described herein.

[0006] Figure 4 A block diagram of an exemplary computing device capable of performing one or more of the methods disclosed herein, according to one or more embodiments described herein, is shown.

[0007] Figure 5 A block diagram of an exemplary non-limiting system that can facilitate the process of tracking the acquisition of input and output signals according to one or more embodiments described herein is shown.

[0008] Figure 6 A block diagram of another exemplary non-limiting system that can facilitate the process of tracking the acquisition of input and output signals according to one or more embodiments described herein is shown.

[0009] Figure 7 This document demonstrates one or more embodiments that can be derived from the present invention. Figure 6 The flowchart shows the signal acquisition workflow of a non-restricted system.

[0010] Figure 8 This document demonstrates one or more embodiments that can be derived from the present invention. Figure 6 The flowchart of the signal acquisition and tracking workflow executed by the unrestricted system.

[0011] Figure 9 This document demonstrates one or more embodiments that can be derived from the present invention. Figure 6 Another flowchart of the signal acquisition and tracking workflow performed by the unrestricted system.

[0012] Figure 10 This document demonstrates one or more embodiments that can be derived from the present invention. Figure 5 A flowchart of one or more processes performed by a signal tracking system.

[0013] Figure 11 This document demonstrates one or more embodiments that can be derived from the present invention. Figure 6 Another flowchart of one or more processes performed by the signal tracking system.

[0014] Figure 12 This document illustrates one or more embodiments based on the description herein. Figure 11 The can be made by Figure 6 A continuation of the flowchart of one or more processes performed by the signal tracking system.

[0015] Figure 13 A block diagram of an exemplary scientific instrument system in which one or more of the methods described herein can be performed, according to one or more embodiments described herein.

[0016] Figure 14 A block diagram illustrating an exemplary operating environment in which embodiments of the subject matter described herein can be incorporated.

[0017] Figure 15 An exemplary schematic block diagram illustrates a computing environment that can be implemented by interacting with and / or at least partially utilizing the topics described herein. Summary of the Invention

[0018] The following overview provides a basic understanding of one or more embodiments described herein. This overview is not intended to identify key or essential elements and / or to depict the scope of a particular embodiment or the claims. Its sole purpose is to present concepts in a simplified form as a prelude to the more detailed description that follows. In one or more embodiments, the systems, computer-implemented methods, apparatuses, and / or computer program products described herein may provide a plug-and-play process for generating identifiers, at least in part, based on an annotation ranking scheme, and / or updating library data storage with such identifiers.

[0019] According to one embodiment, a system may include: a memory storing a computer-executable component; and a processor executing the computer-executable component stored in the memory, wherein the computer-executable component includes: an identification component that identifies a set of inputs and outputs of a scientific instrument; and a parameterization component that tracks the inputs and outputs in the set based on a common clock common to the inputs and outputs in the set.

[0020] According to another embodiment, a computer-implemented method may include: identifying a set of inputs and outputs of a scientific instrument by a system operatively coupled to a processor; and tracking the inputs and outputs in the set by the system based on a common clock common to the inputs and outputs in the set.

[0021] According to yet another embodiment, a computer program product facilitates a process for tracking the inputs and outputs of a scientific device. The computer program product includes a computer-readable storage medium having program instructions embodied therein, which are executable by a processor to cause the processor to: identify a set of inputs and outputs of the scientific instrument; and track the inputs and outputs in the set based on a common clock shared by the inputs and outputs in the set.

[0022] One or more embodiments described herein can be implemented within, connected to, and / or coupled to scientific imaging devices or other scientific instruments, such as charged particle devices.

[0023] One or more embodiments described herein can be employed with different (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 common clock, thereby allowing the inputs and / or outputs of these signal types to be tracked and analyzed relative to each other without data loss, time conversion, etc. Furthermore, environmental disturbances (such as changes in XY position due to physical instability, bumps, vibrations, etc.) will not alter the common clock, as this clock is not based solely on XY position.

[0024] Therefore, parameters can be easily ordered relative to each other, allowing identification of one or more interference frequencies of the environment that interfere with another signal (such as an image output signal), and separation of such one or more interference frequencies.

[0025] In one or more cases, based on one or more embodiments described herein, one or more types of experiments that cannot be performed using existing frameworks can be performed. For example, coincidence measurements and critical dose measurements can benefit from signal comparison provided by using a common universal clock and without signal tracking loss (e.g., signal tracking loss caused by signals obtained serially using XY position tracking as in existing frameworks).

[0026] In one or more cases, since recording the XY position output corresponding to beam blanking can be omitted based on using one or more embodiments described herein, a reduced storage space and bandwidth can be used to store and record the signal.

[0027] One or more implementations described herein can be readily applied to various architectures of existing scientific instruments, signal acquisition instruments, etc. For example, fields such as catalysis, metals, ceramics, magnetic phase transitions, electrical phase transitions, photostimulation, and / or liquid pool research are among those that can benefit from tracking the inputs and outputs of scientific devices relative to a common, universal clock. Detailed Implementation

[0028] The following detailed description is illustrative only and is not intended to limit the implementation and / or application or use of the embodiments. Furthermore, there is no intention to be bound by any express or implied information presented in the foregoing Summary or Detailed Description sections. One or more embodiments are now described with reference to the accompanying drawings, wherein the same reference numerals are used throughout to refer to the same elements. In the following description, numerous specific details are set forth for purposes of explanation in order to provide a more thorough understanding of one or more embodiments. However, it will be apparent that one or more embodiments may be practiced without these specific details in various circumstances.

[0029] Various operations can be described as multiple discrete actions or operations in a manner most conducive to understanding the subject matter disclosed herein. However, the order of description should not be construed as implying that these operations must depend on a specific order. In particular, these operations may be performed in an order different from the order in which they are presented. The described operations may be performed in an order different from the described embodiments. Various additional operations may be performed, and / or the described operations may be omitted in additional embodiments.

[0030] Turning now to the general topic of signal acquisition, a process that can be performed in multiple experimental, information gathering, monitoring, industrial, manufacturing, and / or other scientific processes. It is generally desirable to acquire multiple different signal types, at least partially, in parallel with each other. These signal types can include, but are not limited to, stimulus, detection, scanning, optical, magnetic, electrical phase transition, and / or dynamic excitation signals. These signals can be analyzed offline (e.g., separately from the operation of the corresponding process, experiment, etc.) and / or online (e.g., during the operation of the corresponding process, experiment, etc.).

[0031] Part of this analysis might involve comparing different signals that occur at the same time, relative to the same location, etc. Such analysis can be fraught with difficulties 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 vibration, bumps, etc.) can affect signal acquisition, leading to variations in the acquired signal and / or the reference tracking used. Because of these factors, comparisons between different signal types can be difficult, if not entirely impossible, and require undesirable amounts of bandwidth, time, power, and / or manpower.

[0032] One such example could include image acquisition using a scanning transmission electron microscope (STEM) or other scientific imaging equipment. The operation of such a STEM device could 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 each other. However, the various signal sets may be asynchronous and uncorrelated. Therefore, event recording can be difficult due to the aforementioned drawbacks. For example, vibration may cause movement of the X position, Y position, or XY position (e.g., either or both of X and Y positions). Thus, one signal type may be based on XY position, while another may be collected based on sequential time points. Consequently, sorting the data based on the acquired signals can be difficult because time is constant but XY positions are unstable. Furthermore, based on this, related errors may be introduced into artifact compensation and / or dynamic behavior analysis based on the acquired signals / data obtained from them.

[0033] These correlated errors may be difficult to identify and / or filter out. In one or more cases, such correlated errors may go undetected, leading to inaccurate data. In one or more cases, such correlated errors may cause data loss, signal / data misalignment, and / or inability to align signals / data with each other. In one or more cases, such correlated errors may result in undesirable amounts of bandwidth, time, power, and / or manpower associated with event logging and / or dynamic experimental setups. In fact, such correlated errors may make it difficult to reproduce such dynamic experiments.

[0034] Another example of this could involve dynamic excitation via laser, where a scaffold or other device positioned in the electron beamline can employ a clock to monitor changes in stimulation parameters over time; this clock is separate from the excitation clock used to monitor the excitation. Because the corresponding timelines are not correlated, a phase-locked loop experiment may not be possible. Therefore, events on the illumination side of such an experiment are temporally uncorrelated with events on the detection side.

[0035] In other words, STEM scanning experiments can include serial acquisition of accessed scan points, as well as serial acquisition in time and space by accessing scan points in a time-point sequence. This may mean that at least the XY positions differ from other dynamically changing optical aspects (e.g., deflectors, blanking devices, stimulators, etc.), and therefore the detected signals may be uncorrelated. Therefore, stamping the data obtained from the signals with the time of the events may be impossible or extremely difficult. To achieve such stamping, various signals need to be synchronized to the event stream. This can lead to ordering parameters that may change due to environmental disturbances to the experiment and / or the system operating the experiment.

[0036] To address one or more shortcomings of existing frameworks of this kind, this paper describes one or more implementations that can provide improved accuracy and / or efficiency in data correlation based on the acquisition of different types of multimodal signals. Different signals may be based on different timelines, clocks, and / or other tracking methods, but are synchronized to a single or common general-purpose clock through one or more implementations described herein.

[0037] In other words, STEM scanning experiments addressed by one or more embodiments described herein can include serial acquisition of accessed scan points, as well as serial acquisition in time space by accessing scan points in a time-point sequence. Based on the use of a common universal clock and without using XY position as a tracking method, XY position can be used for other dynamically changing optical aspects (e.g., deflectors, blankers, stimulators, etc.), and the detected signals can be time-stamped with the time of event occurrence. To achieve this stamping, various signals can be synchronized to the event stream based on a common universal clock. This can include stamping the XY position with timestamps similar to those of detectors, active blankers, and / or ultrafast cavity components (e.g., parameterizing the XY position). Therefore, sorting parameters that do not change due to environmental disturbances, such as conventional XY position, can be employed because time is constant, while XY position may vary due to its instability.

[0038] In one or more cases, by timestamping all events, a five-dimensional (5D) space can be generated for the X-position or Y-position of a beam in a static experiment. The 5D space in a static experiment can further include the energy loss spectrum (e.g., approximately 0–40 keV) of the energy-dispersive X-ray spectrum or the electron energy loss spectrum (e.g., approximately 0–40 keV), denoted as dE. The 5D space in a static experiment can further include electrons detected below the sample at different scattering angles kx and ky (e.g., within the 0–300 mRa sq. dV range). Additionally and / or alternatively, detecting backscattered electrons and / or secondary electrons, as well as signals above the cathodoluminescent sample, can increase the dimension of the timestamped space. Additionally and / or alternatively, a seven-dimensional space can be further generated, and this seven-dimensional space can include electron use or non-use and stimulus dynamics from non-static experiments.

[0039] One or more benefits may include better instability compensation for multimodal signals through software and / or hardware (whether or not artificial intelligence analysis is used). As used herein, the term "multimodal" refers to a signal or other tracking data having different types of data, also referred to herein as a signal. Examples may include, but are not limited to, stimulus, optical, scanning, detection, and / or excitation signals and / or XY positions.

[0040] For example, compared to better instability compensation via software, interference frequencies of environmental disturbances can be found when the time axis is used as a reference for a STEM image signal or spectral signal map, allowing such interference frequencies to be separated from the desired signal. Environmental disturbances and / or interference frequencies can include, but are not limited to, energy axis time-varying (EELS), drift, vibration, and / or fixed frequencies in real space (e.g., X& position artifacts). Frequencies in energy space can be found in real space, and correlations can allow for better identification of frequencies for software compensation according to one or more embodiments described herein.

[0041] For another example, compared to better instability compensation via hardware, the dwell time per pixel can be defined by the frequency of access to that pixel when scanning at the fastest speed of the scanning unit. During analysis, the time series of the signal in that pixel can provide information about damage and / or scanning artifacts. It should be noted that when using variable dwell times, only one point in time is provided, making this analysis impossible. When using existing frames, compensation can be performed across the entire frame, which allows for compensation drift but not for compensation frequency (marking) or sample degradation (damage). In contrast, using one or more embodiments described herein, and distributing energy more evenly with the fastest dwell time, can be addressed through synchronized tracking. Additionally and / or alternatively, temperature gradients, damage-causing electronic gradients (charging), and / or scanning artifacts can be addressed through synchronized tracking.

[0042] Additionally and / or alternatively, one or more other benefits may include: the ability to correlate various types of signals (e.g., to correlate multimodal signals), the insensitivity of environmental interference to the acquired signal, the ability to easily separate unwanted frequencies, the ability to employ new types of dynamic experiments, the ability to use the system described herein in various signal acquisition frameworks (e.g., various different hardware, software and / or firmware), the ability to apply one or more embodiments described herein to multiple different industries, and / or the reduction in time, energy, memory and / or bandwidth used for signal acquisition due to not recording signal / data points corresponding to beam blanking.

[0043] The following discussion turns to a general discussion of one or more scientific instrument systems, related methods, computing devices, and / or computer-readable media disclosed herein. For example, in one or more embodiments, the system may include: a memory storing computer-executable components; and a processor executing the computer-executable components stored in the memory, wherein 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 inputs and outputs in the set based on a common clock common to the inputs and outputs in the set.

[0044] One or more embodiments disclosed herein can achieve improved performance relative to existing methods, as noted above. For example, using a common universal clock to track XY position and other acquired signals (e.g., acquired multimodal signals) allows for the tracking and analysis of inputs and / or outputs of these signal types relative to each other without data loss, time conversion, etc. Furthermore, environmental disturbances (such as changes in XY position due to physical instability, bumps, vibrations, etc.) do not alter the universal clock, as this clock is not solely based on XY position.

[0045] Therefore, the embodiments disclosed herein can provide improvements to scientific instrumentation techniques (e.g., improvements to the computer technology supporting such scientific instruments, and others) applicable to sample analysis in a variety of fields, including, but not limited to, optics, signal processing, spectroscopy (e.g., electron energy loss spectroscopy, mass spectrometry, 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 may include, but are not limited to, those related to catalysis, metals, ceramics, magnetic phase transitions, electrical phase transitions, photostimulation, and / or liquid pool research.

[0046] The various implementations of the embodiments disclosed herein can improve upon existing methods to achieve the technical advantages of high-information and / or accurate information analysis based on multimodal signal acquisition, from which such information can be obtained. In other words, one or more embodiments described herein can provide parameterization of various signal inputs and / or outputs of the same experiment, operation, and / or process, while allowing identification of one or more interference frequencies of another signal (such as an image output signal) that interfere with the environment, and the separation of such one or more interference frequencies.

[0047] In one or more cases, based on one or more embodiments described herein, one or more types of experiments that cannot be performed using existing frameworks can be performed. For example, coincidence measurements and critical dose measurements can benefit from signal comparison provided by using a common universal clock and without signal tracking loss (e.g., signal tracking loss caused by signals obtained serially using XY position tracking as in existing frameworks).

[0048] In one or more cases, since recording the XY position output corresponding to beam blanking can be omitted based on using one or more embodiments described herein, a reduced storage space and bandwidth can be used to store and record the signal.

[0049] One or more implementation schemes described herein can be applied plug-and-play to various architectures of existing scientific instruments, signal acquisition instruments, etc.

[0050] These may be useful applications and / or processes for various industries employing materials analysis, product manufacturing, quality control, etc. Therefore, the embodiments disclosed herein can provide improvements to scientific instrumentation technology (e.g., improvements to the computer technology supporting such scientific instruments, and others).

[0051] These technological advantages are unattainable by conventional and / or existing methods as described above, and all user entities that include systems with such implementations can benefit from these advantages (e.g., by assisting user entities in performing technical tasks, such as cross-modal information analysis based on multimodal signal acquisition).

[0052] Therefore, apart from, but not limited to, the technical features of the embodiments disclosed herein (e.g., the application of a common clock, the addition of timestamps according to the common clock, the identification of interference frequencies, etc.) are obviously unconventional in signal acquisition in the general field of materials analysis, as are the combinations of features of the embodiments disclosed herein.

[0053] As further discussed 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 not only relate to the collection and / or comparison of information, but can apply new analytical and technical techniques to transform the operation of computer analysis of material compounds. For example, by employing a common universal clock, allowing the generation and application of timestamps that can correlate with each other without differences (such as due to environmental influences), comparisons used to determine relationships between acquired signals, event determination based on multimodal signals, and other tasks that can be performed by classical computers and / or one or more artificial intelligences employing the results of one or more embodiments described herein, can become more efficient and accurate over time. In other words, because signals are acquired and synchronized according to a common universal clock without using variable XY positions as synchronization elements, but rather synchronizing the XY positions along with other inputs and outputs, a larger scale of accurate comparison data is generated for searches, queries, event determinations, signal comparisons, and / or other analyses performed relative to various multimodal signals synchronized through one or more embodiments described herein. Therefore, one or more non-limiting systems described herein (including signal tracking systems, as described herein) can be self-improving.

[0054] Therefore, this disclosure introduces functionality that is impossible for existing computing devices and humans to perform. Conversely, such existing computing devices are ineffective in analyzing multimodal acquired signal data and / or synchronizing multimodal signals, including serially tracking XY positions, without considering XY position differences and / or environmental interference data, while one or more embodiments described herein provide this process. Operating under the limitations of existing methods is impractical, considering the time, energy, and / or data loss involved.

[0055] Therefore, embodiments of this disclosure can serve any of a number of technical purposes, such as controlling a particular technical system or process; determining how to control a machine based on measurements; digital audio, image, or video enhancement 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 sensor data processing. In particular, this disclosure provides technical solutions to technical problems, including but not limited to: holographic modification; image / signal blurring; application of combined blurring techniques; and / or subsequent image reconstruction, thereby resulting in faster, more thorough, and / or more efficient processing of the generated images and thus of the material sample or other target composition being imaged.

[0056] Therefore, the embodiments disclosed herein provide improvements to materials analysis techniques (e.g., improvements to computer technologies that support materials analysis, and others).

[0057] As used in this article, the phrase “based on” should be understood to mean “at least partially based on”, unless otherwise specified.

[0058] As used herein, the term "component" may refer to an atomic element, a molecular element, a phase of atomic or molecular elements, or a combination thereof.

[0059] As used in this article, the term "data" may include metadata.

[0060] As used herein, the terms “entity,” “requesting entity,” and “user entity” can refer to a machine, device, component, hardware, software, intelligent device, party, organization, individual, and / or human being.

[0061] As used herein, the term "sample" can refer to a single material, multiple materials, a composition, a compound, a solution, a product, etc.

[0062] As used herein, the term "signal" can refer to input and / or output communications, transmissions, readings, etc., provided in any suitable format, including but not limited to digital data, electrical signals, fiber optic signals, magnetic signals, optical signals, visible light, audible sound, sound, vibration, and / or tactile signals.

[0063] One or more embodiments will now be described with reference to the accompanying drawings, wherein the same reference numerals are used throughout to refer to the same drawing elements. In the following description, numerous specific details are set forth for illustrative purposes in order to provide a more thorough understanding of one or more embodiments. However, it will be apparent that in various cases, one or more embodiments may be practiced without these specific details.

[0064] Furthermore, it should be understood that the embodiments depicted in one or more of the accompanying drawings described herein are for illustrative purposes only, and therefore the architecture of the embodiments is not limited to the systems, devices and / or components depicted therein, nor to any particular order, connection and / or coupling of the systems, devices and / or components depicted therein.

[0065] Specifically, let's now turn to one or more accompanying figures, starting with... Figure 1 This document illustrates a block diagram of a scientific instrument module 100 for performing materials analysis operations using a signal tracking process, according to various embodiments described herein. The scientific instrument module 100 may be implemented by a computing device with circuitry (e.g., including electrical and / or optical components) such as programming. The logic components of the scientific instrument module 100 may be included in a single computing device or distributed across multiple computing devices that may communicate with each other, as appropriate. References herein Figure 4 The computing device 400 discusses examples of computing devices that can implement the scientific instrument module 100 alone or in combination, and this document refers to Figure 13 The scientific instrument system 1300 discusses an example of an interconnected computing device system in which scientific instrument modules 100 can be implemented across one or more computing devices.

[0066] Scientific instrument module 100 may include a first logic unit 102, a second logic unit 104, a third logic unit 106, and a fourth logic unit 108. As used herein, the term "logic unit" may include means for performing a set of operations logically associated. For example, any logic element included in module 100 may be implemented by one or more computing devices programmed with instructions to cause one or more processing devices of the computing device to perform an associated set of operations. In a particular embodiment, 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 an associated set of operations. 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 in a module may take the same form or may take different forms. For example, some logic elements in a module may be implemented by a programmed general-purpose processing device, while other logic elements in the module may be implemented by an application-specific integrated circuit (ASIC). In another example, different logical elements within a module may be associated with different sets of instructions executed by one or more processing devices. A module may omit one or more logical elements depicted in the associated diagram; for example, a module may include a subset of the logical elements depicted in the associated diagram when it is to perform a subset of the operations discussed herein with reference to the module.

[0067] The first logic unit 102 can receive, locate, download, request, measure, and / or otherwise determine a set of signals, and thus determine a set of inputs and outputs (e.g., data and / or metadata) corresponding to that set of signals. That is, the first logic unit 102 can obtain data for processing and subsequently for generating timestamps and / or performing signal comparisons.

[0068] The second logic unit 104 can perform a data timestamping process by timestamping the inputs and outputs based on the data output from the general-purpose clock. That is, the second logic unit 104 can use the output of the first logic unit 102 as the trigger for the second logic unit 104.

[0069] The third logic unit 106 can track inputs and outputs based on a general-purpose clock and a timestamp output from the second logic unit 104, specifically by filtering out interference frequencies corresponding to interference outputs of the inputs and outputs. In other words, the third logic unit 106 can be executed using the output of the second logic unit 104.

[0070] The fourth logic unit 108 can analyze the data output from the general-purpose clock in order to specifically synchronize another clock with the general-purpose clock.

[0071] Figure 2 Flowcharts are shown of methods 200 performed by a scientific instrument module 100 according to various embodiments. Although the operation of method 200 may be referenced to specific embodiments disclosed herein (e.g., references herein to…),… Figure 1 Module 100 of scientific instruments discussed in this article; references. Figure 3 The GUI 300 discussed in this article is referenced. Figure 4 The computing device 400 discussed and / or referenced herein Figure 13 The scientific instrument system 1300 discussed is used for illustration, but method 200 can be used in any suitable setup to perform any suitable operation. Figure 2 Operations are displayed once in a specific order, but can be reordered and / or repeated as needed and as appropriate (e.g., different operations can be executed in parallel where appropriate).

[0072] At 202, a first operation can be performed. For example, the first logic component 102 of module 100 can perform the first operation 202. The first operation 202 may include receiving, searching, locating, downloading, requesting, measuring and / or otherwise determining a set of signals, and thus determining a set of inputs and outputs (e.g., data and / or metadata) corresponding to that set of signals.

[0073] At 204, a second operation can be performed. For example, the second logic component 104 of module 100 can perform the second operation 204. The second operation 204 may include comparing data output from a general-purpose clock with metadata associated with the inputs and outputs to generate timestamps based on the general-purpose clock and apply them to the inputs and outputs.

[0074] At 206, a third operation can be performed. For example, the third logic unit 106 of module 100 can perform the third operation 206. The third operation 206 may include analyzing the inputs and outputs based on timestamps to determine the interference frequency outputs related to the interference of at least partially overlapping imaging outputs, and filtering out unwanted interference frequency outputs.

[0075] At 208, a fourth operation can be performed. For example, the fourth logic unit 108 of module 100 can perform a fourth operation 208. The fourth operation 208 may include analyzing the data output from the general-purpose clock to synchronize another clock (such as the excitation clock) with the general-purpose clock.

[0076] The scientific instrumentation methods disclosed herein may include interactions with user entities (e.g., via references herein). Figure 13The discussion focuses on user-local computing devices (1320). These interactions may include providing information to user entities (e.g., about scientific instruments such as...). Figure 13 Information on the operation of the scientific instrument 1310; information about the sample being analyzed or other tests or measurements performed by the scientific instrument; information retrieved from local or remote databases; or other information, or providing options for the user entity to input commands (e.g., controlling the scientific instrument, such as...). Figure 13 The scientific instrument 1310 can be used to operate or control the analysis of data generated by the scientific instrument, query (e.g., query a local or remote database), or other information. In some embodiments, these interactions can be performed via a graphical user interface (GUI), which includes a display device (e.g., referenced herein). Figure 4 A visual display on a display device 410 (discussed herein) that provides output to a user entity and / or prompts the user entity to provide input (e.g., via reference herein). Figure 4 Other I / O devices discussed 412 include one or more input devices, such as a keyboard, mouse, trackpad, or touchscreen. The scientific instrument system 1300 disclosed herein may include any GUI suitable for interaction with a user entity.

[0077] Next turn Figure 3 This document depicts an exemplary GUI 300, which can be used to perform one or more of the methods described herein, according to various embodiments. As noted above, the GUI 300 can be set in a scientific instrument system (e.g., as referenced herein). Figure 13 The computing device of the scientific instrument system 1300 discussed herein (e.g., referenced herein) Figure 4 The display device of the computing device 400 discussed herein (e.g., referenced herein) Figure 4 The display device discussed is 410), and the user entity can use any suitable input device (e.g., the one referenced herein). Figure 4 Other I / O devices (including any input devices in the discussion 412) and input technologies (e.g., cursor movement, motion capture, facial recognition, gesture detection, speech recognition, button actuation, etc.) interact with GUI 300.

[0078] The GUI 300 may include a data display area 302, a data analysis area 304, a scientific instrument control area 306, and a settings area 308. Figure 3 The specific number and arrangement of areas depicted are merely illustrative, and any number and arrangement of areas, including any desired characteristics thereof, may be included in GUI 300.

[0079] Data display area 302 can display data generated by scientific instruments (e.g., as referenced in this article). Figure 13The data generated by the scientific instrument 1310 discussed. For example, the data display area 302 can display one or more output results, which may include one or more timing, signal frequency, input, output, timestamp, etc., but are not limited to.

[0080] Data analysis area 304 can display the results of data analysis (e.g., the results of analyzing the data displayed in data display area 302 and / or other data). For example, data analysis area 304 can display one or more analyses comparing a pair of signals based on their corresponding timestamps. In one or more embodiments, data display area 302 and data analysis area 304 can be combined in GUI 300 (e.g., including data output from scientific instruments and some analysis of the data in a public graphic or area).

[0081] Scientific instrument control area 306 may include allowing a user entity to control a scientific instrument (e.g., as referenced herein). Figure 13 Options for the scientific instrument 1310 under discussion. For example, the scientific instrument control area 306 may include one or more controls for customizing the amount of data being analyzed (e.g., number of signals, frequency range, signal time range, etc.).

[0082] Setting up area 308 may include features and functions that allow user entities to control GUI 300 (and / or other GUIs), and / or perform common computational operations on data display area 302 and data analysis area 304 (e.g., storing data on storage devices, such as those referenced herein). Figure 4 The discussion covers storage device 404; sending data to another user entity; timestamping data, etc. For example, settings area 308 may include one or more options for changing the color, fill, or format of a graphic (such as a graphic of one or more acquired and tracked signals).

[0083] As noted above, the scientific instrument module 100 can be implemented by one or more computing devices. Therefore, the following discussion turns to... Figure 4 The figure illustrates a block diagram of computing devices 400 that can perform some or all of the scientific instrument methods disclosed herein, according to various embodiments. In one or more embodiments, the scientific instrument module 100 may be implemented by a single computing device 400 or multiple computing devices 400. Further, as discussed below, the computing device 400 (or multiple computing devices 400) implementing the scientific instrument module 100 may be... Figure 13 A part of one or more of the scientific instrument 1310, the user local computing device 1320, the service local computing device 1330, or the remote computing device 1340.

[0084] Figure 4 The computing device 400 is shown as having multiple components, but any one or more of these components may be omitted or duplicated depending on the application and setup. As shown, these components may include one or more of a processor 402, a storage device 404, an interface device 406, a battery / power circuit 408, a display device 410, and other input / output (I / O) devices 412, which will be described below.

[0085] In one or more embodiments, one or more components included in computing device 400 may be attached to one or more motherboards and encapsulated in a housing (e.g., including plastic, metal, and / or other materials). In one or more embodiments, some of these components may be fabricated onto a single system-on-a-chip (SoC) (e.g., the 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 be omitted. Figure 4 One or more of the components shown are included. 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, such as 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 (e.g., connectors and driver circuitry) to which display device 410 may be coupled.

[0086] Computing device 400 may include processor 402 (e.g., one or more processing devices). As used herein, the term "processing device" can refer to any device or part of a device that processes electronic data from registers and / or memory to convert that 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 (GPUs), cryptographic processors (dedicated processors that execute cryptographic algorithms within hardware), server processors, or any other suitable processing devices.

[0087] Computing device 400 may include storage device 404 (e.g., one or more storage devices). Storage device 404 may include one or more memory devices, such as random access memory (RAM) (e.g., static RAM (SRAM) devices, magnetic RAM (MRAM) devices, dynamic RAM (DRAM) devices, resistive RAM (RRAM) devices, or conductive bridged RAM (CBRAM) devices), hard disk drive-based memory devices, solid-state memory devices, networked drives, cloud drives, or combinations of any memory devices. In one or more embodiments, storage device 404 may include memory sharing a die with processor 402. In such embodiments, the memory may be used as a cache and may include embedded dynamic random access memory (eDRAM) or spin-transfer torque magnetic random access memory (STT-MRAM), etc. In one or more embodiments, 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 computing device 400 to perform any suitable method or portion thereof of the methods disclosed herein.

[0088] 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 communication between computing device 400 and other computing devices. For example, interface device 406 may include circuitry for managing wireless communication of data transmission to and from computing device 400. The term "wireless" and its derivatives can be used to describe circuits, devices, systems, methods, techniques, communication channels, etc., that can transmit data through a non-solid medium using modulated electromagnetic radiation. This term does not mean that the associated device does not contain any wiring, but in one or more embodiments, the associated device may not contain any wiring. The circuitry included in interface device 406 for managing wireless communications can implement any of a variety of wireless standards or protocols, including but not limited to Institute of Electrical and Electronics Engineers (IEEE) standards, including Wi-Fi (IEEE 802.11 series), IEEE 802.16 standards (e.g., IEEE 802.16-2005 amendments), Long Term Evolution (LTE) projects, and any amendments, updates, and / or revisions (e.g., Advanced LTE projects, Ultra Mobile Broadband (UMB) projects (also known as “3GPP2”), etc.). In one or more embodiments, the circuitry included in interface device 406 for managing wireless communications can operate according to Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Universal Mobile Telecommunications System (UMTS), High Speed ​​Packet Access (HSPA), Evolved HSPA (E-HSPA), or LTE networks. In one or more embodiments, the circuitry included in interface device 406 for managing wireless communications may operate according to Enhanced Data GSM Evolution (EDGE), GSM EDGE Radio Access Network (GERAN), Universal Terrestrial Radio Access Network (UTRAN), or Evolved UTRAN (E-UTRAN). In one or more embodiments, the circuitry included in interface device 406 for managing wireless communications may operate according to Code Division Multiple Access (CDMA), Time Division Multiple Access (TDMA), Digital Enhanced Cordless Telecommunications (DECT), Evolved Data Optimization (EV-DO) and its derivative protocols, as well as any other wireless protocol designated as 3G, 4G, 5G, etc. In one or more embodiments, interface device 406 may include one or more antennas (e.g., one or more antenna arrays) to receive and / or transmit wireless communications.

[0089] In one or more embodiments, interface device 406 may include circuitry for managing wired communications, such as electrical communication protocols, optical communication protocols, or any other suitable communication protocols. For example, interface device 406 may include circuitry supporting communications based on Ethernet technology. In one or more embodiments, interface device 406 may support both wireless and wired communications, and / or may support multiple wired communication protocols and / or multiple wireless communication protocols. For example, a first set of circuitry for interface device 406 may be dedicated to short-range wireless communications such as Wi-Fi or Bluetooth, while a second set of circuitry for interface device 406 may be dedicated to long-range wireless communications such as Global Positioning System (GPS), EDGE, GPRS, CDMA, WiMAX, LTE, EV-DO, etc. In one or more embodiments, a first set of circuitry for interface device 406 may be dedicated to wireless communications, while a second set of circuitry for interface device 406 may be dedicated to wired communications.

[0090] The computing device 400 may include a battery / power circuit 408. The battery / power circuit 408 may include one or more energy storage devices (e.g., batteries or capacitors) and / or circuitry for coupling components of the computing device 400 to a power source (e.g., AC line power) separate from the computing device 400.

[0091] The computing device 400 may include a display device 410 (e.g., multiple display devices). The display device 410 may include any visual indicator, such as a head-up display, computer monitor, projector, touch screen display, liquid crystal display (LCD), light-emitting diode display, or flat panel display.

[0092] The computing device 400 may include other input / output (I / O) devices 412. For example, other I / O devices 412 may include one or more audio output devices (e.g., speakers, headphones, earphones, alarms, etc.), one or more audio input devices (e.g., microphones or microphone arrays), positioning devices (e.g., GPS devices that communicate with satellite-based systems to receive the location of the computing device 400, as known in the art), audio codecs, video codecs, printers, sensors (e.g., thermocouples or other temperature sensors, humidity sensors, pressure sensors, vibration sensors, accelerometers, gyroscopes, etc.), image capture devices such as cameras, keyboards, cursor control devices such as mice, styluses, trackballs, or touchpads, barcode readers, quick-response (QR) code readers, or radio frequency identification (RFID) readers.

[0093] The computing device 400 may have any suitable form factor for its application and setup, such as a handheld or mobile computing device (e.g., a mobile phone, smartphone, mobile internet device, tablet computer, laptop computer, netbook computer, ultrabook computer, personal digital assistant (PDA), ultra-mobile personal computer, etc.), a desktop computing device, a server computing device, or other networked computing components.

[0094] Now for reference Figure 5 and Figure 6 In one or more implementation schemes, Figure 5 and Figure 6 The non-limiting systems 500 and / or 600 and / or systems thereof shown herein may further include the computing environments referenced herein (such as...). Figure 15 The computing environment 1500 shown herein describes one or more computers and / or computing-based elements. In one or more of the described embodiments, the computers and / or computing-based elements can be combined to achieve a combination. Figure 5 and / or Figure 6 Used in conjunction with other accompanying drawings illustrated and / or described herein, and / or in connection with one or more of the operations implemented by the system, device, component, and / or computer.

[0095] First turn Figure 5 The figure illustrates a block diagram of an exemplary non-limiting system 500, which may include a signal tracking system 502. The signal tracking system 502 typically facilitates the synchronization and tracking of multimodal signals, such as signals associated with scientific instruments.

[0096] In one or more embodiments, the signal tracking system 502 may consist at least in part of the computing device 400.

[0097] It should be noted that the signal tracking system 502 is described only briefly to provide information on... Figure 6 The description leads to a more complex and / or broader signal tracking system 602. That is, further details regarding the processes that can be performed by one or more embodiments described herein will be provided below. Figure 6 The unrestricted system 600 is provided.

[0098] Still referencing Figure 5 The signal tracking system 502 may include at least a memory 504, a bus 505, a processor 506, an identification component 510, and / or a parameterization component 514. The processor 506 may be the same as, comprise, or different from the processor 402. The memory 504 may be the same as, comprise, or different from the storage device 404.

[0099] Using the components described above, the signal tracking system 502 can facilitate the process of tracking multimodal signals acquired relative to the scientific instrument 501.

[0100] Typically, the identification component 510 can identify the multimodal signal set 530, and further can identify the input and output set 532 corresponding to, composed of, and / or generated from the data / metadata of the multimodal signal set 530. The signal set 530 may have been acquired, such as by the signal tracking system 502 and / or by the scientific instrument 501. The signal set 530 may have been output by the scientific instrument 501 or another scientific instrument 501. For example, the scientific instrument 501 capable of outputting the multimodal signal set 530 may be an imaging device, such as a charged particle device.

[0101] In other words, the identification component 510 can typically identify the input and output set 532 of the scientific instrument 501.

[0102] The identification component 510 can typically determine whether each signal type of the multimodal signal set 530 has been identified for synchronization with each other. That is, the identification component 510 can compare and contrast the signal sets 530 relative to each other to determine the differences between them, such as determining the individual types in the multimodal type set of the multimodal signal set 530.

[0103] Furthermore, parameterization component 514 can typically track the inputs and outputs 532 in set 532 based on a common clock 538 shared by the inputs and outputs in set 532. That is, parameterization component 514 can perform one or more processes to analyze the inputs and outputs in set 532 according to synchronizations (e.g., timestamps and / or other parameters) applied to the inputs and outputs in set 532 to allow correlation and / or association between signal sets 530.

[0104] Because of these components, various multimodal signals 530 can be compared with each other to determine, for example, how multiple signals affect events occurring at one or more signals. Such events can be based on different types of signals, the location of the sample, the energy applied to the sample, etc.

[0105] Identification component 510 and / or parameterization component 514 may be operatively coupled to processor 506, which may be operatively coupled to memory 504. Bus 505 may provide operative coupling. Processor 506 may facilitate the execution of identification component 510 and / or parameterization component 514. Identification component 510 and / or parameterization component 514 may be stored in memory 504.

[0106] Typically, the non-restrictive system 500 can employ any suitable communication method (e.g., electronic, communication, Internet, infrared, fiber optic, etc.) to provide communication between the signal tracking system 502, library data storage, and / or any device associated with the user entity.

[0107] As a summary of the above components and their functions, the following is a brief reference. Figure 10 A flowchart of an exemplary non-limiting method 1000 is shown, which can facilitate the process of multimodal signal tracking. While the non-limiting method 1000 is relative to... Figure 5 The non-limiting system 500 described herein, but the non-limiting method 1000 can also be applied to other systems described herein, such as... Figure 6 A non-limiting system 600. For the sake of brevity, repeated descriptions of similar elements and / or processes used in the corresponding embodiments are omitted.

[0108] At 1002, the non-limiting method 1000 may include: a set of inputs and outputs (e.g., set of inputs and outputs 532) of a scientific instrument (e.g., scientific instrument 501) identified by a system (e.g., identification component 510) operatively coupled to the processor.

[0109] At 1004, the non-limiting method 1000 may include: determining by the system (e.g., identification component 510) whether each signal type of the multimodal signal set (e.g., multimodal signal set 530) has been identified for synchronization with each other. If not, the non-limiting method 1000 may return to step 1002. If yes, the non-limiting method may proceed to step 1006.

[0110] At 1006, the non-limiting method 1000 may include: the system (e.g., parameterization component 516) tracking the inputs and outputs in the set based on a common clock (e.g., common clock 538) common to the inputs and outputs in the set.

[0111] Next turn Figure 6 The illustration shows a non-limiting system 600, which may include a signal tracking system 602, a scientific instrument 601, and a library data storage (DS) 644. For brevity, repeated descriptions of similar elements and / or processes employed in corresponding embodiments are omitted. Relative to Figure 5 The description of the implementation scheme can be applied to Figure 6 The implementation plan. Similarly, relative to... Figure 6 The description of the implementation scheme can be applied to Figure 5 The implementation plan.

[0112] Typically, the signal tracking system 602 can facilitate the process of tracking the multimodal signal 630 acquired relative to the scientific instrument 601.

[0113] In one or more embodiments, the signal tracking system 602 may consist at least in part of the computing device 400.

[0114] One or more communications between one or more components of the non-limiting system 600 may be provided via wired and / or wireless means, including but not limited to cellular networks, wide area networks (WANs) (e.g., the Internet), and / or local area networks (LANs). Suitable wired or wireless technologies for supporting communications may include (but are not limited to) Wi-Fi, Global System for Mobile Communications (GSM), Universal Mobile Telecommunications System (UMTS), Global Microwave Access Interoperability (WiMAX), Enhanced General Packet Radio Service (Enhanced GPRS), 3GPP Long Term Evolution (LTE), 3GPP2 Ultra Mobile Broadband (UMB), High Speed ​​Packet Access (HSPA), Zigbee and other 802.XX wireless technologies and / or traditional telecommunications technologies. Session Initiation Protocol (SIP) RF4CE protocol, WirelessHART protocol, 6LoWPAN (IPv6 on low power wireless local area network), Z-Wave, advanced and / or adaptive networking technology (ANT), ultra-wideband (UWB) standard protocol and / or other proprietary and / or non-proprietary communication protocols.

[0115] The signal tracking system 602 can be integrated with cloud computing environments (such as... Figure 15 It is associated with a cloud computing environment (1500), such as being accessible through that cloud computing environment.

[0116] The signal tracking system 602 may include multiple components. These components 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 can facilitate the tracking of a multimodal signal 630 acquired relative to a scientific instrument 601, such as by typically synchronizing the multimodal signal 630 relative to a common general-purpose clock 638.

[0117] The following discussion turns to the processor 606, memory 604, and bus 605 of the signal tracing system 602. For example, in one or more embodiments, the signal tracing system 602 may include a processor 606 (e.g., a computer processing unit, microprocessor, classical processor, and / or similar processor). In one or more embodiments, components associated with the signal tracing system 602, as described herein (without referring to one or more figures of one or more embodiments), may include one or more computer and / or machine-readable, writable, and / or executable components and / or instructions that can be executed by the processor 606 to provide execution of one or more processes defined by the components and / or instructions. In one or more embodiments, the processor 606 may include 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.

[0118] In one or more embodiments, the signal tracking system 602 may include a computer-readable storage 604 operatively connected to the processor 606. The storage 604 may store computer-executable instructions that, when executed by the processor 606, cause the processor 606 and / or one or more other components of the 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 actions. In one or more embodiments, the storage 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).

[0119] The signal tracking system 602 and / or its components as described herein can be communicatively, electrically, operatively, optically, and / or otherwise coupled to each other via bus 605. 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 employ one or more bus architectures. One or more of these examples of bus 605 may be used.

[0120] In one or more embodiments, the signal tracking system 602 may be coupled (e.g., communication ground, electrical ground, operational ground, optical ground, and / or similar functions) to one or more external systems (e.g., an electrical output generating system not shown, one or more output targets and / or output target controllers), sources, and / or devices (e.g., computing devices, communication devices, and / or similar devices), such as via a network. In one or more embodiments, one or more components of the signal tracking system 602 and / or the non-limiting system 600 may reside in the cloud and / or may reside locally in a local computing environment (e.g., at a designated location).

[0121] In addition to the processor 606 and / or memory 604 described above, the signal tracking system 602 may also include one or more computer and / or machine-readable, writable and / or executable components and / or instructions that, when executed by the processor 606, can provide execution of one or more operations defined by the components and / or instructions.

[0122] The following discussion turns to the additional components of the 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). Typically, the signal tracking system 602 can perform a set of processes, which can be divided into various steps, including but not limited to: identifying the input and output set 632, timestamping the inputs and outputs 632, tracking the inputs and outputs 632 (this tracking may include interference filtering, recording, evaluation, analysis, identifying time delays, etc.), and synchronizing a universal clock 638 with another clock associated with one or more inputs and outputs in the input and output set 632.

[0123] First, it should be noted that in one or more implementations, 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 requiring one or more other components among 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, timestamp component 612, parameterization component 614, filtering component 616, synchronization component 618, evaluation component 620, and / or recording component 622 may be comprised of an advanced analysis component 603. One or more of the following functions of the identification component 610, timestamp component 612, parameterization component 614, filtering component 616, synchronization component 618, evaluation component 620, and / or recording component 622 may be performed by the advanced analysis component 603, and / or the omission of one or more of the omitted functions of the identification component 610, timestamp component 612, parameterization component 614, filtering component 616, synchronization component 618, evaluation component 620, and / or recording component 622 may be performed by the advanced analysis component 603.

[0124] First, turn to the identification component 610, which typically identifies the multimodal signal set 630, and further identifies the input and output set 632 corresponding to, composed of, and / or generated from the data / metadata of the multimodal signal set 630. For now, look to... Figure 9 In addition, there are Figure 6 Steps 902 and 904 can be performed by the identification component 610.

[0125] The signal set 630 may have been acquired, such as by the signal tracking system 602 and / or by the scientific instrument 601. The signal set 630 may have been output by the scientific instrument 601 or another scientific instrument 601. For example, the scientific instrument 601 capable of outputting the multimodal signal set 630 may be an imaging device, such as a charged particle device, a scanning electron microscope (SEM), a scanning transmission electron microscope (STEM), etc.

[0126] In other words, the identification component 610 can typically identify the input and output set 632 of the charged particle device 601. More specifically, the identification component 610 can scan one or more frequencies, communications, signal paths, communication packets, operation logs, etc., corresponding to the scientific instrument 601 to identify the multimodal signal set 630, which may include the input and output set 632. The determination between the inputs and outputs in set 632 can be based on the source of the signals in the signal set 630 tracked by the identification component 610 (e.g., whether the signal was initiated / transmitted by the scientific instrument 601 or received / acquired by the scientific instrument 601).

[0127] In one or more embodiments, the identification component 610 can typically determine whether each signal type of the multimodal signal set 630 has been identified for synchronization with each other. That is, the identification component 610 can compare and contrast the signals in the signal set 630 to determine the differences between them, such as determining the individual types in the multimodal type set of the multimodal signal set 630.

[0128] For example, a temporary shift Figure 7 The diagram shows one or more signal types, but is not limited to these. More or fewer signal types than those listed at situation workflow 700 may be employed by scientific instrument 601 and therefore may be identified by identification component 610. Examples may include interference frequency data 732F (described below), imaging data 740, excitation data 732G, XY position data 732A, stimulus data 732B, detection data 732C, scan data 732D, and / or optical data 732E, etc. As shown, each data may employ a separate tracking method, such as an independent clock 732, excitation clock 742, and / or XY position tracking 744. Therefore, correlating and / or synchronizing different data types (e.g., corresponding to the respective signal types) can be difficult, if not impossible. This can lead to difficulties in understanding events that occur during the experiment. For example, this can make it difficult for artificial intelligence to correlate the various data generated by the experiment with each other.

[0129] Refer again Figure 6 and Figure 9The stamping component 612 can typically generate one or more timestamps 634 for inputs and outputs based on the data output from the general-purpose clock 638, where the timestamps 634 are unaffected by changes in the XY position outputs in the outputs (set 632). That is, at step 906, the stamping component 612 can determine the data output 636 from the general-purpose clock 638. Based on this, the stamping component 612 can compare the serial count of the general-purpose clock 638 with the metadata of the inputs and outputs in the input and output set 632. Based on this comparison, the stamping component 612 can generate metadata defining the timestamp 634 for each data point in the acquired (e.g., identified by the identification component 610) set 632.

[0130] In one or more embodiments, this generation and application of timestamp 634 can be performed dynamically, such as in parallel and / or close proximity to data acquired by the identification component 610. In one or more other embodiments, this generation and application of timestamp 634 can be applied some time after data acquisition, such as after the start of an experiment. Regardless, metadata associated with the inputs and outputs in set 632 can be used to compare the inputs and / or outputs with the data output 636 of the universal clock 638. This can include comparing XY position tracking 744 along the timeline of the universal clock 638.

[0131] In one or more embodiments, the timestamp 634 may be stored in memory 604, library data storage 644, and / or any other suitable location communicatively accessible to the signal tracking system 602.

[0132] For now, we turn to a general-purpose clock 638, which can be a component of processor 606 or a component of any other processor that the signal tracking system 602 can communicatively access. General-purpose clock 638 can provide continuous (e.g., serial) time counting in any suitable unit increment.

[0133] At step 908, parameterization component 614 can typically track the inputs and outputs 632 in set 632 based on a common clock 638 common to the inputs and outputs in set 632. That is, a single common clock 638 and therefore a single timing can be used for multimode signal set 630, and thus for input and output set 632 consisting of multimode signal set 630.

[0134] Based on this, parameterization component 614 can perform one or more processes to analyze the inputs and outputs in set 632 according to the synchronization (e.g., timestamps and / or other parameters) applied to the inputs and outputs in set 632, so as to allow correlation and / or association between signal sets 630.

[0135] This tracking may include, but is not limited to, interference filtering, recording, evaluation, analysis, and identifying time delays.

[0136] It should be understood that, at least based on the processes performed by the stamping component 612 and the parameterization component 614, the general-purpose clock 638 can be employed without any adjustments to the general-purpose clock 638 (e.g., without any adjustments to any clock used for tracking the signal set 630) based on environmental disturbances 660 to the scientific instrument. For example, environmental disturbances 660 may cause differences, drifts, stops, and / or jumps in the output and / or input signals to the experiment. In one example, environmental disturbances 660 may cause vibrations, bumps, etc., in the XY position, resulting in differences in the XY position outputs (in the input and output set 632). Therefore, such differences can also be reflected in the XY position tracking 744. For another example, the experimental output can be used to find the interference frequencies of the environment within energy axis instabilities; this understanding can be applied to correct one or more instabilities in the XY position, and vice versa.

[0137] Without using one or more of the embodiments described herein, the invariance of clock timing may be difficult and / or incomparable to that of variable XY position tracking 744. For example, in ultrafast experiments utilizing cavity or laser-excited illumination, timing accuracy can reach femtosecond or attosecond levels, and in embodiments where multiple clock phase shifts may occur between tracking points, these phase shifts may be undesirably difficult to compensate for afterwards. In practice, synchronizing multiple input / output clocks after an experiment can be time-consuming and may be undesirably difficult or impossible to process real-time data in existing situations where a common timestamping does not occur online. That is, for an experiment where scan rates can reach nanosecond per pixel levels, this may require XY position tracking with nanosecond accuracy synchronized with the input / output signals.

[0138] Unlike conventional XY position tracking 744, which employs one or more processes based on the timing of a general-purpose clock 638 using the stamping component 612 and / or the parameterization component 614, a sequencing parameter (e.g., corresponding to the time of the general-purpose clock 638) can be used. This sequencing parameter will not change due to environmental disturbances 660 as in conventional XY position tracking 744. This is likely because time is constant, while XY position tracking 744 may vary due to instabilities such as physical instabilities.

[0139] For example, a temporary shift Figure 8 As demonstrated in Solution Workflow 800, each different data type (corresponding to the corresponding signal type) can employ a single and common tracking method based on the general-purpose clock 638.

[0140] Refer again Figure 6 and Figure 9 Based on instructions from parameterization component 614 (e.g., communication, signal, etc.), various additional components of signal tracking system 602 can perform various corresponding processes 908A-908D.

[0141] For example, at step 908B, the filtering component 616 can filter out the interference frequency output 732F in the output 632 that is affecting the imaging output 740 in the output 632. This can be achieved by scanning the interference frequency corresponding to the interference frequency output 732F according to the universal clock 638. Such a process cannot be performed using existing frameworks due to the lack of synchronization between the different signal types acquired from the scientific instrument 601.

[0142] In another example, at step 908C, evaluation component 620 can identify time delays 640 between inputs, outputs, or different combinations of both in set 632 based on general-purpose clock 638. That is, a data gap can be associated with a first signal in set 630, but not with other signals in set 630. This gap can be interpreted based on the procedures performed by stamping component 612 and / or parameterization component 614. Such procedures cannot be performed using existing frameworks due to the lack of synchronization between different signal types acquired from scientific instrument 601.

[0143] In another example, in step 908A, recording component 622 may record a set of XY position outputs 732A-NB from the outputs 632 of scientific instrument 601, wherein recording component 622 omits recording the XY position outputs 732A-B corresponding to beam blanking. That is, when a fast beam blanker is used during scanning of scientific instrument 601, a sparse XY pattern can be generated. Normally, all empty XY positions would be recorded. By using the timing of a universal clock 638 only when the beam is not blanked as a reference, only such unblanking-related signals / data (e.g., XY position outputs 732A-NB) are recorded. This can significantly reduce bandwidth, power consumption, time, storage space, memory, and / or the amount of data used, because there is no need to record the corresponding blanking-related signals / data (e.g., XY position outputs 732A-B). Such a process cannot be performed using existing frameworks due to the lack of synchronization between the different signal types acquired from scientific instrument 601.

[0144] Recording performed by recording component 622 may include write operations (e.g., update 642) or any other suitable operation on a suitable storage (such as library data storage (DS) 644).

[0145] For another example, at step 908D, various comparisons (not specifically defined herein) may be performed between / among signal types 631. That is, the procedures and / or results of using the signal tracking system 602 are not limited to those explicitly described herein.

[0146] Furthermore, at step 910, based on the data output 636 of the general-purpose clock 638, the synchronization component 618 can determine a second timing for the excitation clock 742 used for dynamic excitation by the scientific instrument 601. The synchronization component 618 can accordingly synchronize the first timing of the general-purpose clock 638 with the second timing of the excitation clock 742, and vice versa.

[0147] For example, in dynamic experiments, the zero point of time can be defined as the point at which the excitation is applied. In irreversible experiments, the response corresponding to the sample can be measured in real time for decay time experiments. In stroboscopic settings, periodic pulsed illumination can be synchronized with the 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 time response can be measured by changing the phase shift between the excitation and illumination. In one or more cases, the phase shift can be detected by using a time-resolved detector by timestamping the detection of the sample excitation event and the signal on the sensor. In contrast, existing frameworks employ only a single pulse beam or stroboscopic excitation synchronized with the sample excitation time. On the other hand, one or more embodiments described herein can provide simultaneous synchronization of beam scanning, source, and detection events with the sample excitation time.

[0148] In fact, in one or more other implementations, the general-purpose clock 638 can be set based on the corresponding output data of any other independent clock 738 (e.g., in parallel with it).

[0149] Due to the various components 610-622 discussed above, the various multimodal signals 630 can be compared with each other to determine how the multiple signals may affect events occurring at or defined by one or more signals. Such events may be based on different signal types 631, the XY position of the sample 732A, the energy applied to the sample, etc.

[0150] In one or more embodiments, artificial intelligence (AI) analysis can be used to determine compensation for artifacts produced by the experiment at scientific instrument 601, a determination made possible because the time reference remains undisturbed (e.g., unchanged).

[0151] In one or more embodiments, based on one or more embodiments described herein, one or more types of experiments that cannot be performed using existing frameworks can be performed. For example, coincidence measurements and / or critical dose measurements can benefit from signal comparison provided by using a common universal clock 638 and without signal tracking loss (e.g., signal tracking loss caused by signals obtained by tracking serially using XY position 732A as in existing frameworks). As another example, such new experiments can include the easy integration of new dynamic third-party components, such as scaffolds, lasers, and / or fast detectors, based on the process described above, which can be performed by at least identification component 610, stamping component 612, and parameterization component 614.

[0152] Furthermore, as an additional and / or alternative result of using one or more embodiments described herein, one or more of the following benefits may be provided, but not limited to: easy and reproducible setup of dynamic experimental workflows, accurate event logging for offline analysis, improved temporal resolution down to the nanosecond level, improved accuracy of multimodal data correlation via timestamping, and / or improved drift correction accuracy in dynamic experiments via the fastest scan speed.

[0153] As a summary of the components and / or their functions mentioned above, please refer to the following... Figure 11 and Figure 12 The document illustrates a flowchart of an exemplary non-limiting method 1100, based on one or more embodiments described herein, that can facilitate a process for multimodal signal tracking, such as... Figure 6 The non-restrictive system 600. Although the non-restrictive method 1100 is relative to Figure 6 The non-limiting system 600 described herein, but the non-limiting method 1100 can also be applied to other systems described herein, such as... Figure 5 Non-limiting system 500. For the sake of brevity, repeated descriptions of similar elements and / or processes used in the corresponding embodiments are omitted.

[0154] At 1102, the non-limiting method 1100 may include: a set of inputs and outputs (e.g., set of inputs and outputs 632) of a scientific instrument (e.g., scientific instrument 601) identified by a system (e.g., identification component 610).

[0155] At 1104, the non-limiting method 1100 may include: determining by the system (e.g., identification component 610) whether each signal type (e.g., signal type 631) of the multimodal signal set (e.g., multimodal signal set 630) has been identified for synchronization with each other. If not, the non-limiting method 1100 may return to step 1102. If yes, the non-limiting method may proceed to step 1106.

[0156] At 1106, the non-limiting method 1100 may include: the system (e.g., the stamping component 612) timestamps the input and output with a timestamp (e.g., timestamp 634) based on the data output (e.g., data output 636) from a general-purpose clock (e.g., general-purpose clock 638).

[0157] At 1108, the non-limiting method 1100 may include: a universal clock being adopted by the system (e.g., stamping component 612) in the absence of any adjustment to the universal clock based on environmental disturbances to the scientific instrument (e.g., environmental disturbance 660), including variations in the XY position output (e.g., XY position output 732A).

[0158] At 1110, the non-limiting method 1100 may include: the system (e.g., parameterization component 614) tracking the inputs and outputs in the set based on a common clock common to the set of inputs and outputs.

[0159] At 1112, the non-limiting method 1100 may include: the system (e.g., filtering component 616) filtering out the interference frequency output (e.g., interference frequency output 732F) that is affecting the imaging output (e.g., imaging output 740) in the output by scanning the interference frequency corresponding to the interference frequency output according to a general clock.

[0160] At 1114, the non-limiting method 1100 may include: a second timing determined by the system (e.g., synchronization component 618) for an excitation clock (e.g., excitation clock 742) for dynamic excitation by a scientific instrument.

[0161] At 1116, the non-limiting method 1100 may include: synchronizing a first timing of a general-purpose clock with a second timing of an excitation clock by a system (e.g., synchronization component 618).

[0162] At 1118, the non-limiting method 1100 may include: a time delay between different combinations of inputs, outputs, or both in the set of inputs and outputs identified by the system (e.g., evaluation component 620) according to a common clock (e.g., time delay 640).

[0163] At 1120, the non-limiting method 1100 may include: recording the set of XY position outputs from the output of a scientific instrument by a system (e.g., recording component 622).

[0164] At 1122, the non-limiting method 1100 may include: the system (e.g., recording component 622) omitting the XY position output corresponding to the bundle blanking (e.g., XY position outputs 732A-B).

[0165] Additional Invention Content

[0166] For simplicity, the computer-implemented and non-computer-implemented methods provided herein are depicted and / or described as a series of actions. It should be understood that the invention is not limited to the actions and / or the order of actions shown; for example, actions may occur in one or more orders and / or simultaneously, and together with other actions not presented or described herein. Furthermore, not all actions shown can be used to implement the computer-implemented and non-computer-implemented methods according to the described subject matter. Additionally, computer-implemented and non-computer-implemented methods may alternatively be represented as a series of interrelated states via state diagrams or events. Furthermore, the computer-implemented methods described below and throughout this specification can be stored in an article of manufacture for transporting and transferring to a computer. As used herein, the term "article of manufacture" is intended to cover a computer program accessible from any computer-readable device or storage medium.

[0167] This document has (and / or will further) described systems and / or devices with respect to the interaction between one or more components. Such systems and / or components may include those components or sub-components specified herein, one or more of the specified components and / or sub-components, and / or additional components. Sub-components may be implemented as components communicatively coupled to other components rather than being included within a parent component. One or more components and / or sub-components may be combined into a single component that provides aggregate functionality. For brevity, a component may interact with one or more other components not specifically described herein but known to those skilled in the art.

[0168] In summary, one or more systems, computer program products, and / or computer-implemented methods provided herein relate to processes for acquiring multimodal signals, such as those synchronized from a charged particle device or other scientific instrument based on a common clock for various multimodal signals. A system may include: a memory storing computer-executable components; and a processor executing the computer-executable components stored in the memory, wherein the computer-executable components include an identification component that identifies a set of inputs and outputs of a scientific instrument; and a parameterization component that tracks the inputs and outputs in the set based on a common clock common to the inputs and outputs in the set.

[0169] One or more embodiments described herein can employ a novel system that can be used with different (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, thereby allowing the inputs and / or outputs of these signal types to be tracked and analyzed relative to each other without data loss, time conversion, etc. Furthermore, environmental disturbances (such as changes in XY position due to physical instability, bumps, vibrations, etc.) will not alter the universal clock, because this clock is not solely based on XY position.

[0170] In practice, given the one or more embodiments described herein, the practical application of the one or more systems, computer-implemented methods, and / or computer program products described herein can be the ability to easily sort parameters relative to each other based on multimodal signal acquisition, thereby allowing the identification of one or more interference frequencies of another signal (such as an image output signal) that interfere with the environment, and the separation of such one or more interference frequencies. These are useful and practical applications of computers, thereby providing enhanced (e.g., improved and / or optimized) compound analysis and / or image analysis outputs. In general, such computerized tools can constitute concrete and tangible technological improvements in the field of materials analysis, particularly in the field of materials analysis based on multimodal signal acquisition.

[0171] Furthermore, based on the disclosed teachings, one or more implementations described herein can be adopted in real-world systems. For example, one or more implementations described herein can provide parameterization of various signal inputs and / or outputs of the same experiment, operation, and / or process, while allowing identification of one or more interference frequencies of another signal (such as an image output signal) that interfere with the environment, and separating such one or more interference frequencies.

[0172] In one or more cases, based on one or more embodiments described herein, one or more types of experiments that cannot be performed using existing frameworks can be performed. For example, coincidence measurements and critical dose measurements can benefit from signal comparison provided by using a common universal clock and without signal tracking loss (e.g., signal tracking loss caused by signals obtained serially using XY position tracking as in existing frameworks).

[0173] In one or more cases, since recording the XY position output corresponding to beam blanking can be omitted based on using one or more embodiments described herein, a reduced storage space and bandwidth can be used to store and record the signal.

[0174] One or more implementation schemes described herein can be applied plug-and-play to various architectures of existing scientific instruments, signal acquisition instruments, etc.

[0175] These processes may be useful for various industries employing materials analysis, product manufacturing, quality control, and / or similar techniques. Therefore, the embodiments disclosed herein can provide improvements to scientific instrumentation technology (e.g., improvements to the computer technology supporting such scientific instruments, and others).

[0176] Furthermore, in one or more cases, the implementations described herein can be self-improving. In fact, due to the use of a common universal clock, timestamps that can be correlated with each other without differences (such as due to environmental influences) are allowed for comparisons to determine relationships between acquired signals, event determination based on multimodal signals, etc., which can be performed by classical computers and / or one or more artificial intelligences employing the results of one or more implementations described herein, and can become more efficient and accurate over time. That is, since the signals are acquired and synchronized according to a common universal clock without using variable XY positions as synchronization elements but rather synchronizing the XY positions along with other inputs and outputs, a larger scale of accurate comparison data is generated for searches, queries, event determination, signal comparisons, and / or other analyses performed relative to various multimodal signals synchronized through one or more implementations described herein. Therefore, one or more non-limiting systems described herein (including signal tracking systems, as described herein) can be self-improving.

[0177] Furthermore, one or more implementations described herein can achieve an operational-scale level. For example, two or more different signals can be synchronized and tracked at least partially simultaneously with each other using timestamps generated and applied relative to the same experiment and / or process, and / or the same operation can be performed at least partially simultaneously with each other relative to two or more different experiments and / or processes.

[0178] This document has (and / or will further) described systems and / or devices with respect to the interaction between one or more components. Such systems and / or components may include those components or sub-components specified herein, one or more of the specified components and / or sub-components, and / or additional components. Sub-components may be implemented as components communicatively coupled to other components rather than being included within a parent component. One or more components and / or sub-components may be combined into a single component that provides aggregate functionality. For brevity, a component may interact with one or more other components not specifically described herein but known to those skilled in the art.

[0179] One or more embodiments described herein may be inherently and / or unavoidably related 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 program and / or program instruction execution more efficiently or even more feasiblely, such as relative to the reading, synchronization, and / or stamping of digital data corresponding to multimodal signal acquisition. Systems, computer-implemented methods, and / or computer program products that provide these process performances have great utility in the field of materials analysis and cannot be implemented in a reasonably feasible manner outside of a computing environment.

[0180] One or more implementations described herein can employ hardware and / or software to solve highly technical, non-abstract problems that cannot be performed by humans through a set of mental behaviors. For example, one person, or even thousands, cannot efficiently, accurately, and / or effectively read, synchronize, and / or stamp digital data corresponding to multimodal signal acquisition, while one or more implementations described herein can provide this process. Furthermore, as performed by one or more implementations described herein, one or more of these processes cannot be performed by humans or those holding pen and paper.

[0181] In one or more embodiments, one or more processes described herein may be performed by one or more dedicated computers (e.g., dedicated processing units, dedicated classic computers, and / or another type of dedicated computer) to perform prescribed tasks related to one or more of the technologies described above. One or more embodiments described herein and / or components thereof may be used to address new problems arising from advancements in the technologies described above, the use of cloud computing systems, computer architectures, and / or other technologies.

[0182] One or more implementations described herein may be used entirely to perform one or more other functions (e.g., full power-on, full execution, and / or another function), while also performing one or more of the operations described herein.

[0183] To provide additional details about the invention, a list of embodiments and their features is provided below.

[0184] A system comprising: a memory storing computer-executable components; and a processor executing the computer-executable components stored in the memory, wherein the computer-executable components include: an identification component identifying a set of inputs and outputs of a scientific instrument; and a parameterization component tracking the inputs and outputs in the set based on a common clock common to the inputs and outputs in the set.

[0185] According to the system described in the preceding paragraph, the inputs and outputs in the set include XY position inputs and outputs, as well as detection inputs and outputs.

[0186] According to any of the preceding paragraphs, the computer-executable component further includes: a stamping component that timestamps the input and output based on a data output from the universal clock, wherein the timestamps are unaffected by changes in the XY position output of the output.

[0187] According to any of the preceding paragraphs, the computer-executable component further includes a filtering component that filters out the interference frequency output that is affecting the imaging output in the output by scanning the interference frequency corresponding to the interference frequency output with the general clock.

[0188] According to any of the preceding paragraphs, the computer-executable component further includes: a synchronization component that determines a second timing of an excitation clock used by the scientific instrument for dynamic excitation, and synchronizes a first timing of the general-purpose clock with the second timing of the excitation clock.

[0189] According to any of the preceding paragraphs, the universal clock is used without any adjustment to the universal clock based on environmental disturbances to the scientific instrument, including changes in the XY position output of the output.

[0190] According to any of the preceding paragraphs, the computer-executable component further includes: an evaluation component that identifies time delays between different combinations of inputs, outputs, or both in the set of inputs and outputs based on the general clock.

[0191] According to any of the preceding paragraphs, the computer-executable component further includes: a recording component that records a set of XY position outputs from the output of the charged particle device, wherein the recording component omits recording the XY position outputs corresponding to beam blanking.

[0192] A computer-implemented method comprising: identifying a set of inputs and outputs of a charged particle device by a system operatively coupled to a processor; and tracking the inputs and outputs in the set by the system based on a common clock common to the set of inputs and outputs.

[0193] According to the computer-implemented method described in the preceding paragraph, the computer-implemented method further includes: the system generating timestamps for the input and output based on data output from the general clock, wherein the timestamps are unaffected by changes in the XY position output in the output.

[0194] According to any of the preceding paragraphs, the computer-implemented method further includes: the system filtering out the interference frequency output that is affecting the imaging output in the output by scanning the interference frequency corresponding to the interference frequency output according to the universal clock.

[0195] According to any of the preceding paragraphs, the computer-implemented method further includes: the system determining a first timing of an excitation clock used for dynamic excitation by the charged particle device; and the system synchronizing a second timing of the general-purpose clock with the first timing of the excitation clock.

[0196] According to any of the preceding paragraphs, the computer-implemented method further includes: the system using the universal clock without any adjustment to the universal clock, the adjustment being based on environmental disturbances to the scientific instrument, including changes in the XY position output of the output.

[0197] The computer-implemented method according to any of the preceding paragraphs further includes: the system identifying time delays between different combinations of inputs, outputs, or both in the set of inputs and outputs according to the universal clock.

[0198] According to any of the preceding paragraphs, the computer-implemented method further includes: recording by the system a set of XY position outputs from the output of the charged particle device, wherein the recording includes omitting records of XY position outputs corresponding to beam blanking.

[0199] A computer program product facilitating the process of tracking inputs and outputs of a scientific device, the computer program product comprising a computer-readable storage medium having program instructions embodied therein, and the program instructions being executable by a processor to cause the processor to: identify a set of inputs and outputs of a charged particle device; and track the inputs and outputs in the set based on a common clock common to the set of inputs and outputs in the set.

[0200] According to the computer program product described in the preceding paragraph, 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 from the general-purpose clock, wherein the timestamps are unaffected by changes in the XY position outputs of the outputs.

[0201] According to any of the preceding paragraphs, the computer program product wherein the program instructions are further executable by the processor to cause the processor to: filter out the interference frequency output that is affecting the imaging output in the output by scanning the interference frequency corresponding to the interference frequency output according to the general clock.

[0202] According to any of the preceding paragraphs, the computer program product wherein the program instructions are further executable by the processor to cause the processor to: use the general-purpose clock without adjustment of the general-purpose clock, the adjustment being based on environmental disturbances to the scientific instrument, including changes in the XY position output in the output.

[0203] According to any of the preceding paragraphs, the computer program product wherein the program instructions are further executable by the processor to cause the processor to: identify, according to the general clock, the time delay between different combinations of inputs, outputs, or both of the inputs and outputs in the set.

[0204] Scientific Instrument System Description

[0205] Next turn Figure 13 This provides an overview of the article. Figures 1 to 12 A detailed description of the additional context for one or more embodiments described herein. 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 A block diagram of an exemplary scientific instrument system 1300 is shown, in which one or more of the scientific instrument methods or other methods disclosed herein can be performed according to various embodiments described herein. The scientific instrument modules and methods disclosed herein (e.g., Figure 1 Scientific instrument module 100 and Figure 2 Method 200 can be implemented by one or more of the scientific instruments 1310, user local computing device 1320, service local computing device 1330 and / or remote computing device 1340 of the scientific instrument system 1300.

[0206] 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 be included in the references herein. Figure 4Any implementation of the computing device 400 discussed herein, and any of the scientific instrument 1310, user local computing device 1320, service local computing device 1330, and / or remote computing device 1340 may be adopted with reference to this document. Figure 4 The computing device 400 discussed may take the form of any one or more suitable implementations.

[0207] One or more 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 a processing device 1302, a storage device 1304, and / or an interface device 1306. The processing device 1302 may take any suitable form, including those referenced herein. Figure 4 The processor 402 discussed may take any form. Processing devices 1302, including those in scientific instrument 1310, user local computing device 1320, service local computing device 1330, and / or remote computing device 1340, may take the same or different forms. Storage device 1304 may take any suitable form, including those referenced herein. Figure 4 The storage device 404 discussed may take any form. Storage device 1304, including in different types such as scientific instrument 1310, user local computing device 1320, service local computing device 1330, and / or remote computing device 1340, may take the same or different forms. Interface device 1306 may take any suitable form, including those referenced herein. Figure 4 The interface device 406 discussed can take any form. The interface device 1306 included in different devices such as scientific instrument 1310, user local computing device 1320, service local computing device 1330 and / or remote computing device 1340 may take the same or different forms.

[0208] Scientific instrument 1310, user local computing device 1320, service local computing device 1330, and / or remote computing device 1340 can communicate with other components of scientific instrument system 1300 via communication path 1308. Communication path 1308 can communicatively couple interface devices 1306 of different components of scientific instrument system 1300, as shown, and can be a wired or wireless communication path (e.g., according to references herein). Figure 4 The interface device 406 of the computing device 400 (discussing any communication technologies). Figure 13The specific scientific instrument system 1300 depicted includes communication paths between each pair of scientific instrument 1310, user local computing device 1320, service local computing device 1330, and remote computing device 1340. However, this "fully connected" implementation is merely illustrative, and various paths in the communication path 1308 may be omitted in various embodiments. 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, but may instead 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.

[0209] Scientific instrument 1310 may include any suitable scientific instrument, such as separation or mass spectrometry (MS) instruments, or other instruments that facilitate the analysis of materials.

[0210] User-local computing device 1320 may be a user-local computing device located on scientific instrument 1310 (e.g., any embodiment of computing device 400 discussed herein). In one or more embodiments, user-local computing device 1320 may also be located locally on scientific instrument 1310, but this is not mandatory; for example, user-local computing device 1320 associated with a user entity's home, office, or other building may be located remotely to scientific instrument 1310 but communicate with it so that the user entity can use user-local computing device 1320 to control and / or access data on scientific instrument 1310. In one or more embodiments, user-local computing device 1320 may be a laptop, smartphone, or tablet device. In one or more embodiments, user-local computing device 1320 may be a portable computing device. In one or more embodiments, user-local computing device 1320 may be deployed in the field.

[0211] The servicing local computing device 1330 may be a computing device located at the location of the entity servicing the scientific instrument 1310 (e.g., any embodiment of the computing device 400 discussed herein). For example, the servicing local computing device 1330 may be located at the location of the manufacturer of the scientific instrument 1310 or a third-party service company. In one or more embodiments, the servicing 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., self-test results of the scientific instrument 1310, calibration coefficients used by the scientific instrument 1310, sensor measurements associated with the scientific instrument 1310, etc.). In one or more embodiments, the serving local computing device 1330 may communicate with scientific instrument 1310, user local computing device 1320, and / or remote computing device 1340 (e.g., via direct communication path 1308 or via multiple “indirect” communication paths 1308, as discussed above) to transfer data to scientific instrument 1310, user local computing device 1320, and / or remote computing device 1340 (e.g., updating programming instructions, such as firmware, in scientific instrument 1310; initiating the execution of a test or calibration sequence in scientific instrument 1310; updating programming instructions, such as software, in user local computing device 1320 or remote computing device 1340). The user entity of scientific instrument 1310 may use scientific instrument 1310 or user local computing device 1320 to communicate with service local computing device 1330 to report problems with scientific instrument 1310 or user local computing device 1320, request technician access to improve the operation of scientific instrument 1310, order consumables or replacement parts associated with scientific instrument 1310, or for other purposes.

[0212] Remote computing device 1340 may be a computing device located remotely from scientific instrument 1310 and / or user local computing device 1320 (e.g., any embodiment of computing device 400 discussed herein). In one or more embodiments, remote computing device 1340 may be included in a data center or other large-scale server environment. In one or more embodiments, remote computing device 1340 may include network-attached storage (e.g., as part of storage device 1304). Remote computing device 1340 may store data generated by scientific instrument 1310, perform analysis on data generated by scientific instrument 1310 (e.g., according to programming instructions), facilitate communication between user local computing device 1320 and scientific instrument 1310, and / or facilitate communication between service local computing device 1330 and scientific instrument 1310.

[0213] In one or more implementations, this can be omitted. Figure 13 The scientific instrument system 1300 shown in the image includes one or more components. Furthermore, in one or more embodiments, Figure 13 Multiple components of the scientific instrument system 1300 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 located in different locations). In another example, the scientific instrument system 1300 may include multiple scientific instruments 1310, all of which communicate with a serving local computing device 1330 and / or a remote computing device 1340; in this embodiment, the serving local computing device 1330 may monitor these multiple scientific instruments 1310, and the serving local computing device 1330 may enable updates or other information to be “broadcast” to the multiple scientific instruments 1310. The different scientific instruments 1310 in the scientific instrument system 1300 may be close to each other (e.g., in the same room) or far apart (e.g., on different floors of a building, in different buildings, in different cities, etc.). In one or more embodiments, scientific instrument 1310 may be connected to an Internet of Things (IoT) stack that allows command and control of scientific instrument 1310 via web-based applications, virtual or augmented reality applications, mobile applications, and / or desktop applications. A user entity operating a user local computing device 1320 that communicates with scientific instrument 1310 via an intervening remote computing device 1340 can access any of these applications. In one or more embodiments, scientific instrument 1310 may be sold by the manufacturer as part of a local scientific instrument computing unit 1312, along with one or more associated user local computing devices 1320.

[0214] In one or more embodiments, the different scientific instruments 1310 included in the scientific instrument system 1300 may be of different types; for example, one scientific instrument 1310 may be an EDS device, while another scientific instrument 1310 may be an analytical device for analyzing the results of the EDS device. In some such embodiments, a remote computing device 1340 and / or a user-local computing device 1320 may combine data from the different types of scientific instruments 1310 included in the scientific instrument system 1300.

[0215] Exemplary operating environment

[0216] Figure 14This is a schematic block diagram of an operating environment 1400 with which the described subject can interact. The operating environment 1400 includes one or more remote components 1410. Remote components 1410 can be hardware and / or software (e.g., threads, processes, computing devices). In one or more embodiments, remote component 1410 can be a distributed computer system connected to a local autoscaling component and / or a program using distributed computer system resources via a communication framework 1440. The communication framework 1440 can include wired network devices, wireless network devices, mobile devices, wearable devices, radio access network devices, gateway devices, femtocell devices, servers, etc.

[0217] The operating environment 1400 also includes one or more local components 1420. Local components 1420 may be hardware and / or software (e.g., threads, processes, computing devices). In one or more embodiments, local components 1420 may include autoscaling components connected to a remote distributed computing system via a communication framework 1440 and / or programs that communicate with / use remote resources 1410 and 1420.

[0218] One possible communication between remote component 1410 and local component 1420 could be in the form of data packets suitable for transmission between two or more computer processes. Another possible communication between remote component 1410 and local component 1420 could be in the form of circuit-switched data suitable for transmission between two or more computer processes in a radio time slot. Operating environment 1400 includes a communication framework 1440 that can be used to facilitate communication between remote component 1410 and local component 1420, and may include an air interface, such as an interface to a UMTS network, via an LTE network, etc. Remote component 1410 can be operatively connected to one or more remote data storage devices 1450, such as hard disk drives, solid-state drives, Subscriber Identity Module (SIM) cards, electronic SIMs (eSIMs), device memory, etc., which can be used to store information on the remote component 1410 side of communication framework 1440. Similarly, local component 1420 can be operatively connected to one or more local data storage devices 1430, which can be used to store information on the local component 1420 side of communication framework 1440.

[0219] Exemplary computing environment

[0220] To provide additional background for the various implementation schemes described in this article Figure 15The following discussion is intended to provide a brief overview of suitable computing environments 1500 in which the various implementations of the embodiments described herein can be implemented. While the embodiments have been described above in the general context of computer-executable instructions that can run 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.

[0221] Generally speaking, program modules include routines, programs, components, data structures, etc., that perform tasks or implement abstract data types. Furthermore, these methods can be practiced with other computer system configurations, including single-processor or multi-processor computer systems, minicomputers, mainframes, Internet of Things (IoT) devices, distributed computing systems, and personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics, each of which is operatively coupled to one or more associated devices.

[0222] The implementation schemes shown in this paper can also be practiced in distributed computing environments, where some tasks are performed by remote processing devices linked via a communication network. In a distributed computing environment, program modules can reside in both local and remote memory storage devices.

[0223] Computing devices typically include a variety of media, which may include computer-readable storage media, machine-readable storage media, and / or communication media. These two terms are used interchangeably herein, as follows. A computer-readable storage media or a machine-readable storage media can be any available storage medium accessible by a computer and includes volatile and non-volatile media, removable and non-removable media. By way of example and not limitation, a computer-readable storage media or a machine-readable storage media can be implemented in conjunction with any method or technology used for storing information, such as computer-readable or machine-readable instructions, program modules, structured data, or unstructured data.

[0224] Computer-readable storage media 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 technologies, compressed optical disc read-only memory (CD-ROM), digital versatile optical disc (DVD), Blu-ray disc (BD) or other optical disc storage devices, magnetic tape cassettes, magnetic tape, disk storage devices or other magnetic storage devices, solid-state drives or other solid-state storage devices, or other tangible and / or non-transitory media that can be used to store desired information. In this regard, the terms “tangible” or “non-transitory” used herein to describe storage devices, memories, or computer-readable media exclude only the propagation of transient signals themselves as a modifier, and do not waive the rights of all standard storage devices, memories, or computer-readable media that do not merely propagate transient signals themselves.

[0225] Computer-readable storage media can be accessed by one or more local or remote computing devices, for example via access requests, queries or other data retrieval protocols, for various operations concerning the information stored on the media.

[0226] Communication media typically contain computer-readable instructions, data structures, program modules, or other structured or unstructured data in data signals (such as modulated data signals, such as carrier waves or other transmission mechanisms), and include any information transmission or delivery medium. The term "modulated data signal" or signal refers to a signal whose one or more characteristics are set or altered to encode information in one or more signals. By way of example (but not limited to), communication media include wired media (such as wired networks or direct wired connections) and wireless media (such as acoustic, RF, infrared, and other wireless media).

[0227] Still referencing Figure 15 An example computing environment 1500, which can implement one or more embodiments described herein, 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 multiprocessor architectures can also be used as the processing unit 1504.

[0228] System bus 1508 can be any of several types of bus architectures, which can be further interconnected to memory bus (with or without memory controller), peripheral bus, and local bus using any of a variety of commercially available bus architectures. System memory 1506 includes ROM 1510 and RAM 1512. The Basic Input / Output System (BIOS) can be stored in non-volatile memory, such as ROM, erasable programmable read-only memory (EPROM), or EEPROM, containing basic routines that facilitate the transfer of information between components within computer 1502, such as during startup. RAM 1512 may also include high-speed RAM, such as static RAM for caching data.

[0229] Computer 1502 further includes an internal hard disk drive (HDD) 1514 (e.g., EIDE, SATA) and may include one or more external storage devices 1516 (e.g., floppy disk drive (FDD) 1516, memory stick or flash drive reader, memory card reader, etc.). Although the internal HDD 1514 is shown as residing within computer 1502, the internal HDD 1514 may also be configured for external use in a suitable chassis (not shown). Additionally, although not shown in computing environment 1500, a solid-state drive (SSD) may be used as a supplement or alternative to the HDD 1514.

[0230] Other internal or external storage 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 disc drive that can read from or write to removable media such as CD-ROMs, DVDs, BDs, etc.). External storage 1516 may be facilitated by a network virtual machine. HDD 1514, external storage device 1516, and storage device (e.g., drive) 1520 may be connected to system bus 1508 via HDD interface 1524, external storage interface 1526, and drive interface 1528, respectively.

[0231] The drive and its associated computer-readable storage medium provide non-volatile storage of data, data structures, computer-executable instructions, etc. For computer 1502, the drive and storage medium are adapted to store any data in a suitable digital format. Although the description of computer-readable storage media above refers to a corresponding type of storage device, other types of storage media capable of being read 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 medium may contain computer-executable instructions for performing the methods described herein.

[0232] Multiple program modules can be stored in the drive and RAM 1512, including an operating system 1530, one or more application programs 1532, other program modules 1534, and program data 1536. All or part of the operating system, application programs, modules, and / or data can 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.

[0233] 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, and the emulated hardware may optionally be compatible with... Figure 15 The hardware shown differs from that in this implementation. In such an implementation, the operating system 1530 may include one of a plurality of virtual machines (VMs) hosted on the computer 1502. Furthermore, the operating system 1530 may provide a runtime environment for the application 1532, such as the Java Runtime Environment or the .NET Framework. A runtime environment is a consistent execution environment that allows the application 1532 to run on any operating system that includes that runtime environment. Similarly, the operating system 1530 may support containers, and the application 1532 may be in the form of a container. A container is a lightweight, standalone, executable software package that includes, for example, code, runtime, system tools, system libraries, and application settings.

[0234] Furthermore, computer 1502 can enable security modules, such as a Trusted Processing Module (TPM). For example, using a TPM, the boot component hashes the next boot component over time and waits for the result to match a security value before loading the next boot component. This process can occur at any layer of the computer 1502's code execution stack, such as at the application execution level or the operating system (OS) kernel level, thereby achieving security at any level of code execution.

[0235] User entities can input commands and information into computer 1502 through one or more wired / wireless input devices (such as keyboard 1538, touchscreen 1540, and pointing devices such as mouse 1542). Other input devices (not shown) may include microphones, infrared (IR) remote controls, radio frequency (RF) remote controls or other remote controls, joysticks, virtual reality controllers and / or virtual reality headsets, game controllers, styluses, image input devices (e.g., cameras), gesture sensor input devices, visual motion sensor input devices, emotion or face detection devices, biometric input devices (e.g., fingerprint or iris scanners), etc. These and other input devices are typically connected to processing unit 1504 via input device interface 1544, which may be coupled to system bus 1508, but may also be connected via other interfaces such as parallel ports, IEEE 1394 serial ports, game ports, USB ports, IR interfaces, etc. Interfaces, etc.

[0236] Monitor 1546 or other types of display devices can also be connected to system bus 1508 via an interface (such as video adapter 1548). In addition to monitor 1546, the computer typically includes other peripheral output devices (not shown), such as speakers, printers, etc.

[0237] Computer 1502 can operate in a networked environment using logical connections to one or more remote computers (such as remote computer 1550) via wired and / or wireless communications. Remote computer 1550 can be a workstation, server computer, router, personal computer, laptop computer, microprocessor-based entertainment device, peer-to-peer device, or other common network node, and typically includes many or all of the elements described relative to computer 1502, although for simplicity only memory / storage device 1552 is shown. The depicted logical connections include wired / wireless connections to a local area network (LAN) 1554 and / or a larger network (e.g., a wide area network (WAN) 1556). Such LAN and WAN networking environments are common in offices and companies and facilitate the establishment of enterprise-wide computer networks (such as intranets), all of which can connect to global communications networks (e.g., the Internet).

[0238] When used in a LAN network environment, computer 1502 can connect to local network 1554 via a wired and / or wireless communication network interface or adapter 1558. Adapter 1558 can facilitate wired or wireless communication to LAN 1554, which may also include a wireless access point (AP) configured thereon for communicating with adapter 1558 in wireless mode.

[0239] When used in a WAN network environment, computer 1502 may include modem 1560, or may connect to a communication server on WAN 1556 via other means (such as via the Internet) to establish communication through WAN 1556. Modem 1560 (which may be internal or external, and may be a wired or wireless device) may be connected to system bus 1508 via input device interface 1544. In a networked environment, program modules depicted relative to computer 1502 or parts thereof may be stored in remote memory / storage device 1552. The network connections shown are merely examples, and other methods may be used to establish communication links between computers.

[0240] When used in a LAN or WAN network environment, computer 1502 can access cloud storage systems or other network-based storage systems as a supplement to or replacement of the aforementioned external storage device 1516. Typically, the connection between computer 1502 and the cloud storage system can be established via LAN 1554 or WAN 1556, for example, via adapter 1558 or modem 1560, respectively. After connecting computer 1502 to the associated cloud storage system, external storage interface 1526 can manage the storage provided by the cloud storage system with the help of adapter 1558 and / or modem 1560, just as it would manage other types of external storage. For example, external storage interface 1526 can be configured to provide access to cloud storage sources as if these sources were physically connected to computer 1502.

[0241] Computer 1502 can operatively communicate with any wireless device or entity operatively configured in wireless communication, such as printers, scanners, desktop and / or portable computers, personal digital assistants, communication satellites, any device or location associated with wirelessly detectable tags (e.g., kiosks, newsstands, store shelves, etc.), and telephones. This can include Wi-Fi and Wireless technology. Therefore, communication can be structured in the same way as existing networks, or simply self-organizing communication between at least two devices.

[0242] Additional Information

[0243] The embodiments described herein can be applied to one or more systems, methods, apparatuses, and / or computer program products at any possible level of technical detail integration. A computer program product may include a computer-readable storage medium (or media) having computer-readable program instructions thereon for causing a processor to execute aspects of one or more embodiments described herein. A computer-readable storage medium can be a tangible device capable of retaining and storing instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, superconducting storage devices, and / or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media may also include: portable computer floppy disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable optical disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices (such as punched cards or recessed structures with protrusions for recording instructions), and / or any suitable combination of the foregoing. As used herein, computer-readable storage media should not be construed as transient signals themselves, such as radio waves and / or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides and / or other transmission media (e.g., optical pulses transmitted through fiber optic cables) and / or electrical signals transmitted through wires.

[0244] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to a corresponding computing / processing device and / or via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network) to an external computer or external storage device. This network may include copper transmission cables, optical fiber transmission, wireless transmission, 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 them to a computer-readable storage medium within the corresponding computing / processing device. The computer-readable program instructions used to perform the operations of one or more embodiments described herein can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, configuration data for integrated circuits, and / or source code and / or object code written in any combination of one or more programming languages ​​(including object-oriented programming languages ​​such as Smalltalk, C++, etc.) and / or procedural programming languages ​​(such as the "C" programming language and / or similar programming languages). Computer-readable program instructions may be executed entirely on a computer, partially on a computer, as a standalone software package, partially on a computer and / or partially on a remote computer, or entirely on a remote computer and / or a server. In the latter case, the remote computer may be connected to the computer via any type of network (including local area network (LAN) and / or 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)) may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry in order to perform aspects of one or more embodiments described herein.

[0245] The aspects of one or more embodiments described herein are 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 should be understood that each block in 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, special-purpose computer, and / or other programmable data processing apparatus to produce a machine, such that the instructions, executable via the processor of the computer or other programmable data processing apparatus, can create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that can direct a computer, programmable data processing apparatus, and / or other apparatus to operate in a particular manner. The computer-readable storage medium storing the instructions can include an article of manufacture comprising instructions that can implement aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram. Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus and / or other apparatus to cause a series of operations to be performed on the computer, other programmable apparatus and / or other apparatus, thereby producing a computer-implemented process, such that the instructions, which execute on the computer, other programmable apparatus and / or other apparatus, perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0246] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and / or operation of possible implementations of a system, computer-implementable method, and / or computer program product according to one or more embodiments described herein. In this regard, each box in a flowchart or block diagram may represent a module, segment, and / or portion of instructions, including one or more executable instructions for implementing a specified logical function. In one or more alternative embodiments, the functions marked in the boxes may occur in a different order than indicated in the figures. For example, two consecutively displayed boxes may execute substantially simultaneously, and / or sometimes in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and / or combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware system capable of performing the specified functions and / or actions, and / or executing one or more combinations of dedicated hardware and / or computer instructions.

[0247] Although the subject matter has been described above in the general context of computer-executable instructions for computer program products running on computers and / or computers, those skilled in the art will recognize that one or more embodiments described 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 specific tasks and / or implement specific abstract data types. Furthermore, the aforementioned computer-implemented methods can be practiced with other computer system configurations, including single-processor and / or multi-processor computer systems, small computing devices, mainframe computers, and computers, handheld computing devices (e.g., PDAs, telephones), and / or microprocessor-based or programmable consumer and / or industrial electronic devices. The aspects shown can also be practiced in a distributed computing environment, where tasks are performed by remote processing devices connected via a communication network. However, one or more (if not all) aspects of one or more embodiments described herein can be practiced on a standalone computer. In a distributed computing environment, program modules can reside in both local memory storage devices and remote memory storage devices.

[0248] As used herein, the terms “component,” “system,” “platform,” and / or “interface” may refer to and / or include computer-related entities or entities associated with an operating machine having one or more specific functions. Entities described herein may be hardware, a combination of hardware and software, software, or software in execution. For example, a component may be, but is not limited to, a process running on a processor, a processor, an object, an executable program, a thread of execution, a program, and / or a computer. As an example, an application running on a server and the server itself may both be components. One or more components may reside within a process and / or a thread of execution, and components may reside on a single computer and / or be distributed across two or more computers. In another example, a corresponding component may be executable from various computer-readable media that store various data structures. These components may communicate, for example, via local and / or remote processes based on signals having one or more data packets (e.g., data from one component interacts with another component in a local system, a distributed system, and / or with other systems via a network such as the Internet). As another example, a component may be a device having specific functionality provided by mechanical parts operated by electrical or electronic circuitry, which is operated by software and / or firmware applications executed by a processor. In this scenario, the processor can be internal and / or external to the device and can execute at least a portion of the software and / or firmware applications. As yet another example, the component can be a means of providing specific functionality through electronic components without mechanical parts, wherein the electronic components can include a processor and / or other means for executing software and / or firmware that at least partially endow the electronic components with functionality. In one aspect, the component can be simulated via a virtual machine, for example, within a cloud computing system.

[0249] Furthermore, the term “or” is intended to mean inclusive “or” rather than exclusive “or.” That is, unless otherwise specified or clearly apparent from the context, “X uses A or B” is intended to mean any natural inclusive arrangement. In other words, if X uses A; X uses B; or X uses both A and B, then “X uses A or B” is satisfied in any of the foregoing examples. Furthermore, unless otherwise specified or clearly apparent from the context that a singular form is involved, the article “a” as used in the subject matter description and accompanying drawings should generally be interpreted as meaning “one or more.” As used herein, the terms “example” and / or “exemplary” are used to indicate as an example, instance, or illustration. For the avoidance of doubt, the subject matter described herein is not limited to such examples. Moreover, 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, nor does it exclude equivalent exemplary structures and techniques known to those skilled in the art.

[0250] As used in this subject matter specification, the term "processor" can refer to virtually any computing processing unit and / or device, including but not limited to: a single-core processor; a single processor with software multithreading capabilities; a multi-core processor; a multi-core processor with software multithreading capabilities; a multi-core processor with hardware multithreading technology; a parallel platform; and / or a parallel platform with distributed shared memory. Additionally, a processor can refer to an integrated circuit, application-specific integrated circuit (ASIC), digital signal processor (DSP), field-programmable gate array (FPGA), programmable logic controller (PLC), complex programmable logic device (CPLD), discrete gate or transistor logic components, discrete hardware components, and / or any combination thereof designed to perform the functions described herein. Furthermore, processors can utilize nanoscale architectures, such as, but not limited to, molecular-based transistors, switches, and / or gates, to optimize space utilization and / or enhance the performance of the associated device. A processor can be implemented as a combination of computing processing units.

[0251] In this document, terms such as “storage,” “memory,” “data storage,” “database,” and any other information storage component substantially related to the operation and function of a component are used to refer to a “memory component,” an entity embodied in “memory,” or a component containing memory. The memory and / or memory components described herein can be volatile or non-volatile memory, or may include both. By way of illustration and not limitation, non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), flash memory, and / or non-volatile random access memory (RAM) (e.g., ferroelectric RAM (FeRAM)). Volatile memory may include RAM, which may, for example, act as external cache memory. By way of example and not limitation, RAM can take many forms, such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous linked DRAM (SLDRAM), direct Rambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), and / or Rambus dynamic RAM (RDRAM). Furthermore, the memory components and / or computer-implemented methods of the systems described herein are intended to include, but are not limited to, these and / or any other suitable types of memory.

[0252] The foregoing only includes examples of systems and computer-implemented methods. It is certainly impossible to describe every conceivable combination of components and / or computer-implemented methods for the purpose of describing one or more embodiments, but those skilled in the art will recognize that many further combinations and / or arrangements of one or more embodiments are possible. Furthermore, with regard to the use of the terms “comprising,” “having,” “possessing,” etc., in the detailed description, claims, appendices, and / or drawings, these terms are intended to be inclusive in a manner similar to how the term “comprising” is interpreted when used as a transitional word in the claims.

[0253] Descriptions of various implementation schemes may use the phrases “implementation scheme,” “various implementation schemes,” “one or more implementation schemes,” and / or “some implementation schemes,” each of which may refer to one or more identical or different implementation schemes.

[0254] Various embodiments have been described for illustrative purposes, but these descriptions 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 chosen to best explain the principles, practical applications, and / or technical improvements relative to market technology of the embodiments, and / or to enable others skilled in the art to understand the embodiments described herein.

Claims

1. A system comprising: Memory, which stores computer-executable components; as well as A processor that executes a computer-executable component stored in the memory, wherein the computer-executable component includes: Identification component, the identification component identifying the input and output set of a charged particle device; as well as A parameterized component that tracks the inputs and outputs in the set based on a common clock shared by the inputs and outputs in the set.

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

3. The system of claim 1, wherein the computer-executable component further comprises: A timestamping component that timestamps the inputs and outputs based on data output from the universal clock. The timestamp is unaffected by changes in the XY position output in the output.

4. The system of claim 1, wherein the computer-executable component further comprises: A filtering component that filters out interference frequency outputs that are affecting the imaging output in the output by means of interference frequencies corresponding to the interference frequency output of the general clock scan.

5. The system of claim 1, wherein the computer-executable component further comprises: A synchronization component that determines a second timing of an excitation clock used by the scientific instrument for dynamic excitation and synchronizes a first timing of the general-purpose clock with the second timing of the excitation clock.

6. The system of claim 1, wherein the universal clock is used without adjustment of the universal clock, the adjustment being based on environmental interference with the scientific instrument, the environmental interference including changes in the XY position output of the output.

7. The system of claim 1, wherein the computer-executable component further comprises: An evaluation component that identifies the time delay between different combinations of inputs, outputs, or both in the set of inputs and outputs based on the universal clock.

8. The system of claim 1, wherein the computer-executable component further comprises: A recording component that records the XY position output set from the output of the scientific instrument. The recording component omits recording the XY position output corresponding to the beam blanking.

9. A computer-implemented method, the computer-implemented method comprising: A system identifier is a collection of inputs and outputs of a scientific instrument that is operatively coupled to a processor. as well as The system tracks the inputs and outputs in the set based on a common clock shared by the inputs and outputs in the set.

10. The computer-implemented method according to claim 9, wherein the computer-implemented method further comprises: The system generates timestamps for the inputs and outputs based on data output from the universal clock, wherein the timestamps are unaffected by changes in the XY position output in the output.

11. The computer-implemented method according to claim 9, wherein the computer-implemented method further comprises: The system filters out the interference frequency output that is affecting the imaging output by scanning the interference frequency output with the general clock.

12. The computer-implemented method according to claim 9, wherein the computer-implemented method further comprises: The system determines the first timing of the excitation clock used by the scientific instrument for dynamic excitation; as well as The system synchronizes the second timing of the general-purpose clock with the first timing of the excitation clock.

13. The computer-implemented method according to claim 9, wherein the computer-implemented method further comprises: The system uses the universal clock without adjusting the universal clock based on environmental disturbances to the scientific instrument, including changes in the XY position output.

14. The computer-implemented method according to claim 9, wherein the computer-implemented method further comprises: The system identifies the time delay between different combinations of inputs, outputs, or both in the set of inputs and outputs according to the universal clock.

15. The computer-implemented method according to claim 9, wherein the computer-implemented method further comprises: The system records the XY position output set from the output of the scientific instrument. The records mentioned include the XY position output corresponding to the omitted records and the bundle blanking.

16. 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 therein, and the program instructions being executable by a processor to cause the processor to: The processor identifies the set of inputs and outputs of the scientific instrument; and The processor tracks the inputs and outputs of the set based on a common clock shared by the inputs and outputs of the set.

17. The computer program product of claim 16, wherein the program instructions are further executable by the processor to cause the processor to: The processor generates timestamps for the inputs and outputs based on data output from the general clock, wherein the timestamps are unaffected by changes in the XY position output in the output.

18. The computer program product of claim 16, wherein the program instructions are further executable by the processor to cause the processor to: The processor filters out the interference frequency output that is affecting the imaging output in the output by scanning the interference frequency corresponding to the interference frequency output according to the general clock.

19. The computer program product of claim 16, wherein the program instructions are further executable by the processor to cause the processor to: The processor uses the universal clock without adjusting the universal clock based on environmental disturbances to the scientific instrument, including changes in the XY position output.

20. The computer program product of claim 16, wherein the program instructions are further executable by the processor to cause the processor to: The processor identifies the time delay between different combinations of inputs, outputs, or both in the set of inputs and outputs according to the general clock.

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