Dynamically adaptive threshold for qubit resetting

Abstract

One or more systems, devices, computer program products, and / or computer-implemented methods of use provided herein relate to a process for dynamically determining a threshold for determining a state of a qubit and applying the threshold for manipulating pulses to de-excite the qubit. The system may include a memory storing computer-executable components and a processor executing the computer-executable components stored in the memory, and the computer-executable components may include a determination component configured to determine a threshold from a plurality of thresholds to apply to a measurement of the state of the qubit based on a probability distribution of the states of the qubit, wherein a measurement on one side of the threshold indicates the qubit is in a ground state and a measurement on the other side of the threshold indicates the qubit is in an excited state.

Description

[Technical Field]

[0001] The present disclosure relates to determining the state of a qubit in a quantum system, and more particularly to dynamically determining a threshold for accurately determining the state of a qubit in a quantum system. [Background technology]

[0002] In quantum computing systems, resetting a qubit to a lower excited or ground state may be performed, such as to reuse the qubit in the same or a different quantum operation. Summary of the Invention

[0003] STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT This invention was made with government support under Contract No. W911NF-16-1-0114 awarded by the Intelligence Advanced Research Projects Activity (IARPA). The U.S. Government has certain rights in this invention.

[0004] The following presents a summary to provide a basic understanding of one or more embodiments described herein. This summary is not intended to identify key or critical elements and / or to delineate the scope of particular embodiments or the claims. Its sole purpose is to present concepts in a simplified form as a prelude to the more detailed description that is presented later. In one or more embodiments described herein, a system, computer-implemented method, apparatus, and / or computer program product may provide a process for dynamically determining a threshold for determining the state of a qubit and, optionally, applying the threshold to manipulate pulses to de-excite the qubit to its ground state.

[0005] According to an embodiment, the system may include a memory storing computer-executable components and a processor executing the computer-executable components stored in the memory, and the computer-executable components may include a determination component configured to determine one of a plurality of thresholds to apply to a measurement of the state of the qubit based on a probability distribution of the state of the qubit, wherein a measurement on one side of the threshold indicates that the qubit is in a ground state and a measurement on the other side of the threshold indicates that the qubit is in an excited state.

[0006] An advantage of the above system may be that it determines in real time the threshold to apply to the measurement of the qubit state, allowing for more accurate measurements of the device, thereby reducing the number of operations required to produce an acceptable result.

[0007] According to another embodiment, a computer-implemented method may comprise determining, by a system operably coupled to a processor, one of a plurality of thresholds to apply to a measurement of a state of a qubit based on a probability distribution of the states of the qubit, wherein a measurement on one side of the threshold represents the qubit being in a ground state and a measurement on the other side of the threshold represents the qubit being in an excited state.

[0008] An advantage of the above method may be that the threshold applied to the measurement of the qubit state can be determined in real time to enable more accurate measurements of the device, thereby reducing the number of operations required to produce acceptable results.

[0009] According to yet another embodiment, a computer program product providing a process for dynamically determining a threshold for determining the state of a qubit may comprise a computer-readable storage medium having program instructions embodied thereon, the program instructions being executable by the processor to cause the processor to perform the following procedure: determine, by the processor, based on a probability distribution of the states of the qubit, one threshold of a plurality of thresholds to apply to a measurement of the state of the qubit, wherein a measurement on one side of the threshold represents the qubit being in a ground state and a measurement on the other side of the threshold represents the qubit being in an excited state.

[0010] An advantage of the above computer program product may be that it determines in real time the threshold to apply to measurements of the state of a qubit to enable more accurate measurements of the instrument, thereby reducing the number of operations required to produce an acceptable result.

[0011] Another advantage of one or more of the above systems, computer-implemented methods, and / or computer program products may be the ability to dynamically adapt the thresholds utilized to determine the state of a qubit based on the determined current probability distribution. In such a case, a more accurate determination of the actual state of the qubit may be utilized. This may reduce inaccurate decisions and thus increase the performance of the implemented quantum circuit. That is, additional operations may be performed to optimize the coherence time usage of one or more qubits. Furthermore, as a result of reducing inaccurate decisions, the final measurement of the implemented quantum circuit may be more accurate.

[0012] In one or more embodiments of the above systems, computer-implemented methods and / or computer program products, the determination component may be configured to selectively determine the threshold value based on one or more electrical, mechanical or structural parameters of a qubit physical circuit that includes the qubit, or one or more electrical, mechanical or structural parameters of a quantum device that includes the qubit.

[0013] According to one or more embodiments of the above system, computer-implemented method, and / or computer program product, the readout component may be configured to determine a plurality of measurements defining a plurality of states of the qubit at different instances, the calibration component may combine the plurality of measurements to map the plurality of states to one-dimensional signal values representing selected probability distributions for the excited and ground states of the qubit, the classification component may be configured to calculate a probability distribution of a state classification error of the qubit based on the signal values, and the determination component may be configured to apply one threshold among different thresholds that minimizes the probability of a state classification error of the qubit.

[0014] An advantage of one or more of the above systems, computer-implemented methods, and / or computer program products may be the dynamic application of accurate, probability distribution-based thresholds compared to the continuous use of inapplicable thresholds, such as for multiple reset iterations.

[0015] In one or more embodiments of the above systems, computer-implemented methods, and / or computer program products, the readout component may be configured to measure the state of the qubit, and the pulse generation component may generate a pulse that resets the qubit to its ground state based on a determination that the qubit is in an excited state, and one of the different thresholds is applied to provide the determination.

[0016] An advantage of one or more of the above systems, computer-implemented methods and / or computer program products may be the ability to reset a qubit to its true ground state rather than incorrectly resetting it to a lower excited state that is not the true ground state. [Brief explanation of the drawings]

[0017] [Figure 1]FIG. 1 shows a block diagram of an example non-limiting system that can provide a process for dynamically determining a threshold for determining the state of a qubit, according to one or more embodiments described herein.

[0018] [Figure 2] FIG. 1 shows a block diagram of another exemplary, non-limiting system that may provide a process for dynamically determining a threshold for determining the state of a qubit, and optionally applying a threshold for manipulating pulses to de-excite the qubit to its ground state, in accordance with one or more embodiments described herein.

[0019] [Figure 3] 3 shows a set of graphs illustrating the concept of one or more thresholds associated with the execution of one or more processes by the non-limiting system of FIG. 2, in accordance with one or more embodiments described herein.

[0020] [Figure 4] 3 shows a graph illustrating the concept of one or more probability distributions associated with the execution of one or more processes by the non-limiting system of FIG. 2, in accordance with one or more embodiments described herein.

[0021] [Figure 5] 3 shows another graph illustrating the concept of one or more probability distributions associated with the execution of one or more processes by the non-limiting system of FIG. 2, in accordance with one or more embodiments described herein.

[0022] [Figure 6] 1 illustrates an overview of a process for determining and using a threshold value according to one or more embodiments described herein.

[0023] [Figure 7]FIG. 1 illustrates a process flow for providing dynamic determination of a threshold for determining the state of a qubit, and optionally applying a threshold for manipulating pulses to de-excite the qubit to its ground state, according to one or more embodiments described herein.

[0024] [Figure 8] 1 illustrates a block diagram of an exemplary non-limiting operating environment in which one or more embodiments described herein may be provided.

[0025] [Figure 9] 1 illustrates a block diagram of an example non-limiting cloud computing environment in accordance with one or more embodiments described herein.

[0026] [Figure 10] 1 illustrates a block diagram of exemplary, non-limiting abstraction model layers according to one or more embodiments described herein. DETAILED DESCRIPTION OF THE INVENTION

[0027] The following detailed description is merely exemplary and is not intended to limit the embodiments and / or the application or uses of the embodiments. Furthermore, there is no intention to be bound by any express or implied information presented in the foregoing Summary section or the Detailed Description section. One or more embodiments will now be described with reference to the drawings, in which like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a more thorough understanding of one or more embodiments. It will be apparent, however, that in various instances, one or more embodiments may be practiced without these specific details.

[0028] As used herein, a quantum circuit may be a set of operations, such as gates, that are performed on a set of real-world physical qubits for the purpose of obtaining one or more qubit measurements. A quantum processor may comprise one or more real-world physical qubits.

[0029] A qubit state may exist (or be coherent) for only a finite amount of time. Thus, a goal of operation of a quantum logic circuit (e.g., including one or more qubits) may be to maximize utilization of the coherence time of the utilized qubits. The time spent operating a quantum logic circuit may disadvantageously reduce the available time for operations on one or more qubits. This may be due to the available coherence time of one or more qubits before decoherence of the one or more qubits. For example, the qubit state may be lost within 100-200 microseconds in one or more cases.

[0030] The operation of the quantum circuit may be supported by a pulse component (also referred to herein as a waveform generator) or the like to generate one or more physical pulses and / or other waveforms, signals and / or frequencies to alter one or more states of one or more physical qubits. The altered states can be measured, thus allowing one or more computations to be performed on the qubits and / or their respective altered states.

[0031] Operations on qubits may generally introduce some errors, such as some level of decoherence and / or some level of quantum noise, which may refer to noise resulting from the discrete and / or stochastic nature of quantum interactions, further affecting the usability of the qubits.

[0032] Initializing qubits to a known state may be a standard element of general quantum computing. Initialization may typically utilize a qubit measurement followed by an operation that is conditional on the measurement result. This initialization scheme may be limited by measurement fidelity and may be improved by performing more than one measure-and-reset operation. However, because the optimal measurement threshold used to distinguish the qubit state from the measurement signal may depend on an expected distribution (e.g., a probability distribution) of the qubit states, which is not constant throughout the sequence, using a single threshold may result in high initialization errors.

[0033] For example, a conditional reset (also referred to herein as an active reset) may be utilized to read out the qubit state, and a reset pulse may be applied based on the result. That is, the qubit readout process may map the qubit state to a one-dimensional "signal value," such as through digital downconversion to in-phase and quadrature (I, Q) components, integration and rotation, and / or other applicable processes. The integration of the signal value may be performed using a matched filter kernel. The signal value may represent the sum of (multiple) normal distributions for each of the qubit's excited and ground states. Based on a calibration run, a state threshold, also referred to herein as a state threshold, may be utilized. The actual qubit state may be classified using the state threshold. For example, If the signal value is greater than or equal to the threshold, then the state is excited (|1>), or If signal value < threshold, then ground (|0>) state.

[0034] A reset pulse can be conditionally generated to affect the qubit based on the determined actual qubit state, such as when the qubit is not yet in the basis state (e.g., the signal value is greater than or equal to a threshold). However, repeated conditional resets are not guaranteed to continuously reduce the population of remaining |1>. Rather, repeatedly using the same threshold can be harmful and introduce initialization errors, such as inaccurate determination of the qubit state, thus resulting in a non-basis state qubit being utilized in quantum circuit operations, subsequently introducing errors into quantum circuit measurement results.

[0035] In an example, briefly referring to graph 300 of FIG. 3 , thresholds that may be utilized to minimize decision error for the |+> state are shown. The graph shows ground and excited state probability distributions (e.g., logarithms of probabilities) for qubit states (e.g., 0 to 1). As shown, one or more peaks 302 of excited state probability distribution 304 may be classified as ground states, such as when peak 302 may arise from T1 decay. Also shown, one or more peaks 306 of ground state probability distribution 308 may be classified as excited states, such as when peak 306 may arise from a “hot” qubit state or measurement backaction. Additional sources of such error for either peak 302 or 306 may additionally and / or alternatively include frequency- or amplitude-based calibration inaccuracies and / or crosstalk.

[0036] Referring now briefly to graph 350 of FIG. 3 , ground state probability distribution 358 and excited state probability distribution 354 are shown for the same thresholds as shown in graph 300. As shown, the conditional reset may alter qubit state distributions 308 and 304 to qubit state distributions 358 and 354, respectively, such as increasing |0〉 and decreasing |1〉. Furthermore, in applications, dynamic effects in the qubit, damping, noise, and / or the like may change the shape of the distributions after each reset iteration. That is, use of the same threshold may result in erroneous determination of the qubit's state, and therefore inaccurate measurements from quantum circuit operation utilizing the qubit after the conditional reset.

[0037] To address one or more shortcomings of existing techniques for qubit reset, one or more embodiments of a system, computer-implemented method and / or computer program product are provided that may generally provide a process for dynamically determining a threshold for determining the state of a qubit, and optionally applying a threshold for manipulating pulses that de-excite the qubit to its ground state.

[0038] This may be desirable because it allows the qubit to be reused in operations on the same quantum circuit and / or the qubit to be reset to more quickly begin operation of a second quantum circuit. Accurate resetting may allow for reduced errors in quantum circuit operations and the resulting measurements determined therefrom. Accurate resetting may also generally allow for an increased usable coherence time of one or more qubits in a system. For example, a more quickly and more accurately resetting a first qubit may affect a longer usable coherence time of a second qubit that interacts with the first qubit after the first qubit is reset.

[0039] Generally, a threshold may be determined based on one or more measurement readouts of each qubit in its excited and / or ground state. Based on the measurements, a probability distribution of a particular state of the qubit may be determined. Also based on the measurements, an applicable threshold may be determined. The threshold may be used to determine the actual state of the qubit. One or more iterations may be performed. If the qubit is not yet in its ground state, the resulting information may be used to generate a reset pulse that affects (e.g., de-excites) the qubit. The process of measurement and threshold determination may be repeated to determine whether one or more additional reset pulses need to be generated, with the goal of accurately de-exciting the qubit to its respective ground state.

[0040] One or more embodiments will now be described with reference to the drawings. Like reference numerals are used to refer to like elements throughout. As used herein, the terms "entity," "requesting entity," and "user entity" may refer to machines, devices, components, hardware, software, smart devices, and / or humans. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a more thorough understanding of one or more embodiments. It will be apparent, however, that in various instances, one or more embodiments may be practiced without these specific details.

[0041] Furthermore, the embodiments illustrated in one or more figures described herein are merely exemplary, and thus the architecture of the embodiments is not limited to the systems, devices, and / or components illustrated therein, or to any particular order, connection, and / or coupling of the systems, devices, and / or components illustrated therein. For example, in one or more embodiments, non-limiting systems described herein, such as non-limiting systems 100 and / or 200 shown in Figures 1 and 2, and / or systems thereof, may further comprise, be associated with, and / or be coupled to, one or more computers and / or computing-based elements described herein with reference to an operating environment, such as operating environment 800 shown in Figure 8. In one or more described embodiments, the computers and / or computing-based elements may be used in connection with implementing one or more of the systems, devices, components, and / or computer-implemented operations shown and / or described in connection with Figures 1 and / or 2 and / or other figures described herein.

[0042] Referring first generally to Figure 1 , one or more embodiments described herein may include one or more devices, systems, and / or apparatus that may provide a process for dynamically determining a threshold for determining the state of a qubit, as briefly described above. Shown in Figure 1 is a block diagram of an exemplary, non-limiting system 100 that may provide such a probing process, according to one or more embodiments described herein. Referring now to one or more processes, simplifications, and / or uses of non-limiting system 100, the descriptions provided both above and below herein may also relate to one or more other non-limiting systems described herein, such as non-limiting system 200, as described in detail below.

[0043] 1, non-limiting system 100 can include a classical system 102 that can be utilized with a quantum system (not shown). Classical system 102, such as qubit reset system 102, can include one or more components, such as memory 104, quantum processor 106, bus 105, analysis component 116, and / or decision component 118.

[0044] In general, qubit reset system 102 may utilize a determination component to determine one threshold 119 of multiple thresholds to apply to the measurement of the state of the qubit. This determination may be based on a probability distribution of the state of the qubit. Unlike the illustration of FIG. 3, the threshold may be determined from a set of thresholds. Also, unlike the illustration of FIG. 3, the threshold may take into account a probability distribution in which there is no continued use of the same or previous threshold. That is, state threshold 119 may be dynamically determined based on the probability distribution. A measurement on one side of the threshold, e.g., below, may indicate that the qubit is in a ground state, and a measurement on another side of the threshold, e.g., above, may indicate that the qubit is in an excited state, such as a first excited state. In one or more embodiments, the probability distribution data (e.g., data and / or metadata) may be determined by analysis component 116.

[0045] 2, a diagram of an exemplary, non-limiting system 200 that can provide a process for dynamically determining a threshold for determining the state of a qubit and optionally applying a threshold for steering pulses to de-excite the qubit to the ground state is shown. For example, FIG. 2 shows a block diagram of an exemplary, non-limiting system 200 that can utilize a waveform generator 210 to affect qubit 207A based on the use of a threshold 219 that can be dynamically changed for different measurement iterations (e.g., quantum measurement readout 220) that result in different probability distributions of the qubit state of qubit 207A.

[0046] In general, non-limiting system 200 may apply one or more processes for resetting a qubit while minimizing reset error due to iteration. More specifically, non-limiting system 200 may perform a readout of the qubit, use the readout to dynamically determine threshold 219, use threshold 219 to determine the actual state of the qubit, and use waveform generator 210 to further reset the qubit if conditionally desired, such as when the qubit is not already in a ground state and it is desired that the qubit be reset to the ground state of the qubit.

[0047] Repeated descriptions of similar elements and / or processes utilized in each embodiment are omitted for the sake of brevity. As previously indicated, descriptions regarding the embodiment of Figure 1 may be applicable to the embodiment of Figure 2. Similarly, descriptions regarding the embodiment of Figure 2 may be applicable to the embodiment of Figure 1.

[0048] In one or more embodiments, non-limiting system 200 may be a hybrid system and thus may include both quantum and classical systems, such as quantum system 201 and classical-based system 202 (also referred to herein as classical system 202). In one or more other embodiments, quantum system 201 may be separate from, but function in combination with, classical system 202 (e.g., qubit reset system 202). In one or more embodiments, one or more components of quantum system 201, such as readout electronics 213, may be at least partially constituted by, or otherwise included external to, quantum system 201. In one or more embodiments, one or more components of classical system 202 may be at least partially constituted by, or otherwise included external to, quantum system 201.

[0049] One or more communications between one or more components of the non-limiting system 200 may be provided by wired and / or wireless means, including, but not limited to, utilizing a cellular network, a wide area network (WAN) (e.g., the Internet), and / or a local area network (LAN). Suitable wired or wireless technologies for supporting communications may include, but are not limited to, Wireless Fidelity (Wi-Fi), Global System for Mobile Communications (GSM), Universal Mobile Telecommunications System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX), Enhanced General Packet Radio Service (Enhanced GPRS), Third Generation Partnership Project (3GPP) Long Term Evolution (LTE), Third Generation Partnership Project 2 (3GPP2) Ultra Mobile Broadcast (UMB), High Speed Packet Access (HSPA), Zigbee and other 802.XX wireless technologies and / or legacy telecommunications technologies, BLUETOOTH®, Session Initiation Protocol (SIP), ZIGBEE®, RF4CE protocol, WirelessHART protocol, 6LoWPAN (IPv6 over Low Power Wireless Area Network), Z-Wave, ANT, Ultra Wideband (UWB) standard protocols, and / or other proprietary and / or non-proprietary communication protocols.

[0050] Classical system 202 and / or quantum system 201 may be associated with (e.g., accessible through) a cloud computing environment 950, described below with reference to Figure 9, and / or one or more functional abstraction layers (e.g., hardware and software layer 1060, virtualization layer 1070, management layer 1080, and / or workload layer 1090), described below with reference to Figure 10. For example, classical system 202 may be associated with a cloud computing environment 950 such that aspects of classical processing may be distributed between classical system 202 and cloud computing environment 950.

[0051] Referring first to quantum system 201, generally based on a quantum job request 224 that includes, for example, a quantum circuit to be executed, quantum operations component 203 and / or quantum processor 215 may direct the execution of the quantum circuit in quantum logic circuit 208.

[0052] Generally, quantum system 201 (e.g., a quantum computer system, a superconducting quantum computer system, and / or the like) may utilize quantum algorithms and / or quantum circuitry, including computing components and / or devices, to perform quantum operations and / or functions on input data to generate results that may be output to an entity. Quantum circuitry may include quantum bits (qubits), such as multi-bit qubits, physical circuit-level components, higher-level components, and / or functions. Quantum circuitry may include physical pulses that may be structured (e.g., configured and / or designed) to perform desired quantum functions and / or computations on data (e.g., input data and / or intermediate data derived from the input data) and generate one or more quantum results as output. Quantum results, e.g., quantum measurement readout 220, may be responsive to quantum job request 224 and associated input data and may be based, at least in part, on the input data, quantum functions, and / or quantum computations.

[0053] In one or more embodiments, quantum system 201 may include components such as quantum operations component 203, quantum processor 215, pulse component 210 (e.g., a waveform generator), and / or readout electronics 213. In other embodiments, readout electronics 213 may be included at least in part by classical system 202 and / or may be external to quantum system 201. Quantum processor 215 may include quantum logic circuitry 208 that includes one or more, such as multiple, qubits 207. Individual qubits 207A, 207B, and 207C may be fixed frequency and / or single junction qubits, such as transmon qubits.

[0054] Quantum processor 215 may be any suitable processor. Quantum processor 215 may generate one or more instructions for controlling one or more processes of quantum operations component 203 and / or for controlling quantum logic circuit 208.

[0055] Quantum operations component 203 may obtain (e.g., download, receive, retrieve, and / or the like) quantum job requests 224 requesting the execution of one or more quantum programs and / or physical qubit layouts. Quantum job requests 224 may be provided in any suitable format, such as text format, binary format, and / or another suitable format. In one or more embodiments, quantum job requests 224 may be received by a component other than quantum system 201, such as a component of classical system 202.

[0056] Quantum operations component 203 may determine one or more quantum logic circuits, such as quantum logic circuit 208, to execute the quantum program. In one or more embodiments, quantum operations component 203 and / or quantum processor 215 may instruct waveform generator 210 to generate one or more pulses 211, tones, waveforms, and / or the like to affect one or more qubits 207.

[0057] Waveform generator 210 may generally perform one or more quantum processes, calculations, and / or measurements to shift the frequency of one or more qubits 207, such as when in their respective excited states. For example, waveform generator 210 may operate one or more qubit effectors, such as qubit oscillators, harmonic oscillators, pulse generators, and / or the like, to cause one or more pulses to stimulate and / or manipulate the state of one or more qubits 207 comprised by quantum system 201.

[0058] Readout electronics 213 may provide for the transmission, eg, readout, of one or more measurements, signals, and / or the like to a classical system, such as calibration component 212 of qubit reset system 202 .

[0059] Some or all of quantum logic circuit 208 and waveform generator 210 may be contained in a cryogenic environment, such as generated by a cryogenic chamber 217, such as a dilution refrigerator. Indeed, signals may be generated by waveform generator 210 to affect one or more of qubits 207. If qubits 207 are superconducting qubits, cryogenic temperatures, such as about 4 K or below, may be utilized for the function of these physical qubits. Accordingly, one or more elements of readout electronics 213 may also be constructed to perform at such cryogenic temperatures.

[0060] Readout electronics 213, or at least a portion thereof, may be contained in cryogenic chamber 217, such as for reading out the state, frequency and / or other properties of the excited, damped, or otherwise qubit.

[0061] Furthermore, the above description refers to a single set of diagnostic operations being performed on a single qubit. However, where appropriate, diagnostic applications can be provided on one or more qubits of a quantum system at a time. For example, non-neighboring qubits of a qubit logic circuit can be measured simultaneously.

[0062] The operation of classical system 202 will now be described with reference to operations that may be performed on and / or utilized with respect to the readout output from quantum system 201 to provide for the generation of threshold 219 and subsequent qubit state determination of qubit 207.

[0063] Referring specifically now to classical systems, classical system 202 may generally include any suitable type of component, machine, device, equipment, appliance, and / or instrument, including a processor, and / or may be capable of friendly and / or operative communication with wired and / or wireless networks. All such embodiments are contemplated. For example, classical system 202 may comprise a server device, a computing device, a general-purpose computer, an application-specific computer, a quantum computing device (e.g., a quantum computer), a tablet computing device, a handheld device, a server-class computing machine and / or database, a laptop computer, a notebook computer, a desktop computer, a mobile phone, a smartphone, a consumer electronics appliance and / or instrumentation, an industrial and / or commercial device, a digital assistant, a multimedia Internet-enabled phone, a multimedia player, and / or another type of device and / or computing device. Similarly, classical system 202 may be disposed on and / or executed by any suitable device, such as, but not limited to, a server device, a computing device, a general-purpose computer, an application-specific computer, a quantum computing device (e.g., a quantum computer), a tablet computing device, a handheld device, a server-class computing machine and / or database, a laptop computer, a notebook computer, a desktop computer, a mobile phone, a smartphone, consumer electronics and / or instrumentation, an industrial and / or commercial device, a digital assistant, a multimedia Internet-enabled phone, a multimedia player, and / or another type of device and / or computing device.

[0064] Qubit reset system 202 may include multiple components, which may include memory 204, processor 206, bus 205, calibration component 212, classification component 214, analysis component 216, decision component 218, analytical model 222, and / or training component 226.

[0065] Generally, the qubit reset system 202 may obtain a quantum measurement readout 220 from the quantum system 201 and provide a threshold 219 determination based thereon.

[0066] Brief reference will now be made to processor 206, memory 204, and bus 205 of qubit reset system 202. For example, in one or more embodiments, classical system 202 may include processor 206 (e.g., a computer processing unit, microprocessor, classical processor, quantum processor, and / or the like). In one or more embodiments, components associated with qubit reset system 202 described herein, with or without reference to one or more figures of one or more embodiments, may include one or more computer-readable and / or machine-readable, writable and / or executable components and / or instructions that may be executed by processor 206 to provide for the execution of one or more processes defined by such components and / or instructions. In one or more embodiments, processor 206 may include calibration component 212, classification component 214, analysis component 216, determination component 218, analytical model 222, and / or training component 226.

[0067] In one or more embodiments, qubit reset system 202 may include computer-readable memory 204, which may be operably coupled to processor 206. Memory 204 may store computer-executable instructions that, when executed by processor 206, may cause processor 206 and / or one or more other components of qubit reset system 202 (e.g., calibration component 212, classification component 214, analysis component 216, determination component 218, analytical model 222, and / or training component 226) to perform one or more actions. In one or more embodiments, memory 204 may store computer-executable components (e.g., calibration component 212, classification component 214, analysis component 216, determination component 218, analytical model 222, and / or training component 226).

[0068] The qubit reset system 202 and / or its components described herein may be communicatively, electrically, operatively, optically, and / or otherwise coupled to one another via a bus 205. The bus 205 may include one or more of a memory bus, a memory controller, a peripheral bus, an external bus, a local bus, a quantum bus, and / or another type of bus, which may utilize one or more bus architectures. One or more of these examples of bus 205 may be utilized.

[0069] In one or more embodiments, qubit reset system 202 may be communicatively coupled (e.g., communicatively, electrically, operatively, optically, and / or similarly) to one or more external systems (e.g., an electrical output generating system, not shown, one or more output targets, an output target controller, and / or the like), sources and / or devices (e.g., classical and / or quantum computing devices, communication devices, and / or the like), such as via a network. In one or more embodiments, one or more of the components of qubit reset system 202 and / or the components of non-limiting system 200 may reside in the cloud and / or may reside locally in a local computing environment (e.g., at a designated location).

[0070] In addition to the processor 206 and / or memory 204 described above, qubit reset system 202 may include one or more computer- and / or machine-readable, writable, and / or executable components and / or instructions that, when executed by processor 206, may provide for the performance of one or more operations defined by such components and / or instructions.

[0071] Now, referring to the additional components of qubit reset system 202 (e.g., calibration component 212, classification component 214, analysis component 216, decision component 218, analytical model 222 and / or training component 226), generally, qubit reset system 202 may obtain quantum measurement readout 220 from quantum system 201 and determine threshold 219 based thereon.

[0072] Referring first to calibration component 212, calibration component 212 may locate, find, search, and / or otherwise determine quantum measurement readout 220 from quantum system 201 relative to qubit 207. For example, calibration component 212 may locate quantum measurement readout 220 based on one or more instructions from processor 206 and / or a user entity. Quantum measurement readout 220 may be output by readout electronics that may determine multiple measurements (e.g., quantum measurement readout 220) that define multiple states of the qubit at different instances.

[0073] Based on the quantum measurement readout 220, the calibration component 212 may integrate multiple measurements of the quantum measurement readout 220 to map multiple states to one-dimensional signal values representing a selected probability distribution, such as a known probability distribution or a sum of normal distributions, for the excitation and ground states of the qubit.

[0074] For example, the readout of the quantum state of qubit 207 can be approximated by the sum of two normal distributions with mean ±μ and identical standard deviation σ weighted by P(1)=α and P(0)=1−P(1)=1−α in Equation 1.

[0075] Equation 1:αN μ,σ (t)+(1-α)N- μ,σ (t).

[0076] N μ,σ (t) can be a normal distribution with mean μ and standard deviation σ. Normal distributions relate to (classical) measurement results, not quantum states, so they can be summed like mixed states.

[0077] For example, briefly referring to FIG. 4 , the sets of histograms 402 and 404 may represent the ground states. Histogram 402 may represent the probability distribution of the ground states of a qubit before any reset. Histogram 404 may represent the probability distribution of the ground states of a qubit after one reset. Histograms 406, 408, 410, 412, and 414 may represent the excited states of a qubit. Histogram 406 may represent the probability distribution of the excited states of a qubit before any reset. Histogram 408 may represent the probability distribution of the excited states of a qubit after one reset. Histograms 410, 412, and 414 may represent the probability distribution of the excited states of a qubit after additional successive resets 2, 3, and 4, respectively. As shown, repeated resets using an optimal threshold (e.g., dynamically determined threshold 219) for each pass may produce the desirable result of reduced error.

[0078] Additionally, referring to FIG. 5, an actual histogram of the probability distribution is illustrated. As shown, the distribution may not exactly match a perfect theoretical shape such as that shown in FIG. 4. Note that group 502 (■), group 504 (x), and group 506 (+) are actual qubit measurements, while group 508 (□) represents only the estimated state population of the excited state after one reset. Group 506 (+) is the result of measuring a qubit in the |+> state after one reset. In one or more other cases, the excited state population after one reset may be determined as the actual qubit measurement, such as by calibration component 212. Addition of group 502 (■) and group 508 (□), scaled by the population ratio (minimal change, not shown), yields the actual expected state distribution after one reset.

[0079] These multiple measurements may be output to classification component 214. Classification component 214 may generally calculate a probability distribution of the state classification error of the qubit based on the signal values. See, for example, graph 360 of FIG. 3. As shown, the classification error for a given threshold may be given by the sizes of four regions, designated by the excited state classification as base region 362 and by the ground state classification as excited region 366. The optimal threshold may be determined by an exclusive search between the two main peaks of the probability distribution, such as by calculating the error (total region size) for each predicted threshold.

[0080] For example, when measurements are approximated by the sum of two normal distributions, the probability of a state classification error for a threshold τ to classify these results can be given by Equation 2:

[0081] Formula 2:

number

[0082] In Equation 2, the first term is a normal cumulative distribution function Cμ,σ(t) with weight α, which represents the probability that a |1> state readout is misclassified as a |0> state. The second term is (1-C-μ,σ(t)) with weight (1-α), which represents the probability that a |0> readout is misclassified as a |1> state. These errors can result in a |1> state after a conditional reset operation. The existence of a minimum can be derived from the fact that C(t) monotonically increases over t, C(-inf)=0 and C(+inf)=0, where "inf" denotes infinity. In one or more embodiments, E(a,t) can be estimated by using experimental data (e.g., histogram binning) or a spreadsheet.

[0083] It should be noted that in one or more embodiments, the classification component 214 and the calibration component 212 may be comprised by or comprise an analysis component (eg, analysis component 116) as shown in FIG.

[0084] Using the results of the calibration component 212 and the classification component 214, the determination component 218 may determine one of multiple thresholds 219 to apply to the measurement of the state of the qubit based on the probability distribution of the state and / or the probability distribution of the qubit state classification error.

[0085] In one or more embodiments, the decision component 218 may utilize and / or include an analytical model 222. The analytical model 222 may be, include, and / or consist of a classical model, such as a predictive model, a neural network, and / or an artificial intelligence model. The artificial intelligence model and / or neural network (e.g., a convolutional network and / or a deep neural network) may include and / or utilize artificial intelligence (AI), machine learning (ML), and / or deep learning (DL), where learning may be supervised, semi-supervised, and / or unsupervised. For example, the analytical model 222 may include a deep neural network (DNN) or a recurrent neural network (RNN).

[0086] For example, determination component 218 may utilize a supervised learning model (e.g., analytical model 222) to determine threshold 219 to apply for a particular quantum circuit based on one or more kernels 612 (FIG. 6) that may apply to the environment of the particular quantum circuit or qubit. For example, threshold 219 may be one of a number of historical and / or stored thresholds determined by an analytical model, such as illustrated in diagram 600 of FIG. 6 (as described in more detail below).

[0087] The kernel 612 may be written based on multiple calibration measurements that define multiple states of the qubit at different instances. The decision component 218 may further determine a threshold 219 from a set of different thresholds to apply to the qubit (e.g., to measurements and / or data based on readout of the qubit) based on one or more of the kernels 612. The kernel 612 may be and / or include a classification that enables shot integration in a more accurate manner. The kernel 612 may define the use of the qubit and may be specific to one or more thresholds 219 from a set of thresholds, and additionally correspond to particular calibration measurements, such as history, and therefore apply to a particular probability distribution for a particular qubit, etc. In one or more embodiments, the kernel 612 may be integrated across the readout data and thus may be mathematically “multiplicatively commutative” with the thresholds, e.g., where the set of kernels 612 may be multiplied by an appropriate scaling factor so that the same threshold can be used in all cases.

[0088] In one or more embodiments, kernel 612 may not be used and / or may not be defined, such as in cases where only a threshold may be applied.

[0089] Additionally or alternatively, in one or more embodiments, determination component 218 may selectively determine threshold 219 based, at least in part, on one or more electrical, mechanical, or structural parameters of a qubit physical circuit (e.g., qubit physical circuit 208) that includes the qubit, or one or more electrical, mechanical, or structural parameters of a quantum device that includes the qubit. For example, in a particular implementation of a qubit physical circuit, the envelope amplitudes of the excited and / or ground states were different.

[0090] A measurement on one side of, e.g., below, a determined threshold 219 may indicate that the qubit is in a ground state, and a measurement on another side of, e.g., above, the threshold 219 may indicate that the qubit is in an excited state, such as a first excited state. The decision component 218, and thus the threshold 219, may take into account a probability distribution that there is not a continued use of the same or previous threshold. That is, the state threshold 219 may be dynamically determined based on the probability distribution.

[0091] 2, the determined threshold 219 may be utilized by decision component 218 to output the current state of the qubit for which quantum measurement readout 220 was obtained. Conditionally, if it is desired that the qubit be in a ground state, and it is determined by decision component 218 that the qubit is not in a ground state, a communication may be sent to quantum system 201 defining and / or requesting that a reset pulse 211 be generated by waveform generator 210 to further affect the respective qubit. In one or more cases, the particular reset pulse 211 may be based on the determination of decision component 218.

[0092] In one or more cases, the reset pulse may be a conditional Pi rotation about the X-axis of the Bloch sphere that may change the first excited state to the ground state. In one or more other cases, the reset pulse may reset the second excited state (|2>) to the ground state if decision component 218 determines that the qubit is in the second excited state.

[0093] In one or more embodiments, qubit reset system 202 may include a training component 226. Training component 226 may train analytical model 222 based on previously utilized thresholds 219, kernels 612, probability distributions, signal values, and / or the like. In one or more cases, historical data may be stored in memory 204 and / or any other suitable store internal and / or external to qubit reset system 202. Training component 226 may perform training at any suitable frequency, such as after each calibration / classification / decision process iteration, based on selected timing and / or on-demand. Analytical model 222 may be continually updated according to the training. Furthermore, training may make subsequent iterations of use of qubit reset system 202 more accurate and / or efficient.

[0094] 6, a measurement readout 220 may be obtained, such as from readout electronics 213. The signal may be defined by voltage as a function of time.

[0095] The local oscillator 602 may downconvert the signal from the readout electronics 213. An analog-to-digital converter 604 may be utilized to digitize the downconverted signal.

[0096] The integration unit 606 may integrate one or more kernels 612 with the digitized signal, such as supported by an analytical model 222, based on stored data (e.g., thresholds 219, kernels 612, probability distributions, signal values, and / or the like). That is, the voltage may be integrated using phase information to achieve a point in a 2D plane. Depending on the qubit state, the point tends to be in one region or another of the plane. The integration results for the qubit measurement may then be projected onto a known state vector as one-dimensional signal values, and statistics such as a histogram of the qubit readout may be obtained. That is, for example, in cases where integrating the measurement results with a kernel results in two-dimensional (2D) values, the 2D points may be projected onto the state vector, and a previous histogram analysis may be applied, reducing the 2D points to one-dimensional (1D) signal values, thereby utilizing the 1D data.

[0097] In one or more embodiments, the local oscillator 602, the ADC 604, and / or the integration unit 606 may be configured and / or utilized by the calibration component 212 and / or the classification component 214.

[0098] In one or more embodiments, up to 256 thresholds / kernels may be stored per ADC channel. In one or more embodiments, multiple ADC channels may be utilized. For example, thresholds and kernels may be pre-computed (not real-time, as this may take time to perform within the coherence time of the utilized qubits) based on previous measurements and “kept” in some type of “storage” for use. This may be to prepare before execution, such as when a running calculation of the circuit may disadvantageously use the available coherence time of the utilized qubits. The thresholds / kernels may be obtained quickly enough to complete the entire quantum circuit operation within the qubit coherence time.

[0099] The integrated output from the integration unit 606 may be obtained by a comparator, such as configured and / or utilized by a decision component 618. The decision component 618 may output one or more thresholds 219 for determining what reset pulse 211 to generate and / or whether to generate a reset pulse 211. The decision component 618 may utilize an analytical model 222, which may utilize one or more stored thresholds 219. For example, measurements may be performed when an electrical trigger signal is asserted, with one measurement per assertion of the trigger signal. For purposes of simplicity, how the trigger is asserted may be determined by an overall quantum operation.

[0100] As an example, if one wishes to perform three resets in succession to achieve a desired level of low error, such a loop may involve the use of three different thresholds and / or kernels, cycling through the first through third thresholds and / or kernels for successive measurements, then returning to the first.

[0101] Upon a new measurement, the new signal may be compared to the statistics, the plane may be collapsed into a single line, and the qubit state may then be determined. Note that the result of integrating the readout data with the kernel may result in a data set consisting of 2D (two-dimensional) values. For example, the final integrated signal value may be compared to a defined threshold 219. That is, as mentioned above, the measurement may be performed when the electrical trigger signal is asserted. A "new" measurement may refer to a measurement upon assertion of the trigger, which may occur after (e.g., immediately after) the measurement is completed.

[0102] That is, the actual qubit state may be classified, such as by decision component 218, using state thresholds 219. For example: If the signal value is greater than or equal to the threshold, then the state is excited (|1>), or If the signal value < threshold, then the ground (|0>) state, and vice versa.

[0103] A conditional pulse generator, such as constituted by, is and / or utilized by waveform generator 210, then generates reset pulses 211 to control each qubit, such as to de-excite the qubit towards or to the ground state. That is, a reset pulse may be conditionally generated to affect the qubit based on the determined actual qubit state, such as when the qubit is not yet in the ground state (e.g., the signal value is greater than or equal to a threshold value).

[0104] Figure 7 next shows a flow diagram of an exemplary non-limiting method 700 that may provide a process for dynamically determining a threshold for determining the state of a qubit, and optionally applying a threshold for manipulating pulses to de-excite the qubit to the ground state, according to one or more embodiments described herein, such as non-limiting 200 of Figure 2. Although non-limiting method 700 is described with respect to non-limiting system 200 of Figure 2, non-limiting method 700 may also be applicable to other systems described herein, such as non-limiting system 100 of Figure 1. Repeated descriptions of similar elements and / or processes utilized in each embodiment are omitted for the sake of brevity.

[0105] At 702, non-limiting method 700 may include measuring the state of a qubit (eg, qubit 207; 207A) by a system operably coupled to a processor (eg, readout electronics 213).

[0106] At 704, non-limiting method 700 may include determining, by a system (eg, calibration component 212), a plurality of measurements (eg, quantum measurement readout 220) that define a plurality of states of the qubit at different instances.

[0107] At 706, non-limiting method 700 may include integrating the multiple measurements by a system (e.g., calibration component 212) to map the multiple states to one-dimensional signal values representing selected probability distributions for the excitation and ground states of the qubit.

[0108] At 708, non-limiting method 700 may include calculating, by a system (eg, classification component 214), a probability distribution of a state classification error of the qubit based on the signal value.

[0109] At 710, non-limiting method 700 may include determining, by a system (e.g., determination component 218 and / or analytical model 222), one of a plurality of thresholds to apply to the measurement of the state of the qubit based on a probability distribution of the state of the qubit and / or a probability distribution of the state classification error of the qubit.

[0110] At 712, non-limiting method 700 may include determining, by a system (e.g., determination component 218 and / or analytical model 222), a threshold to apply to the qubit based on one or more kernels defining the use of the qubit (the kernels corresponding to multiple calibration measurements), or based on one or more electrical, mechanical, or structural parameters of a qubit physical circuit that includes the qubit, or one or more electrical, mechanical, or structural parameters of a quantum device that includes the qubit.

[0111] At 714, non-limiting method 700 may include applying a threshold (e.g., threshold 219) by a system (e.g., decision component 218 and / or analytical model 222) that minimizes the probability of a qubit state classification error.

[0112] At 716, non-limiting method 700 may include a step of generating, by a system (e.g., waveform generator 210), a pulse (e.g., reset pulse 211) that resets the qubit to the ground state of the qubit based on a determination that the qubit is in an excited state, wherein one of different thresholds is applied to provide the determination.

[0113] Additionally, one or more practical considerations may apply to the use of one or more of the embodiments described above. For example, the conditional reset of a qubit may be performed in real time; T1 decay between readout and reset pulses may increase reset error; other qubits that are not reset may still deteriorate through T1 decay and T2 decoherence; T1 and T2 may be on the order of 50-100 μs for a superconducting transmon qubit; the conditional reset cycle time (from sending the measurement pulse to the end of the reset) may be about 1 μs; and hardware may be controlled to read out the qubit state and control the conditional pulses without software intervention.

[0114] For simplicity of explanation, the computer-implemented and non-computer-implemented methods provided herein are depicted and / or described as a series of acts. It should be understood that the subject innovation is not limited by the acts depicted and / or the order of acts. For example, acts may occur in one or more orders and / or simultaneously, along with other acts not shown and described herein. Furthermore, not all depicted acts may be utilized to implement computer-implemented and non-computer-implemented methods in accordance with the described subject matter. In addition, computer-implemented and non-computer-implemented methods may alternatively be represented as a series of interrelated states via state diagrams or events. Additionally, the computer-implemented methods described hereinafter and throughout this specification may be stored on an article of manufacture to transfer and migrate the computer-implemented methods to a computer. The term article of manufacture, as used herein, is intended to encompass a computer program accessible from any computer-readable device or storage medium.

[0115] Systems and / or devices have been described (and / or further described) herein with respect to interactions between one or more components. Such systems and / or components may include those components or subcomponents, one or more of the specified components and / or subcomponents, and / or additional components, as specified therein. Subcomponents may be implemented as components communicatively coupled to other components rather than being included in a parent component. One or more components and / or subcomponents may be combined into a single component that provides aggregate functionality. Components may interact with one or more other components known to those skilled in the art, but not specifically described herein for the sake of brevity.

[0116] In summary, one or more systems, devices, computer program products, and / or computer-implemented methods of use provided herein relate to a process for dynamically determining a threshold for determining a state of a qubit and applying the threshold for manipulating a pulse to de-excite the qubit. The system may include a memory storing computer-executable components and a processor executing the computer-executable components stored in the memory, and the computer-executable components may include a determination component configured to determine a threshold from a plurality of thresholds to apply to a measurement of the state of the qubit based on a probability distribution of the states of the qubit, wherein a measurement on one side of the threshold indicates the qubit is in a ground state and a measurement on the other side of the threshold indicates the qubit is in an excited state.

[0117] An advantage of one or more of the above systems, computer-implemented methods and / or computer program products may be that the thresholds applied to measurements of qubit states are determined in real time to enable more accurate measurements of the device, thereby reducing the number of operations utilized to produce acceptable results.

[0118] An advantage of one or more of the above systems, computer-implemented methods, and / or computer program products may be the ability to dynamically adapt a threshold utilized to determine the state of a qubit based on the determined current probability distribution. In such a case, a more accurate determination of the actual state of the qubit may be utilized. This may reduce inaccurate decisions and thus increase the performance of the implemented quantum circuit. That is, additional operations may be performed to optimize the coherence time usage of one or more qubits. Furthermore, as a result of reducing inaccurate decisions, the final measurement of the implemented quantum circuit may be more accurate.

[0119] Another advantage of one or more of the above systems, computer-implemented methods, and / or computer program products may be the dynamic application of accurate probability distribution-based thresholds compared to the continuous use of inapplicable thresholds, such as for multiple reset iterations.

[0120] Yet another advantage of one or more of the above systems, computer-implemented methods and / or computer program products may be the ability to reset the qubit to the true ground state rather than incorrectly resetting to a lower excited state that is not the true ground state.

[0121] Indeed, in view of one or more embodiments described herein, a practical application of the systems, computer-implemented methods, and / or computer program products described herein may be the ability to generate signals that precisely de-excite qubits, such as to their ground states, which is a useful and practical computer application, thus providing enhanced (e.g., improved and / or optimized) operation of utilized qubits, such as within quantum logic circuits having a plurality of qubits, such as about 1000 qubits or more. Overall, such computerized tools may constitute a concrete and tangible technological improvement in the field of quantum computing.

[0122] Furthermore, one or more embodiments described herein may be utilized in real-world systems based on the disclosed teachings. For example, one or more embodiments described herein may function within a quantum system that may receive a quantum job request as an input and measure the real-world qubit state of one or more qubits, such as superconducting qubits, of the quantum system. The measurement may be utilized to dynamically determine a threshold for determining the state of the qubits prior to application of a reset pulse in order to de-excite the qubits to their ground state, such as for reusing the qubits in an implemented quantum circuit.

[0123] Additionally, the devices and / or methods described herein may be implemented in one or more domains, such as the quantum domain, to enable scaled quantum program execution. Indeed, use of the devices described herein may be scalable, such as when multiple thresholds and associated kernels are determined and / or stored, such as for multiple different measurements (or sets of measurements) for each of multiple qubits. These one or more processes may be performed at least partially concurrently with one another.

[0124] Systems and / or devices have been described (and / or further described) herein with respect to interactions between one or more components. Such systems and / or components may include those components or subcomponents, one or more of the specified components and / or subcomponents, and / or additional components, as specified therein. Subcomponents may be implemented as components communicatively coupled to other components rather than being included in a parent component. One or more components and / or subcomponents may be combined into a single component that provides aggregate functionality. Components may interact with one or more other components known to those skilled in the art, but not specifically described herein for the sake of brevity.

[0125] One or more embodiments described herein may, in one or more embodiments, be inherently and / or intimately tied to computer technology and cannot be implemented outside of a computing environment. For example, one or more processes performed by one or more embodiments described herein may provide for more efficient and even more feasible program and / or program instruction execution, such as with respect to waveform generation, compared to existing systems and / or techniques. Systems, computer-implemented methods, and / or computer program products that provide for the execution of these processes have considerable utility in the fields of quantum computing and superconducting quantum systems and cannot be equally feasibly implemented in a sensible manner outside of a computing environment.

[0126] One or more embodiments described herein may utilize hardware and / or software to solve problems that are not highly technical, abstract, and cannot be performed as a set of mental activities by a human. For example, a human, or even thousands of humans, cannot efficiently, accurately, and / or effectively determine a threshold for determining the state of a qubit based on a qubit readout measurement, as one or more embodiments described herein can provide. And a human, or even thousands of humans, cannot efficiently, accurately, and / or effectively determine the state of a qubit using a threshold and then apply a reset pulse, if applicable. Also, the human mind, or a human using pen and paper, cannot perform one or more of these processes, as performed by one or more embodiments described herein.

[0127] In one or more embodiments, one or more of the processes described herein may be executed by one or more specialized computers (e.g., specialized processing units, specialized classical computers, specialized quantum computers, specialized hybrid classical / quantum systems, and / or another type of specialized computer) to perform defined tasks for one or more of the techniques described above. One or more embodiments described herein and / or components thereof may be utilized to solve new problems that arise through the use of advances in the above-referenced technologies, quantum computing systems, cloud computing systems, computer architectures, and / or other technologies.

[0128] One or more embodiments described herein may be fully operational (e.g., fully powered on, fully running, and / or another function) to perform one or more other functions, while also performing one or more of the one or more operations described herein.

[0129] 8-10, additional context for one or more embodiments described herein in FIGS. 1-7 is provided in the detailed description.

[0130] Figure 8 and the following discussion are intended to provide a brief, general description of a suitable operating environment 800 in which one or more embodiments described herein in Figures 1-7 may be implemented. For example, one or more components and / or other aspects of the embodiments described herein may be implemented in or associated with, e.g., accessible through, operating environment 800. Furthermore, while one or more embodiments are described above in the general context of computer-executable instructions that may be executed on one or more computers, those skilled in the art will recognize that one or more embodiments may also be implemented in combination with other program modules and / or as a combination of hardware and software.

[0131] Generally, program modules include routines, programs, components, data structures, and / or the like that perform particular tasks and / or implement particular abstract data types. Furthermore, the above methods may be practiced with other computer system configurations, including single-processor or multi-processor computer systems, minicomputers, mainframe computers, Internet of Things (IoT) devices, distributed computing systems, and personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics and / or the like, each of which may be operatively coupled to one or more associated devices.

[0132] Computing devices typically include a variety of media, which may include computer-readable storage media, machine-readable storage media, and / or communication media. The two terms are used interchangeably herein as follows. A computer-readable storage medium or machine-readable storage medium may be any available storage medium that can be accessed by a computer, and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, a computer-readable storage medium and / or machine-readable storage medium may be implemented in connection with any method or technology for storage of information, such as computer-readable and / or machine-readable instructions, program modules, structured and / or unstructured data, etc.

[0133] A computer-readable storage medium may include, but is not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory, or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), Blu-ray disc (BD) and / or other optical disc storage, magnetic cassettes, magnetic tape, magnetic disc storage and / or other magnetic storage devices, solid-state drives, or other solid-state storage devices, and / or other tangible and / or non-transitory media that may be used to store specified information. In this regard, the terms "tangible" or "non-transitory" herein as applied to storage, memory, and / or computer-readable medium are understood as modifiers to exclude merely transmitting transitory signals per se, and do not waive any right to all standard storage, memory, and / or computer-readable media that are not merely transmitting transitory signals per se.

[0134] The computer-readable storage medium may be accessed by one or more local or remote computing devices, for example, via access requests, queries and / or other data retrieval protocols for various operations on the information stored by the medium.

[0135] Communication media typically embodies computer-readable instructions, data structures, program modules, or other structured or unstructured data in a modulated data signal, such as a carrier wave or other transport mechanism, and includes any information delivery or transport medium. The term "modulated data signal" or signal refers to a signal that has one or more of its characteristics set and / or changed in such a manner as to encode information in the signal or signals. By way of example, and not limitation, communication media may include wired media, such as a wired network, direct-wired connection, and / or wireless media (such as acoustic, radio frequency, infrared and / or other wireless media).

[0136] 8 , an exemplary operating environment 800 for implementing one or more embodiments of the aspects described herein may include a computer 802, the computer 802 including a processing unit 806, a system memory 804, and / or a system bus 808. One or more aspects of the processing unit 806 may apply to processors such as 106, 215, and / or 206 of non-limiting systems 100 and / or 200. The processing unit 806 may be implemented in combination with and / or as an alternative to processors such as 106, 215, and / or 206.

[0137] Memory 804 may store one or more computer-readable and / or machine-readable, writable and / or executable components and / or instructions that, when executed by processing unit 806 (e.g., a classical processor, a quantum processor, and / or the like), may provide for the performance of operations defined by the executable components and / or instructions. For example, memory 804 may store computer- and / or machine-readable, writable and / or executable components and / or instructions that, when executed by processing unit 806, may provide for the performance of one or more functions described herein for non-limiting system 100 and / or non-limiting system 200, as described herein with or without reference to one or more figures of one or more embodiments.

[0138] The memory 804 may include volatile memory (e.g., random access memory (RAM), static RAM (SRAM), dynamic RAM (DRAM), and / or the like), non-volatile memory (e.g., read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), and / or electrically erasable programmable ROM (EEPROM), and / or the like), which may utilize one or more memory architectures.

[0139] Processing unit 806 may include one or more types of processors and / or electronic circuitry (e.g., classical processors, quantum processors, and / or the like) that may implement one or more computer-readable and / or machine-readable, writable and / or executable components and / or instructions, which may be stored in memory 804. For example, processing unit 806 may perform one or more operations that may be specified by computer-readable and / or machine-readable, writable and / or executable components and / or instructions, including, but not limited to, logic, control, input / output (I / O), arithmetic, and / or the like. In one or more embodiments, processing unit 806 may be any one or more commercially available processors. In one or more embodiments, processing unit 806 may include one or more central processing units, multi-core processors, microprocessors, dual microprocessors, microcontrollers, systems-on-chips (SOCs), array processors, vector processors, quantum processors, and / or other types of processors. Examples of processing unit 806 may be utilized to implement one or more embodiments described herein.

[0140] The system bus 808 may couple system components, including but not limited to the system memory 804, to the processing unit 806. The system bus 808 may include one or more types of bus structures that may further interconnect a memory bus, a peripheral bus, and / or a local bus (with or without a memory controller) using one or more of a variety of commercially available bus architectures. The system memory 804 may include ROM 810 and / or RAM 812. The basic input / output system (BIOS) may be stored in non-volatile memory such as ROM, erasable programmable read-only memory (EPROM), and / or EEPROM. The BIOS contains the basic routines that help to transfer information between elements within the computer 802, such as during start-up. The RAM 812 may include high-speed RAM, such as static RAM for caching data.

[0141] The computer 802 may include an internal hard disk drive (HDD) 814 (e.g., EIDE, SATA), one or more external storage devices 816 (e.g., a magnetic floppy disk drive (FDD), memory stick, or flash drive reader, memory card reader, and / or the like), and / or a drive 820 (e.g., a solid-state drive or optical disk drive, etc.) that can read from or write to a disk 822, such as a CD-ROM disk, DVD, BD, and / or the like. Additionally and / or alternatively, if a solid-state drive is involved, the disk 822 may not be included unless separate. While the internal HDD 814 is shown as located within the computer 802, the internal HDD 814 may also be configured for external use in a suitable chassis (not shown). Additionally, although not shown in the operating environment 800, a solid-state drive (SSD) may be used in addition to or in place of the HDD 814. HDD 814, external storage device 816, and drive 820 may be connected to system bus 808 by HDD interface 824, external storage interface 826, and drive interface 828, respectively. HDD interface 824 for external drive implementations may include Universal Serial Bus (USB) and / or Institute of Electrical and Electronics Engineers (IEEE) 1394 interface technologies. Other external drive connection technologies are within the contemplation of the embodiments described herein.

[0142] The drives and their associated computer-readable storage media provide non-volatile storage of data, data structures, computer-executable instructions, etc. For computer 802, the drives and storage media correspond to the storage of any data in a suitable digital format. Although the above description of computer-readable storage media refers to each type of storage device, other types of computer-readable storage media, now existing or developed in the future, may be used in the exemplary operating environment, and / or any such storage media may include computer-executable instructions for performing the methods described herein.

[0143] A number of program modules may be stored in the drives and RAM 812, including an operating system 830, one or more applications 832, other program modules 834, and / or program data 836. All or portions of the operating system, applications, modules, and / or data may also be cached in RAM 812. The systems and / or methods described herein may be implemented using one or more commercially available operating systems and / or combinations of operating systems.

[0144] Computer 802 may optionally include emulation technology. For example, a hypervisor (not shown) or other intermediary may emulate a hardware environment for operating system 830, and the emulated hardware may optionally differ from the hardware shown in FIG. 8. In a related embodiment, operating system 830 may include one virtual machine (VM) of multiple VMs hosted on computer 802. Additionally, operating system 830 may provide a runtime environment, such as the Java Runtime Environment or the .NET Framework, for application 832. A runtime environment is a consistent execution environment that may allow application 832 to run on any operating system that includes the runtime environment. Similarly, operating system 830 may support containers, and application 832 may be in the form of a container. A container is a lightweight, standalone, executable package of software that includes, for example, code, runtime, system tools, system libraries, and / or settings for an application.

[0145] Additionally, computer 802 may be enabled with a security module, such as a Trusted Processing Module (TPM). For example, a TPM allows a boot component to hash the next boot component in time and wait for the resulting match against a secure value before loading the next boot component. This process may occur at any layer of computer 802's code execution stack, for example, applied at the application execution level and / or the operating system (OS) kernel level, thereby enabling security at any level of code execution.

[0146] An entity may enter and / or send commands and / or information to computer 802 through one or more wired / wireless input devices, such as a keyboard 838, a touch screen 840, and / or a pointing device such as a mouse 842. Other input devices (not shown) may include a microphone, an infrared (IR) remote control, a radio frequency (RF) remote control and / or other remote controls, a joystick, a virtual reality controller and / or a virtual reality headset, a game pad, a stylus pen, an image input device such as a camera, a gesture sensor input device, a visual motion sensor input device, an emotion or facial expression detection device, a biometric input device such as a fingerprint scanner and / or an iris scanner, and / or the like. These and other input devices may be connected to processing unit 806 through an input device interface 844, which may be coupled to system bus 808, but may also be connected to other interfaces, such as a parallel port, an IEEE 1394 serial port, a game port, a USB port, an IR interface, a Bluetooth interface, and / or the like.

[0147] A monitor 846 or other type of display device may additionally and / or alternatively be connected to the system bus 808 via an interface, such as a video adapter 848. In addition to the monitor 846, computers typically include other peripheral output devices (not shown), such as speakers, printers, and / or the like.

[0148] Computer 802 may operate in a networked environment using logical connections via wired and / or wireless communications to one or more remote computers, such as remote computer 850. Remote computer 850 may be a workstation, a server computer, a router, a personal computer, a portable computer, a microprocessor-based entertainment device, a peer device, and / or other common network node, and typically includes many or all of the elements described relative to computer 802, although for purposes of simplicity, only memory storage device 852 is shown. Additionally and / or alternatively, computer 802 may be communicatively coupled (e.g., communicatively, electrically, operatively, optically, and / or the like) to one or more external systems, sources, and / or devices (e.g., classical and / or quantum computing devices, communication devices, and / or the like) via data cables (e.g., High-Definition Multimedia Interface (HDMI), Recommended Standard (RS) 232, Ethernet cables, and / or the like).

[0149] In one or more embodiments, the network may include one or more wired and / or wireless networks, including, but not limited to, a cellular network, a wide area network (WAN) (e.g., the Internet), or a local area network (LAN). For example, one or more embodiments described herein may be configured with, but are not limited to, wireless networks such as Wireless Fidelity (Wi-Fi), Global System for Mobile Communications (GSM), Universal Mobile Telecommunications System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX), Enhanced General Packet Radio Service (Enhanced GPRS), 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE), 3rd Generation Partnership Project 2 (3GPP2) Ultra Mobile Broadcast (UMB), High Speed Packet Access (HSPA), ZigBee, and others. It may communicate with one or more external system sources and / or devices, e.g., computing devices (and vice versa), using virtually any specified wired or wireless technology, including bee and other 802.XX wireless technologies and / or legacy telecommunications technologies, BLUETOOTH®, Session Initiation Protocol (SIP), ZIGBEE®, RF4CE protocol, WirelessHART protocol, 6LoWPAN (IPv6 over Low Power Wireless Area Network), Z-Wave, ANT, Ultra-Wideband (UWB) standard protocols, and / or other proprietary and / or non-proprietary communication protocols.In a related example, one or more embodiments described herein may include hardware (e.g., a central processing unit (CPU), a transceiver, a decoder, quantum hardware, a quantum processor, and / or the like), software (e.g., a set of threads, a set of processes, running software, a quantum pulse schedule, a quantum circuit, a quantum gate, and / or the like), and / or a combination of hardware and / or software that supports communication of information between one or more embodiments described herein and external systems, sources, and / or devices (e.g., computing devices, communication devices, and / or the like).

[0150] The logical connections depicted include wired / wireless connectivity to a local area network (LAN) 854 and / or larger networks, such as a wide area network (WAN) 856. LAN and WAN networking environments may be commonplace in offices and companies and may facilitate enterprise-wide computer networks, such as intranets, all of which may be connected to a general communications network, e.g., the Internet.

[0151] When used in a LAN networking environment, the computer 802 may be connected to the local network 854 through a wired and / or wireless communication network interface or adapter 858. The adapter 858 may facilitate wired and / or wireless communication to the LAN 854. The LAN 854 may also include a wireless access point (AP) disposed thereon for communicating with the adapter 858 in a wireless mode.

[0152] When used in a WAN networking environment, the computer 802 may include a modem 860 and / or be connected to a communications server on the WAN 856 via means such as the Internet, or other means for establishing communications over the WAN 856. The modem 860, which may be internal and / or external, and wired and / or wireless devices, may be connected to the system bus 808 via the input device interface 844. In a networked environment, program modules depicted relative to the computer 802, or portions thereof, may be stored in the remote memory storage device 852. The network connections shown are merely exemplary, and one or more other means of establishing a communications link between the computers may be used.

[0153] When used in either a LAN or WAN networking environment, computer 802 may access a cloud storage system or other network-based storage system in addition to and / or instead of external storage device 816 described above, such as, but not limited to, a networked virtual machine, which provides one or more aspects of information storage and / or processing. Generally, the connection between computer 802 and the cloud storage system may be established over LAN 854 or WAN 856, for example, by adapter 858 or modem 860, respectively. Upon connecting computer 802 to an associated cloud storage system, external storage interface 826 may manage the storage provided by the cloud storage system like other types of external storage, such as with the aid of adapter 858 and / or modem 860. For example, external storage interface 826 may be configured to provide access to cloud storage sources as if the sources were physically connected to computer 802.

[0154] The computer 802 may be operable to communicate with any wireless device and / or entity operably arranged in wireless communication, such as a printer, a scanner, a desktop and / or portable computer, a portable data assistant, a communications satellite, a telephone, and / or any equipment or location associated with a radio-detectable tag (e.g., a kiosk, a newsstand, a store shelf, and / or the like). This may include Wireless Fidelity (Wi-Fi) and Bluetooth® wireless technologies. Thus, communication may be in a predefined structure, similar to a traditional network, or may simply be ad-hoc communication between at least two devices.

[0155] The example embodiments described herein may also be implemented in distributed computing environments (e.g., cloud computing environments) where certain tasks are performed by remote processing devices that are linked through a communications network, such as those described below with respect to Figure 10. In a distributed computing environment, program modules may be located in both local and / or remote memory storage devices.

[0156] For example, one or more embodiments described herein and / or one or more components thereof may utilize one or more computing resources of cloud computing environment 950, described below with reference to example 900 of FIG. 9 and / or with reference to one or more functional abstraction layers (e.g., quantum software and / or the like), described below with reference to FIG. 10, to perform one or more operations in accordance with one or more embodiments described herein. For example, cloud computing environment 950 and / or one or more of functional abstraction layers 1060, 1070, 1080 and / or 1090 may include one or more classical computing devices (e.g., classical computers, classical processors, virtual machines, servers and / or the like), quantum hardware, quantum software (e.g., quantum computing devices, quantum computers, quantum processors, quantum circuit simulation software, and / or superconducting circuits and / or the like), which may be utilized by one or more embodiments described herein and / or components thereof to perform one or more operations in accordance with one or more embodiments described herein. For example, one or more embodiments described herein and / or components thereof may utilize such one or more classical and / or quantum computing resources to perform one or more classical and / or quantum mathematical functions, calculations and / or equations, computing and / or processing scripts, algorithms, models (e.g., artificial intelligence (AI) models, machine learning (ML) models, and / or similar models), and / or other operations according to one or more embodiments described herein.

[0157] Although one or more embodiments described herein include detailed descriptions related to cloud computing, it should be understood that implementation of the teachings referred to herein is not limited to a cloud computing environment. Rather, one or more embodiments described herein can be implemented in conjunction with any other type of computing environment now known or developed in the future.

[0158] Cloud computing is a service delivery model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and / or services) that can be rapidly provisioned and released with minimal management effort or interaction with the service provider. The cloud model can include at least five characteristics, at least three service models, and at least four deployment models.

[0159] The characteristics are as follows:

[0160] On-Demand Self-Service: Cloud consumers can unilaterally provision computing capacity, such as server time and network storage, automatically as needed, without requiring human interaction with the service provider.

[0161] Wide network access: Capabilities are available over the network and accessed through standard mechanisms that facilitate use by heterogeneous thin or thick client platforms (e.g., cell phones, laptops, and PDAs).

[0162] Resource Pooling: A provider's computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically allocated and reallocated according to demand. Although consumers generally have no control or knowledge of the exact location of the resources provided, there is an implication of location independence in that they may be able to specify location at a higher level of abstraction (e.g., country, state, and / or data center).

[0163] Rapid Elasticity: Capacity can be rapidly and elastically provisioned, in one or more cases automatically, for rapid scale out and rapidly released for rapid scale in. To the consumer, the capacity available for provisioning can appear unlimited and can be purchased in any amount at any time.

[0164] Measured Services: Cloud systems automatically control and optimize resource usage by leveraging measurement capabilities at one or more levels of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and / or active user accounts). Resource usage can be monitored, controlled, and / or reported, providing transparency to both providers and consumers of utilized services.

[0165] The service model is as follows:

[0166] Software as a Service (SaaS): The consumer is offered the ability to use a provider's applications running on a cloud infrastructure. The applications are accessible from a variety of client devices through thin-client interfaces such as web browsers (e.g., web-based email). The consumer does not manage or control the underlying cloud infrastructure, including the network, servers, operating systems, storage, and / or individual application capabilities, with the possible exception of limited user-specific application configuration settings.

[0167] Platform as a Service (PaaS): The ability offered to consumers is to deploy applications they create or acquire, written using programming languages and tools supported by the provider, onto a cloud infrastructure. The consumer does not manage or control the underlying cloud infrastructure, including networks, servers, operating systems, and / or storage, but does have control over the deployed applications and, in some cases, application hosting environment configuration.

[0168] Infrastructure as a Service (IaaS): The ability offered to consumers is to provision processing, storage, network, and / or other basic computing resources on which the consumer can deploy and run any software, which may include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure, but does have control over the operating system, storage, deployed applications, and / or possibly limited control of selected networking components (e.g., host firewalls).

[0169] The deployment model is as follows:

[0170] Private Cloud: Cloud infrastructure is operated solely for an organization. It can be managed by the organization or a third party and can exist on-premise or off-premise.

[0171] Community Cloud: Cloud infrastructure is shared by several organizations and supports a specific community with shared interests (e.g., roles, security requirements, policies and / or compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises.

[0172] Public Cloud: Cloud infrastructure is made available to the general public or large industry organizations and is owned by organizations that sell cloud services.

[0173] Hybrid Cloud: A combination of two or more clouds (private, community, or public) that remain distinct entities, but are bound together by standardized or proprietary technologies (e.g., cloud bursting for load balancing between clouds) that enable data and application portability.

[0174] A cloud computing environment is a service oriented environment that emphasizes statelessness, low coupling, modularity, and / or semantic interoperability. At the core of cloud computing is an infrastructure that includes a network of interconnected nodes.

[0175] Additionally, non-limiting system 100 and / or exemplary operating environment 800 may be associated with and / or included in a data analysis system, a data processing system, a graph analysis system, a graph processing system, a big data system, a social network system, a speech recognition system, an image recognition system, a graphical modeling system, a bioinformatics system, a data compression system, an artificial intelligence system, an authentication system, a syntactic pattern recognition system, a medical system, a health monitoring system, a network system, a computer network system, a communication system, a router system, a server system, a highly soluble server system (e.g., a Telecom server system), a web server system, a file server system, a data server system, a disk array system, a power insert board system, a cloud-based system, and / or the like. Accordingly, non-limiting system 100 and / or exemplary operating environment 800 may be utilized to solve problems that are highly technical in nature, using hardware and / or software, that are not abstract and / or cannot be performed as a set of human mental activities.

[0176] Referring now to details of one or more aspects depicted in FIG. 9 , an exemplary cloud computing environment 950 is illustrated. As shown, the cloud computing environment 950 includes one or more cloud computing nodes 910 with which local computing devices used by cloud consumers may communicate, such as, for example, a personal digital assistant (PDA) or mobile phone 954A, a desktop computer 954B, a laptop computer 954C, and / or an automobile computer system 954N. Although not shown in FIG. 9 , the cloud computing nodes 910 may further include a quantum platform (e.g., a quantum computer, quantum hardware, quantum software, and / or the like) with which local computing devices used by cloud consumers may communicate. The cloud computing nodes 910 may communicate with each other. They may be physically or virtually grouped (not shown) in one or more networks, such as a private cloud, a community cloud, a public cloud, or a hybrid cloud, or combinations thereof, as described above. The cloud computing environment 950 thereby enables cloud consumers to offer infrastructure-as-a-service, platform-as-a-service, and / or software-as-a-service services without having to maintain resources on their local computing devices. It should be understood that the types of computing devices 954A-N shown in FIG. 9 are intended to be illustrative only, and that the cloud computing node 910 and cloud computing environment 950 may communicate with any type of computerized device via any type of network and / or network-addressable connection (e.g., using a web browser).

[0177] Referring now to details of one or more aspects illustrated in FIG. 10 , a set of functional abstraction layers 1000, such as those provided by cloud computing environment 950 ( FIG. 9 ), is illustrated. One or more embodiments described herein may be associated with (e.g., accessible through) one or more functional abstraction layers (e.g., hardware and software layer 1060, virtualization layer 1070, management layer 1080, and / or workload layer 1090) described below with reference to FIG. 10 . It should be understood in advance that the components, layers, and / or functions illustrated in FIG. 10 are intended to be illustrative only, and that the embodiments described herein are not limited thereto. As illustrated, the following layers and / or corresponding functions are provided:

[0178] Hardware and software layer 1060 may include hardware and software components. Examples of hardware components include mainframe 1061, RISC (minimum instruction set computer) architecture-based servers 1062, servers 1063, blade servers 1064, storage devices 1065, and / or networks and / or networking components 1066. In one or more embodiments, software components may include network application server software 1067, Quantum Platform routing software 1068, and / or Quantum software (not shown in FIG. 10 ).

[0179] The virtualization layer 1070 may provide an abstraction layer from which the following examples of virtual entities may be provided: virtual servers 1071, virtual storage 1072, virtual networks including virtual private networks 1073, virtual applications and / or operating systems 1074, and / or virtual clients 1075.

[0180] In one example, management layer 1080 may provide the functions described below. Resource provisioning 1081 may provide dynamic procurement of computing and other resources that can be utilized to execute tasks within the cloud computing environment. Metering and pricing 1082 may provide cost tracking as resources are used within the cloud computing environment and / or charging and / or billing for the consumption of these resources. In one example, these resources may include one or more application software licenses. Security may provide identity verification for cloud consumers and / or tasks and protection for data and / or other resources. User (or entity) portal 1083 may provide access to the cloud computing environment for consumers and system administrators. Service level management 1084 may provide cloud computing resource allocation and / or management to ensure required service levels are met. Service level agreement (SLA) planning and fulfillment 1085 may provide advance arrangements and procurement for cloud computing resources that anticipate future requirements according to SLAs.

[0181] Workload tier 1090 may provide examples of functionality for which a cloud computing environment may be utilized. Non-limiting examples of workloads and functions that may be provided from this tier include mapping and navigation 1091, software development and lifecycle management 1092, virtual classroom instruction delivery 1093, data analytics processing 1094, transaction processing 1095, and / or application transformation software 1096.

[0182] The embodiments described herein may relate to one or more of a system, method, apparatus, and / or computer program product at any possible level of technical detail of integration. A computer program product may include a computer-readable storage medium (or media) having computer-readable program instructions for causing a processor to perform aspects of one or more embodiments described herein. A computer-readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. Computer-readable storage media may 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 diskettes, 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 compact disk read-only memory (CD-ROM), digital versatile disk (DVD), memory sticks, floppy disks, mechanically encoded devices such as punch cards or raised structures in grooves with instructions recorded thereon, and / or any suitable combination of the above. As used herein, computer-readable storage media should not be construed as transitory signals per se, such as radio waves and / or other freely propagating electromagnetic waves, electromagnetic waves propagated through waveguides and / or other transmission media (e.g., light pulses passing through fiber optic cables) and / or electrical signals transmitted through wires.

[0183] The computer-readable program instructions described herein may be downloaded from a computer-readable storage medium to each computing / processing device and / or to an external computer or external storage device over a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium in the respective computing / processing device. The computer-readable program instructions for carrying out the operations of one or more embodiments described herein may be source code and / or object code written in any combination of one or more programming languages, including assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for integrated circuits, and / or procedural programming languages, such as object-oriented programming languages, e.g., Smalltalk, C++, or the like, and / or the "C" programming language and / or similar programming languages. The computer-readable program instructions may be executed entirely on the computer, partially on the computer, as a standalone software package, partially on the computer, and / or partially on a remote computer, or entirely on a remote computer and / or server. In the latter scenario, the remote computer may be connected to the computer through any type of network, including a local area network (LAN) and / or a wide area network (WAN), and / or the connection to the external computer may be made (e.g., through 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 to perform aspects of one or more embodiments described herein.

[0184] Aspects of one or more embodiments described herein will be described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to one or more embodiments described herein. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions. These computer-readable program instructions may be provided to a processor of a general-purpose computer, a special-purpose computer, and / or other programmable data processing apparatus to create a machine. The instructions, executed by the processor of the computer or other programmable data processing apparatus, may thereby form means for implementing the function / acts specified in a block or blocks of the flowchart illustrations and / or block diagrams. These computer-readable program instructions may also be stored on a computer-readable storage medium that can instruct a computer, programmable data processing apparatus, and / or other device to function in a particular manner. A computer-readable storage medium having instructions stored thereon may thereby include an article of manufacture including instructions that can implement aspects of the function / acts specified in a block or blocks of the flowchart illustrations and / or block diagrams. The computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, and / or other device and cause a series of operational acts to be executed on the computer, other programmable apparatus, and / or other device to generate a computer-implemented process, whereby the instructions executing on the computer, other programmable apparatus, and / or other device implement the function / acts specified in the block or blocks of the flowcharts and / or block diagrams.

[0185] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and / or operation of possible implementations of systems, computer-implementable methods, and / or computer program products according to one or more embodiments described herein. In this regard, each block in a flowchart or block diagram may represent a module, segment, and / or portion of instructions, including one or more executable instructions for implementing the specified logical function(s). In one or more implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may be executed substantially concurrently, depending on the functionality involved, and / or the blocks may possibly be executed in the reverse order. It should also be noted that each block of the block diagrams and / or flowchart diagrams, and / or combinations of blocks in the block diagrams and / or flowchart diagrams, may be implemented by a dedicated hardware-based system that may perform the specified functions and / or actions and / or execute one or more combinations of dedicated hardware and / or computer instructions.

[0186] While the subject matter has been described above in the general context of computer-executable instructions for a computer program product executing on a computer and / or multiple computers, those skilled in the art will recognize that one or more embodiments herein can also be implemented in combination with one or more other program modules. Generally, program modules include routines, programs, components, data structures, and / or the like that perform particular tasks and / or implement particular abstract data types. Additionally, the computer-implemented methods described above may be practiced with single-processor and / or multi-processor computer systems, multi-computing devices, mainframe computers, and other computer system configurations, including computers, handheld computing devices (e.g., PDAs, phones), microprocessor-based or programmable consumer and / or industrial electronic devices, and / or the like. The illustrated aspects may also be practiced in distributed computing environments where tasks are performed by remote processing devices linked through a communications network. However, some, but not all, aspects of one or more embodiments described herein may be practiced on stand-alone computers. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

[0187] As used herein, terms such as “component,” “system,” “platform,” “interface,” and / or the like may refer to and / or include computer-related entities or entities associated with an operating machine having one or more particular functions. An entity 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, a thread of execution, a program, and / or a computer. By way of illustration, both an application running on a server and the server may be a component. One or more components may reside within a process and / or thread of execution, and a component may be localized on one computer and / or distributed between two or more computers. In another example, each component may execute from various computer-readable media having various data structures stored thereon. Components may communicate via local and / or remote processes, such as according to signals comprising one or more data packets (e.g., data from one component interacting with another component in a network, such as the Internet, with other systems, local systems, distributed systems, and / or signals). As another example, a component may be a device having a specific functionality provided by mechanical parts operated by electrical or electronic circuitry operated by software and / or firmware applications executed by a processor. In such cases, the processor may be internal and / or external to the device and may execute at least a portion of the software and / or firmware applications. As yet another example, a component may be a device that provides a specific functionality without mechanical parts but through electronic components that may include a processor and / or other means for executing software and / or firmware that provide at least a portion of the functionality of the electronic component.In some aspects, the component may emulate an electronic component via a virtual machine, for example, in a cloud computing system.

[0188] Additionally, the term "or" is intended to mean an inclusive "or," rather than an exclusive "or." That is, unless otherwise specified or clear from the context, "X utilizes A or B" is intended to mean any of the natural inclusive permutations. That is, in any of the foregoing examples, "X utilizes A or B" is satisfied when X utilizes A, when X utilizes B, or when X utilizes both A and B. Furthermore, as used in this specification and the accompanying drawings, the articles "a" and "an" should generally be construed to mean "one or more" unless otherwise specified or unless the context clearly indicates a reference to the singular form. As used herein, the terms "example" and / or "exemplary" are used to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter described herein is not limited to such examples. Additionally, any aspect or design described herein as "example" and / or "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects or designs, and is not intended to exclude equivalent exemplary structures and techniques known to those skilled in the art.

[0189] The term "processor" as used herein may 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 execution capabilities, a multi-core processor, a multi-core processor with software multithreading execution capabilities, a multi-core processor with hardware multithreading technology, a parallel platform, and / or a parallel platform with distributed shared memory. Additionally, a processor may refer to an integrated circuit, an application-specific integrated circuit (ASIC), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic controller (PLC), a complex programmable logic device (CPLD), discrete gate or transistor logic, discrete hardware components, and / or any combination thereof designed to perform the functions described herein. Furthermore, a processor may utilize nanoscale architectures, such as, but not limited to, molecular and quantum dot-based transistors, switches, and / or gates, to optimize space utilization and / or enhance the performance of associated equipment. A processor may be implemented as a combination of computing processing units.

[0190] As used herein, terms such as “store,” “storage,” “data store,” “data storage,” “database,” and substantially any other information storage component associated with the operation and functionality of a component are used to refer to a “memory” or a “memory component” entity embodied in a component that includes memory. The memory and / or memory components described herein may be either volatile or nonvolatile memory, or may include both volatile and nonvolatile memory. By way of example and not limitation, nonvolatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM), flash memory, and / or nonvolatile random access memory (RAM) (e.g., ferroelectric RAM (FeRAM)). Volatile memory may include RAM, which may act as external cache memory, for example. By way of example, and not limitation, RAM may be available in many forms, such as synchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink DRAM (SLDRAM), direct Rambus RAM (DRRAM), direct Rambus dynamic RAM (DRDRAM), and / or Rambus dynamic RAM (RDRAM). Additionally, the described memory components of the systems and / or computer-implemented methods herein are intended to include, but are not limited to, these and / or any other suitable types of memory.

[0191] What has been described above includes only example systems and computer-implemented methods. Of course, for purposes of describing one or more embodiments, it is not possible to describe every conceivable combination of components and / or computer-implemented methods, but one of ordinary skill in the art may recognize that many additional combinations and / or permutations of one or more embodiments are possible. Furthermore, when terms such as "including," "having," "comprising," and the like are used in the detailed description, claims, appendices, and / or drawings, such terms are intended to be inclusive in the same manner as the term "comprising" is interpreted when used as a transitional phrase in the claims.

[0192] The description of one or more embodiments is presented for purposes of illustration and is not intended to be exhaustive or limited to the embodiments described herein. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein has been selected to best explain the principles, practical applications, and / or technical improvements of the embodiments over technologies found in the marketplace, and / or to enable others skilled in the art to understand the embodiments described herein.

Claims

1. a memory for storing computer-executable components; a processor for executing the computer-executable components stored in the memory, the computer-executable components comprising: a determination component configured to determine one of a plurality of thresholds to apply to a measurement of a state of a qubit based on a probability distribution of the state of the qubit, wherein a measurement on one side of the threshold indicates that the qubit is in a ground state and a measurement on the other side of the threshold indicates that the qubit is in an excited state; system.

2. 10. The system of claim 1, wherein the determination component is configured to selectively determine the threshold based on one or more electrical, mechanical, or structural parameters of a qubit physical circuit that includes the qubit or one or more electrical, mechanical, or structural parameters of a quantum device that includes the qubit.

3. a readout component configured to determine a plurality of measurements defining a plurality of states of the qubit at different instances; a calibration component configured to combine the measurements to map the states to one-dimensional signal values representing selected probability distributions for excitation and ground states of the qubit; a classification component configured to calculate a probability distribution of a state classification error of the qubit based on the signal value, wherein the decision component is configured to apply one of the different thresholds that minimizes a probability of a state classification error of the qubit. A system according to any preceding claim.

4. 10. The system of any preceding claim, wherein the determination component is configured to selectively determine the threshold based on one or more electrical, mechanical, or structural parameters of a qubit physical circuit that includes the qubit, or one or more electrical, mechanical, or structural parameters of a quantum device that includes the qubit.

5. 10. The system of any preceding claim, wherein the decision component is configured to utilize a supervised learning model that determines the threshold to apply for a particular quantum circuit based on one or more kernels that apply to the particular quantum circuit or an environment of the qubit, the kernels being written based on a plurality of calibration measurements that define a plurality of states of the qubit at different instances.

6. 10. The system of claim 9, further comprising: a classification component configured to calculate a probability distribution of a state classification error of the qubit based on a plurality of calibration measurements defining a plurality of states of the qubit at different instances; and wherein the determination component is configured to determine one of the different thresholds to apply to the qubit based on the probability distribution of the state classification error of the qubit.

7. 7. The system of claim 6, wherein the determination component is further configured to determine the thresholds of the different thresholds to apply to the qubit based on one or more kernels defining a usage of the qubit, the kernels corresponding to the plurality of calibration measurements.

8. a readout component configured to measure a state of the qubit; and and a pulse generation component configured to generate a pulse that resets the qubit to its ground state based on a determination that the qubit is in the excited state, wherein one of the different thresholds is applied to provide the determination. A system according to any preceding claim.

9. 1. A computer-implemented method comprising: determining, by a system operatively coupled to a processor, one of a plurality of thresholds to apply to a measurement of a state of a qubit based on a probability distribution of the state of the qubit, wherein a measurement on one side of the threshold indicates that the qubit is in a ground state and a measurement on the other side of the threshold indicates that the qubit is in an excited state.

10. 10. The computer-implemented method of claim 9, further comprising selectively determining the threshold based on one or more electrical, mechanical, or structural parameters of a qubit physical circuit that includes the qubit, or one or more electrical, mechanical, or structural parameters of a quantum device that includes the qubit.

11. determining, by the system, a plurality of measurements defining a plurality of states of the qubit at different instances; combining, by the system, the measurements to map the states to one-dimensional signal values representing selected probability distributions for excitation and ground states of the qubit; calculating, by the system, a probability distribution of state-classification errors of the qubit based on the signal values; applying, by the system, one of the different thresholds that minimizes the probability of a state classification error of the qubit; The computer-implemented method of claim 9 further comprising:

12. 12. The computer-implemented method of claim 9, further comprising determining, by the system, the threshold value based on one or more electrical, mechanical, or structural parameters of a qubit physical circuit that includes the qubit, or one or more electrical, mechanical, or structural parameters of a quantum device that includes the qubit.

13. utilizing a supervised learning model where the system determines the threshold to apply for a particular quantum circuit based on one or more kernels that apply to the particular quantum circuit or the environment of the qubit; writing, by the system, the kernel based on a plurality of calibration measurements defining a plurality of states of the qubit at different instances; The computer-implemented method of claim 9 , further comprising:

14. calculating, by the system, a probability distribution of a state classification error of the qubit based on a plurality of calibration measurements defining a plurality of states of the qubit at different instances; determining, by the system, one of the different thresholds to apply to the qubit based on a probability distribution of state classification errors of the qubit; The computer-implemented method of claim 9 , further comprising:

15. determining, by the system, the one of the different thresholds to apply to the qubit based on one or more kernels defining a usage of the qubit, the kernels corresponding to the plurality of calibration measurements.

15. The computer-implemented method of claim 14.

16. measuring, with the system, the state of the qubit; generating, by the system, a pulse to reset the qubit to its ground state based on a determination that the qubit is in the excited state, wherein one of the different thresholds is applied to provide the determination.

16. A computer-implemented method according to any one of claims 9 to 15.

17. 1. A computer program product that enables a process for dynamically determining a threshold for determining a state of a qubit, the computer program product comprising a computer-readable storage medium having program instructions embodied thereon, the program instructions causing a processor to: a step executable by the processor to cause the processor to perform a step of determining, based on a probability distribution of states of the qubit, one threshold of a plurality of thresholds to apply to the measurement of the state of the qubit; a measurement on one side of the threshold indicates that the qubit is in a ground state, and a measurement on the other side of the threshold indicates that the qubit is in an excited state; Computer program products.

18. The program instructions further cause the processor to: utilizing, by the processor, a supervised learning model to determine, for a particular quantum circuit, the threshold to apply based on one or more kernels that apply to the particular quantum circuit or the environment of the qubit; writing, by the processor, the kernel based on a plurality of calibration measurements defining a plurality of states of the qubit at different instances; 20. The computer program product of claim 17, executable by the processor to cause:

19. The program instructions further cause the processor to: calculating, by the processor, a probability distribution of a state classification error of the qubit based on a plurality of calibration measurements defining a plurality of states of the qubit at different instances; determining, by the processor, one of the different thresholds to apply to the qubit based on a probability distribution of state classification errors of the qubit; and determining the one of the different thresholds to apply to the qubit based on one or more kernels defining a usage of the qubit, the kernels corresponding to the plurality of calibration measurements. A computer program product according to any of claims 17 to 18.

20. The program instructions further cause the processor to: measuring, by the system, the state of the qubit; and generating a pulse to reset the qubit to its ground state based on a determination that the qubit is in an excited state, wherein the different threshold values are applied to provide the determination.

20. A computer program product according to any one of claims 17 to 19.

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