A method for determining a quantum state transmission scheme and a related device

Abstract

The application discloses a quantum state transmission scheme determination method and related device, the method comprises the following steps: using the obtained control bit and the hamiltonian corresponding to the target spin chain, all candidate quantum circuit modules are constructed; searching in all candidate quantum circuit modules, obtaining a target candidate quantum circuit module combination; based on the target candidate quantum circuit module combination and the current circuit parameters corresponding to the target candidate quantum circuit module combination, a target quantum circuit is constructed, and the target quantum circuit is used to determine the quantum state transmission scheme corresponding to the target spin chain. By using the embodiment of the application, the determination of the quantum state transmission scheme can be realized by using quantum computing, and the further development of quantum state transmission application is promoted.

Description

Technical Field

[0001] This invention belongs to the field of quantum state transmission technology, and in particular to a method and related apparatus for determining a quantum state transmission scheme. Background Technology

[0002] In the field of quantum information, quantum communication is the first research direction to move towards practical application. It is a novel communication method that transmits information through quantum entanglement, mainly involving quantum dense coding, quantum teleportation, and quantum cryptography. The transfer of quantum states plays a crucial role in the realization of quantum information processing and quantum computing; the processing of quantum information is usually accompanied by information transfer between participants. The development of quantum computers has provided an opportunity for the development of short-distance quantum communication, as the various components within a quantum computer need to communicate through channels.

[0003] Due to their inherent entanglement properties and manipulability, spin-chain systems allow qubits within the chain to become entangled through spin coupling. Entanglement can be transferred through the evolution of the spin chain, thereby enabling the transfer of quantum states. Spin chains, with their inherent characteristics, are considered the optimal carrier for quantum information transmission, and quantum information transmission using spin chains as channels is a hot research topic in the field of quantum information.

[0004] When using spin chains as channels for quantum state transmission, it is necessary to first determine the quantum state transmission scheme within the spin chain, and then control the transmission of the quantum state based on the determined scheme. Traditionally, determining the transmission scheme mostly requires direct calculation of 2... n Multidimensional matrices are computationally very difficult, especially when parameter optimization is involved, making computation almost impossible. However, this problem can be solved using quantum computing. Therefore, how to determine the quantum state transmission scheme through quantum computing is a technical problem that needs to be solved. Summary of the Invention

[0005] The purpose of this invention is to provide a method and related apparatus for determining a quantum state transmission scheme, which overcomes the shortcomings of the prior art. It can utilize quantum computing to determine the quantum state transmission scheme and promote the further development of quantum state transmission applications.

[0006] One embodiment of this application provides a method for determining a quantum state transmission scheme, the method comprising:

[0007] Using the obtained control bits and Hamiltonian corresponding to the target spin chain, all candidate quantum circuit modules are constructed, wherein the control bits are the quantum bits participating in the control among the quantum bits corresponding to the target spin chain, and all candidate quantum circuit modules include circuit parameters;

[0008] Search among all the candidate quantum circuit modules to obtain the target candidate quantum circuit module combination;

[0009] Based on the target candidate quantum circuit module combination and the circuit parameters corresponding to the target candidate quantum circuit module combination, a target quantum circuit is constructed, and the quantum state transmission scheme corresponding to the target spin chain is determined using the target quantum circuit.

[0010] Optionally, the step of constructing all candidate quantum circuit modules using the obtained control bits and the Hamiltonian corresponding to the target spin chain includes:

[0011] Based on the obtained control bits, determine the control method of the control parameters;

[0012] Using the Hamiltonian corresponding to the target spin chain and the determined control method, all candidate quantum circuit modules are constructed.

[0013] Optionally, the step of searching among all candidate quantum circuit modules to obtain the target quantum circuit module combination includes:

[0014] In response to the fact that the number of samplings in one iteration is less than a preset sampling threshold, the constructed probability distribution model is used to sample the combination of candidate quantum circuit modules constructed from all the candidate quantum circuit modules to obtain the quantum circuit corresponding to the sampled combination of candidate quantum circuit modules. The probability distribution model is used to determine the sampling probability of each of the candidate quantum circuit module combinations under the current probability distribution parameters.

[0015] In response to the sampling number in one iteration being equal to the preset sampling domain value, the probability distribution parameters and the corresponding circuit parameters are updated using the quantum circuit obtained from the sampling.

[0016] When the iteration meets the preset iteration stop condition, the candidate quantum circuit module combination with the highest probability is determined according to the current probability distribution parameters and the probability distribution model, and is used as the target candidate quantum circuit module combination.

[0017] Optionally, the step of responding to the sampling number within one iteration being equal to the preset sampling domain value, and using the quantum circuit obtained from the sampling to update the probability distribution parameters and the corresponding circuit parameters, includes:

[0018] For each quantum circuit obtained by sampling within one iteration, the corresponding circuit parameters are obtained from the current parameter pool;

[0019] Based on the obtained circuit parameters, the gradient of the probability distribution parameters and the gradient of the corresponding circuit parameters are obtained using the quantum circuit.

[0020] In response to the number of samples in one iteration being equal to the preset sampling range value, the probability distribution parameters and the line parameters in the parameter pool are updated.

[0021] Optionally, the step of obtaining the gradient of the probability distribution parameters and the gradient of the line parameters using the quantum circuit based on the obtained circuit parameters includes:

[0022] Based on the obtained circuit parameters, the quantum circuit is run and measured to determine the value of the loss function corresponding to the quantum circuit.

[0023] Using the function value, calculate the gradient of the probability distribution parameter and the gradient of the corresponding line parameter.

[0024] Optionally, calculating the gradient of the probability distribution parameter and the gradient of the corresponding line parameter using the function value includes:

[0025] Calculate the gradient of the corresponding line parameters using the following formula:

[0026]

[0027] in, Let θ be the gradient of the line parameters, and θ be the line parameters. For loss function, The quantum circuit obtained from sampling, Let be a vector consisting of the indices of the candidate quantum circuit modules included in the quantum circuit, and α be a probability distribution parameter. It is a probability distribution model;

[0028] Calculate the gradient of the probability distribution parameters using the following formula:

[0029]

[0030] in, a represents the layer number of the quantum circuit, and i,j represents the numbers of the candidate quantum circuit modules.

[0031] Optionally, the step of constructing a target quantum circuit based on the target candidate quantum circuit module combination and the circuit parameters corresponding to the target candidate quantum circuit module combination, and using the target quantum circuit to determine the quantum state transmission scheme, includes:

[0032] The candidate quantum circuit modules in the target candidate quantum circuit module combination are sequentially connected to obtain the target quantum circuit, wherein the target quantum circuit contains the circuit parameters currently corresponding to the target candidate quantum circuit module combination;

[0033] Based on the target quantum circuit, the parameters of the target circuit are obtained using a variable quantum algorithm;

[0034] Based on the target circuit parameters and the control method corresponding to the combination of the target quantum circuit modules, the quantum state transmission scheme corresponding to the target spin chain is determined.

[0035] Another embodiment of this application provides a device for determining a quantum state transmission scheme, the device comprising:

[0036] A construction module is used to construct all candidate quantum circuit modules using the obtained control bits and the Hamiltonian corresponding to the target spin chain, wherein the control bits are the quantum bits participating in the control among the quantum bits corresponding to the target spin chain, and all candidate quantum circuit modules include circuit parameters;

[0037] The module is used to search among all the candidate quantum circuit modules to obtain the target combination of candidate quantum circuit modules;

[0038] The determination module is used to construct a target quantum circuit based on the target candidate quantum circuit module combination and the circuit parameters currently corresponding to the target candidate quantum circuit module combination, and to determine the quantum state transmission scheme corresponding to the target spin chain using the target quantum circuit.

[0039] Optionally, the building module is specifically used for:

[0040] Based on the obtained control bits, determine the control method of the control parameters;

[0041] Using the Hamiltonian corresponding to the target spin chain and the determined control method, all candidate quantum circuit modules are constructed.

[0042] Optionally, the obtaining module includes:

[0043] The obtaining unit is used to sample the combination of candidate quantum circuit modules constructed from all the candidate quantum circuit modules in response to the number of samplings in one iteration being less than a preset sampling threshold value, by using the constructed probability distribution model to obtain the quantum circuit corresponding to the sampled combination of candidate quantum circuit modules. The probability distribution model is used to determine the sampling probability of each combination of candidate quantum circuit modules under the current probability distribution parameters.

[0044] The update unit is used to update the probability distribution parameters and the corresponding circuit parameters using the quantum circuit obtained by sampling when the number of samplings in one iteration is equal to the preset sampling domain value.

[0045] The determining unit is used to determine the candidate quantum circuit module combination with the highest probability as the target candidate quantum circuit module combination when the iteration meets the preset iteration stopping condition, based on the current probability distribution parameters and the probability distribution model.

[0046] Optionally, the update unit is specifically used for:

[0047] For each quantum circuit obtained by sampling within one iteration, the corresponding circuit parameters are obtained from the current parameter pool;

[0048] Based on the obtained circuit parameters, the gradient of the probability distribution parameters and the gradient of the corresponding circuit parameters are obtained using the quantum circuit.

[0049] In response to the number of samples in one iteration being equal to the preset sampling range value, the probability distribution parameters and the line parameters in the parameter pool are updated.

[0050] Optionally, the update unit is further specifically used for:

[0051] Based on the obtained circuit parameters, the quantum circuit is run and measured to determine the value of the loss function corresponding to the quantum circuit.

[0052] Using the function value, calculate the gradient of the probability distribution parameter and the gradient of the corresponding line parameter.

[0053] Optionally, the update unit is further specifically used for:

[0054] Calculate the gradient of the corresponding line parameters using the following formula:

[0055]

[0056] in, Let θ be the gradient of the line parameters, and θ be the line parameters. For loss function, The quantum circuit obtained from sampling, Let be a vector consisting of the indices of the candidate quantum circuit modules included in the quantum circuit, and α be a probability distribution parameter. It is a probability distribution model;

[0057] Calculate the gradient of the probability distribution parameters using the following formula:

[0058]

[0059] in, a represents the layer number of the quantum circuit, and i,j represents the numbers of the candidate quantum circuit modules.

[0060] Optionally, the determining module is specifically used for:

[0061] The candidate quantum circuit modules in the target candidate quantum circuit module combination are sequentially connected to obtain the target quantum circuit, wherein the target quantum circuit contains the circuit parameters currently corresponding to the target candidate quantum circuit module combination;

[0062] Based on the target quantum circuit, the parameters of the target circuit are obtained using a variable quantum algorithm;

[0063] Based on the target circuit parameters and the control method corresponding to the combination of the target quantum circuit modules, the quantum state transmission scheme corresponding to the target spin chain is determined.

[0064] One embodiment of this application provides a storage medium storing a computer program, wherein the computer program is configured to implement the method described in any of the above-described embodiments when running.

[0065] One embodiment of this application provides an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to implement the method described in any of the above-described embodiments.

[0066] Compared with existing technologies, this invention first utilizes the obtained control bits and the Hamiltonian corresponding to the target spin chain to construct all candidate quantum circuit modules. Then, it searches among these candidate quantum circuit modules to obtain a combination of target candidate quantum circuit modules. Next, based on this combination of target candidate quantum circuit modules and its corresponding circuit parameters, a target quantum circuit is constructed. Finally, using this target quantum circuit, the quantum state transmission scheme corresponding to the target spin chain is determined. This enables the determination of quantum state transmission schemes using quantum computing, promoting the further development of quantum state transmission applications. Attached Figure Description

[0067] Figure 1 Hardware structure block diagram of a computer terminal for a method of determining a quantum state transmission scheme provided in an embodiment of the present invention;

[0068] Figure 2 A flowchart illustrating a method for determining a quantum state transmission scheme according to an embodiment of the present invention;

[0069] Figure 3 This is a schematic diagram of a device for determining a quantum state transmission scheme, provided in an embodiment of the present invention. Detailed Implementation

[0070] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0071] The present invention first provides a method for determining a quantum state transmission scheme, which can be applied to electronic devices, such as computer terminals, specifically ordinary computers, quantum computers, etc.

[0072] A quantum computer is a physical device that performs high-speed mathematical and logical operations, stores and processes quantum information in accordance with the laws of quantum mechanics. When a device processes and calculates quantum information and runs quantum algorithms, it is a quantum computer. Because of its ability to process mathematical problems more efficiently than ordinary computers—for example, reducing the time to crack RSA keys from hundreds of years to hours—quantum computers have become a key technology under research.

[0073] The following detailed explanation uses a computer terminal as an example. Figure 1 This is a hardware structure block diagram of a computer terminal for a method of determining a quantum state transmission scheme provided in an embodiment of the present invention. (See diagram below.) Figure 1 As shown, a computer terminal may include one or more ( Figure 1 Only one is shown in the diagram. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. Optionally, the computer terminal may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the computer terminal described above. For example, the computer terminal may also include components that are more complex than those described above. Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0074] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / modules corresponding to the method for determining the quantum state transmission scheme in the embodiments of this application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to a computer terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0075] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider for the computer terminal. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0076] Quantum computing is a novel computing paradigm that manipulates quantum information units according to the laws of quantum mechanics. One of the most fundamental principles upon which quantum computing is based is the superposition principle of quantum mechanical states. This principle allows quantum information units to exist in a superposition of multiple possible states, thus giving quantum information processing greater potential efficiency compared to classical information processing. A quantum system contains several particles that move according to the laws of quantum mechanics; this system is said to be in a certain quantum state in the state space. For chemical molecules, quantum chemical simulation can be achieved, providing research support for quantum computing.

[0077] It's important to note that a true quantum computer has a hybrid structure, comprising two main parts: a classical computer responsible for performing classical computations and control, and a quantum device responsible for running quantum programs to achieve quantum computation. A quantum program is a sequence of instructions written in a quantum language such as QRunes that can run on a quantum computer, supporting operations on quantum logic gates and ultimately enabling quantum computing. Specifically, a quantum program is a sequence of instructions that operates on quantum logic gates according to a specific timing order.

[0078] In practical applications, due to limitations in the development of quantum device hardware, quantum computing simulations are often required to verify quantum algorithms, quantum applications, and so on. Quantum computing simulation is the process of simulating the execution of a quantum program corresponding to a specific problem using a virtual architecture (i.e., a quantum virtual machine) built with the resources of a regular computer. Typically, it is necessary to construct a quantum program corresponding to a specific problem. The quantum program referred to in this embodiment of the invention is a program written in a classical language that represents qubits and their evolution, wherein qubits, quantum logic gates, etc., related to quantum computing all have corresponding classical code representations.

[0079] Quantum circuits, also known as quantum logic circuits, are a common manifestation of quantum programming and are the most widely used general-purpose quantum computing model. They represent circuits that operate on qubits under an abstract concept. They consist of qubits, circuits (timelines), and various quantum logic gates. Finally, the results are often read out through quantum measurement operations.

[0080] Unlike traditional circuits that use metal wires to transmit voltage or current signals, in quantum circuits, the circuits can be seen as being connected by time. That is, the state of a quantum bit evolves naturally over time, following the instructions of the Hamiltonian operator until it encounters a logic gate and is operated on.

[0081] A quantum program corresponds to a single quantum circuit. The quantum program described in this invention refers to this single quantum circuit, where the total number of qubits in the single quantum circuit is the same as the total number of qubits in the quantum program. This can be understood as follows: a quantum program can consist of a quantum circuit, measurement operations on the qubits within the quantum circuit, registers for storing measurement results, and control flow nodes (jump instructions). A single quantum circuit can contain dozens, hundreds, or even thousands of quantum logic gate operations. The execution of a quantum program is the process of executing all the quantum logic gates in a specific timing order. It should be noted that the timing order refers to the chronological sequence in which individual quantum logic gates are executed.

[0082] It should also be noted that this invention relates to quantum computers. In conventional silicon-based computing devices, the processing chip units are CMOS (Complementary Metal Oxide Semiconductor) transistors. These computing units are not limited by time or coherence; that is, they are always available without time constraints. Furthermore, currently, the number of these computing units in silicon chips is sufficient; a single chip currently contains tens of thousands of computing units. The sufficient number of computing units and the fixed selectable computing logic of CMOS transistors, such as AND logic, allow for computational efficiency through a combination of numerous CMOS transistors and limited logic functions.

[0083] Unlike the logical units in ordinary computing devices, the basic computing unit in current quantum computers is the qubit. The input of a qubit is limited by coherence and coherence time; that is, a qubit is limited by its usage time and is not always available. Making full use of qubits within their available usage time is a key challenge in quantum computing. Furthermore, the number of qubits in a quantum computer is a crucial challenge. The number of qubits is also one of the representative indicators of a quantum computer's performance. Each qubit performs computational functions through on-demand configured logical functions. Given the limited number of qubits and the diverse logical functions in quantum computing, such as Hadamard gates (H gates), Pauli-X gates (X gates), Pauli-Y gates (Y gates), Pauli-Z gates (Z gates), RX gates, RY gates, RZ gates, CNOT gates, CR gates, iSWAP gates, Tofoli gates, etc., quantum logic gates are generally represented using unitary matrices. A unitary matrix is ​​not only a matrix form but also a type of operation and transformation. In general, the action of a quantum logic gate on a quantum state is calculated by left-multiplying a unitary matrix by the matrix corresponding to the right vector of the quantum state. In quantum computing, a finite number of qubits combined with diverse logical functions achieves computational effects.

[0084] Given these differences in quantum computers, the design of logical functions applied to qubits (including the design of whether qubits are used and the design of the efficiency of each qubit's use) is crucial for improving the computational performance of quantum computers and requires specialized design. The aforementioned design considerations for qubits are technical problems that ordinary computing devices do not need to address.

[0085] See Figure 2 , Figure 2 A flowchart illustrating a method for determining a quantum state transmission scheme according to an embodiment of the present invention may include the following steps:

[0086] S201: Using the obtained control bits and the Hamiltonian corresponding to the target spin chain, construct all candidate quantum circuit modules, wherein the control bits are the quantum bits participating in the control among the quantum bits corresponding to the target spin chain, and all candidate quantum circuit modules contain circuit parameters.

[0087] A spin chain is a system formed by a series of particles (or entities that can be considered particles, such as special waveguides, quantum dots, etc., collectively referred to as particles) arranged in a row, with each particle interacting and connecting with its neighbors in some form. In practical applications, an initial state is assigned to the spin chain, and the goal is to find a scheme that alters the interactions between particles so that the quantum states in the spin chain can evolve over time through free dynamics to a desired outcome. This process is called quantum state transfer in the spin chain.

[0088] Spin chains have various models, and their classification varies depending on the perspective. In terms of shape, there are linear, toroidal, and star-shaped spin chains, etc.; in terms of interaction range, there are neighbor-particle interactions and next-nearest-neighbor interactions, etc.; and in terms of the characteristics of the interaction in different directions, there are XY, XX, XXZ, and Ising, etc. Once the spin chain is determined, the Hamiltonian and the number of qubits corresponding to it are also determined.

[0089] In some embodiments of the present invention, the Hamiltonian can be expressed by the following formula:

[0090]

[0091] Where H is the Hamiltonian, i is the particle number, and H n,n+1 The interparticle interaction term is determined by the type of the target spin chain. For single-particle interaction, B n Let n be the magnetic field strength for particle n. Let be the Pauli Z operator for particle n.

[0092] The Hamiltonian corresponding to a target spin chain typically includes inter-particle interaction terms and single-particle interaction terms. The inter-particle interaction terms may differ for different types of spin chains; for example, for an XY spin chain... Regarding the Heisinberg spin chain, J n Characterizing the coupling strength between particles n and n+1, These represent the coupling strength in different directions.

[0093] Hamiltonians are categorized into time-dependent and time-independent Hamiltonians. When the Hamiltonian is time-dependent, quantum circuits cannot directly simulate time-dependent Hamiltonians. Instead, a time interval needs to be divided into many small time segments, where the Hamiltonian is assumed to change little within each segment, or in other words, the Hamiltonian corresponding to each segment does not change with time. Then, Trotter decomposition is performed on each segment to obtain a series of evolution operators. These evolution operators can be used to simulate quantum state propagation using quantum circuits. For example, for an XY spin chain, a series of evolution operators can be obtained as shown in the following equation:

[0094]

[0095] Among them, U i (t) is the evolution operator, where the coupling strength in each direction does not change with time, B n(t) = {0, 1}, meaning that at any given moment, the magnetic field has only two possibilities: it exists or it does not exist.

[0096] To ensure the fidelity of quantum state transmission on a spin chain or achieve perfect transmission, the control parameters need to be changed during the transmission process. These control parameters can include magnetic fields, coupling strength, etc. The control bits are determined based on the particle whose control parameters need to be changed. For example, if the magnetic field of particle 1 needs to be changed during quantum state transmission, then qubit 1 is the control bit. In this embodiment of the invention, all qubits corresponding to the target spin chain can be used as control bits, or a portion of the qubits corresponding to the target spin chain can be selected as control bits. The specific selection method can be determined according to the actual situation. For example, based on previous experience, for a certain type of spin chain, controlling the first three qubits and the last three qubits can achieve the required quantum state transmission; therefore, the control bits are the first three qubits and the last three qubits. Alternatively, the control bits can be calculated based on the characteristics of the target spin chain according to a certain algorithm.

[0097] Once the control parameters and control bits are determined, the specific behavior of the evolution operator is also determined, as are the candidate quantum circuit modules used to simulate different evolution operators. Each candidate quantum circuit module corresponds to a control method. Taking a magnetic field as the control parameter as an example, one control method represents certain particles being controlled by a constant magnetic field for a certain period of time, while other particles remain unchanged. The circuit parameter in the candidate quantum circuit module represents the required control time. The number of qubits corresponding to the target spin chain is generally the number of particles in the target spin chain, and particles can be paired one-to-one with qubits. The order of the qubits corresponds to the order of the particles. For example, the target spin chain contains 5 particles from left to right: the leftmost particle corresponds to qubit 1, the second particle from the left corresponds to qubit 2, and the rightmost particle corresponds to qubit 5.

[0098] The alternative quantum circuit modules include a first simulation module simulating inter-particle interactions and a second simulation module simulating single-particle interactions. The qubits interacting with the first and second simulation modules are determined, and these modules are applied to the determined qubits to construct different alternative quantum circuit modules. The first simulation module can contain one or more of H-gates, CNOT gates, RX gates, RY gates, and RZ gates, while the second simulation module can contain RZ gates. It should be noted that the functionality of quantum logic gates can also be implemented using combinations of other quantum logic gates. Therefore, both the first and second simulation modules have multiple implementation methods, and different first and second simulation modules can be constructed according to different requirements.

[0099] S202: Search among all the candidate quantum circuit modules to obtain the target candidate quantum circuit module combination.

[0100] In this embodiment of the invention, Quantum Architecture Search (QAS) technology can be used to search all candidate quantum circuit modules to determine the target candidate quantum circuit module combination. Alternatively, all candidate quantum circuit modules can be used to determine different module combinations using the principle of permutation and combination. From these module combinations, modules that meet the requirements can be selected as the target candidate quantum circuit module combination. It should be noted that the target candidate quantum circuit module combination may contain the same candidate quantum circuit modules. For example, the target candidate quantum circuit module combination may contain 5 candidate quantum circuit modules. These 5 candidate quantum circuit modules may be the same, or 2 of them may be the same, or all 5 may be different, depending on the actual situation.

[0101] S203: Based on the target candidate quantum circuit module combination and the circuit parameters corresponding to the target candidate quantum circuit module combination, construct a target quantum circuit, and use the target quantum circuit to determine the quantum state transmission scheme corresponding to the target spin chain.

[0102] Initially, the number of layers in the target quantum circuit is fixed, but the specific structure of each layer is uncertain. A module needs to be selected from candidate quantum circuit modules for each layer. Once the structure of each layer is determined, the overall structure of the target quantum circuit is also determined. The target quantum circuit contains a combination of target candidate quantum circuit modules. Running the target quantum circuit yields a final state. Based on the final state, it is determined whether the circuit parameters in the target quantum circuit need to be updated. When the circuit parameters of the target quantum circuit stop updating, a quantum state transmission scheme is determined based on the latest circuit parameters. The transmission scheme includes the particles to be controlled, the circuit parameters, and the control method determined by the corresponding candidate quantum circuit modules. For example, the quantum state transmission scheme could be to control particles 1 and 2 with a constant magnetic field during time period 1 (0-3 seconds), control particles 3, 8, and 9 during time period 2 (3-4 seconds), and control particles 7 and 8 during time period 3 (4-6 seconds). Here, the time periods are determined based on the circuit parameters, which are the durations corresponding to each time period.

[0103] In this embodiment of the invention, based on different requirements, corresponding control bits are determined, candidate quantum circuit modules are determined based on the control bits, target quantum circuits for simulating quantum state transmission are determined using the candidate quantum modules, simulation of quantum state transmission is achieved using the target quantum circuit, and then the control scheme for quantum state transmission on the spin chain is determined to ensure that the quantum state is transmitted in a controllable manner to obtain the desired result, thereby realizing the determination of the quantum state transmission scheme through quantum computing.

[0104] As can be seen, this embodiment of the invention first uses the obtained control bits and the Hamiltonian corresponding to the target spin chain to construct all candidate quantum circuit modules. Then, it searches among all candidate quantum circuit modules to obtain the target candidate quantum circuit module combination. Based on the target candidate quantum circuit module combination and its current corresponding circuit parameters, it constructs the target quantum circuit and uses the target quantum circuit to determine the quantum state transmission scheme corresponding to the target spin chain. This can facilitate the determination of quantum state transmission schemes using quantum computing, promoting the further development of quantum state transmission applications.

[0105] In some possible embodiments of the present invention, the step of constructing all candidate quantum circuit modules using the obtained control bits and the Hamiltonian corresponding to the target spin chain includes:

[0106] Based on the obtained control bits, determine the control method of the control parameters;

[0107] Using the Hamiltonian corresponding to the target spin chain and the determined control method, all candidate quantum circuit modules are constructed.

[0108] The control method is related to the control bits, specifically the number of control bits. For example, control bits control the magnetic field, with the control bits being the qubits corresponding to the first three particles and the qubits corresponding to the last three particles. The corresponding control methods are 15(2). 3 +2 3 -1), specifically, the control method can be B. n (t) indicates that B n(t) has [000…000], [001…000], [010…000], [100…000], [011…000], [101…000], [110…000], [111…000], [000…001], [000…010], [000…100], [000…011], [000…101], [000…110], [000…111]. 0 represents not being in the corresponding particle's magnetic field, and 1 represents being in the corresponding particle's magnetic field. These 15 control methods correspond to 15 candidate quantum circuit modules, that is, 15 U... i The difference between each candidate quantum circuit module lies in its different control methods, which correspond to different circuit structures. For example, in the candidate quantum circuit module corresponding to control method [001...000], an RZ gate is applied to qubit 3; in the candidate quantum circuit module corresponding to control method [001...000], RZ gates are applied to qubits 2 and 3. If the Hamiltonian is not included, then from 15 U... i Choose a candidate quantum circuit module combination as the target. If the Hamiltonian is time-independent, the target quantum circuit contains multiple layers. The specific number of layers can be obtained empirically or through calculation. Then, for each layer, from 15 U... i Choose one U i The obtained combination of target candidate quantum circuit modules is formed by selecting U at each layer. i Gather in an orderly manner.

[0109] In some possible embodiments of the present invention, the step of searching among all candidate quantum circuit modules to obtain a target quantum circuit module combination includes:

[0110] In response to the fact that the number of samplings in one iteration is less than a preset sampling threshold, the constructed probability distribution model is used to sample the combination of candidate quantum circuit modules constructed from all the candidate quantum circuit modules to obtain the quantum circuit corresponding to the sampled combination of candidate quantum circuit modules. The probability distribution model is used to determine the sampling probability of each of the candidate quantum circuit module combinations under the current probability distribution parameters.

[0111] In response to the sampling number in one iteration being equal to the preset sampling domain value, the probability distribution parameters and the corresponding circuit parameters are updated using the quantum circuit obtained from the sampling.

[0112] When the iteration meets the preset iteration stop condition, the candidate quantum circuit module combination with the highest probability is determined according to the current probability distribution parameters and the probability distribution model, and is used as the target candidate quantum circuit module combination.

[0113] In this embodiment of the invention, to obtain the target candidate quantum circuit module combination, multiple iterations are required. Each iteration involves sampling a preset sampling threshold number of times. Each sampling yields a candidate quantum circuit module combination. Based on the sampled candidate quantum circuit module combinations, the corresponding quantum circuit is obtained. To facilitate subsequent calculations, a mapping method can be predetermined, associating a combination with a mathematical form, and all candidate quantum circuit module combinations can be represented by a vector. This means that if the sampled Then, corresponding to candidate quantum circuit modules 1, 4, 3, and 8, these candidate quantum circuit modules are sequentially grouped to obtain the quantum circuit corresponding to the sample. It should be noted that vectors... The number of elements in the target quantum circuit is the number of layers.

[0114] The probability distribution model can be α is the current probability distribution parameter. If the layers in the target quantum circuit are independent of each other, then... and j represents the number of the candidate quantum circuit module. A probability distribution model is used to select combinations of candidate quantum circuit modules; combinations with higher calculated probabilities are more likely to be selected.

[0115] When the number of samples in an iteration reaches the preset sampling threshold, it means that all quantum circuits obtained from the sampling in that iteration are used to update the probability distribution parameters and the corresponding circuit parameters, thus completing one iteration.

[0116] The preset iteration stopping condition can be: the current iteration number equals the maximum iteration number; or the current iteration number is less than the maximum iteration number, and the function value of the loss function corresponding to the current iteration is less than the preset precision; or the function value of the loss function corresponding to the current iteration is less than the function value of the loss function corresponding to the previous iteration, and the difference between the function value of the loss function corresponding to the current iteration and the preset threshold is less than the preset precision, etc. The preset iteration stopping condition can be one of the above conditions, a reasonable combination of the above conditions, or other conditions, as long as a satisfactory combination of alternative quantum circuit modules can be obtained when the iteration stops. It should be noted that the function value of the loss function corresponding to the current iteration is obtained by processing the function value of the loss function of the quantum circuit sampled in the current iteration.

[0117] In this embodiment of the invention, the objective is to find a set of candidate quantum circuit module combinations, that is, to find a set of U... i (t), calculate the final state Make F = 1 - |<ψ f |ψ t >|2 Minimize as much as possible, while making ∑ i t i Minimize it as much as possible, that is, minimize 1-F+αT. i (t) still varies with time, but the change is no longer continuous but discrete. It remains constant within each time interval, but the length of each time interval is no longer limited to a very short range, but can be used as a parameter for adjustment by the variational circuit. In this embodiment of the invention, the loss function L can be expressed as L=1-|〈N|U|1〉|+α∑ i t i For one iteration, the loss function can be expressed as: θ is the length of the time interval and also a line parameter. Therefore, the loss function for the current iteration can be expressed as:

[0118]

[0119] When the iteration stops, the probability distribution parameters stop updating. Under the current probability distribution parameters, the target candidate quantum circuit module combination is determined using the probability distribution model.

[0120] In some possible embodiments of the present invention, the step of responding to the sampling number within one iteration being equal to the preset sampling threshold, and updating the probability distribution parameters and the corresponding circuit parameters using the quantum circuit obtained from the sampling, includes:

[0121] For each quantum circuit obtained by sampling within one iteration, the corresponding circuit parameters are obtained from the current parameter pool;

[0122] Based on the obtained circuit parameters, the gradient of the probability distribution parameters and the gradient of the corresponding circuit parameters are obtained using the quantum circuit.

[0123] In response to the number of samples in one iteration being equal to the preset sampling range value, the probability distribution parameters and the line parameters in the parameter pool are updated.

[0124] If every U i There are l parameters, p layers in the quantum circuit, and m candidate quantum circuit modules. Therefore, a total of lm is required. p The number of θ parameters required is very large, and many parameters need to be updated during the iteration process, which increases the workload for determining the quantum state transmission scheme. In this embodiment of the invention, a parameter pool is used to solve this problem. The parameter pool is a p×m×l tensor Θ. Regardless of other parts of the quantum circuit, if both quantum circuits select the j-th candidate quantum circuit module in the i-th layer, then they use the same parameters in that layer. This serves as initialization. This approach reduces the number of variable parameters that need to be maintained to lmp, thereby reducing resource consumption.

[0125] In some possible embodiments of the present invention, the number of candidate quantum circuit modules included in each candidate quantum circuit module combination is the same as the number of layers of the target quantum circuit, and there is a correspondence between the candidate quantum circuit modules and the number of layers. If there are identical candidate quantum circuit modules in the candidate quantum circuit module combination, then the layers corresponding to the candidate quantum circuit modules are different. If the corresponding layers are different, the corresponding circuit parameters can also be different. The specific parameters need to be determined according to the parameters in the parameter pool.

[0126] One way to obtain the circuit parameters corresponding to the quantum circuit from the current parameter pool is as follows:

[0127] For each quantum circuit obtained by sampling in one iteration, based on the layer of the candidate quantum circuit module corresponding to the quantum circuit in the quantum circuit, the position of the corresponding circuit parameter in the current parameter pool is determined. The parameter pool stores the circuit parameters corresponding to all candidate quantum circuit modules in each layer of the quantum circuit.

[0128] From the determined location, obtain the circuit parameters corresponding to the quantum circuit.

[0129] The obtained circuit parameters are substituted into the corresponding quantum circuit, and the quantum circuit is run. Based on the running results, the gradients of the probability distribution parameters and the corresponding circuit parameters are obtained. During iteration, the probability distribution parameters and the circuit parameters in the parameter pool are updated using the gradients of all probability distribution parameters and circuit parameters obtained in the current iteration.

[0130] In some possible embodiments of the present invention, obtaining the gradient of the probability distribution parameters and the gradient of the line parameters using the quantum circuit based on the obtained line parameters includes:

[0131] Based on the obtained circuit parameters, the quantum circuit is run and measured to determine the value of the loss function corresponding to the quantum circuit.

[0132] Using the function value, calculate the gradient of the probability distribution parameter and the gradient of the corresponding line parameter.

[0133] The obtained circuit parameters are input into the quantum circuit, and the final state of the quantum circuit is obtained by running and measuring. Using the final state and the pre-established loss function, the function value of the loss function is calculated. Then, using the function value, the gradient of the probability distribution parameters and the gradient of the corresponding circuit parameters are calculated.

[0134] In some embodiments of the present invention, calculating the gradient of the probability distribution parameter and the gradient of the corresponding line parameter using the function value may include:

[0135] Calculate the gradient of the corresponding line parameters using the following formula:

[0136]

[0137] in, Let θ be the gradient of the line parameters, and θ be the line parameters. For loss function, The quantum circuit obtained from sampling, Let be a vector consisting of the indices of the candidate quantum circuit modules included in the quantum circuit, and α be a probability distribution parameter. It is a probability distribution model;

[0138] Calculate the gradient of the probability distribution parameters using the following formula:

[0139]

[0140] in, a represents the layer number of the quantum circuit, and i,j represents the numbers of the candidate quantum circuit modules.

[0141] The gradients of line parameters can be obtained using finite difference methods, parameter offsetting, automatic line finding, or other methods. For the gradients of probability distribution parameters, in general, the following holds:

[0142]

[0143] Since the probability distribution is normalized, Therefore, we only need to focus on the first point. We assume that the layers of a quantum circuit are independent, i.e. and In this form, it can be easily calculated that:

[0144]

[0145] When j = a, then δ ja =1, when j≠a, then δ ja =0.

[0146] In some possible embodiments of the present invention, the step of updating the probability distribution parameters and the line parameters in the parameter pool in response to the number of samples in one iteration being equal to the preset sampling threshold includes:

[0147] Based on each sampled quantum circuit, the circuit parameters to be updated are determined from the parameter pool;

[0148] In response to the number of samples in one iteration being equal to the preset sampling range value, the average value of the gradients of all line parameters calculated in that iteration is obtained as the first average value;

[0149] The determined line parameters to be updated are updated using the obtained first average value.

[0150] The average value of the gradients of all probability distribution parameters calculated in this iteration is obtained as the second average value;

[0151] The probability distribution parameters are updated using the obtained second average value.

[0152] For a single iteration, numerous samples are taken, resulting in many candidate quantum circuit module combinations. Each combination corresponds to circuit parameters in the parameter pool. Therefore, based on the information from the sampling records, the position of the circuit parameters of the quantum circuits sampled in this iteration within the parameter pool can be determined. Based on this position, the circuit parameters to be updated are determined. The average gradient of all circuit parameters calculated within this iteration is used to update the circuit parameters to be updated. Specifically, a circuit parameter update calculation formula can be used, which includes a first average value and a preset learning rate for the circuit parameters. Based on the average gradient of all probability distribution parameters calculated within this iteration and the probability distribution parameter update calculation formula, the probability distribution parameters are updated. Besides directly using the average gradient to update the corresponding parameters, the gradient can also be processed first, such as removing some with large deviations, or fitting the gradient distribution, and then using the processed data to update the corresponding parameters.

[0153] In some possible embodiments of the present invention, the step of constructing a target quantum circuit based on the target candidate quantum circuit module combination and the circuit parameters currently corresponding to the target candidate quantum circuit module combination, and using the target quantum circuit to determine a quantum state transmission scheme, includes:

[0154] The candidate quantum circuit modules in the target candidate quantum circuit module combination are sequentially connected to obtain the target quantum circuit, wherein the target quantum circuit contains the circuit parameters currently corresponding to the target candidate quantum circuit module combination;

[0155] Based on the target quantum circuit, the parameters of the target circuit are obtained using a variable quantum algorithm;

[0156] Based on the target circuit parameters and the control method corresponding to the combination of the target quantum circuit modules, the quantum state transmission scheme corresponding to the target spin chain is determined.

[0157] The candidate quantum circuit modules in the target candidate quantum circuit module combination are ordered. Combining these modules sequentially yields the target quantum circuit. The circuit parameters in the target quantum circuit are the corresponding parameters of the target candidate quantum circuit module combination in the parameter pool. These parameters can be obtained using a variable quantum algorithm. Specifically, the target quantum circuit is run to simulate the propagation of quantum states in a spin chain. The quantum states evolve in the target quantum circuit to obtain a final state. Based on the constructed loss function, the value of the loss function is calculated, and the target circuit parameters are determined based on this value. The loss function can be constructed based on the measured distance between the final state and the target quantum state. The calculated value of the loss function is the distance between these two states. Alternatively, the loss function can be constructed based on the measured energy expectation of the final state and the energy expectation of the target quantum state. The value of the loss function is the difference between these energy expectations. Different loss functions can be constructed according to different requirements.

[0158] When the loss function meets the preset conditions, it means that the final state obtained by the measurement is the desired final state, that is, the current quantum state simulation transmission has been completed, and the circuit parameters contained in the current target quantum circuit are the target circuit parameters. When the loss function does not meet the preset conditions, it means that the current quantum state simulation transmission has not been completed, and the circuit parameters in the target quantum circuit need to be updated for re-simulation. There are several ways to update the circuit parameters. An optimizer can be used to calculate the optimization gradient based on the loss function value. Based on the optimization gradient and the circuit parameters currently contained in the target quantum circuit, the updated circuit parameters can be calculated, and then the current circuit parameters contained in the target quantum circuit can be replaced with the updated circuit parameters.

[0159] See Figure 3 , Figure 3 This is a schematic diagram of the structure of a device for determining a quantum state transmission scheme provided in an embodiment of the present invention. Figure 2 Corresponding to the process shown, the apparatus includes:

[0160] The construction module 301 is used to construct all candidate quantum circuit modules using the obtained control bits and the Hamiltonian corresponding to the target spin chain, wherein the control bits are the quantum bits participating in the control among the quantum bits corresponding to the target spin chain, and all candidate quantum circuit modules include circuit parameters.

[0161] The module 302 is used to search among all the candidate quantum circuit modules to obtain a target combination of candidate quantum circuit modules.

[0162] The determining module 303 is used to construct a target quantum circuit based on the target candidate quantum circuit module combination and the circuit parameters currently corresponding to the target candidate quantum circuit module combination, and to determine the quantum state transmission scheme corresponding to the target spin chain using the target quantum circuit.

[0163] In some possible embodiments of the present invention, the building module 301 may be specifically used for:

[0164] Based on the obtained control bits, determine the control method of the control parameters;

[0165] Using the Hamiltonian corresponding to the target spin chain and the determined control method, all candidate quantum circuit modules are constructed.

[0166] In some possible embodiments of the present invention, the obtaining module 302 may include:

[0167] The obtaining unit is used to sample the combination of candidate quantum circuit modules constructed from all the candidate quantum circuit modules in response to the number of samplings in one iteration being less than a preset sampling threshold value, by using the constructed probability distribution model to obtain the quantum circuit corresponding to the sampled combination of candidate quantum circuit modules. The probability distribution model is used to determine the sampling probability of each combination of candidate quantum circuit modules under the current probability distribution parameters.

[0168] The update unit is used to update the probability distribution parameters and the corresponding circuit parameters using the quantum circuit obtained by sampling when the number of samplings in one iteration is equal to the preset sampling domain value.

[0169] The determining unit is used to determine the candidate quantum circuit module combination with the highest probability as the target candidate quantum circuit module combination when the iteration meets the preset iteration stopping condition, based on the current probability distribution parameters and the probability distribution model.

[0170] In some possible embodiments of the present invention, the updating unit may be specifically used for:

[0171] For each quantum circuit obtained by sampling within one iteration, the corresponding circuit parameters are obtained from the current parameter pool;

[0172] Based on the obtained circuit parameters, the gradient of the probability distribution parameters and the gradient of the corresponding circuit parameters are obtained using the quantum circuit.

[0173] In response to the number of samples in one iteration being equal to the preset sampling range value, the probability distribution parameters and the line parameters in the parameter pool are updated.

[0174] In some possible embodiments of the present invention, the updating unit may also be specifically used for:

[0175] Based on the obtained circuit parameters, the quantum circuit is run and measured to determine the value of the loss function corresponding to the quantum circuit.

[0176] Using the function value, calculate the gradient of the probability distribution parameter and the gradient of the corresponding line parameter.

[0177] In some possible embodiments of the present invention, the updating unit may also be specifically used for:

[0178] Calculate the gradient of the corresponding line parameters using the following formula:

[0179]

[0180] in, Let θ be the gradient of the line parameters, and θ be the line parameters. For loss function, The quantum circuit obtained from sampling, Let be a vector consisting of the indices of the candidate quantum circuit modules included in the quantum circuit, and α be a probability distribution parameter. It is a probability distribution model;

[0181] Calculate the gradient of the probability distribution parameters using the following formula:

[0182]

[0183] in, a represents the layer number of the quantum circuit, and i,j represents the numbers of the candidate quantum circuit modules.

[0184] In some possible embodiments of the present invention, the determining module 303 may be specifically used for:

[0185] The candidate quantum circuit modules in the target candidate quantum circuit module combination are sequentially connected to obtain the target quantum circuit, wherein the target quantum circuit contains the circuit parameters currently corresponding to the target candidate quantum circuit module combination;

[0186] Based on the target quantum circuit, the parameters of the target circuit are obtained using a variable quantum algorithm;

[0187] Based on the target circuit parameters and the control method corresponding to the combination of the target quantum circuit modules, the quantum state transmission scheme corresponding to the target spin chain is determined.

[0188] As can be seen, this embodiment of the invention first uses the obtained control bits and the Hamiltonian corresponding to the target spin chain to construct all candidate quantum circuit modules. Then, it searches among all candidate quantum circuit modules to obtain the target candidate quantum circuit module combination. Based on the target candidate quantum circuit module combination and its current corresponding circuit parameters, it constructs the target quantum circuit and uses the target quantum circuit to determine the quantum state transmission scheme corresponding to the target spin chain. This can facilitate the determination of quantum state transmission schemes using quantum computing, promoting the further development of quantum state transmission applications.

[0189] This invention also provides a storage medium storing a computer program, wherein the computer program is configured to implement the steps in any of the above method embodiments when running.

[0190] Specifically, in this embodiment, the storage medium can be configured to store a computer program for implementing the following steps:

[0191] S201: Using the obtained control bits and Hamiltonian corresponding to the target spin chain, construct all candidate quantum circuit modules, wherein the control bits are the quantum bits participating in the control among the quantum bits corresponding to the target spin chain, and all candidate quantum circuit modules include circuit parameters;

[0192] S202: Search among all the candidate quantum circuit modules to obtain the target candidate quantum circuit module combination;

[0193] S203: Based on the target candidate quantum circuit module combination and the circuit parameters corresponding to the target candidate quantum circuit module combination, construct a target quantum circuit, and use the target quantum circuit to determine the quantum state transmission scheme corresponding to the target spin chain.

[0194] This invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the steps in any of the above method embodiments.

[0195] Specifically, the aforementioned electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the aforementioned processor, and the input / output device is connected to the aforementioned processor.

[0196] Specifically, in this embodiment, the processor described above can be configured to implement the following steps via a computer program:

[0197] S201: Using the obtained control bits and Hamiltonian corresponding to the target spin chain, construct all candidate quantum circuit modules, wherein the control bits are the quantum bits participating in the control among the quantum bits corresponding to the target spin chain, and all candidate quantum circuit modules include circuit parameters;

[0198] S202: Search among all the candidate quantum circuit modules to obtain the target candidate quantum circuit module combination;

[0199] S203: Based on the target candidate quantum circuit module combination and the circuit parameters corresponding to the target candidate quantum circuit module combination, construct a target quantum circuit, and use the target quantum circuit to determine the quantum state transmission scheme corresponding to the target spin chain.

[0200] The above description, based on the embodiments shown in the figures, details the structure, features, and effects of the present invention. The above description is only a preferred embodiment of the present invention, but the present invention is not limited to the scope of implementation shown in the figures. Any changes made in accordance with the concept of the present invention, or equivalent embodiments modified to have equivalent changes, that do not exceed the spirit covered by the specification and figures, should be within the protection scope of the present invention.

Claims

1. A method for determining a quantum state transport scheme, characterized in that, The method includes: Using the obtained control bits and Hamiltonian corresponding to the target spin chain, all candidate quantum circuit modules are constructed, wherein the control bits are the quantum bits participating in the control among the quantum bits corresponding to the target spin chain, and all candidate quantum circuit modules include circuit parameters; In response to the fact that the number of samplings in one iteration is less than a preset sampling threshold, the constructed probability distribution model is used to sample the combination of candidate quantum circuit modules constructed from all the candidate quantum circuit modules to obtain the quantum circuit corresponding to the sampled combination of candidate quantum circuit modules. The probability distribution model is used to determine the sampling probability of each of the candidate quantum circuit module combinations under the current probability distribution parameters. In response to the sampling number in one iteration being equal to the preset sampling domain value, the probability distribution parameters and the corresponding circuit parameters are updated using the quantum circuit obtained from the sampling. When the iteration meets the preset iteration stopping condition, the candidate quantum circuit module combination with the highest probability is determined according to the current probability distribution parameters and the probability distribution model, and is used as the target candidate quantum circuit module combination. The candidate quantum circuit modules in the target candidate quantum circuit module combination are sequentially connected to obtain the target quantum circuit, wherein the target quantum circuit contains the circuit parameters currently corresponding to the target candidate quantum circuit module combination; Based on the target quantum circuit, the parameters of the target circuit are obtained using a variable quantum algorithm; Based on the target circuit parameters and the control methods corresponding to the combination of target candidate quantum circuit modules, the quantum state transmission scheme corresponding to the target spin chain is determined.

2. The method according to claim 1, characterized in that, The process involves using the obtained control bits and the Hamiltonian corresponding to the target spin chain to construct all candidate quantum circuit modules, including: Based on the obtained control bits, determine the control method of the control parameters; Using the Hamiltonian corresponding to the target spin chain and the determined control method, all candidate quantum circuit modules are constructed.

3. The method according to claim 2, characterized in that, The response is that the number of samples within one iteration is equal to the preset sampling threshold. Using the quantum circuit obtained from the sampling, the probability distribution parameters and the corresponding circuit parameters are updated, including: For each quantum circuit obtained by sampling within one iteration, the corresponding circuit parameters are obtained from the current parameter pool; Based on the obtained circuit parameters, the gradient of the probability distribution parameters and the gradient of the corresponding circuit parameters are obtained using the quantum circuit. In response to the number of samples in one iteration being equal to the preset sampling range value, the probability distribution parameters and the line parameters in the parameter pool are updated.

4. The method according to claim 3, characterized in that, The process of obtaining the gradients of the probability distribution parameters and the line parameters using the quantum circuit based on the obtained circuit parameters includes: Based on the obtained circuit parameters, the quantum circuit is run and measured to determine the value of the loss function corresponding to the quantum circuit. Using the function value, calculate the gradient of the probability distribution parameter and the gradient of the corresponding line parameter.

5. The method according to claim 4, characterized in that, The step of using the function value to calculate the gradient of the probability distribution parameter and the gradient of the corresponding line parameter includes: Calculate the gradient of the corresponding line parameters using the following formula: in, The gradient of the line parameters, For line parameters, For loss function, The quantum circuit obtained from sampling, This is a vector consisting of the indices of the candidate quantum circuit modules included in the quantum circuit. These are the probability distribution parameters. It is a probability distribution model; Calculate the gradient of the probability distribution parameters using the following formula: in, , The layer numbering for the quantum circuit. This is the numbering for the candidate quantum circuit modules.

6. A device for determining a quantum state transmission scheme, characterized in that, The device includes: A construction module is used to construct all candidate quantum circuit modules using the obtained control bits and the Hamiltonian corresponding to the target spin chain, wherein the control bits are the quantum bits participating in the control among the quantum bits corresponding to the target spin chain, and all candidate quantum circuit modules include circuit parameters; The module obtains a quantum circuit by sampling a combination of candidate quantum circuit modules constructed from all the candidate quantum circuit modules, in response to the number of samplings in one iteration being less than a preset sampling threshold. The sampling is performed using a constructed probability distribution model to obtain the quantum circuit corresponding to each sampled combination. The probability distribution model is used to determine the sampling probability of each candidate quantum circuit module combination under the current probability distribution parameters. In response to the number of samplings in one iteration being equal to the preset sampling threshold, the sampling quantum circuit is used to update the probability distribution parameters and the corresponding circuit parameters. When the iteration meets a preset iteration stop condition, the candidate quantum circuit module combination with the highest probability is determined as the target candidate quantum circuit module combination based on the current probability distribution parameters and the probability distribution model. A determining module is used to sequentially connect the candidate quantum circuit modules in the target candidate quantum circuit module combination to obtain the target quantum circuit, wherein the target quantum circuit contains the circuit parameters currently corresponding to the target candidate quantum circuit module combination; based on the target quantum circuit, the target circuit parameters are obtained using a variable quantum algorithm; and the quantum state transmission scheme corresponding to the target spin chain is determined according to the target circuit parameters and the control mode corresponding to the target candidate quantum circuit module combination.

7. A storage medium, characterized in that, The storage medium stores a computer program, wherein the computer program is configured to implement the method described in any one of claims 1 to 5 when it is run.

8. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to implement the method of any one of claims 1 to 5.

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