Quantum computer system and method for operating the quantum computer system

Abstract

To acquire highly accurate quantum calculation results at a high speed with high efficiency.SOLUTION: A quantum computer system includes: a virtual quantum computer that simulates, on the basis of predetermined parameters, the operation of a real quantum computer that executes quantum operations using a group of qubits; and a control device that controls the real quantum computer and the virtual quantum computer. The virtual quantum computer has an estimation unit that estimates the state of a qubit of interest in the group of qubits by simulating the operation of the real quantum computer. The control device has a feedback controller that changes the parameters until a deviation between the estimated state of the qubit of interest estimated by the estimation unit and a quantum operation result from the real quantum computer becomes a first design value or less, and transmits the changed parameters to the virtual quantum computer.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a quantum computer system that operates a quantum computer and a method of operating the same. [Background technology]

[0002] The development of quantum computers, especially gate-type quantum computers, is accelerating worldwide. Currently, the mainstream method is superconducting, and quantum computers of about 50 Qubits have been put to practical use. In addition, quantum supremacy has been shown as one indicator of the superiority of quantum computers (Non-Patent Document 1), and expectations for quantum computers are rising. Another issue with quantum computers is the low error tolerance of quantum bits, and technology to correct quantum bit errors is also being developed (Non-Patent Document 2).

[0003] However, the surface coding technology described in Non-Patent Document 2 requires a large number of quantum bits for error correction, and further requires the implementation of multi-stage quantum operations. This makes it extremely difficult to apply it to current quantum computers with around 50 quantum bits. In this context, the concept of a medium-scale quantum computer (NISQ (Noisy Intermediate-Scale Quantum) computer) that does not have perfect error correction and allows for the effects of noise has been proposed (Non-Patent Document 3), and development of the quantum computer is underway. [Prior art documents] [Non-patent literature]

[0004] [Non-Patent Document 1] Frank Arute et al, “Quantum supremacy using a programmable superconducting processor,” Nature , Vol 574 , pp, 505 - 510, No. 24 OCTOBER 2019 [Non-Patent Document 2] Austin G. Fowler, et al. “Surface codes: Towards practical large-scale quantum computation”. 27 Oct 2012. [Non-Patent Document 3] John Preskill, “Quantum Computing in the NISQ era and beyond,”. 31 Jul 2018. [Non-Patent Document 4] DM Zajac1 et. al, “Quantum CNOT Gate for Spins in Silicon”, Science (2017). Summary of the Invention [Problem to be solved by the invention]

[0005] The problem that this invention aims to solve is a technology to avoid the low accuracy and high error rate of quantum operations, which are also issues with NISQ quantum computers. Unlike classical computers, quantum computers cannot directly observe and detect how much calculation error has accumulated when performing quantum operations. This is a requirement of quantum mechanics, not a technical difficulty. Therefore, a technology is needed to improve the accuracy of calculations without directly observing the results of quantum bit calculations.

[0006] As mentioned above, conventional technology has proposed using quantum error correction technology to grasp and correct calculation errors. However, there are issues such as the large hardware scale and complex implementation algorithms. In addition, in order to perform calculations using the NISQ type, it is possible to take measures such as terminating the calculation before the cumulative calculation error becomes large, but this makes it impossible to perform complex quantum calculations.

[0007] An object of the present invention is to obtain highly accurate quantum computing results quickly and efficiently. [Means for solving the problem]

[0008] A quantum computer system according to one aspect of the invention disclosed in the present application comprises a real quantum computer that executes quantum operations using a group of quantum bits, a virtual quantum computer that simulates the operation of the real quantum computer based on predetermined parameters, and a control device that controls the real quantum computer and the virtual quantum computer, the virtual quantum computer having an estimation unit that simulates the operation of the real quantum computer and estimates a state of a quantum bit of interest in the group of quantum bits, and the control device and the virtual quantum computer perform the following in parallel with the operation of the real quantum computer: changing the parameters for each of the quantum bits of interest until a first deviation between an estimated state of the quantum bit of interest by the estimation unit and an ideal state becomes equal to or less than a first design value, and transmitting the changed parameters to the virtual quantum computer until a second deviation between the estimated state of the quantum bit of interest based on the changed parameters when the first deviation becomes equal to or less than the first design value and a quantum operation result from the real quantum computer becomes equal to or less than a second design value. The present invention is characterized by having a feedback control section. Effect of the Invention

[0009] According to the representative embodiments of the present invention, highly accurate quantum computation results can be obtained quickly and efficiently. Problems, configurations and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0010] [Figure 1] FIG. 1 is a block diagram showing a first configuration example of a quantum computer system. [Diagram 2] FIG. 2 is an explanatory diagram showing a second configuration example of a quantum computer system. [Diagram 3] FIG. 3 is a block diagram showing a detailed configuration example of the quantum computer system shown in FIG. [Figure 4] FIG. 4 is a block diagram showing an example of the hardware configuration of a quantum computer system. [Diagram 5] FIG. 5 is an explanatory diagram showing an example of the contents stored in the third memory of the digital twin control device. [Figure 6] FIG. 6 is an explanatory diagram showing another example of the contents stored in the third memory of the digital twin control device. [Figure 7] FIG. 7 is a block diagram showing an example of the configuration of a quantum bit array. [Figure 8] FIG. 8 is a flowchart illustrating an example of a procedure for adjusting the quantum bit control model by the quantum computer system. [Figure 9] FIG. 9 is a flowchart showing an example of a processing procedure for creating a quantum bit control model that takes into account variability in the control of a single quantum bit and two quantum bits by a quantum computer system. [Figure 10] FIG. 10 is a flowchart showing an example of a process for creating a quantum bit control model that includes the influence of noise from the surroundings. [Figure 11] FIG. 11 is a flowchart showing an example 1 of a digital twin operation processing procedure. [Figure 12] FIG. 12 is a flowchart showing an example 2 of a digital twin operation processing procedure. [Figure 13] FIG. 13 is an explanatory diagram showing an example of displaying digital twin operations. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] According to the principles of quantum mechanics, it is impossible to observe the state of a quantum bit during a calculation without affecting the calculation. Therefore, rather than directly observing the quantum bit during a calculation, it is necessary to indirectly infer the quantum bit state by monitoring the quantum bit's control parameters and environmental conditions.

[0012] A control parameter, which is one of the objects to be monitored, is an ideal value of a control signal that controls a quantum bit, and specifically, is a set of parameter values ​​such as a voltage value, a current amount, and in the case of an RF signal, a phase and a delay. Here, the control parameter is the control amount required to control the quantum bit. However, there may be a discrepancy between the control parameter and the control amount from the control circuit.

[0013] Here, the control amount from the control circuit is called the "control signal parameter." The control signal parameter is the setting value of each of the above parameters when the control signal is transmitted from the control circuit. When the control parameter is a DC (Direct Current) value, the control parameter and the control signal parameter have almost the same value, but when the control parameter changes over time due to transmission, a delay or other discrepancy generally occurs between the control parameter and the control signal parameter. Another environmental condition to be monitored is the ambient temperature of the quantum bit, fluctuations in the applied magnetic field, and fluctuations in the power supply.

[0014] If it is possible to grasp in this indirect manner the amount of deviation from the ideal value (the value of the control parameter) that has increased, it will be possible to evaluate the accuracy of the calculation, and if it is possible to correct the amount of deviation, then performing a correction calculation will lead to improved accuracy of the quantum calculation.

[0015] Sensor data from various sensors installed inside the actual quantum computer is used to evaluate the control parameters and environmental conditions. For example, for the control parameters, sensor data detected by the control circuit (hereinafter, the first control parameter measurement value) and sensor data detected in the vicinity of the quantum bit (hereinafter, the second control parameter measurement value) are used. The first control parameter measurement value is a value close to the control signal parameter, and the second control parameter measurement value is a value close to the control parameter. In this way, the deviation between the control parameter and the control signal parameter becomes clear.

[0016] Superconducting quantum bits and semiconductor electron spin quantum bits need to operate at the extremely low temperatures realized by a dilution refrigerator, and due to the implementation constraints of the refrigeration space in a dilution refrigerator, it may be difficult to integrate the control circuitry and quantum bits in the same cooling temperature space. In such cases, it may be possible to distribute the control circuitry in relatively high-temperature locations in the dilution refrigerator to control the quantum bits.

[0017] However, in this case, the value of the control signal parameter assumed by the control circuit may differ from the value of the control parameter actually applied to the quantum bit. In order to improve the accuracy of the quantum bit state estimation, it is necessary to accurately grasp the control parameters applied to the quantum bit. In addition, environmental conditions such as temperature, external magnetic field, and power supply may fluctuate, and the impact of such fluctuations on quantum bit operations cannot be ignored.

[0018] Therefore, it is desirable to monitor the environmental conditions and calibrate the control parameters according to the amount of fluctuation. Furthermore, the accuracy of quantum operations can be improved by using each sensor data and performing correction operations when possible.

[0019] Therefore, in order to improve the computational fidelity of quantum bits, it is necessary to determine the correlation between the control parameters (and thus the control signal parameters) and the state of the quantum bit, estimate the state of the quantum bit of interest with high accuracy by simply simulating the control parameters, and perform correction computations as necessary.

[0020] In conventional simulations, operations are simulated based on assumed scenarios, but the digital twin of a quantum computer goes further by utilizing the control parameters (and thus control signal parameters) that control the quantum bits to quantitatively capture deviations from the assumed scenario and, by monitoring the computational fidelity of quantum bits of particular interest, it becomes possible to appropriately correct the control of the quantum bits so that the computational fidelity falls within the design value.

[0021] In order to estimate the computational fidelity of a quantum bit in real time, it is necessary to monitor the quality of the control parameters for the target quantum bit that is performing the quantum computation (variations in voltage values, current values, and RF signal phase and delay), as well as sensing data for the surrounding environmental conditions, and also to evaluate the impact of noise on asymmetric quantum bits that are not the subject of the computation.

[0022] The quantum computer system according to the present embodiment described below uses this information to grasp the state of all quantum bits related to quantum operations, evaluates deviations from the ideal operation state, and applies feedback to the actual quantum computer as necessary. This improves the fidelity of the operation of the quantum bits. The following (1) to (4) are possible methods for using the results of the operation of this digital twin.

[0023] (1) A quantum computer system tunes the control parameters (and thus the control signal parameters) and applies feedback to the next identical quantum operation. Here, a quantum operation is assumed to be a primitive operation such as rotation in the x direction (Rx). When tuning, it is necessary to verify the operation result by measurement after the quantum operation is performed. Since the control signal parameters are adjusted after the operation verification, in this case, it is possible to improve the calculation accuracy of the next identical quantum operation.

[0024] (2) A quantum computer system tunes the accuracy of each command and applies feedback to the next operation on a different set of quantum bits. The difference is that (1) is a primitive quantum operation, while (2) is a composite quantum operation that is a collection of multiple primitive quantum operations. In other words, (2) is equivalent to tuning the entire subprogram-like operation that is a collection of several primitive operations in (1). In this case, the calculation accuracy of the next different quantum operation is improved.

[0025] (3) The quantum computer system tunes the control parameters in the middle of a quantum operation and applies feedback to the remaining quantum operations. In this case, the quantum computer system adjusts the control signal parameters by compensating for the difference between the control parameters and the control signal parameters and for changes in the environmental conditions. This reduces the decrease in accuracy of the quantum operation caused by deviations in the control parameters due to changes in the environmental conditions, and improves accuracy from the middle of the quantum operation.

[0026] (4) The quantum computer system tunes the control parameters (and thus the control signal parameters) during the quantum operation and performs correction operations to compensate for the accumulated quantum operation errors. In this case, since errors can be corrected during the execution of the quantum operation, it is possible to increase the number of quantum operation stages, i.e., to execute more complex quantum operations.

[0027] In general, quantum computing rarely produces results in a single operation, and the solution is often determined by generating the expected value of the results obtained through multiple repeated operations. Therefore, the same operation must be repeated multiple times, and even when finding a solution to the same operation, the digital twin operation improves the accuracy of the operation. Therefore, even in the same operation, there is an opportunity for correction.

[0028] Hereinafter, examples of the present invention will be described with reference to the drawings. However, the present invention should not be interpreted as being limited to the description of the embodiments shown below. It will be easily understood by those skilled in the art that the specific configuration can be changed without departing from the concept or purpose of the present invention.

[0029] In the configuration of the invention described below, the same parts or parts having similar functions are commonly designated by the same reference numerals in different drawings, and duplicated explanations may be omitted. In the embodiments, when there are multiple components that can be considered equivalent, they may be distinguished by adding a subscript to the same symbol or number. However, when there is no particular need to distinguish them, the subscript may be omitted.

[0030] The designations "first," "second," "third," and the like in this specification are given to identify components and do not necessarily limit the number or order. Furthermore, numbers for identifying components are used in different contexts, and a number used in one context does not necessarily indicate the same configuration in another context. Furthermore, a component identified by a certain number is not prevented from also having the function of a component identified by another number.

[0031] In order to facilitate understanding of the invention, the position, size, shape, range, etc. of each component shown in the drawings, etc. may not represent the actual position, size, shape, range, etc. Therefore, the present invention is not necessarily limited to the position, size, shape, range, etc. disclosed in the drawings, etc.

[0032] <Example of quantum computer system configuration> 1 is a block diagram showing a first configuration example of a quantum computer system. The basic concept is to realize a digital twin in a quantum computer. The quantum computer system 100 includes a real quantum computer 101, a virtual quantum computer 102, and a digital twin control device 103.

[0033] The real quantum computer 101 executes quantum operations. The real quantum computer 101 is, for example, a NISQ quantum computer. The virtual quantum computer 102 is a digital twin of the real quantum computer 101, and evaluates the operation state of the real quantum computer 101 by simulation. The digital twin control device 103 controls each of the real quantum computer 101 and the virtual quantum computer 102.

[0034] The quantum computer system 100 simulates quantum operations on a real quantum computer 101 in parallel with the execution of quantum operations by a virtual quantum computer 102, and corrects the operations and readjusts control parameters (specifically, control signal parameters) if operation errors accumulate as a result of the simulation. This improves the accuracy of quantum computation.

[0035] Figure 2 is an explanatory diagram showing a second configuration example of the quantum computer system 100. The difference from Figure 1 is that there are multiple real quantum computers 101 and virtual quantum computers 102. For example, when the real quantum computers 101 are of a superconducting type or an electron spin type and one real quantum computer 101 is configured for one dilution refrigerator, the real quantum computers 101 are defined for each dilution refrigerator.

[0036] Also, in the case where an independently operating quantum bit array is built on one semiconductor LSI, such as a silicon electron spin type, each quantum bit array can be regarded as a real quantum computer 101. The virtual quantum computer 102 is a simulator built on a classical computer, and can be built not only on one classical computer, but also distributed over a network. In the following explanation, for the sake of simplicity, the quantum computer system 100 shown in FIG. 1 will be used for explanation.

[0037] Fig. 3 is a block diagram showing a detailed configuration example of the quantum computer system 100 shown in Fig. 1. The real quantum computer 101 executes quantum operation 301, control signal parameter / control parameter status monitoring 302, and environmental parameter monitoring 303.

[0038] Specifically, for example, the actual quantum computer 101 executes the quantum operation 301 to be quantitatively evaluated, and outputs the quantum operation result to the digital twin control device 103.

[0039] Furthermore, in the control signal parameter / control parameter status monitoring 302, the actual quantum computer 101 monitors the control signal parameters and control parameters, such as the values ​​of the voltage, current, and RF signal, and outputs the control signal parameters and control parameters to the digital twin control device 103. This makes it possible to predict the behavior of the quantum bit's quantum operation 301. The accuracy of predictions regarding the effects of the control signal parameters and control parameters on the quantum bit can be improved by conducting experiments in advance to obtain correlations. At that time, environmental factors also have an effect.

[0040] In addition, the real quantum computer 101 monitors environmental conditions such as temperature and electromagnetic wave intensity using various sensors through environmental parameter monitoring 303, and outputs the detected sensing data to the digital twin control device 103 as environmental parameters.

[0041] The virtual quantum computer 102 performs a control parameter simulation 121 regarding the effect of the control parameters on the quantum bits, and a quantum operation simulation 122, to infer the quantum bit state of the real quantum computer 101. The virtual quantum computer 102 performs a simulation of the control parameters. The real quantum computer 101 controls the control signal parameters, and adjusting the control signal parameters is to control the control parameters to a more ideal state. The virtual quantum computer 102 models the relationship between the control parameters and the control signal parameters. This enables the virtual quantum computer 102 to perform a simulation using the control signal parameters. The following will explain using the control parameters.

[0042] Control parameter simulation 121 executes control parameter monitoring 121A and executes quantum bit operation fidelity calculation 121B. Quantum operation bit fidelity calculation 121B is a calculation process that evaluates the influence of a combination of control parameters of a quantum bit on the operation state of the quantum bit as, for example, the fidelity of the quantum operation.

[0043] It is difficult to make the quantum operation simulation 122 the same scale as the actual quantum computer 101. Therefore, for example, it is desirable that the quantum operation simulation 122 has a function of tracing quantum operations globally and a function of simulating a part of interest in detail. For example, it is effective to selectively select a method for the quantum operation simulation 122, such as using a global quantum operation operation matrix sparse model 122A that makes the operation matrix of the global quantum operation sparse and executes it, or a partial quantum operation bit operation model 122B that executes partial quantum operations in detail by bit operations.

[0044] The digital twin control device 103 acquires quantum operation results from the real quantum computer 101, control signal parameter values ​​(the setting values ​​of the control signals in a control circuit that controls the quantum bits (for example, the first sequencer 411 described later) or their sensing data), and control parameter values ​​(sensing data immediately before being applied to the quantum bits). The digital twin control device 103 also acquires quantum operation simulation results, control parameter simulation results, and operation fidelity based on the simulation from the virtual quantum computer 102.

[0045] The digital twin control device 103 uses data obtained from the real quantum computer 101 and data obtained from the virtual quantum computer 102 to perform a comparison 131 of the operation results of the real quantum computer 101 and the virtual quantum computer 102 (hereinafter referred to as "virtual-real operation result comparison"), and performs a deviation calculation 132 of the computational fidelity of the quantum bits.

[0046] There are various definitions of the fidelity of a quantum bit. For example, the fidelity of the quantum state |φ before >, the ideal quantum state after quantum operation is |φ after_ideal >, the actual quantum state is |φ after_real >, then fidelity can be taken as the magnitude of the dot product of both states, i.e., |<φ after_real |φ after_ideal If the computational fidelity is "1", it indicates that the actual quantum state coincides with the ideal state (there is no deviation), and the lower the computational fidelity is below "1", that is, the greater the deviation (1 - computational fidelity), the more the actual quantum state deviates from the ideal state.

[0047] If the deviation in the computational fidelity of the quantum bit becomes greater than a threshold value, the digital twin control device 103 executes a virtual parameter change 133 of the virtual quantum computer 102 or a real parameter change 134 of the real quantum computer 101.

[0048] When changing the virtual parameters 133 and changing the real parameters 134, the digital twin control device 103 uses a preset reference table to determine the amount of change in the control signal parameters based on the relationship between the calculation results of the real quantum computer 101 and the calculation results of the virtual quantum computer 102 and the control signal parameters. It is desirable for the digital twin control device 103 to store such evaluation results as a database 135. Utilizing this data has the effect of making it easier to adjust the quantum bit calculations as the system is improved in the future.

[0049] 4 is a block diagram showing an example of a hardware configuration of a quantum computer system 100. The quantum computer system 100 includes a real quantum computer (QPU) 101, a virtual quantum computer (QSIM) 102, a digital twin control device (DTCTL) 103, and a host computer (HOST) 400. The host computer 400 is a classical computer including a processor and a memory. The virtual quantum computer 102 and the digital twin control device 103 may be implemented by a classical computer. In addition, at least two of the host computer 400, the virtual quantum computer 102, and the digital twin control device 103 may be implemented in the same classical computer.

[0050] In a host computer 400, a quantum program written in a quantum assembler (QASM) 401 is converted into quantum microcode (QuCODE) 402, which is a hardware control language for quantum computers, and input to a real quantum computer 101 and a virtual quantum computer 102.

[0051] The actual quantum computer 101 converts the received quantum microcode 402 into a program for controlling quantum bits and stores it in a first sequencer (SEQ1) 411. The first sequencer 411 is connected to a first memory (MEM1) 412, which holds design values ​​(hereinafter, control parameter setting values) of voltage, current, timing, and RF signal.

[0052] The control signal parameters from the first sequencer 411 to the quantum bit array (QA) 413 are transmitted as analog signals via a DA converter and an RF oscillator circuit (not shown). The control signal parameters are set values ​​at the time of transmission of the control signal transmitted from the first sequencer 411 to the quantum bit array 413 via a signal line 417, based on the control parameter set values ​​stored in the first memory 412. When a microcode instruction sequence is executed, the first sequencer 411 outputs an appropriate signal waveform to the quantum bit array 413 using the control parameter set values ​​stored in the first memory 412.

[0053] The real quantum computer 101 has a sensor (SEN0) 414 and a sensor (SEN1) 415 that detect the voltage, current, timing, and frequency of a control signal issued from a first sequencer 411. The sensor data when the sensor (SEN0) 414 detects a control signal is the first measured value of the control parameter described above, and the sensor data when the sensor (SEN1) 415 detects a control signal is the second measured value of the control parameter described above.

[0054] Superconducting or electron spin quantum computers require quantum bits to be cooled to extremely low temperatures (<100 mK), but this extremely low temperature must be generated by a dilution refrigerator, and the cooling performance of the dilution refrigerator determines the constraints on heat generation in the quantum bit array 413. As the temperature is lowered, the required cooling capacity must be stronger, while the amount of heat that can be cooled tends to decrease.

[0055] Controlling quantum bits requires analog circuits that generate RF signals and generate voltages and currents, but these analog circuits generate a large amount of heat. Therefore, it is often difficult to install such analog circuits in the vicinity of the quantum bit array 413. For this reason, it is desirable to install quantum bit control circuits such as the first sequencer 411 in a relatively high temperature region (for example, about 4 K), which would increase the physical distance between the quantum bit array 413 and the analog circuits.

[0056] As the physical distance increases, signal integrity decreases, and it becomes more likely that control of the quantum bit will not proceed as expected. For this reason, it is desirable to measure the control parameter in the vicinity of the quantum bit and utilize the data (although this will result in a discrepancy between the control signal parameter and the control parameter). Therefore, in this embodiment, sensor 414 is placed closer to first sequencer 411 than quantum bit array 413, and outputs a first measured value of the control parameter. Also, sensor 415 is placed closer to quantum bit array 413 than sensor 414, and outputs a second measured value of the control parameter.

[0057] In addition, it is advantageous to mount a sensor (SEN2) 416 that measures the influence of the environment on the actual quantum computer 101. Possible sensors include a temperature sensor and an applied magnetic field sensor. The sensing data of such a sensor 416 is also important for correcting the quantum bit control.

[0058] Note that observation of control parameters near the quantum bit array 413 may cause unintended kickback control to the quantum bits. In that case, it is desirable to control the sensors 415, 416 near the quantum bit array 413 to be turned off while the quantum operation 301 is being performed. However, even in such a case, it is desirable to appropriately operate the sensors 415, 416 near the quantum bit array 413 when the quantum operation 301 is not being performed, thereby dynamically calibrating the signal.

[0059] The virtual quantum computer 102 is composed of a classical computer, and has the following functions: a quantum bit simulation execution unit (QUBIT SIM) 421, an evaluation unit (FIDELITY ESTIMATE) 422, a quantum logic simulation execution unit (QLSIM) 423, and a computation fidelity accumulation unit (FIDELITY ACCM) 424. These functions are realized by having the processor execute a program.

[0060] The quantum bit simulation execution unit 421 executes the control parameter simulation 121. Specifically, for example, the quantum bit simulation execution unit 421 simulates the state of a quantum bit from control parameters transmitted through a signal line 403 for decoding the quantum microcode 402 and a signal line 417 for the quantum bit array 413. The control signal parameters from the signal line 403 for decoding the quantum microcode 402 are input to the quantum bit simulation execution unit 421 via a second sequencer 425.

[0061] The evaluation unit 422 calculates the computational fidelity by the quantum bit computational fidelity deviation calculation 132, and calculates the amount of deviation of the quantum bit computational fidelity obtained from the simulation result of the quantum bit simulation execution unit 421 from the ideal state.

[0062] The quantum logic simulation execution unit 423 executes the operation sequence of the quantum bit array 413 and simulates the quantum operation 301 for each sequence.

[0063] The computational fidelity accumulating unit 424 accumulates the deviation amount of computational fidelity when performing the quantum computation 301. Since the fidelity is calculated multiple times, the computational fidelity accumulating unit 424 accumulates the deviation amount of computational fidelity. The accumulated deviation amount of computational fidelity is stored in the third memory 434 by the correction amount calculating unit 433.

[0064] There are two output systems from the second sequencer (SEQ2) 425 in the virtual quantum computer 102. One is an output to a quantum logic simulation execution unit 423, and the other is an output to a quantum bit simulation execution unit 421. The quantum logic simulation execution unit 423 digitally executes a logical simulation of quantum bits, and the quantum bit simulation execution unit 421 simulates the state of each quantum bit.

[0065] The quantum logic simulation execution unit 423 digitally executes a logical simulation of quantum bits, and the quantum bit simulation execution unit 421 simulates the state of each quantum bit. The simulation by the quantum bit simulation execution unit 421 can be performed in an analog manner or digitally. For analog simulation, AC (Alternating Current) analysis or transition analysis of electromagnetic waves, voltage, and current is preferable. However, these simulations take a relatively long time.

[0066] Therefore, the quantum logic simulation execution unit 423 grasps the relationship between the control signal parameters and the control parameters, and then generates a learning model that models the correlation between the control parameters and the quantum bit state (the spin direction of one quantum bit). This learning model is defined as a function that obtains the quantum bit state when the control parameter is input. In creating this learning model, it is effective to construct the actual quantum bit state by machine learning using big data of many experimental results.

[0067] The digital twin control device 103 has a first comparison unit (COMP1) 431, a second comparison unit (COMP2) 432, a correction amount calculation unit (CCU: Correction Calcuration Unit) 433, a third memory (MEM0) 434, and a feedback control unit (FBC) 435.

[0068] The first comparison unit 431 compares a first measured value of the control parameter (voltage value, current value, RF frequency, control timing) output from the first sequencer 411 and detected by the sensor 414 with a second measured value of the control parameter (voltage value, current value, RF frequency, control timing) detected by the sensor 415 in the vicinity of the quantum bit array 413.

[0069] In the simplest example, the first comparison unit 431 compares the first measured value of the control parameter with the second measured value of the control parameter (this comparison result is 1A). At this time, if the design value of the control parameter is also stored in the first memory 412 or the like, it can also be read out and the magnitude of the read design value of the control parameter and the second measured value of the control parameter can be compared (this comparison result is 1B). By using the comparison result 1B as well, the amount of error in the control can be grasped and the amount of correction can be appropriately set. Using both comparison results 1A and 1B obtained in this way, the correction amount calculation unit (CCU) 433 calculates the amount of change in the value of the control signal parameter. Feedback control to the real quantum computer 101 and the virtual quantum computer 102 is executed based on this calculation result. Below, a specific explanation will be given mainly on an example using the comparison result 1A.

[0070] The first comparison unit 431 compares the second measured value of the control parameter with the design value of the control parameter based on the wiring length and temperature of the signal line 417, and calculates the amount of deviation as a comparison result 1A. In response to the comparison result 1A, the correction amount calculation unit (CCU) 433 sets a correction value for the control signal parameter required for the control parameter to become a value (here, the control parameter design value) that produces a state with high computational fidelity. Specifically, for example, the correction amount calculation unit (CCU) 433 performs correction so that the amount of deviation approaches 0. When the comparison result 1B is used, the setting of the circuit output and the amount of deviation of the comparison result 1B are further known, so that it becomes possible to control the amount of deviation to approach 0.

[0071] However, even if it is assumed that the control signal parameters will be set as designed, there are often cases where the control parameter values ​​do not match the design values ​​due to the ambient temperature of the quantum bit array 413 or noise from other wiring. In order to grasp such situations, it is desirable to measure the environmental parameters using a sensor (SEN2) 416 near the quantum bit array 413.

[0072] This measurement provides a second measured value of the control parameter and an environmental parameter. As an example of control for adjusting the value of the control signal parameter, the first comparison unit 431 compares the first measured value of the control parameter with the second measured value of the control parameter to obtain a comparison result 1A. Furthermore, the first comparison unit 431 compares the measured second measured value of the control parameter with a design value of the control parameter (which can be calculated taking into account the surrounding conditions once the control signal parameter is determined) to obtain a comparison result 1B.

[0073] If the deviation of all the parameters of the measured second measurement value of the control parameter from the design value is large in the comparison result 1A by the first comparison unit 431, the correction amount calculation unit 433 calculates a correction amount for decreasing the value of the control signal parameter, and the feedback control unit 435 performs further correction by taking into consideration the value of the environmental parameter when performing correction with the correction amount for decreasing the value of the control signal parameter. Conversely, if the deviation of all the parameters of the measured second measurement value of the control parameter from the design value is small, the feedback control unit 435 may perform control for increasing the value of the control signal parameter including the correction amount taking into consideration the value of the environmental parameter so that the second measurement value of the control parameter approaches the design value of the control parameter.

[0074] It should be noted that the deviation amount of all the parameters of the second measured control parameter from the design value may be targeted, but the deviation amount of the most sensitive parameter from the design value may be targeted instead. In addition, when further correction is performed taking into account the value of an environmental parameter, for example, when considering temperature as an environmental parameter, if the temperature rises, the optimal value under the temperature conditions changes. Therefore, by updating the design value according to the change in temperature (environmental parameter), control corresponding to the change in the environment becomes possible.

[0075] It is desirable for the first comparison unit 431 to hold the difference between the values ​​of the parameters with a sign. The comparison results 1A and 1B of the first comparison unit 431 are used for feedback for subsequent quantum bit control. A control parameter is used to estimate the quantum bit state, which will be described later, and the control parameter is adjusted by adjusting the control signal parameter by the first sequencer 411.

[0076] Therefore, it is desirable to store the deviation (comparison result 1A) between the control signal parameter (actually the first measured value of the control parameter) and the control parameter (actually the second measured value of the control parameter) in the third memory 434. By collecting this deviation history also when adjusting the control signal parameter from the next time onwards, it is possible to know the change in the deviation between the control signal parameter and the control parameter, and therefore to make the adjustment of the control signal parameter more efficient.

[0077] The second comparison unit 432 compares the operation result of the quantum operation 301 by the real quantum computer 101 with the simulation result of the quantum operation simulation 122 by the virtual quantum computer 102. Since the quantum operation 301 of the quantum computer uses the results of multiple quantum operations, the second comparison unit 432 compares the distribution information of the observation results of the quantum bits.

[0078] Here, the result of the quantum operation is obtained by measuring (observing) the quantum bit to be observed. After performing a quantum operation, the quantum bit to be measured has a certain probability amplitude, so one measurement (observation) will obtain a single value according to that probability amplitude. In other words, by performing this measurement (observation) multiple times, the expected value of the quantum bit to be observed is obtained as the result of the quantum operation, and thus the expected value as the result of the quantum operation is obtained. By measuring (observing) the quantum bit, the quantum state with the probability amplitude collapses and changes to a certain definite value. Therefore, in order to perform multiple measurements (observations) to obtain the expected value, it is necessary to perform the quantum operation and observe the quantum bit multiple times.

[0079] Specifically, for example, when performing a calculation using four quantum bits Q0 to Q3, the state of each quantum bit can be obtained by performing a quantum operation on these four quantum bits Q0 to Q3 and then observing these four quantum bits Q0 to Q3. If the result of one quantum operation is that the quantum bit spin is 1 for an upward direction and 0 for a downward direction, then for example, Q0=1, Q1=1, Q2=0, Q3=0 is obtained, and the result of the next quantum operation is, for example, Q0=1, Q1=0, Q2=1, Q3=0, and the result of each quantum operation is different.

[0080] By performing this multiple times, we can calculate the probability that each quantum bit will be 1, and obtain a probability distribution such as the probability that Q0 will be 1, P(Q0) = 0.8, the probability that Q1 will be 1, P(Q1) = 0.1, the probability that Q2 will be 1, P(Q2) = 0.07, and the probability that Q3 will be 1, P(Q3) = 0.03.

[0081] This is the procedure known as quantum operation and observation. Multiple quantum operations here means performing one quantum operation multiple times, and measuring (observing) the values ​​of each quantum bit Q0 to Q3 observed after each operation to obtain the probability distribution of the quantum bits. The sum of the probabilities of each quantum bit Q0 to Q3 equals 1, but the observation results for each time have variation due to the probability amplitude of each quantum bit being measured.

[0082] The correction amount calculation unit 433 calculates the correction amount of the control signal parameter when executing the quantum operation 301 of the real quantum computer 101 based on the first comparison results 1A and 1B of the first comparison unit 431 and the second comparison result of the second comparison unit 432. The correction amount calculation unit 433 calculates the correction amount of the control signal parameter by modeling the response of the operation result of the quantum operation 301 due to the change in the control parameter. Specifically, for example, the correction amount calculation unit 433 graphs the relationship between the control signal parameter setting value and the second measured value of the control parameter, and calculates the amount of deviation by looking up in a table.

[0083] The response of the operation result of quantum operation 301 is the movement of the quantum bit spin when controlled by a certain control parameter. For example, suppose that the quantum bit rotates by an angle of α when controlled by control parameter set A, and rotates by an angle of β when controlled by control parameter set B. In this case, α and β are the response of the operation result. We decided to do so.

[0084] This modeling may involve, for example, observing how the computational fidelity changes when the value of the control signal parameter is changed, and clarifying the relationship between the amount of change in the control signal parameter and the computational fidelity. The third memory 434 holds the comparison results of the first comparing unit 431 and the second comparing unit 432, and the correction amount calculated by the correction amount calculating unit 433.

[0085] The feedback control unit 435 transmits the correction amount of the control signal parameter calculated by the correction amount calculation unit 433 to the real quantum computer 101 and the virtual quantum computer 102. The feedback control unit 435 outputs the correction amount of the control signal parameter to the first sequencer of the real quantum computer 101, and also outputs it to the second sequencer 425 via the second memory 426 of the virtual quantum computer 102.

[0086] Fig. 5 is an explanatory diagram showing an example of the contents stored in the third memory 434 of the digital twin control device 103. Fig. 5 shows an example in which the number of quantum bits in the quantum bit array 413 is 128, and control parameters are stored in a table 500 for each quantum bit.

[0087] The table 500 has fields such as a quantum bit ID 501, a voltage variation (ΔV) 502, a current variation (ΔI) 503, and a voltage application time variation (Δt V ) 504 and the current application time variation (Δt I ) 505, the amplitude variation of the RF signal (ΔRF amp) 506, the frequency variation of the RF signal (ΔRF freq) 507, and the RF signal application time variation (Δt RF) 508, phase shift of the RF signal (ΔRF φ) 509, temperature variation (ΔTEMP) 510, applied magnetic field variation (ΔMag.Field) 511, manufacturing process variation (Δprocess) 512, and quantum bit computational fidelity (Fidelity) 513 (specifically, for example, the accumulated deviation in computational fidelity).

[0088] Voltage variation (ΔV) 502 is the amount of deviation from a designed value of voltage V. Current variation (ΔI) 503 is the amount of deviation from a designed value of current I.

[0089] Voltage application time variation (Δt V ) 504 is the voltage application time t V The deviation from the current application time (Δt I ) 505 is the current application time t I This is the deviation amount relative to (comparison result 1B).

[0090] The RF signal amplitude variation (ΔRF amp) 506 is the amount of deviation from the RF signal amplitude as a design value. The RF signal frequency variation (ΔRF freq) 507 is the amount of deviation from the RF signal frequency as a design value. The RF signal application time variation (Δt RF ) 508 is the RF signal application time t RF This is the amount of deviation relative to

[0091] The temperature variation (ΔTEMP) 510 is the deviation between the measurement value of the sensor (SEN2) 416 and the operating temperature as the environmental parameter setting value.

[0092] The applied magnetic field variation (ΔMag.Field) 511 is the amount of deviation between the applied magnetic field as an environmental parameter setting value and the amount measured by the sensor (SEN2) 416.

[0093] The manufacturing process variation (Δprocess) 512 is the amount of variation in the process when manufacturing the quantum bit chip LSI.

[0094] 5, an entry for each quantum bit is held for one step of the quantum operation 301, but in reality, an entry for each quantum bit is held for each step of the quantum operation 301. Each of the control parameters (502 to 513) is stored in, for example, 16 bits. Therefore, a memory capacity of 16 (bit) x 12 (field) x 128 (number of quantum bits) = 3 KB is required.

[0095] Since this table 500 stores data for one quantum operation, when the quantum operation 301 is executed for example 30 steps, a memory capacity of 90 KB is required. Note that the data length of each of the control parameters 502 to 513 is not limited to 16 bits. The number of bits can be changed appropriately based on the required accuracy.

[0096] In addition, the number of control parameters is 12 in this example, but this is only an example. For example, when multiple voltage signals are used to control the quantum bit, the evaluation accuracy can be improved by tabulating them individually. Furthermore, it is possible to include control parameters other than those mentioned above.

[0097] For example, in the above example, the voltage application time t V is the control parameter, and the difference from the initial design value is the voltage application time variation (Δt V ) 504, the evaluation accuracy may be improved by including the rise time and fall time of the voltage application as control parameters. In that case, such control parameters may be held independently. I and RF signal application time t RF The same applies to.

[0098] When simulating the quantum operation 301 as a matrix operation, assuming a quantum computer system 100 with N (N is an integer equal to or greater than 1) quantum bits, typically, 2 N There are states, and the matrices to be handled are (2 N ) 2 =2 2N If N=128, a large matrix of 2 128 =3.96×10 28 This would require an enormous amount of memory space of GB, and the quantum operation 301 would require matrix operations using a memory space squared by that amount.

[0099] By the way, if we assume that the control parameters correspond to the operation accuracy of the quantum bit, by adjusting the voltage, current, and application of the RF signal, the control of the quantum bit will change according to a certain function according to those values. The quantum operation 301 changes over time according to the Hamiltonian that describes the quantum bit, and the value of the control parameter that causes the time change of the energy is described by the Hamiltonian.

[0100] In reality, it is necessary to apply the Hamiltonian to the state ket (|φ>) to find out how the state ket changes, but if it is assumed that the changes in the control parameters and the changes in the state ket are linked by a certain function, then the state of the quantum bit can be estimated from the combination information of the control parameters.

[0101] By tabulating the relationship between the values ​​of these control parameters and the state of the quantum bit from numerous basic experiments, it is possible to tabulate the computational fidelity for the quantum operation 301 as well. However, even if it is difficult to formulate this table in a closed form, it is possible to create it experimentally. In this way, this method does not sequentially simulate the quantum state of the quantum bit with the quantum operation 301, but estimates the computational fidelity of the quantum operation 301 with the control parameters for executing the quantum operation 301. Therefore, in principle, the amount of computation can be significantly reduced.

[0102] However, in this embodiment, it is not possible to derive the contents of the quantum operation 301, but rather to estimate the degree to which the spin state of the quantum bit is affected. Since the purpose of a digital twin is to grasp the operation state of the quantum bit, if the operation fidelity 513 of the quantum bit can be calculated by executing the minimum necessary quantum operation 301, it is possible to significantly reduce the memory capacity.

[0103] FIG. 6 is an explanatory diagram showing another example of the contents stored in the third memory 434 of the digital twin control device 103. FIG. 6 is applicable to cases where there is almost no variation in the characteristics of each quantum bit. In particular, the size of a semiconductor electron spin quantum bit is very small, and when manufactured using a semiconductor microprocess, the uniformity of the characteristics of each element is kept high. In such a device, the individual process variation of each quantum bit is kept small.

[0104] Therefore, control parameters such as process, voltage, and temperature can be considered as parameters common to each quantum bit. Specifically, for example, table 600 has fields such as RF signal frequency variation (ΔRF freq) 507, voltage variation (ΔV) 502, current variation (ΔI) 503, RF signal amplitude variation (ΔRF amp) 506, temperature variation (ΔTEMP) 510, applied magnetic field variation (ΔMag.Field) 511, and process variation (Δprocess) 512. This has the effect of reducing the memory capacity used.

[0105] 7 is a block diagram showing a configuration example of the quantum bit array 413. The quantum bit array 413 is a quantum bit subarray module (QBSM) having a quantum bit subarray 701, an X selection circuit (XDEC) 702, a Y selection circuit (YDEC) 703, a read circuit (ROC) 704, a current sensor (ASEN) 704, a voltage sensor (VSEN) 705, a delay detection sensor (DSEN) 706, a temperature detection sensor (TSEN) 707, an applied static magnetic field measurement sensor (FSEN) 708, and a phase detection circuit (PD) 709.

[0106] The quantum bit subarray 701 is an assembly in which a plurality of quantum bits 700 are integrated in a matrix shape. The X-selection circuit 702 selects a column of quantum bits 700 in the X-direction of the quantum bit subarray 701. The Y-selection circuit 703 selects a row of quantum bits 700 in the Y-direction of the quantum bit subarray 701.

[0107] Current sensor 704 detects an applied current when a current is applied to create and control a magnetic field gradient to selectively flip qubit 700 to select qubit 700 .

[0108] For example, in the case of an electron spin quantum bit, the voltage sensor 705 detects the applied voltage of two quantum dots each storing two quantum bits 700. Although not shown here, if dynamically changing the voltage improves the efficiency or fidelity of the quantum operation 301, it is effective to include detection of a delay in the voltage change.

[0109] Since the application timing of the RF signal is the most important factor in quantum bit operations, it is effective to detect the application timing of the RF signal. Therefore, delay detection sensor 706 detects the delay of the RF signal. Temperature detection sensor 707 detects the temperature inside quantum bit array 413. Applied static magnetic field measurement sensor 708 detects the static magnetic field applied to quantum bit 700. Phase detection circuit 709 detects the phase of the RF signal that controls quantum bit 700.

[0110] It is also possible to mount a plurality of quantum bit arrays 413 in one LSI. In this case, various sensors 704 to 709 are independently mounted on each quantum bit array 413. This makes it possible to measure the control parameters of quantum bit 700 with high accuracy.

[0111] In addition, if there is concern about area overhead or increased power consumption due to the inclusion of these sensors 704 to 709, it is possible to appropriately limit the number of sensors to be installed. Note that, if the spatial change of the object to be observed is small, mounting one or several of the applied static magnetic field measurement sensor 708 and the temperature detection sensor 707 on one chip has the effect of saving area.

[0112] <Incorporating simple deviations from ideal conditions and changes over time> Fig. 8 is a flowchart showing an example of a procedure for adjusting a quantum bit control model by the quantum computer system 100. Fig. 8 is effective when executed as preparation before the digital twin control device 103 executes a digital twin operation. Note that several quantum bit control models are possible. It is assumed that the control of a typical quantum bit 700 follows the Hamiltonian (H) of the following formula (1) (Non-Patent Document 4).

[0113]

number

[0114] Here, S L ,S R is the spin, which is expressed as a spin matrix. Also, B L ,B R , Spin S L ,S R Also, J(t) denotes the magnetic field applied to the spin S at time t. L ,S R The first term on the right side of the above formula (1) represents a two-qubit operation involving two qubits 700, and the second and third terms represent a one-qubit operation. Here, two spins S L ,S R is a function of time J(t). The applied magnetic field can also be considered as a function of time. There are various possible Hamiltonians for the quantum bit 700, but in this specification, the above formula (1) will be described as a quantum bit control model.

[0115] One possible method for controlling quantum bit 700 is to emulate the operation of quantum bit 700 using electromagnetic field simulation (hereinafter referred to as method 1). Method 1 is a method in which the operation of a circuit that controls quantum bit 700 is simulated to obtain signal waveform data of a control parameter for controlling quantum bit 700, the signal waveform data is used to determine the magnetic field to be applied to quantum bit 700, and the quantum state is calculated by solving the Schrödinger equation using the Hamiltonian of formula (1) above. This method utilizes electromagnetic field simulation and uses the time change in the strength of the applied magnetic field, so it has high calculation accuracy but requires high calculation resources.

[0116] The other method is to construct a correlation between each control parameter of the quantum bit 700 and the operation of the quantum bit 700, and to simulate the operation of the quantum bit 700 using this correlation (hereinafter, the second method). Specifically, instead of the control parameters, the control signal parameters are used after obtaining the correlation between the control parameters and the control signal parameters. The following explanation uses the control signal parameters. The second method can be executed with fewer computational resources because the quantum bit control model is simplified. FIG. 8 shows an example of a processing procedure common to both methods.

[0117] 8, the virtual quantum computer 102 acquires control signal parameters (step S801) and constructs a quantum bit control model for controlling the quantum bit 700 in an ideal state (step S802). For example, the virtual quantum computer 102 sets the Hamiltonian of the quantum bit 700 with electromagnetic interactions taken into account, and calculates the value of the potential barrier due to the applied voltage, the shift in the value of the static magnetic field due to the application of a current, and the spin rotation operation due to the application of an RF signal to the quantum bit 700. In this way, the quantum bit control model is constructed.

[0118] Then, the virtual quantum computer 102 starts adjusting the control signal parameters (step S803). The digital twin control device 103 changes the control signal parameters set in the quantum bit control model by the virtual parameter change 133 (step S804). However, if step S807 has not been executed, no changes are made.

[0119] In step S804, the first comparison unit 431 obtains a comparison result 1B by comparing the changed control signal parameter with the second measured value of the control parameter (voltage value, current value, RF frequency, control timing) near the quantum bit array 413, and then the correction amount calculation unit 433 changes the value of the control signal parameter if it is necessary to change the control signal parameter, for example, by decreasing the value of the control signal parameter when the second measured value of the control parameter is greater than a certain threshold value, and by increasing the value of the control signal parameter when the second measured value of the control parameter is less than a certain threshold value. The algorithm for this comparison may be a table reference based on empirical values, and an arithmetic circuit may be implemented in the correction amount calculation unit 433.

[0120] The virtual quantum computer 102 uses the quantum bit control model to estimate the state of the quantum bit 700 (step S805). Specifically, for example, the virtual quantum computer 102 uses the following formula (2) to calculate how the state of the quantum bit 700 changes when the control parameters are input to the quantum bit control model. Thereafter, the digital twin control device 103 compares the calculation results in COMP2 and performs the necessary corrections.

[0121]

number

[0122] B L (t), B R (t) is the spin S at time t L ,S R The virtual quantum computer 102 changes the control signal parameters (step S804) to change the functions J(t), BL (t), B R (t) or set the fitting parameters α, β, and γ.

[0123] The virtual quantum computer 102 compares the state of the quantum bit 700 (for example, the spin direction of the quantum bit 700 on the Bloch sphere) estimated in step S805 using the control signal parameters after the change (step S804) by the virtual-actual machine operation result comparison 131 with the ideal state of the quantum bit 700 in the second comparison unit 432 (step S806), and determines whether the deviation from the ideal state (i.e., the deviation amount (1-computational fidelity)) is within the design value (step S807). If the deviation is not within the design value (step S807: No), the value of the control signal parameter after the change is not appropriate, so the process returns to step S804. Then, the digital twin control device 103 changes the control signal parameter again by the virtual parameter change 133 (step S804).

[0124] Specifically, for example, the digital twin control device 103 may change at least one of the values ​​of the control signal parameters by adding or subtracting a value by a predetermined change amount, or the value may be changed by an arbitrary input by the user of the digital twin control device 103. After this change, the virtual quantum computer 102 again estimates the state of the quantum bit 700 (step S805).

[0125] On the other hand, if the deviation is within the design value, the value of the control signal parameter is determined to be appropriate, and the virtual quantum computer 102 completes the adjustment of the control signal parameter (step S808).

[0126] Thereafter, the digital twin control device 103 applies the control signal parameters used when estimating the quantum bit state to the quantum bit 700 of the real quantum computer 101, and causes the real quantum computer 101 to measure the state of the quantum bit 700. Then, the digital twin control device 103 obtains the measurement value of the quantum bit state measured by the real quantum computer 101 from the real quantum computer 101 as the quantum operation result (step S809).

[0127] The digital twin control device 103 compares the acquired quantum operation result with the estimated result based on the quantum bit control model whose adjustment was completed in step S808 in the second comparison unit 432 (step S810), and determines whether the deviation from the quantum operation result is less than or equal to the design value (step S811).

[0128] If the deviation from the quantum operation result is not equal to or less than the design value (step S811: No), the quantum bit control model is deemed inappropriate, and the process returns to step S802, where the virtual quantum computer 102 reconstructs the quantum bit control model (step S802). Specifically, for example, the digital twin control device 103 adjusts the values ​​of fitting parameters α, β, and γ other than the control parameters, and provides them to the virtual quantum computer 102.

[0129] The quantum computer system 100 sequentially executes such iterations, and when the deviation from the quantum operation result is finally within the design value (step S811: Yes), it is determined that the adjustment of the control parameters is completed, and the construction of the quantum bit control model is completed.

[0130] As mentioned above, there are two possible methods for such modeling. The first method involves constructing a quantum bit control model for executing emulation based on physical phenomena.

[0131] On the other hand, by modeling using the second method, a quantum bit control model is constructed that specifies the correlation between the control signal parameters (the application timing of various signals, the voltage, current, phase, amplitude, and frequency of the RF signal) given to each electrode to control the quantum bit 700 and the state of the quantum bit 700 that is realized when the control parameters are actually applied to the quantum bit 700.

[0132] By using the quantum bit control model modeled by this second method, it is possible to set control signal parameters to simulate the state of quantum bit 700 when controlling quantum bit 700. The state of quantum bit 700 can be calculated as spin interactions of electron spins by electromagnetic field analysis or the like when control signal parameters such as the voltage of each electrode controlling quantum bit 700, the applied current, the frequency and phase of the RF signal, and the timing at which these are actually applied to quantum bit 700 are determined.

[0133] In this way, the spin state of quantum bit 700 can be calculated, for example, as information on a Bloch sphere. This calculation involves electromagnetic field analysis and requires high computational resources, but if a quantum bit control model can be constructed that associates the control parameters with the spin state of quantum bit 700 resulting from their application, the state of quantum bit 700 can be inferred from the value of the control parameter. Furthermore, if the relationship between the control parameters and the control signal parameters is clear, a quantum bit control model can be constructed that associates the control signal parameters with the spin state of quantum bit 700 resulting from their application.

[0134] The quantum bit control model modeled by the second method is an effective model for performing effective calculations using a classical computer. In many cases, it is effective to emulate the behavior of the quantum bit 700 of the actual quantum computer 101 with a so-called lightweight model that does not require such a large amount of computational resources. Of course, when detailed simulation is required due to environmental conditions, etc., a hybrid type evaluation is also possible in which some calculations are replaced by calculations using such a model that requires a large amount of computational resources.

[0135] The following flowcharts (FIGS. 9 to 12) will be explained with a quantum bit control model in mind that utilizes the correlation between the control signal parameters and quantum bit 700.

[0136] The above-described quantum bit control model is, so to speak, a model that represents an ideal state, in that no operations are performed on any quantum bit other than the target quantum bit 700, and the influence of crosstalk noise when controlling quantum bits 700 other than the target quantum bit 700 and noise due to environmental changes such as temperature are not included.

[0137] The behavior of the actual quantum computer 101 generally deviates from the ideal state. This is because it is affected by environmental factors such as the ambient temperature, magnetic field, physical layout, and device variability. Using this quantum bit control model as a base, it is effective to observe the behavior of the quantum bits 700 in the quantum bit array 413 of the actual quantum computer 101 and, if necessary, modify the quantum bit control model to create an effective quantum bit control model.

[0138] It is desirable to improve the ideal quantum bit control model for the quantum bit control model set by the control signal parameters of the quantum bit 700 that deviates from the ideal state. It is also assumed that the quantum bit control model may change depending on the actual operating environment. When operating the actual quantum computer 101, it is effective to correct the ideal quantum bit control model before starting calculations.

[0139] Furthermore, when operating the actual quantum computer 101, changes in temperature and magnetic field over time also affect the control of the quantum bit 700. In order to eliminate such effects, it may be effective to appropriately correct the quantum bit control model even during operation of the actual quantum computer 101.

[0140] It is desirable to perform this correction in one stage of quantum operation of the actual quantum computer 101. This is because when a large number of quantum bits 700 become entangled with each other, the range of influence spreads widely. Note that one stage of quantum operation is assumed to be a single quantum bit operation (X gate, etc.) or a two-qubit operation (C-NOT gate, etc.). The digital twin control device 103 searches for conditions under which the amount of change from the ideal value of the estimated value of the quantum bit state as a control result (hereinafter referred to as the theoretical deviation value) exceeds the design value.

[0141] If the theoretical deviation value falls below the design value, the digital twin control device 103 actually compares the estimated value of the quantum bit state with the calculation result of the actual quantum computer 101, and calculates the comparison result with the actual quantum computer 101 (hereinafter referred to as the actual estimated deviation value). In this way, the estimated value obtained by emulation is compared with the calculation result of the actual quantum computer 101. If this actual estimated deviation value does not fall below the design value, the digital twin control device 103 changes the quantum bit control model, and again searches for conditions under which the theoretical deviation value exceeds the design value, and calculates the actual estimated deviation value.

[0142] The change of the quantum bit control model includes the improvement of various fitting parameters α, β, and γ other than the control parameters set in the quantum bit control model, or the quantum bit control model itself. If the actual estimated deviation value becomes equal to or smaller than the design value, the adjustment of the quantum bit control model is completed. The following describes in detail how the influence of the variability is incorporated with reference to Figs. 9 to 12.

[0143] <Incorporating the effects of variability> FIG. 9 is a flowchart showing an example of a process for creating a quantum bit control model that takes into account variations in the control of a single quantum bit and two quantum bits by quantum computer system 100 (hereinafter, quantum bit control variation model), and relates to the calibration of each quantum bit 700.

[0144] 8 (step S901), and if step S909: No, changes the quantum bit control variation model created in steps S903 to S908 (step S902).Then, the quantum computer system 100 starts a control parameter variation evaluation (step S903).

[0145] The digital twin control device 103 acquires the control signal parameter and a second measured value of the control parameter from the real quantum computer 101 (step S904), and adjusts the amount of variation of the control signal parameter based on the acquired second measured value of the control parameter and the first measured value of the control signal parameter being controlled (step S905).

[0146] Specifically, for example, the digital twin control device 103 adjusts the amount of variation in the control signal parameters, taking into account the allowable deviation of the quantum bit state from the ideal state under conditions of variously different environmental parameters during operation of the real quantum computer 101. Because the allowable variation changes for each environment in which quantum operations are performed in the real quantum computer 101, in step S905, the digital twin control device 103 quantifies the effect that the variation in the control signal parameters has on the quantum operations.

[0147] Next, the virtual quantum computer 102 estimates the state of the quantum bit 700 of the real quantum computer 101 based only on the fluctuations in the measured values ​​of the control parameters and the fluctuations in the measured values ​​of the environmental parameters during digital twin operation (step S906).

[0148] Specifically, for example, the virtual quantum computer 102 uses the environmental parameters and the control signal parameters whose variations have been adjusted in step S905 to obtain a correlation between the control signal parameters according to each environmental parameter and the spin state of the quantum bit 700 when a quantum bit operation is executed using the control parameters acting on the quantum bit 700 when the control signal parameters are set, to create a quantum bit control variation model. Specifically, for example, the quantum bit control variation model is created using the following equations (3) to (5).

[0149]

number

[0150] In the above formulas (3) to (5), i is the number of the quantum bit 700. i,i+1 (t) is expressed by the above formula (4), and B in the above formula (3) i (t) is expressed by the above formula (5). Here, J in the above formulas (4) and (5) Typ (t), B Typ (t) is a typical function in which the variations in the functions J(t) and B(t) used in the description of FIG. 8 are not taken into consideration.

[0151] J Typ (t), B Typ (t) is a function of time expressed as a quantity that changes depending on the position when the electromagnetic wave applied to each spin is a control parameter (V (voltage), I (current), RF (amplitude, frequency, phase, etc. of the RF signal)) and an environmental parameter (T (temperature), P (variation due to the manufacturing process)) (by obtaining the relationship between the control signal parameter and the control parameter, it can also be expressed as a function of the control signal parameter in the end). The simplest possible approach is to correct it as a constant value. In this way, the virtual quantum computer 102 estimates the quantum bit state for the quantum bit 700 to be operated on using the measured value of the control parameter.

[0152] Next, the digital twin control device 103 applies the control parameters used when estimating the quantum bit state to the quantum bit 700 of the real quantum computer 101, compares the estimate of the quantum bit state with the measured value measuring the state of the quantum bit 700 of the real quantum computer 101, and evaluates the deviation between the estimate and the measured value (step S907). Specifically, for example, the digital twin control device 103 determines whether the deviation between the estimate and the measured value is equal to or smaller than a design value (step S908).

[0153] If the deviation between the estimated value and the measured value is equal to or smaller than the design value (step S908: Yes), the creation of the quantum bit control variation model is completed.

[0154] If the deviation between the estimated value and the measured value is not equal to or less than the design value (step S908: No), the process returns to step S902, and the virtual quantum computer 102 updates the quantum bit control variation model. Specifically, for example, the digital twin control device 103 updates the value α of the fitting parameter that fits the quantum bit control variation model other than the control parameter by the virtual parameter change 133. i , β i , γ i ) and provide it to the virtual quantum computer 102.

[0155] If such adjustments using fitting parameters are not possible, the quantum bit control variability model itself must be considered. For example, the digital twin control device 103 changes the Hamiltonian that defines the behavior of the quantum bit 700 to a quantum bit control model in which the amount of noise is coupled with a certain coupling constant by virtual parameter change 133, as shown in the following formula (6).

[0156]

number

[0157] The above formula (6) is expressed by adding the correction term μ i H Noise(t) is added. In step S902, the digital twin control device 103 changes the correction term μ i H Noise Adjust (t). μ i is the coupling constant, and H Noise (t) is the amount of noise at time t.

[0158] Such a correction term μ i H Noise (t) can be applied not only to the simple noise effect, but also to the case where the effect of the spin-orbit interaction due to the shape of the potential barrier forming the quantum dot is introduced. The correction term μ i H Noise (t) varies depending on the manufacturing method of the actual quantum dot. The efficiency of this modeling can be improved by thoroughly investigating the behavior of the quantum bit 700 based on actual measurement data before performing digital twin operations.

[0159] Alternatively, a higher-order correction term is theoretically known. When the influence is small, the higher-order correction term is set in advance in the above formula (6). The digital twin control device 103 may change the parameter of the higher-order correction term from 0 by the virtual parameter change 133. In this way, the initial modeling by the above formula (6) is constructed over time. The modeling by the above formula (6) is a process independent of FIG. 9.

[0160] On the other hand, even when executing as a digital twin as shown in FIG. 9, it is important to appropriately evaluate the variation fluctuation taking into account the change over time, and it is desirable to correct the parameters of the high-order correction term at a certain set time. This process is executed for each instruction of the quantum bit operation. In this case, it is desirable to execute it separately for the evaluation of a single quantum bit and for basic operations such as the evaluation of two quantum bits. By executing this process, a table for estimating the state of the quantum bit 700 can be created using the relationship between the environmental parameters and the control parameters. When controlling the digital twin, it is possible to estimate the state of the quantum bit 700 by utilizing this table.

[0161] <Ambient noise capture> In general, quantum operations are a combination of multiple operations, and operations are executed sequentially in a time series. When these sequential processing operations are executed, the effect of crosstalk noise on non-controlled quantum bits 700 other than the controlled quantum bit 700 cannot be ignored. It is desirable to model the effect of this noise and apply compensation during digital twin operation.

[0162] When modeling the effects of noise, it is necessary to model in detail the environment of the actual quantum computer 101. In order to model the connection configuration of the qubits 700 and the propagation of noise during control by the control parameters, it is first necessary to operate the small-scale qubit array 413 and evaluate the shadow of crosstalk, etc., by actual measurement.

[0163] 10 is a flowchart showing an example of a process for creating a quantum bit control model that includes the influence of noise from the surroundings (hereinafter, quantum bit control noise model). First, the digital twin control device 103 sets fitting parameters in the quantum bit control model of the virtual quantum computer 102 by the virtual parameter change 133 (step S1001).

[0164] Next, the virtual quantum computer 102 executes one step of quantum operations on a group of quantum bits to be subjected to noise adjustment (hereinafter, the group of quantum bits to be adjusted) by the quantum operation simulation 122 (step S1002). The group of quantum bits to be adjusted is updated every time the program counter is incremented in step S1008.

[0165] Next, the virtual quantum computer 102 evaluates the effect of noise on the group of quantum bits not to be adjusted from the quantum operation result of step S1002 (step S1003). That is, while evaluating the quantum bit state of the group of quantum bits to be adjusted, the virtual quantum computer 102 also evaluates the effect on the group of quantum bits not to be adjusted when controlling the group of quantum bits to be adjusted. Data showing the effect of noise on the group of quantum bits not to be adjusted is referred to as noise data. The evaluation of this noise data can use the results of a circuit simulation such as an electromagnetic field analysis of the quantum bit array 413.

[0166] The effect of the control parameters on the state of the non-adjustment target quantum bits is preferably considered as a response of the non-adjustment target quantum bits to various control parameters for controlling the adjustment target quantum bits. For example, the virtual quantum computer 102 can use the control parameters to obtain a spatially distributed electromagnetic field intensity distribution or the like with an electromagnetic field simulator, thereby modeling the correlation between the control parameters and the state of the quantum bits 700. The virtual quantum computer 102 can use such correlation data to construct a noise model for controlling the adjustment target quantum bits.

[0167] Next, the virtual quantum computer 102 estimates the state of each quantum bit 700 in the group of quantum bits to be adjusted by the quantum operation simulation 122 (step S1004). Specifically, for example, the virtual quantum computer 102 uses the above formula (2) to calculate how the state of each quantum bit 700 in the group of quantum bits to be adjusted changes, as in step S805 of FIG. 8, and performs the necessary correction.

[0168] Next, similar to step S806, the virtual quantum computer 102 compares the state of the quantum bit 700 of the group of quantum bits to be adjusted estimated using the control parameters (for example, the spin direction of the quantum bit 700 on the Bloch sphere) with the ideal state of the quantum bit 700 of the group of quantum bits to be adjusted, and calculates the deviation from the ideal state (i.e., the deviation (1-computational fidelity)) (step S1005). Then, the digital twin control device 103 determines whether the deviation is equal to or smaller than the design value (step S1006).

[0169] If the deviation is not equal to or less than the design value (step S1006: No), the process returns to step S1001, and the digital twin control device 103 resets the values ​​of the fitting parameters to different values. Specifically, for example, the digital twin control device 103 may change at least one of the fitting parameter values ​​by adding or subtracting a value of a predetermined change range, or the user of the digital twin control device 103 may change the value by inputting it arbitrarily.

[0170] On the other hand, if the deviation is equal to or less than the design value (step S1006: Yes), the digital twin control device 103 determines whether the quantum operation has ended (step S1007). End of quantum operation means that there is no group of quantum bits to be adjusted in the virtual quantum computer 102. In other words, this indicates a state in which the program counter cannot be updated any more in step S1008.

[0171] If the quantum operation has not finished (step S1007: No), the virtual quantum computer 102 increments the program counter (step S1008) and returns to step S1002, thereby updating the asymmetric quantum bit group to the focal quantum bit group.

[0172] If the quantum operation has ended in step S1007 (step S1007: Yes), the digital twin control device 103 applies the control parameters used when estimating the quantum bit state to the quantum bit 700 of the real quantum computer 101, and causes the real quantum computer 101 to measure the state of the quantum bit 700. Then, the digital twin control device 103 acquires from the real quantum computer 101 the measurement value of the quantum bit state measured by the real quantum computer 101 (step S1009).

[0173] The digital twin control device 103 compares the estimated values ​​of the quantum bit states of each quantum bit 700 in all groups of quantum bits to be adjusted estimated in step S1004 with the experimental results measuring the states of the quantum bits 700 in the actual quantum computer 101, and calculates the deviation between the estimated values ​​and the measured values ​​(step S1010).

[0174] Each step of the quantum operation is a process of accumulating the calculation error of the quantum operation for the corresponding quantum bit 700 by a matrix operation. In addition, when a quantum entangled state is reached, the quantum bits 700 other than the target of the operation are also affected, but this effect is also incorporated. If there is even one quantum bit 700 whose deviation is not equal to or less than the design value, the fitting parameters will be updated, but it is also possible to shorten the evaluation time by determining the magnitude of the effect and, if the error is sufficiently small, inserting an approximation that ignores it. Then, the digital twin control device 103 determines whether the deviation between the estimated value and the measured value is equal to or less than the design value (step S1011).

[0175] If the deviation between the estimated value and the measured value is equal to or less than the design value (step S1011: Yes), the quantum bit controlled noise model is constructed. On the other hand, if the deviation between the estimated value and the measured value is not equal to or less than the design value (step S1011: No), the digital twin control device 103 updates the fitting parameters of the quantum bit controlled model by the virtual parameter change 133 (step S1012) and returns to step S1001.

[0176] Specifically, for example, the digital twin control device 103 may change at least one of the fitting parameter values ​​by adding or subtracting a value of a predetermined change range using virtual parameter change 133, or the value may be changed by a user of the digital twin control device 103 entering the value arbitrarily.

[0177] If a quantum bit controlled noise model is not constructed in the end even after executing this loop a predetermined number of times, the original quantum bit controlled model itself needs to be updated. In other words, this is the case when adjustments cannot be made using simple fitting parameters. By thoroughly investigating the behavior of the quantum bit 700 based on actual measurement data before executing digital twin operations, the efficiency of constructing the quantum bit controlled noise model is improved.

[0178] Alternatively, a high-order correction term may be set in the quantum bit control model in advance, and the digital twin control device 103 may change the parameter of the high-order correction term from 0. In this way, when setting the initial quantum bit control model, the digital twin control device 103 takes time. This is a process independent of FIG. 10. For this reason, it is desirable to try setting the quantum bit control model using several benchmark quantum bit arrays 413.

[0179] After the quantum bit controlled noise model is constructed by the process shown in Fig. 10, the quantum computer system 100 executes the process of Fig. 10 for the quantum bit controlled noise model. Specifically, for example, the virtual quantum computer 102 executes a quantum operation on a group of target quantum bits (step S1002). The virtual quantum computer 102 evaluates the effect of noise (step S1003) and executes an estimation of the quantum bit state (step S1004).

[0180] The virtual quantum computer 102 calculates the deviation between the estimated quantum bit state and the ideal state for the target quantum bit group (i.e., the deviation (1-computational fidelity)) (step S1005). If the deviation is equal to or less than the design value (step S1006: Yes), the digital twin control device 103 determines whether the quantum operation has ended (step S1007), and if the quantum operation has not ended (step S1007: No), it increments the program counter (step S1008) and obtains the quantum operation result for the next target quantum bit group (step S1002).

[0181] After the quantum operation is completed (step S1007: Yes), the digital twin control device 103 applies the quantum bit control noise model to the quantum bit 700 of the real quantum computer 101, and causes the real quantum computer 101 to measure the state of the quantum bit 700. Then, the digital twin control device 103 acquires from the real quantum computer 101 the measurement value of the quantum bit state measured by the real quantum computer 101 (step S1009).

[0182] The digital twin control device 103 compares the estimates of the quantum bit states of all quantum bit groups to be adjusted estimated in step S1004 with the experimental results of measuring the states of the quantum bits 700 of the actual quantum computer 101, and calculates the deviation between the estimates and the measured values ​​(step S1010). Then, the digital twin control device 103 determines whether the deviation between the estimates and the measured values ​​is equal to or smaller than the design value (step S1011).

[0183] If the deviation between the estimated value and the measured value is equal to or smaller than the design value (step S1011: Yes), the quantum bit control noise model is confirmed. Therefore, the quantum bit control noise model can be applied to the actual quantum computer 101 for use.

[0184] On the other hand, if the deviation between the estimated value and the measured value is not equal to or less than the design value (step S1011: No), the digital twin control device 103 updates the fitting parameters of the quantum bit controlled noise model (step S1012) and returns to step S1001. Specifically, for example, the digital twin control device 103 changes the coupling constants, which will be described later, in addition to the fitting parameters.

[0185] The change in the fitting parameters and coupling constants avoids a decrease in the computational fidelity of the quantum operation 301 when the quantum bit state changes due to the influence of noise. When changing the fitting parameters and coupling constants, first, the coupling constant between an ideal quantum bit control model and an assumed noise model is set as a parameter. The digital twin control device 103 models the influence of noise by adjusting the coupling constants and fitting parameters.

[0186] The Hamiltonian describing the quantum bit 700 is H, the Hamiltonian for the ideal quantum bit control model is H0, and the Hamiltonian describing the effect of noise is H noise Then, the above formula (6) is generally expressed as the following formula (7).

[0187]

number

[0188] Here, α, β, . . . are fitting parameters, and μ is a coupling constant. First, the digital twin control device 103 adjusts the fitting parameters, and then changes the coupling constant μ or the Hamiltonian H noise By changing the Hamiltonian H, we can make the quantum bit control model closer to reality.

[0189] <Digital twin operation> The digital twin operation of this embodiment monitors the state of the control parameters of the quantum bit 700 and infers the state of the quantum bit 700, but does not perform corrections to the operation of the quantum bit group during the quantum operation. Any necessary corrections are performed during the operation of the next quantum circuit. When performing a digital twin operation, the digital twin control device 103 estimates the operating conditions of the actual operation, i.e., the quantum bit state, by reflecting various influences in the actual operation in the control parameters of the quantum bit 700. This improves the quality of the quantum operation.

[0190] Fig. 11 is a flowchart showing digital twin operation processing procedure example 1. Digital twin operation processing procedure example 1 is operated using the model constructed in Figs. 8 to 10. In digital twin operation, the virtual quantum computer 102 executes a quantum operation sequence that is exactly the same as the quantum operations executed by the real quantum computer 101, and evaluates the quantum bit state using quantum bits 700 that have the same quantum bit connection relationship as the real computer.

[0191] The virtual quantum computer 102 sets the control signal parameters in the virtual quantum computer 102 (step S1101). At this time, the virtual quantum computer 102 is set so that quantum bit manipulation is performed based on the quantum bit control model. The virtual quantum computer 102 executes one step of quantum operation on the target quantum bit group based on the quantum bit control model, and transmits the quantum operation result to the digital twin control device 103. The digital twin control device 103 acquires the quantum operation result for one step transmitted from the virtual quantum computer 102 (step S1102).

[0192] Also, similar to step S1003, the virtual quantum computer 102 acquires ambient control noise data and ambient environment sensor data to evaluate the effect of noise on the quantum bit state (step S1103). Then, similar to step S1004, the virtual quantum computer 102 estimates the state of each quantum bit 700 in the target quantum bit group (step S1104). Here, for example, if the target quantum bit group is a group of 128 quantum bits, the digital twin control device 103 estimates the quantum bit states for the 128 quantum bits.

[0193] Then, the digital twin control device 103 calculates the deviation between the estimated value of the quantum bit state and the design value (i.e., the deviation (1-computational fidelity)) (step S1105). Then, the digital twin control device 103 determines whether the quantum operation has been completed (step S1106). If the quantum operation has not been completed (step S1106: No), the virtual quantum computer 102 increments the program counter and executes the operation of the next stage of the quantum bit group (step S1102).

[0194] On the other hand, if the quantum operation has finished (step S1106: Yes), the digital twin control device 103 determines whether the deviation calculated in step S1105 for each stage of the quantum bit group is equal to or less than the design value (step S1108). The digital twin control device 103 sets a Warning only for the quantum bit group whose deviation is not equal to or less than the design value (step S1108: No), and sets a flag indicating that the validity of the quantum operation result is low (step S1109).

[0195] Then, the digital twin control device 103 sets the control parameters in the real quantum computer 101 and acquires measurement values ​​for the quantum bit groups of each stage from the real quantum computer 101 (step S1110). The digital twin control device 103 calculates the deviation between the estimated value in step S1104 and the measurement value in step S1110 for the quantum bit groups of each stage (step S1111).

[0196] Then, the digital twin control device 103 determines the validity of the calculation result of step S1111 for each group of quantum bits, and stores the determination result (including the warning setting flag of step S1109) in the third memory 434 (step S1112). The validity of the calculation result is a flag indicating validity if the deviation is equal to or less than the design value, and invalidity if the deviation is not equal to or less than the design value. This ends the digital twin operation.

[0197] In Fig. 11, the digital twin operation for one quantum operation was explained. One method is to execute the quantum operation many times repeatedly and obtain the expected value of the solution. If the simulation is slower than the actual operation, it is possible to execute the simulation and evaluate the operation of the actual machine while executing the actual operation multiple times. If the simulation can be executed relatively quickly, it is possible to execute processing in parallel with the quantum operation.

[0198] FIG. 12 is a flowchart showing digital twin operation processing procedure example 2. Digital twin operation processing procedure example 2 is an execution example in which, when a quantum bit state deviates from an ideal value during calculation of one quantum bit group, a correction calculation is performed to improve the calculation accuracy of the quantum bit group. Digital twin operation processing procedure example 2 is operated using the model constructed in FIG. 8 to FIG. 10. Digital twin operation evaluates the quantum bit state using the quantum bit array 413 that is exactly the same as the quantum calculation executed by the actual quantum computer 101. The same processes as in FIG. 11 are assigned the same step numbers, and their explanations are omitted.

[0199] After step S1105, if the deviation is equal to or less than the design value (step S1206: Yes), the digital twin control device 103 determines whether correction is possible (step S1207). Note that whether correction is possible may be considered, for example, in the case of uncomputation, which will be described later. In this case, since it is an "inverse operation" of a "certain operation," it is possible to efficiently compensate for errors that have accumulated during the "certain operation." In this way, correction possibility may be found logically. Furthermore, the areas that can be corrected need to take into account the range of influence of entanglement, and it is desirable to determine this from the quantum circuit.

[0200] If it is determined that correction is possible (step S1207: Yes), the digital twin control device 103 executes a correction calculation (step S1208) and proceeds to step S1210. The digital twin control device 103 executes a correction calculation on the target quantum bit group of the real quantum computer 101.

[0201] This correction operation is premised on the fact that the computational fidelity of the quantum bit can be calculated using the value of the control signal parameter. In other words, it is premised on the fact that, for example, the rotation angle of the spin of the quantum bit 700 can be predicted from the value of the control signal parameter. For example, a rotation operation Rx(Θ) around the x-axis can be restored by changing it to Rx(-Θ).

[0202] If you want Rx(Θ) but it turns out to be Rx(Θ'), ΔΘ=Θ'-Θ (Θ'>Θ) If you rotate it in the opposite direction by ΔΘ=Θ-Θ', it becomes Rx(Θ). If Θ'<Θ, rotate it forward by ΔΘ=Θ-Θ'. This rotation calculation of ΔΘ becomes the correction calculation.

[0203] In this way, it is possible to estimate the state of the quantum bit based only on the value of the control signal parameter, and when it deviates from the design value, it is possible to make corrections to bring it closer to the design value. However, when Ry(Θ'') is applied to this, the rotation axis changes from the x-axis to the y-axis, and it cannot be simply restored.

[0204] It is necessary to reverse the quantum operations in order so that if Rx(Θ) is followed by Ry(Θ''), then Ry(-Θ'') will return to the original state. The correction operation is a -ΔΘ rotation operation when ΔΘ rotation is performed too much. In order to determine how much error occurs in the quantum operations, it is necessary to perform a number of quantum operations and then perform an inverse quantum operation to confirm that the original state is restored. As a means of confirmation, an inverse quantum operation is performed to reverse a certain quantum operation in order, and the deviation from the known original state is observed to grasp the amount of deviation.

[0205] In order to realize the correction operation, it is desirable to have a means for checking the result of the quantum operation and the result of the correction operation during actual operation. For this purpose, it is conceivable to add a dedicated quantum circuit separate from the quantum bit array 413 in order to determine whether or not a correction should be performed based on the value of the control signal parameter during the execution of the quantum operation.

[0206] That is, a quantum circuit B (the above-mentioned dedicated quantum circuit) that is completely independent of quantum circuit A that performs the desired quantum operation is provided at the same time. This quantum circuit B is configured as a quantum circuit for calibration that is smaller in scale than quantum circuit A, and quantum circuit B is a quantum circuit configured with quantum bits that have no interaction whatsoever with the quantum bits of quantum circuit A.

[0207] Quantum circuit A and quantum circuit B are arranged in the same quantum bit array and are controlled by the same control signal parameters. Here, quantum circuit B is operated in parallel with the operation of quantum circuit A, and then the digital twin control device 103 calibrates the control signal parameters by observing the quantum state of the quantum bits of quantum circuit B.

[0208] At this time, quantum circuit B performs the observation by taking advantage of the feature that it does not affect quantum circuit A. Such a quantum circuit may be realized, for example, in the example of uncompute. In this example, the desired quantum operation (operation A) is performed using an ancilla qubit (auxiliary qubit), and then the inverse operation of operation A (operation A) is performed to return this ancilla qubit to its initial state.-1 ) and finally returning it to its original state (identity operation).

[0209] In this way, when starting from an initial state, performing an operation and its inverse operation to finally return to the original initial state, an operation is performed to return the rotation angle to the initial state by adding an error, and the ancilla quantum bit can be observed to check the accuracy of the operation during the quantum operation.

[0210] In general, the results of quantum operations cannot be observed until the operation is completed. However, in this way, such as the uncomputation example shown here, by observing the spin state of an ancilla qubit that is not related to the quantum operation after uncomputation, the accuracy of the operation can be confirmed. This is because the qubits after uncomputation are ideally independent and in their initial state. In other words, it becomes possible to confirm the validity of the values ​​of the control signal parameters even during the quantum operation.

[0211] On the other hand, if it is determined that correction is impossible (step S1207: No), the digital twin control device 103 sets a flag in the correction impossible indicator bit for the target quantum bit group and does not execute the correction calculation (step S1209). Then, the process proceeds to step S1210.

[0212] In step S1210, the virtual quantum computer 102 determines whether the quantum operation has ended (step S1210), and if the quantum operation has not ended (step S1210: No), it increments the program counter (step S1211) and executes the quantum operation of the next target group of quantum bits (step S1102).

[0213] After the quantum operation is completed (step S1210: Yes), the digital twin control device 103 executes steps S1110 to S1112. In step S1112, the flag of step S1209 is also stored. This ends the digital twin operation. In digital twin operation processing procedure example 2, it is possible to know whether the result of executing the quantum operation is that the deviation of the quantum bit state from the ideal state is below the design value, or whether the deviation was greater than the design value but a correction operation was performed so that it is now below the design value, or whether a correction operation was performed followed by a quantum operation, resulting in a state where correction is no longer possible.

[0214] In this way, in this embodiment, a digital twin that simulates the operation of the actual quantum computer 101 becomes possible. The digital twin makes it possible to estimate the state without observing the control results of the quantum bit 700, so improved computational accuracy can be expected. Furthermore, if an appropriate correction computation can be performed based on the estimation result, the computational fidelity of the quantum computation 301 will be improved.

[0215] <Digital Twin Operation Dashboard> Fig. 13 is an explanatory diagram showing an example display of digital twin operation. The display example of Fig. 13 is displayed on the display of the digital twin control device 103 or the host computer 400. (A) shows image data 1300 of the entire quantum bit array 413 (hereinafter, quantum bit array 1300) that is operated by a quantum computer. The dotted rectangle 1301 filled with dots is the target quantum bit group (hereinafter, target quantum bit group 1301), and the dotted rectangle 1302 not filled with dots is the asymmetric quantum bit group (hereinafter, asymmetric quantum bit group 1302).

[0216] Simulating the entire quantum bit array 1300 may exceed the hardware limits of the virtual quantum computer 102 used for simulation and evaluation, or may significantly exceed the quantum operation time in terms of calculation time. Therefore, it is desirable to operate the digital twin on only a part of the entire quantum bit array 1300.

[0217] (B) shows a group of target quantum bits 1301 extracted from quantum bit array 1300. (B) shows an operation of taking the absolute value of the value of quantum bit 700 indicated as "a" and adding it to quantum bit 700 indicated as "b", which is expressed by the following equation (8).

[0218] b = b + Abs(a) … (8)

[0219] As is well known, the absolute value operation Abs(a) removes the sign information originally contained in the variable a (the negative sign is removed to make it positive). Therefore, the absolute value operation Abs(a) is not a reversible operation and cannot be realized on a quantum computer as is. As a countermeasure, by adding one quantum bit 700 (ancilla quantum bit, auxiliary quantum bit) and giving this ancilla quantum bit negative sign information, the absolute value operation Abs(a) can be made a reversible operation.

[0220] After that, the variable a needs to be returned to its original value and must be uncomputed. Uncomputing the absolute value operation Abs(a) is the inverse operation of the absolute value operation Abs(a). This operation allows the information of the variable a that was moved to the ancilla to be returned to the variable a, and the subsequent quantum operation can continue. Here, when using this ancilla quantum bit for the next quantum operation, the entanglement with other quantum bits 700 must be stopped and it must be in the initial state (for example, |0> state).

[0221] In this type of calculation, a "certain operation" and its "inverse operation" are combined, so any calculation error that occurs when performing the "certain operation" can be corrected during the inverse operation. If the calculation error during the "certain operation" can be estimated using a digital twin, an appropriate correction operation can be applied during the "inverse operation," making it possible to correct the state of the target quantum bit to a state close to the state before the operation.

[0222] By operating a digital twin, it is possible to estimate and display the spin state of the target quantum bit 700, which has the effect of making it easier to understand the state. For example, (C) is an example display showing the spin state in an ideal state (Ideal) and the actual control result (Actual). This display is called a circular display, and the probability amplitude and spin direction are displayed within the circle. By estimating the quantum bit state in this way, it is possible to evaluate the computational fidelity (Fidelity) of the quantum operation 301, and if the computational fidelity falls below expectations, an appropriate correction operation is performed to prevent the decrease in computational fidelity. (D) is a bar graph showing the probability amplitude during the computation, and the actual computation status can be understood.

[0223] As described above, according to this embodiment, it is possible to obtain highly accurate quantum computation results quickly and efficiently while using the low computation fidelity quantum bit 700. In addition, when assuming the operation of a NISQ type computer, there are effects of obtaining high accuracy of computation results by computation with a quantum logic step number according to the computation fidelity that can be realized even in a noisy environment, and shortening the computation time by performing multiple computations at once.

[0224] In particular, in the case of a method in which multiple quantum operation blocks are used simultaneously to perform operations, voltage control for potential control between quantum bits 700 and high frequency application can be standardized for spin control, which has the effect of miniaturizing the control circuit and improving the efficiency of the control sequence.

[0225] According to this embodiment, by increasing the number of quantum bits of the quantum computer, it is possible to realize quantum acceleration of the computing performance of the quantum computer, which can be applied to fields such as drug discovery, chemical material development, and finance.

[0226] The present invention is not limited to the above-described embodiments, and includes various modified examples and equivalent configurations within the spirit of the appended claims. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those having all of the configurations described. Also, a part of the configuration of one embodiment may be replaced with a configuration of another embodiment. Also, a configuration of another embodiment may be added to a configuration of one embodiment. Also, a part of the configuration of each embodiment may be added, deleted, or replaced with another configuration.

[0227] Furthermore, each of the aforementioned configurations, functions, processing units, processing means, etc. may be realized in hardware, for example by designing some or all of them as an integrated circuit, or may be realized in software by a processor interpreting and executing a program that realizes each function.

[0228] Information such as programs, tables, files, etc. that realize each function can be stored in a storage device such as a memory, a hard disk, or an SSD (Solid State Drive), or in a recording medium such as an IC (Integrated Circuit) card, an SD card, or a DVD (Digital Versatile Disc).

[0229] In addition, the control lines and information lines shown are those considered necessary for the explanation, and do not necessarily show all the control lines and information lines necessary for implementation. In reality, it can be considered that almost all components are connected to each other. [Explanation of symbols]

[0230] 100 Quantum Computer System 101 Actual Quantum Computer 102 Virtual Quantum Computer 103 Digital Twin Control Device 400 Classical Computers 411 1st sequencer 413 Qubit Array 421 Quantum Bit Simulation Execution Department 422 Evaluation Department 423 Quantum Logic Simulation Department 424 Calculation Fidelity Integration Unit 425 Second Sequencer 431 First Comparison Section 432 Second Comparison Section 433 Correction amount calculation unit 435 Feedback control section 700 qubits 701 qubit subarray

Claims

1. A real quantum computer that performs quantum operations using a group of quantum bits; A virtual quantum computer that simulates the operation of the real quantum computer based on predetermined parameters; A control device that controls the real quantum computer and the virtual quantum computer, the virtual quantum computer has an estimation unit that simulates an operation of the real quantum computer to estimate a state of a quantum bit of interest in the group of quantum bits; The control device and the virtual quantum computer have a feedback control unit that changes the parameters for each of the quantum bits of interest in parallel with the operation of the real quantum computer until a first deviation between an estimated state of the quantum bit of interest by the estimation unit and an ideal state becomes equal to or less than a first design value, and transmits the changed parameters to the virtual quantum computer until a second deviation between an estimated state of the quantum bit of interest based on the changed parameters when the first deviation becomes equal to or less than the first design value and a quantum operation result from the real quantum computer becomes equal to or less than a second design value. A quantum computer system comprising:

2. A quantum computer system as claimed in claim 1, The virtual quantum computer has a calculation unit that calculates a computation fidelity regarding the estimated state of the quantum bit of interest by the estimation unit, the feedback control unit changes the parameters until a first deviation, which is a deviation amount of the computation fidelity from the ideal state calculated by the calculation unit for each of the quantum bits of interest, becomes equal to or less than a first design value, and transmits the changed parameters to the virtual quantum computer until a second deviation between an estimated state of the quantum bit of interest based on the changed parameters when the first deviation becomes equal to or less than the first design value and a quantum computation result from the real quantum computer becomes equal to or less than a second design value. A quantum computer system comprising:

3. The quantum computer system of claim 1, the estimation unit constructs a quantum bit control model that estimates the state of the quantum bit of interest, simulates operation of the actual quantum computer by inputting the parameters into the quantum bit control model to estimate the state of the quantum bit of interest in the group of quantum bits, reconstructs the quantum bit control model until the second deviation becomes equal to or less than the second design value, and simulates operation of the actual quantum computer by inputting the parameters into the reconstructed quantum bit control model to estimate the state of the quantum bit of interest. A quantum computer system comprising:

4. A quantum computer system as claimed in claim 3, The real quantum computer is a quantum bit control unit that transmits the parameter that controls the quantum bit of interest to the group of quantum bits as a control signal; a first detector that detects the value of the parameter from the control signal at a position between the quantum bit control unit and the quantum bit group and closer to the quantum bit control unit than to the quantum bit group; a second detection unit that detects the value of the parameter from the control signal at a position between the quantum bit control unit and the quantum bit group and closer to the quantum bit group than the quantum bit control unit; The control device includes: a comparison unit that compares a first detection result by the first detection unit with a second detection result by the second detection unit; a correction amount calculation unit that calculates a correction amount of the parameter based on a comparison result by the comparison unit, The feedback control unit transmits the corrected parameters corrected by the correction amount calculated by the correction amount calculation unit to the virtual quantum computer; the estimation unit inputs the corrected parameters into the quantum bit control model to simulate an operation of the actual quantum computer and estimate a state of a quantum bit of interest in the group of quantum bits; A quantum computer system comprising:

5. A quantum computer system as claimed in claim 4, The real quantum computer is a third detection unit that detects a change in the surrounding environment of the quantum bit group at a position between the quantum bit control unit and the quantum bit group closer to the quantum bit group than the quantum bit control unit; the correction amount calculation unit calculates a correction amount of the parameter based on the comparison result and a third detection result by the third detection unit. A quantum computer system comprising:

6. A quantum computer system according to any one of claims 1 to 5, A quantum computer system comprising a plurality of the real quantum computers and a plurality of the virtual quantum computers.

7. The quantum computer system of claim 1, The estimation unit estimates the state of the quantum bit of interest by simulating an operation of the quantum bit of interest using a quantum bit control model that controls the quantum bit of interest. A quantum computer system comprising:

8. The quantum computer system of claim 1, The quantum computer system according to claim 1, wherein the estimation unit estimates the state of the quantum bit of interest by simulating the operation of the quantum bit of interest using a learning model that indicates a correlation between the quantum bit of interest and the parameters.

9. A method for operating a quantum computer system having a real quantum computer that performs quantum operations using a group of quantum bits, a virtual quantum computer that simulates the operation of the real quantum computer based on predetermined parameters, and a control device that controls the real quantum computer and the virtual quantum computer, comprising: The virtual quantum computer simulates the operation of the real quantum computer to estimate a state of a quantum bit of interest in the group of quantum bits; the control device and the virtual quantum computer change the parameters for each of the quantum bits of interest in parallel with the operation of the real quantum computer until a first deviation between the estimated state of the quantum bit of interest and an ideal state becomes equal to or less than a first design value, and transmit the changed parameters to the virtual quantum computer until a second deviation between the estimated state of the quantum bit of interest based on the changed parameters when the first deviation becomes equal to or less than the first design value and a quantum operation result from the real quantum computer becomes equal to or less than a second design value; A method for operating a quantum computer system comprising:

Images