Quantum Information Processing Method, Apparatus, Electronic Device, and Readable Storage Medium

Abstract

An embodiment of the present invention provides a quantum information processing method, apparatus, electronic device, and readable storage medium. The quantum information processing method is applied to a quantum computer, and the method includes: for any qubit of the quantum computer, determining the bit flip probability of the qubit according to a preset quantum flip prediction model; and in the case where the bit flip probability is greater than a preset probability threshold, correcting the bit value of the qubit to obtain the correct bit value of the corrected qubit, where the correct bit value is the bit value of the qubit before the bit flip occurs. In this way, the correct bit value of the qubit before the bit flip occurs can be conveniently obtained, thereby improving the accuracy of the bit value of the qubit of the quantum computer.

Description

Technical Field

[0001] The present invention belongs to the field of quantum computing, and particularly relates to a quantum information processing method, apparatus, electronic device, and readable storage medium. Background Art

[0002] Quantum computers have powerful quantum information processing capabilities, and are characterized by fast operating speeds, strong information processing capabilities, and wide application ranges. They are rapidly developing and being applied in fields such as communication, finance, medicine, and meteorology.

[0003] In single-bit compressive sensing technology, the sampled values of a signal are quantized to a single bit, that is, only one binary bit is used to represent the sign information of the sampled value, and then the signal is reconstructed according to the sign information to obtain a reconstructed signal that is in the same direction as the original signal.

[0004] When single-bit compressive sensing technology is applied to signal sampling in a quantum computer, the qubit of the quantum computer undergoes a state flip due to electronic interference or magnetic field failure, that is, the bit value of the qubit is incorrect, resulting in errors in the single-bit compressive sensing technology based on the qubit and causing a low accuracy rate of the signal sampling result. Summary of the Invention

[0005] The present invention provides a quantum information processing method, apparatus, electronic device, and readable storage medium to solve the problem that the bit value of the qubit of a quantum computer is incorrect due to the state flip of the qubit.

[0006] To solve the above technical problems, the present invention is implemented as follows:

[0007] In a first aspect, the present invention provides a quantum information processing method applied to a quantum computer, and the method includes:

[0008] For any qubit of the quantum computer, determine the bit flip probability of the qubit according to a preset quantum flip prediction model;

[0009] In the case where the bit flip probability is greater than a preset probability threshold, correct the bit value of the qubit to obtain the correct bit value of the corrected qubit, where the correct bit value is the bit value of the qubit before the bit flip occurs.

[0010] Optionally, the step of for any qubit of the quantum computer, determining the bit flip probability of the qubit according to a preset quantum flip prediction model includes:

[0011] For any qubit of the quantum computer, obtain the bit flip probability of the qubit at the previous moment and the current state transition probability;

[0012] Determine the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the current state transition probability.

[0013] Optionally, the state transition probability includes a first state transition probability and a second state transition probability; before determining the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the current state transition probability, the method further includes:

[0014] Generate a state transition probability matrix of the qubit according to the first state transition probability and the second state transition probability, where the first state transition probability is the probability that the qubit undergoes a state flip and the bit value changes from 0 to 1, and the second state transition probability is the probability that the qubit undergoes a state flip and the bit value changes from 1 to 0;

[0015] Determining the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the current state transition probability includes:

[0016] Determine the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the state transition probability matrix.

[0017] Optionally, the quantum flip prediction model is obtained by the following method:

[0018] For any qubit, obtain the historical bit flip probability and the state transition probability at the latest moment of the qubit;

[0019] Perform model training according to the historical bit flip probability and the state transition probability at the latest moment to obtain the quantum flip prediction model.

[0020] Optionally, before determining the bit flip probability of any qubit of the quantum computer according to a preset quantum flip prediction model, the method further includes:

[0021] Quantize the sampling signal obtained by the quantum computer according to a preset quantization matrix to obtain a first signal quantization value;

[0022] Perform signal reconstruction according to the first signal quantization value according to a preset signal reconstruction model to obtain a signal sampling value;

[0023] Store the signal sampling value in the qubit of the quantum computer.

[0024] Optionally, after correcting the bit value of the qubit when the bit flip probability is greater than a preset probability threshold and obtaining the correct bit value of the corrected qubit, the method further includes:

[0025] According to a preset bit compressive sensing model, perform single-bit quantization on the signal sampling values stored in the quantum computer to obtain second signal quantization values, where the signal sampling values include the correct bit values of the corrected qubits and the bit values of the qubits that have not undergone bit flips;

[0026] Store the second signal quantization values in a specified area of the quantum computer.

[0027] Optionally, the performing single-bit quantization on the signal sampling values stored in the quantum computer according to a preset bit compressive sensing model to obtain second signal quantization values includes:

[0028] Quantize the signal sampling values stored in the quantum computer according to a preset quantization matrix to obtain third signal quantization values;

[0029] Determine the sign information of the third signal quantization value according to the third signal quantization value and a preset signal threshold;

[0030] Convert the sign information into the bit values of the qubits of the quantum computer, and obtain second signal quantization values according to the bit values of the qubits of the quantum computer.

[0031] In a second aspect, the present invention provides a quantum information processing device applied to a quantum computer, and the device includes:

[0032] A determination module, configured to determine the bit flip probability of any qubit of the quantum computer according to a preset quantum flip prediction model;

[0033] An error correction module, configured to correct the bit value of the qubit when the bit flip probability is greater than a preset probability threshold to obtain the correct bit value of the corrected qubit, where the correct bit value is the bit value of the qubit before the bit flip occurs.

[0034] In a third aspect, the present invention provides an electronic device, including: a processor, a memory, and a computer program stored on the memory and executable on the processor, and the processor implements the above-mentioned quantum information processing method when executing the program.

[0035] In a fourth aspect, the present invention provides a readable storage medium, and when the instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the above-mentioned quantum information processing method.

[0036] In an embodiment of the present invention, for any qubit of a quantum computer, the bit flip probability obtained by a preset quantum flip prediction model can predict whether the qubit will undergo a state flip. When the bit flip probability of any qubit is greater than a preset probability threshold, it indicates that the qubit has undergone a state flip. By correcting the bit value of the qubit, the correct bit value before the bit flip of the qubit can be obtained. In this way, the accuracy of the bit value of the qubit of the quantum computer can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other accompanying drawings can be obtained based on these drawings without creative efforts.

[0038] Figure 1 is one of the step flowcharts of a quantum information processing method provided by an embodiment of the present invention;

[0039] Figure 2 is another step flowchart of a quantum information processing method provided by an embodiment of the present invention;

[0040] Figure 3 is yet another step flowchart of a quantum information processing method provided by an embodiment of the present invention;

[0041] Figure 4 is the structural diagram of a quantum information processing device provided by an embodiment of the present invention;

[0042] Figure 5 is the structural diagram of an electronic device provided by an embodiment of the present invention;

[0043] Figure 6 is the hardware structure schematic diagram of another electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the scope of protection of the present invention.

[0045] It should be noted that a quantum computer is a machine that can perform quantum computing, realizing mathematical and logical operations, processing, and storing information through the laws of quantum mechanics. A quantum computer uses quantum states as memory units and information storage forms, and quantum communication and quantum computing based on quantum dynamics evolution as the basis for information transfer and processing. In a quantum computer, the sizes of various components of the hardware reach the atomic or molecular scale. In addition, a quantum computer is a physical system that can store and process information represented by quantum bits. A quantum bit is the unit of quantum information in quantum computing. Similar to a classical bit, a quantum bit only adds the quantum characteristics of physical atoms. Quantum bits represent state memory and entangled states in a quantum computer. Physically, a quantum bit is a quantum state.

[0046] It should be noted that with the rapid development of modern information technology, the amount of information is gradually increasing, and the amount of data to be processed is also continuously increasing. Signal processing mainly compresses signals and processes the compressed signals. Compressed sensing technology is a signal sampling technology that can sample at a rate far lower than the Nyquist sampling rate when the signal satisfies sparsity. Compressed sensing technology can combine compression and sampling and then recover the original signal through a reconstruction algorithm. Single-bit compressed sensing technology is a branch of compressed sensing technology. Single-bit compressed sensing technology performs extreme quantization on the sampling values, quantizing the sampling values of the signal to a single bit, that is, using only one binary bit to represent the sign information of the sampling value, and then recovering the original signal according to the single-bit reconstruction algorithm based on the sign information.

[0047] Figure 1 It is a flowchart of the steps of a quantum information processing method provided by an embodiment of the present invention. As Figure 1 shown, the method may include:

[0048] Step 101, for any quantum bit of the quantum computer, determine the bit flip probability of the quantum bit according to a preset quantum flip prediction model.

[0049] In an embodiment of the present invention, a quantum bit is a unit used to represent information in a quantum computer. After a period of time, due to electron interference or magnetic field failure, the state of the quantum bit may flip, causing an error in the bit value of the quantum bit.

[0050] In the embodiments of the present invention, data can be flipped in advance according to the historical states of the qubits of a quantum computer, and a quantum flip prediction model capable of predicting the qubit flip probability can be trained through machine learning. For example, the bit values of all qubits of the quantum computer at any moment can be obtained. After waiting for a period of time, the bit values of all qubits of the quantum computer are obtained again. The bit values obtained twice are used as model training data, and the model is trained according to the training data. The output of the model is a prediction model of the qubit flip probability. When the model parameters of the prediction model meet the requirements, a quantum flip prediction model is obtained. This is only an example, and the embodiments of the present invention do not limit this.

[0051] In the embodiments of the present invention, the qubit flip probability is used to characterize the probability of a qubit's state flip. For any qubit of the quantum computer, the state flip probability of the qubit can be predicted according to a preset quantum flip prediction model, and the probability value output by the quantum flip prediction model is obtained, and the output probability value is used as the qubit flip probability of the qubit.

[0052] Optionally, step 101 may include:

[0053] For any qubit of the quantum computer, obtain the qubit flip probability at the previous moment and the current state transition probability of the qubit; determine the qubit flip probability at the next moment according to the qubit flip probability at the previous moment and the current state transition probability.

[0054] In the embodiments of the present invention, the qubit flip probability at the previous moment of the qubit is used to characterize the historical qubit flip probability of the qubit. Among them, the qubit flip probability at the previous moment can be the qubit flip probability of the qubit obtained most recently, or the average value of multiple obtained qubit flip probabilities. The embodiments of the present invention do not limit this. The current state transition probability characterizes the transition probability of the qubit's current state flip.

[0055] In the embodiments of the present invention, the qubit flip probability at the next moment of the qubit can be calculated according to the qubit flip probability at the previous moment and the current state transition probability. See the following formula:

[0056] X(k + 1) = X(k) × P(1)

[0057] Wherein, X(k) represents the qubit flip probability of the qubit at t = k, P represents the current state transition probability, and X(k + 1) represents the qubit flip probability of the qubit at t = k + 1.

[0058] In an embodiment of the present invention, for any qubit of a quantum computer, the bit flip probability at the next moment obtained according to the bit flip probability at the previous moment and the current state transition probability can be used to predict whether the qubit will flip its state at the next moment.

[0059] Optionally, the state transition probability includes a first state transition probability and a second state transition probability; before determining the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the current state transition probability, the method further includes:

[0060] Generating a state transition probability matrix of the qubit according to the first state transition probability and the second state transition probability, where the first state transition probability is the probability that the qubit flips its state and the bit value changes from 0 to 1, and the second state transition probability is the probability that the qubit flips its state and the bit value changes from 1 to 0.

[0061] In an embodiment of the present invention, the state transition probability matrix may include a first state transition probability and a second state transition probability. For example, the first state transition probability is 0.4 and the second state transition probability is 0.3. The state transition probability matrix of the qubit generated according to the first state transition probability and the second state transition probability is shown in the following formula:

[0062]

[0063] Wherein, the sum of the elements in each row of the state transition probability matrix is equal to 1.

[0064] It should be noted that whether the qubit flips its state at the next moment is determined by whether there is electronic interference or magnetic field failure in the quantum computer. Therefore, the bit flip probability of the qubit at the next moment is related to whether there is electronic interference or magnetic field failure in the quantum computer, and has nothing to do with the bit flip probability of the qubit at the previous moment. The characteristic that the conditional distribution of the state of a process or system at t>t0 is independent of the state of the process before t0 under the condition that the state of the process or system at t0 is known is called Markov property, and this process is a Markov process. The bit flip probability in the embodiment of the present invention is a discrete quantity. Therefore, the transition probability matrix in a discrete Markov process, that is, a Markov chain, can be used for probability calculation.

[0065] Optionally, determining the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the current state transition probability includes:

[0066] Determine the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the state transition probability matrix.

[0067] In the embodiments of the present invention, the bit flip probability of the qubit at the next moment can be calculated according to the bit flip probability at the previous moment and the state transition probability matrix. See the following formula:

[0068]

[0069] where, P 01 represents the first state transition probability, and P 10 represents the second state transition probability. For example, if the bit flip probability at the previous moment is 0.3, correspondingly, the probability of no bit flip at the previous moment is 0.7, obtaining the vector [0.3 0.7]. According to formula (2), the bit flip probability of the qubit at the next moment can be calculated:

[0070]

[0071] where, the bit flip probability of the qubit at the next moment is 0.39.

[0072] In the embodiments of the present invention, since the state transition probability matrix of the qubit is generated according to the first state transition probability and the second state transition probability, including the cases where the state of the qubit flips, causing the bit value of the qubit to change from 0 to 1 or from 1 to 0, in this way, the bit flip probability at the next moment can be made more accurate.

[0073] Optionally, as Figure 2 shown, before step 101, the method further includes:

[0074] Step 103, quantize the sampling signal obtained by the quantum computer according to a preset quantization matrix to obtain a first signal quantization value.

[0075] In the embodiments of the present invention, the quantization matrix can be an n×m matrix, and each element in the matrix is independently and identically distributed according to a specific distribution. For example, the specific distribution includes a standard normal distribution, a Bernoulli ±1 distribution, etc.

[0076] In the embodiments of the present invention, the sampling signal obtained by the quantum computer can be quantized according to a preset quantization matrix, and the quantization value obtained in the quantization process is used as the first signal quantization value. The quantization process is shown in the following formula:

[0077] y = Q B (Φx) = Φx + n (3)

[0078] where, Q B : R→τ, |τ| = 2B , Q B represents quantizing x into a B-bit binary number. Where, ||n||2 = (∑ i |n i | 2 ) 1 / 2 ≤ ε, n represents the noise value of the noise introduced in the quantization process, ε represents the quantization accuracy. For example, ε can be the quantization interval of a linear quantizer. In the formula, x represents the sampled signal, y represents the quantization value, and Φ represents the quantization matrix.

[0079] Step 104, according to the preset signal reconstruction model, perform signal reconstruction based on the first signal quantization value to obtain the signal sampled value.

[0080] In the embodiment of the present invention, the signal reconstruction model can be a reconstruction model for limited noise. See the following formula:

[0081]

[0082] Where, represents the obtained reconstructed signal, y represents the signal quantization value. The meaning of the formula is to calculate the minimum value of the 1-norm of x under the condition of ||y - Φx||2 ≤ ε. The reconstruction

[0083] error of the signal reconstruction model satisfies Where, C is a constant and is only related to the quantization matrix Φ, and has nothing to do with the sampled signal x.

[0084] It can be understood that when solving a linear programming problem with a constraint condition of "≤" or "≥" type, a non-negative new variable can be added or subtracted on the left side of the inequality to be converted into an equation. This newly added non-negative variable is called a slack variable. In the embodiment of the present invention, when finding the optimal solution of, a slack variable λ can be introduced. See the following formula:

[0085]

[0086] Where, represents the obtained reconstructed signal, y represents the signal quantization value,, represents the square of the 2-norm of (y - Φx).

[0087] In the embodiment of the present invention, the first signal quantization value can be input into the preset signal reconstruction model to obtain the reconstructed signal output by the signal reconstruction model. The reconstructed signal obtained after the sampled signal is quantized and reconstructed is a discrete signal. Further, the amplitude value of the reconstructed signal can be used as the signal sampled value.

[0088] Step 105, store the signal sampled value through the quantum bits of the quantum computer.

[0089] In an embodiment of the present invention, the signal sampling value can be converted into a binary format to obtain the binary data corresponding to the signal sampling value, and the binary data can be stored in the qubits of the quantum computer, so as to realize storing the signal sampling value in the qubits of the quantum computer.

[0090] In an embodiment of the present invention, quantifying the sampling signal obtained by the quantum computer through a quantization matrix can filter out abnormal information in the sampling signal, and signal reconstruction can be performed according to a preset signal reconstruction model and the first signal quantization value, so as to obtain a more accurate signal sampling value.

[0091] Step 102, when the bit flip probability is greater than a preset probability threshold, correct the bit value of the qubit to obtain the correct bit value of the corrected qubit, where the correct bit value is the bit value of the qubit before the bit flip occurs.

[0092] In an embodiment of the present invention, the bit flip probability can be compared with the preset probability threshold, and it can be judged whether the qubit has undergone a state flip according to the comparison result. Among them, the preset probability threshold is used to represent the upper limit of the probability of the qubit undergoing a state flip. That the bit flip probability is greater than the preset probability threshold can indicate that the probability of the qubit undergoing a state flip is relatively large, and it can be determined that the qubit has undergone a state flip, that is, the bit value of the qubit is incorrect. That the bit flip probability is less than or equal to the preset probability threshold can indicate that the probability of the qubit undergoing a state flip is relatively small, and it can be determined that the qubit has not undergone a state flip.

[0093] In an embodiment of the present invention, when the bit flip probability is greater than the preset probability threshold, the bit value of the qubit is incorrect, and the bit value of the qubit can be corrected according to the current bit value of the qubit to obtain the correct bit value of the corrected qubit. For example, when the bit value of the qubit is incorrect, if the current bit value of the qubit is 1, 1 can be corrected to 0, and 0 is the bit value of the qubit before the bit flip occurs. The correct bit value of the corrected qubit is obtained, and the correct bit value is 0. This is only an example here, and the embodiments of the present invention are not limited thereto.

[0094] Optionally, as Figure 3 shown, after step 102, the method further includes:

[0095] Step 106, according to a preset single-bit compressive sensing model, perform single-bit quantization on the signal sampling value stored in the quantum computer to obtain a second signal quantization value, where the signal sampling value includes the correct bit value of the corrected qubit and the bit values of the qubits that have not undergone bit flips.

[0096] In an embodiment of the present invention, signal sampling values can be stored by qubits in a quantum computer. Correspondingly, the signal sampling values include the bit values of one or more qubits in the quantum computer that have not undergone bit flips, and the correct bit values of one or more error-corrected qubits.

[0097] In an embodiment of the present invention, the signal sampling values can be subjected to single-bit quantization through a preset quantization matrix to obtain second signal quantization values. The single-bit quantization process is shown in the following formula:

[0098] y = A(x) := sign(Φx) (6)

[0099] where sign is the sign function, A represents the mapping from x to the Boolean cube B M := {-1, 1} M M represents the number of observation values, for example, the number of bit values of qubits. In the formula, x represents the sampling signal value, y represents the second signal quantization value, and Φ represents the quantization matrix. The meaning of the formula is that y is defined as taking the sign information of the product Φx of the quantization matrix and the signal sampling value. Specifically, y can be represented by 1 for positive and -1 for negative.

[0100] Step 107, store the second signal quantization value in a specified area of the quantum computer.

[0101] In an embodiment of the present invention, the second signal quantization value can be converted into a binary format to obtain binary data corresponding to the second signal quantization value, and the binary data can be stored by qubits in a specified area of the quantum computer, thereby realizing storing the second signal quantization value in the specified area of the quantum computer.

[0102] In an embodiment of the present invention, by performing single-bit quantization on the signal sampling values stored in the quantum computer according to a preset bit compressive sensing model, second signal quantization values are obtained, and the second signal quantization values are stored in a specified area of the quantum computer. Since the signal sampling values include the correct bit values of error-corrected qubits and the bit values of qubits that have not undergone bit flips, in this way, the error of the second signal quantization value caused by incorrect bit values of qubits can be reduced, making the second signal quantization values obtained by single-bit quantization according to the qubits of the quantum computer more accurate.

[0103] Optionally, performing single-bit quantization on the signal sampling values stored in the quantum computer according to a preset bit compressive sensing model to obtain second signal quantization values includes:

[0104] Quantize the signal sampling values stored in the quantum computer according to a preset quantization matrix to obtain third signal quantization values; determine the sign information of the third signal quantization values according to the third signal quantization values and a preset signal threshold; convert the sign information into bit values of qubits of the quantum computer to obtain second signal quantization values.

[0105] In an embodiment of the present invention, the quantization matrix may be an n×m matrix, and each element in the matrix is independently and identically distributed according to a specific distribution. For example, the specific distribution includes a standard normal distribution, a Bernoulli ±1 distribution, etc. The quantization process of quantizing the signal sampling values stored in the quantum computer according to the preset quantization matrix can be seen in the following formula:

[0106] y′=Φx′(7)

[0107] where x′ represents the signal sampling value, y′ represents the third signal quantization value, and Φ represents the quantization matrix.

[0108] In an embodiment of the present invention, the preset signal threshold may be 0. By comparing the third signal quantization value with the preset signal threshold, the positive or negative of the amplitude value of the third signal quantization value can be determined. Further, 1 and -1 can be used to represent positive and negative, and 1 or -1 is used as the sign information of the third signal quantization value. Among them, if the third signal quantization value is greater than the preset signal threshold, it means that the amplitude value of the third signal quantization value is positive, and the sign of the third signal quantization value is recorded as 1. If the third signal quantization value is less than the preset signal threshold, it means that the amplitude value of the third signal quantization value is negative, and the sign of the third signal quantization value is recorded as -1. 1 or -1 is the sign information of the third signal quantization value.

[0109] In an embodiment of the present invention, the sign information can be converted into a binary format to obtain the binary data corresponding to the second signal quantization value, and the binary data can be stored by the qubits of the quantum computer, so as to realize the conversion of the sign information into the bit values of the qubits of the quantum computer. Further, the bit values of the qubits can be used as the second signal quantization values. For example, it can be represented that the sign in the sign information is positive by the bit value of the qubit being 1, and the sign in the sign information is negative by the bit value of the qubit being 0.

[0110] In an embodiment of the present invention, by quantizing the signal sampling values according to the preset quantization matrix, the signal sampling values can be quantized to represent the sign information corresponding to the signal sampling values only by the bit values of one qubit, realizing single-bit quantization of the signal sampling values.

[0111] In an embodiment of the present invention, for any qubit of a quantum computer, the bit flip probability obtained by a preset quantum flip prediction model can predict whether the qubit will undergo a state flip. When the bit flip probability of any qubit is greater than a preset probability threshold, it indicates that the qubit has undergone a state flip. By correcting the bit value of the qubit, the correct bit value before the bit flip of the qubit can be obtained. In this way, the accuracy of the bit value of the qubit of the quantum computer can be improved.

[0112] Optionally, the quantum flip prediction model is obtained by the following method:

[0113] For any qubit, obtain the historical bit flip probability of the qubit and the state transition probability at the latest moment; perform model training according to the historical bit flip probability and the state transition probability at the latest moment to obtain the quantum flip prediction model.

[0114] In an embodiment of the present invention, the historical bit flip probability of a qubit can be the average value of multiple obtained bit flip probabilities, and the state transition probability of the qubit at the latest moment can be the current state transition probability. When performing model training, the historical bit flip probability of the qubit and the state transition probability at the latest moment can be used as the input of the model to be trained, obtain the bit flip probability predicted by the model to be trained for the qubit, and calculate the loss value of the model to be trained according to the bit flip probability predicted by the model and the bit flip probability of the most recent time in the historical bit flip probability. If the loss value does not meet the preset requirements, adjust the model parameters of the model to be trained. After parameter adjustment, train the model to be trained again until the loss value meets the preset requirements. It can be considered that the model parameters of the model to be trained have been adjusted to the optimal state, and the model training is completed. The trained model is used as the quantum flip prediction model.

[0115] In an embodiment of the present invention, since the model training is based on the historical bit flip probability of the qubit and the state transition probability at the latest moment, the prediction result output by the trained quantum flip prediction model can be made more accurate.

[0116] Figure 4 FIG. 16 is a structural diagram of a quantum information processing device provided by an embodiment of the present invention. The device 20 is applied to a quantum computer. The device 20 may include:

[0117] A determination module 201, configured to determine the bit flip probability of any qubit of the quantum computer according to a preset quantum flip prediction model;

[0118] An error correction module 202, configured to correct the bit value of the quantum bit when the bit flip probability is greater than a preset probability threshold, and obtain the correct bit value of the corrected quantum bit, where the correct bit value is the bit value of the quantum bit before the bit flip occurs.

[0119] Optionally, the determination module 201 is specifically configured to:

[0120] For any quantum bit of the quantum computer, obtain the bit flip probability and the current state transition probability of the quantum bit at the previous moment;

[0121] Determine the bit flip probability of the quantum bit at the next moment according to the bit flip probability at the previous moment and the current state transition probability.

[0122] Optionally, the state transition probability includes a first state transition probability and a second state transition probability, and the apparatus 50 further includes:

[0123] A generation module, configured to generate a state transition probability matrix of the quantum bit according to the first state transition probability and the second state transition probability before the determination module 201 determines the bit flip probability of the quantum bit at the next moment according to the bit flip probability at the previous moment and the current state transition probability, where the first state transition probability is the probability that the quantum bit undergoes a state flip and the bit value changes from 0 to 1, and the second state transition probability is the probability that the quantum bit undergoes a state flip and the bit value changes from 1 to 0;

[0124] Optionally, the determination module 201 is further specifically configured to:

[0125] Determine the bit flip probability of the quantum bit at the next moment according to the bit flip probability at the previous moment and the state transition probability matrix.

[0126] Optionally, the quantum flip prediction model is obtained by the following method:

[0127] For any quantum bit, obtain the historical bit flip probability and the state transition probability at the latest moment of the quantum bit;

[0128] Perform model training according to the historical bit flip probability and the state transition probability at the latest moment to obtain the quantum flip prediction model.

[0129] Optionally, the apparatus 20 further includes:

[0130] A quantization module, configured to, before the determination module 201 determines the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the current state transition probability, quantize the sampling signal obtained by the quantum computer according to a preset quantization matrix to obtain a first signal quantization value;

[0131] A reconstruction module, configured to reconstruct a signal according to a preset signal reconstruction model based on the first signal quantization value to obtain a signal sampling value;

[0132] A storage module, configured to store the signal sampling value through the qubits of the quantum computer.

[0133] Optionally, the apparatus 20 further includes:

[0134] A single-bit quantization module, configured to, when the bit flip probability is greater than a preset probability threshold in the error correction module 202 and after obtaining the correct bit value of the qubit after error correction, perform single-bit quantization on the signal sampling value stored in the quantum computer according to a preset bit compressive sensing model to obtain a second signal quantization value, where the signal sampling value includes the correct bit value of the qubit after error correction and the bit values of the qubits that have not undergone bit flips;

[0135] The storage module is further configured to store the second signal quantization value in a specified area of the quantum computer.

[0136] Optionally, the single-bit quantization module is specifically configured to:

[0137] Quantize the signal sampling value stored in the quantum computer according to a preset quantization matrix to obtain a third signal quantization value;

[0138] Determine the sign information of the third signal quantization value according to the third signal quantization value and a preset signal threshold;

[0139] Convert the sign information into the bit value of the qubit of the quantum computer, and obtain a second signal quantization value according to the bit value of the qubit of the quantum computer.

[0140] The quantum information processing apparatus has the same advantages as the above-mentioned quantum information processing method over the prior art, and will not be elaborated here.

[0141] For the apparatus embodiment, since it is basically similar to the method embodiment, the description is relatively simple. For related parts, please refer to the partial description of the method embodiment.

[0142] The present invention further provides an electronic device 30. Refer to Figure 5, including: a processor 301, a memory 302, and a computer program stored on the memory 302 and executable on the processor 301. When the processor 301 executes the program, the quantum information processing method of the foregoing embodiment is implemented.

[0143] Figure 6 It is a schematic diagram of the hardware structure of another electronic device according to an embodiment of the present application.

[0144] The electronic device 40 includes but is not limited to: a radio frequency unit 401, a network module 402, an audio output unit 403, an input unit 404, a sensor 405, a display unit 406, a user input unit 407, an interface unit 408, a memory 409, and a processor 410 and other components.

[0145] Those skilled in the art can understand that the electronic device 40 may further include a power source (such as a battery) for supplying power to each component. The power source can be logically connected to the processor 410 through a power management system, so as to implement functions such as management of charging, discharging, and power consumption management through the power management system. Figure 6 The structure of the electronic device shown in does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0146] It should be understood that in the embodiments of the present application, the input unit 404 may include a graphics processing unit (GPU) 4041 and a microphone 4042. The graphics processing unit 4041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 406 may include a display panel 4061, and the display panel 4061 may be configured in the form of a liquid crystal display, an organic light-emitting diode, etc. The user input unit 407 includes at least one of a touch panel 4071 and other input devices 4072. The touch panel 4071 is also called a touch screen. The touch panel 4071 may include two parts: a touch detection device and a touch controller. The other input devices 4072 may include but are not limited to a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which will not be elaborated here.

[0147] The memory 409 can be used to store software programs and various data. The memory 409 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data. Among them, the first storage area may store an operating system, application programs or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 409 may include a volatile memory or a non-volatile memory, or the memory 409 may include both a volatile and a non-volatile memory. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static RAM (SRAM), a dynamic RAM (DRAM), a synchronous DRAM (SDRAM), a double data rate SDRAM (DDR SDRAM), an enhanced SDRAM (ESDRAM), a synch link DRAM (SLDRAM), and a direct rambus RAM (DRRAM). The memory 409 in the embodiments of the present application includes but is not limited to these and any other suitable types of memories.

[0148] The processor 410 may include one or more processing units; optionally, the processor 410 integrates an application processor and a modem processor. Among them, the application processor mainly processes operations related to the operating system, user interface, and application programs, etc., and the modem processor mainly processes wireless communication signals, such as a baseband processor. It can be understood that the above-mentioned modem processor may not be integrated into the processor 410 either.

[0149] The electronic device has the same advantages as the quantum information processing method described above compared with the prior art, and will not be elaborated here.

[0150] The present invention also provides a readable storage medium. When the instructions in the storage medium are executed by the processor of the electronic device, the electronic device can execute the quantum information processing method of the foregoing embodiments.

[0151] The readable storage medium has the same advantages as the quantum information processing method described above over the prior art, and will not be elaborated here.

[0152] The algorithms and displays provided herein are not inherently related to any particular computer, virtual system, or other device. Based on the above description, the structure required to construct such a system is obvious. In addition, the present invention is not directed to any particular programming language. It should be understood that the content of the present invention described herein can be implemented using various programming languages, and the description of a particular language above is for disclosing the best mode of the present invention.

[0153] In the specification provided herein, a large number of specific details are set forth. However, it can be understood that the embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures, and technologies have not been shown in detail so as not to obscure the understanding of this specification.

[0154] Similarly, it should be understood that, in order to streamline the present invention and assist in understanding one or more of the various inventive aspects, in the foregoing description of the exemplary embodiments of the present invention, the various features of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, the disclosed method should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, the inventive aspects lie in less than all the features of the single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into the detailed description, with each claim standing on its own as a separate embodiment of the present invention.

[0155] Those skilled in the art can understand that the modules in the devices in the embodiments can be adaptively changed and disposed in one or more devices different from the embodiments. The modules or units or components in the embodiments can be combined into one module or unit or component, and in addition, they can be divided into multiple sub-modules or sub-units or sub-components. Except that at least some of such features and / or processes or units are mutually exclusive, any combination can be used to combine all the features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all the processes or units of any method or device so disclosed. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) can be replaced by an alternative feature providing the same, equivalent, or similar purpose.

[0156] Each component embodiment of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art should understand that a microprocessor or a digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components in the sorting device according to the present invention. The present invention can also be implemented as a device or apparatus program for performing part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, or provided on a carrier signal, or in any other form.

[0157] It should be noted that the above embodiments are illustrative of the present invention rather than restrictive, and those skilled in the art can design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in the claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention can be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim listing several devices, several of these devices can be embodied by the same item of hardware. The use of the words first, second, and third, etc. does not denote any order. These words can be interpreted as names.

[0158] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0159] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0160] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present invention, and all of them should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

[0161] It should be noted that in the embodiments of this application, all processes related to obtaining various data are carried out on the premise of complying with the corresponding data protection regulations and policies of the country where the location is located and obtaining the authorization given by the owner of the corresponding device.

Claims

1. A quantum information processing method, characterized in that, Applied to a quantum computer, the method includes: For any qubit of the quantum computer, determine the bit flip probability of the qubit according to a preset quantum flip prediction model; When the bit flip probability is greater than a preset probability threshold, correct the bit value of the qubit to obtain the correct bit value of the corrected qubit, where the correct bit value is the bit value of the qubit before the bit flip occurs; Wherein, after correcting the bit value of the qubit and obtaining the correct bit value of the corrected qubit when the bit flip probability is greater than the preset probability threshold, the method further includes: Perform single-bit quantization on the signal sampling values stored in the quantum computer according to a preset bit compressive sensing model to obtain a second signal quantization value, where the signal sampling values include the correct bit values of the corrected qubits and the bit values of the qubits that have not undergone bit flips; Store the second signal quantization value in a specified area of the quantum computer.

2. The method according to claim 1, wherein The step of determining the bit flip probability of any qubit of the quantum computer according to a preset quantum flip prediction model includes: For any qubit of the quantum computer, obtain the bit flip probability at the previous moment and the current state transition probability of the qubit; Determine the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the current state transition probability.

3. The method according to claim 2, wherein The state transition probability includes a first state transition probability and a second state transition probability; before determining the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the current state transition probability, the method further includes: Generate a state transition probability matrix of the qubit according to the first state transition probability and the second state transition probability, where the first state transition probability is the probability that the qubit undergoes a state flip and the bit value changes from 0 to 1, and the second state transition probability is the probability that the qubit undergoes a state flip and the bit value changes from 1 to 0; The step of determining the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the current state transition probability includes: Determine the bit flip probability of the qubit at the next moment according to the bit flip probability at the previous moment and the state transition probability matrix.

4. The method according to claim 1, characterized in that, The quantum flip prediction model is obtained by the following method: For any qubit, obtain the historical bit flip probability and the state transition probability at the latest moment of the qubit; Perform model training according to the historical bit flip probability and the state transition probability at the latest moment to obtain the quantum flip prediction model.

5. The method according to claim 1, characterized in that, Before determining the bit flip probability of any qubit of the quantum computer according to a preset quantum flip prediction model, the method further includes: Quantize the sampling signal obtained by the quantum computer according to a preset quantization matrix to obtain a first signal quantization value; According to a preset signal reconstruction model, signal reconstruction is performed based on the first signal quantization value to obtain signal sampling values; The signal sampling values are stored through qubits of the quantum computer.

6. The method according to claim 1, wherein The performing single-bit quantization on the signal sampling values stored in the quantum computer according to a preset bit compressed sensing model to obtain second signal quantization values includes: Quantizing the signal sampling values stored in the quantum computer according to a preset quantization matrix to obtain third signal quantization values; Determining the sign information of the third signal quantization value according to the third signal quantization value and a preset signal threshold; Converting the sign information into the bit value of a qubit of the quantum computer, and obtaining second signal quantization values according to the bit value of the qubit of the quantum computer.

7. A quantum information processing device, characterized in that, When applied to a quantum computer, the device includes: A determining module, configured to determine, for any qubit of the quantum computer, the bit flip probability of the qubit according to a preset quantum flip prediction model; An error correction module, configured to correct the bit value of the qubit to obtain the correct bit value of the corrected qubit when the bit flip probability is greater than a preset probability threshold, where the correct bit value is the bit value of the qubit before the bit flip occurs; Wherein, the device further includes: A single-bit quantization module, configured to, when the error correction module corrects the bit value of the qubit to obtain the correct bit value of the corrected qubit when the bit flip probability is greater than a preset probability threshold, perform single-bit quantization on the signal sampling values stored in the quantum computer according to a preset bit compressed sensing model to obtain second signal quantization values, where the signal sampling values include the correct bit value of the corrected qubit and the bit values of qubits that have not undergone bit flips; The storage module is further configured to store the second signal quantization values in a specified area of the quantum computer.

8. An electronic device, characterized in that, including: A processor, a memory, and a computer program stored on the memory and executable on the processor, characterized in that when the processor executes the program, the quantum information processing method according to any one of claims 1-6 is implemented.

9. A readable storage medium, characterized in that, When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute one or more of the quantum information processing methods according to claims 1-6.

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