System, method and related method for simulating quantum computer by using tensor network
The lattice-free tensor network simulation addresses the challenge of simulating quantum systems by dynamically adapting to interaction patterns, improving efficiency and accuracy in quantum computing simulations.
Patent Information
- Application Number
- JP2024225849
- Authority / Receiving Office
- JP · JP
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2023-12-20
- Filing Date
- 2024-12-20
- Publication Date
- 2025-07-02
AI Technical Summary
Simulating quantum systems on classical computers is challenging due to exponentially growing state spaces and inefficiencies in conventional methods that rely on geometric assumptions, leading to inaccuracies.
A lattice-free tensor network simulation that dynamically adapts to interaction patterns in quantum computing, involving initialization of an initial state, application of quantum gates to qubits, calculation of entropy measures, and truncation of connections with the lowest entropy to dimensional parameters, followed by calculation of observable values.
Accurately simulates quantum computing without geometric assumptions, enhancing efficiency and accuracy by dynamically adapting to interaction patterns.
Smart Images
Figure 2025098998000001_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of quantum computing, and more particularly, to a system and method for simulating a quantum computer using a tensor network.
Background Art
[0002] Quantum computing is a rapidly evolving field that utilizes the principles of quantum mechanics to perform computations. Quantum computers have the potential to solve certain types of problems far more efficiently than classical computers. However, simulating a quantum system on a classical computer is a challenging task due to the exponentially growing state space with the number of qubits (quantum bits). Conventional simulation methods often rely on specific geometric assumptions that may not always accurately represent the quantum system being simulated. Moreover, these methods may lead to inefficiencies and inaccuracies during simulation as they are not well-suited to the specific calculations being performed. Therefore, there is a need for improved methods for simulating quantum systems on classical computers.
Summary of the Invention
Means for Solving the Problems
[0003] According to an embodiment, a computer-implemented method for simulating quantum computing using a lattice-free tensor network is provided. The method includes receiving a quantum computing to be simulated and performing a tensor network simulation that dynamically adapts to an interaction pattern in the quantum computing. An initial state is initialized in the tensor network simulation, and quantum gates are applied to two qubits to generate connections within the network structure, and numerical values are truncated using a mathematical decomposition and update process. An entropy measure is calculated for all connections within the network structure, and the connection having the lowest entropy measure is truncated to a dimensional parameter. An expected value of an observable is calculated at the end of the simulation using an approximation method with qubits determined within a submodule.
[0004] According to another embodiment, a computer computing system for simulating quantum computing using a lattice-free tensor network is provided. The system includes modules for receiving a quantum computing, performing a tensor network simulation, initializing an initial state, applying quantum gates to two qubits, calculating an entropy measure for all connections within the network structure, truncating the connection having the lowest entropy measure to a dimensional parameter, and calculating an expected value of an observable at the end of the simulation. The calculation of the expected value requires qubits determined within a submodule and uses an approximation method.
Brief Description of the Drawings
[0005]
Figure 1
Figure 1A
Figure 1B
Figure 1C
Figure 1D
Figure 1E
Figure 1F
Figure 1G
Figure 1H
Figure 2
Figure 2A
Figure 2B
Embodiments for Carrying Out the Invention
[0006] Steps 100 and sub-step 100-a relate to a process of receiving a specific quantum calculation for simulation. This process requires a quantum computing and simulation system. The quantum calculation, which can also be understood as the quantum processing of data (Claim 2), functions as an input to the simulation system. The simulation system is designed to simulate this quantum calculation and thus receives the quantum calculation as an input.
[0007] The quantum calculation provides a specific quantum processing of data that functions as the required input for the simulation system. Next, the simulation system receives this quantum calculation and performs a simulation. Since the goal of the simulation system is to accurately simulate the quantum calculation, it is necessary to receive a specific quantum calculation as an input.
[0008] Regarding the details, definitions, parameters, mechanisms, structures, functions, characteristics, mathematical compositions, metrics, measurement methods, and other forms of the quantum computing and simulation system, quantum calculation is a form of calculation that utilizes the principles of quantum mechanics. It involves data processing using qubits, i.e., quantum bits, which can exist in multiple states simultaneously due to the superposition principle. As a result, quantum calculation can process a vast number of possible events simultaneously.
[0009] The simulation system is a computer system designed to simulate quantum calculations. It utilizes a lattice-free tensor network simulation that dynamically adapts to interaction patterns in quantum calculations (Claim 1). Due to this dynamic adaptation, the simulation system can accurately simulate quantum calculations without the need for any geometric assumptions. The simulation system receives the quantum calculation as an input, initializes the initial state in the tensor network simulation, applies quantum gates to two qubits, and performs several other operations to simulate the quantum calculation.
[0010] Steps 102 and sub-step 102-a relate to the implementation of the received lattice-free tensor network simulation based on quantum computing. This process requires a quantum computing and simulation system. The quantum computing that functions as an input is processed by the simulation system. The simulation system is designed to conform to the interaction pattern in quantum computing and thus implements the lattice-free tensor network simulation.
[0011] Quantum computing provides a specific interaction pattern to the simulation system. The simulation system implements a lattice-free tensor network simulation to simulate the quantum computing. Since the goal of the simulation system is to conform to the interaction pattern in quantum computing, it is necessary to implement the lattice-free tensor network simulation.
[0012] Regarding the details, definitions, parameters, mechanisms, structures, functions, characteristics, mathematical compositions, metrics, measurement methods, and other forms of the quantum computing and simulation system, quantum computing is a form of computing that utilizes the principles of quantum mechanics. It requires data processing using qubits, i.e., quantum bits, which can exist in multiple states simultaneously due to the superposition principle. As a result, quantum computing can process a vast number of possible events simultaneously.
[0013] The simulation system is a computer system designed to simulate quantum computing. It utilizes a lattice-free tensor network simulation that dynamically conforms to the interaction pattern in quantum computing. Due to this dynamic conformity, the simulation system can accurately simulate quantum computing without the need for any geometric assumptions. The simulation system receives quantum computing as an input, initializes the initial state in the tensor network simulation, applies quantum gates to two qubits, and performs several other operations to simulate the quantum computing.
[0014] Step 104 and sub-step 104-a relate to the initialization of the initial state in the tensor network simulation. This process requires an initial state and a simulation system. The initial state, which functions as the starting point of the simulation, is set by the simulation system. The simulation system is designed to simulate quantum computing and thus initializes the initial state in the tensor network simulation.
[0015] The initial state provides starting conditions for the simulation system. The simulation system initializes the initial state to start the simulation. Since the goal of the simulation system is to simulate quantum computing, it is necessary to initialize the initial state in the tensor network simulation.
[0016] Regarding the details, definitions, parameters, mechanisms, structures, functions, characteristics, mathematical compositions, metrics, measurement methods, and other forms of the initial state and the simulation system, the initial state is a state that functions as a starting point for the simulation. It involves setting the initial conditions for the quantum bits, i.e., qubits, used in quantum computing.
[0017] The simulation system is a computer system designed to simulate quantum computing. It utilizes a lattice-free tensor network simulation that dynamically adapts to the interaction pattern in quantum computing. Due to this dynamic adaptation, the simulation system can simulate quantum computing without the need for any geometric assumptions. The simulation system receives quantum computing as input, initializes the initial state in the tensor network simulation, applies quantum gates to two quantum bits, and performs several other operations to simulate quantum computing.
[0018] Step 106 and sub - steps 106 - a and 106 - b relate to the application of quantum gates to two qubits in a tensor network simulation. This process requires a quantum gate, two qubits, i.e., qubits, and a simulation system. The quantum gate that performs a specific operation on the qubits is applied by the simulation system. The simulation system is designed to simulate quantum computing and thus applies quantum gates to two qubits in a tensor network simulation.
[0019] The quantum gate performs a specific operation on two qubits. The simulation system applies the quantum gate to two qubits in order to simulate the operation of the quantum gate. Since the goal of the simulation system is to simulate quantum computing, it is necessary to apply quantum gates to two qubits in a tensor network simulation.
[0020] Regarding the details, definitions, parameters, mechanisms, structures, functions, characteristics, mathematical constitutions, metrics, measurement methods, and other forms of quantum gates, qubits, and simulation systems, a quantum gate is a gate that performs a specific operation on a qubit. It involves the skillful manipulation of the state of a qubit that can exist in multiple states simultaneously according to the superposition principle. Thereby, a quantum gate can perform operations simultaneously.
[0021] A simulation system is a computer system designed to simulate quantum computing. It utilizes a lattice-free tensor network simulation that dynamically adapts to interaction patterns in quantum computing. Due to this dynamic adaptation, the simulation system can simulate quantum computing without any need for geometric assumptions. The simulation system receives quantum computing as input, initializes the initial state in the tensor network simulation, applies quantum gates to two qubits, and performs several other operations to simulate quantum computing.
[0022] Step 108 and sub-steps 108-a, 108-b, 108-c, and 108-d relate to the application of quantum gates to two qubits in the tensor network simulation, thereby generating connections within the network structure and using mathematical decomposition and update processes to truncate numerical values within the network structure. This process requires quantum gates, two qubits, i.e., qubits, connections, numerical values, mathematical decomposition, update processes, and the simulation system. Quantum gates that perform specific operations on qubits are applied by the simulation system. The simulation system is designed to simulate quantum computing and thus applies quantum gates to two qubits in the tensor network simulation, generates connections, and truncates numerical values.
[0023] Quantum gates perform specific operations on two qubits. The simulation system applies quantum gates to two qubits to simulate the operation of the quantum gates. Since the goal of the simulation system is to simulate quantum computing, it is necessary to apply quantum gates to two qubits in the tensor network simulation, generate connections, and truncate numerical values.
[0024] For details, definitions, parameters, mechanisms, structures, functions, characteristics, mathematical compositions, metrics, measurement methods, and other forms of quantum gates, qubits, connections, numerical values, mathematical decompositions, update processes, and simulation systems, a quantum gate is a gate that performs specific operations on qubits. It involves skillful manipulation of the states of qubits, which can exist in multiple states simultaneously according to the superposition principle. As a result, quantum gates can execute operations simultaneously.
[0025] A simulation system is a computer system designed to simulate quantum computing. It utilizes a lattice-free tensor network simulation that dynamically adapts to interaction patterns in quantum computing. Due to this dynamic adaptation, the simulation system can simulate quantum computing without any need for geometric assumptions. The simulation system receives quantum computing as input, initializes the initial state in the tensor network simulation, applies quantum gates to two qubits, generates connections, truncates numerical values, and performs several other operations to simulate quantum computing.
[0026] Step 110 and sub-step 110-a relate to the calculation of entropy measures for all connections within the network structure. This process requires entropy measures, connections, and the simulation system. The entropy measure, which quantifies the amount of functional impairment or irregularity of the connections, is calculated by the simulation system. The simulation system is designed to simulate quantum computing and thus calculates the entropy measures for all connections within the network structure.
[0027] The entropy measurement quantifies the amount of functional impairment or irregularity of the connection part. The simulation system calculates the entropy measurement for all connection parts in order to quantify the amount of functional impairment or irregularity of the connection part. Since the goal of the simulation system is to simulate quantum computing, it is necessary to calculate the entropy measurement for all connection parts within the network structure.
[0028] Regarding the details, definitions, parameters, mechanisms, structures, functions, characteristics, mathematical compositions, metrics, measurement methods, and other forms of the entropy measurement, connection part, and simulation system, the entropy measurement is a measurement quantity that quantifies the amount of functional impairment or irregularity of the connection part. It requires the calculation of specific values for each connection part that can be used to quantify the functional impairment or irregularity of the connection part.
[0029] The simulation system is a computer system designed to simulate quantum computing. It utilizes a lattice-free tensor network simulation that dynamically adapts to interaction patterns in quantum computing. Due to this dynamic adaptation, the simulation system can simulate quantum computing without any need for geometric assumptions. The simulation system receives quantum computing as input, initializes the initial state in the tensor network simulation, applies quantum gates to two quantum bits, generates connection parts, calculates the entropy measurement for all connection parts, and performs several other operations to simulate quantum computing.
[0030] Steps 112 and sub-step 112-a relate to truncating a connection part with the lowest entropy measurement quantity to dimensional parameters. This process requires a connection part, an entropy measurement quantity, dimensional parameters, and a simulation system. A connection part having a certain amount of dysfunction or irregularity quantified by the entropy measurement quantity is truncated by the simulation system. The simulation system is designed to simulate quantum computing, and thus truncates the connection part with the lowest entropy measurement quantity to the dimensional parameters.
[0031] The connection part has a certain amount of dysfunction or irregularity quantified by the entropy measurement quantity. The simulation system truncates the connection part with the lowest entropy measurement quantity to the dimensional parameters in order to reduce the complexity of the network structure. Since the goal of the simulation system is to simulate quantum computing, it is necessary to truncate the connection part with the lowest entropy measurement quantity to the dimensional parameters.
[0032] Regarding the details, definitions, parameters, mechanisms, structures, functions, characteristics, mathematical compositions, metrics, measurement methods, and other forms of the connection part, entropy measurement quantity, dimensional parameters, and simulation system, a connection part having a certain amount of dysfunction or irregularity quantified by the entropy measurement quantity is a connection within the network structure. The dimensional parameter is the value to which the connection part is truncated.
[0033] A simulation system is a computer system designed to simulate quantum computing. It utilizes a lattice-free tensor network simulation that dynamically adapts to interaction patterns in quantum computing. This dynamic adaptation enables the simulation system to simulate quantum computing without any need for geometric assumptions. The simulation system receives quantum computing as input, initializes an initial state in the tensor network simulation, applies quantum gates to two qubits, generates connections, calculates an entropy measurement quantity for all connections, truncates the connection with the lowest entropy measurement quantity to a dimensional parameter, and performs several other operations to simulate quantum computing.
[0034] Steps 114 and sub-step 114-a relate to the calculation of the expected value of an observable at the end of the simulation of quantum computing. This process requires the expected value, the observable, and the simulation system. The simulation system calculates the expected value that quantifies the average result of the measurement values of the observable. The simulation system is designed to simulate quantum computing, and thus calculates the expected value of the observable at the end of the simulation.
[0035] The expected value quantifies the average result of the measurement values of the observable. The simulation system calculates the expected value of the observable to quantify these average results. Since the goal of the simulation system is to simulate quantum computing, it is necessary to calculate the expected value of the observable at the end of the simulation.
[0036] Regarding the details, definitions, parameters, mechanisms, structures, functions, characteristics, mathematical compositions, metrics, measurement methods, and other forms of the expected value, observable, and simulation system, the expected value is a value that quantifies the average result of the measured values of the observable. They require the calculation of specific values for each observable, and using this calculation, the average result of the measured values of the observable can be quantified.
[0037] The simulation system is a computer system designed to simulate quantum computing. It utilizes a lattice-free tensor network simulation that dynamically adapts to the interaction pattern in quantum computing. Due to this dynamic adaptation, the simulation system can simulate quantum computing without the need for any geometric assumptions. The simulation system receives quantum computing as input, initializes the initial state in the tensor network simulation, applies quantum gates to two qubits, generates connections, calculates the entropy measurement quantity for all connections, truncates the connection with the lowest entropy measurement quantity to the dimensional parameter, and finally calculates the expected value of the observable at the end of the simulation.
[0038] The quantum computing simulation system numbered 200 is designed to simulate quantum computing. This system consists of two main components. The first one, known as the quantum processor (202), is responsible for receiving and processing quantum computing. It consists of two sub-components. The quantum state initiator (202-a) sets the initial state in the tensor network simulation. This initial state is an initial generated (product) quantum state. The quantum gate operator (202-b) applies quantum gates to two qubits in the tensor network simulation. By applying this quantum gate, connections are generated within the network structure, and mathematical decomposition and update processes are used to truncate the numerical values within the network structure.
[0039] The second major component of the system is the tensor network simulator (204). This component performs a lattice-free tensor network simulation based on the received quantum computation. The tensor network simulation dynamically adapts to the interaction pattern in the quantum computation. This component also includes two sub-components. The network structure manager (204-a) manages the connections within the network structure, calculates the entropy measurement quantity for all connections, and truncates the connection with the lowest entropy measurement quantity to the dimensional parameter. The expected value calculator (204-b) calculates the expected value of the observable at the end of the simulation of the quantum computation. The calculation of these expected values requires the qubits determined within the sub-module and uses an approximation method.
[0040] The quantum computation simulation system (200) starts its operation together with the quantum processor (202) and receives the quantum computation to be simulated. When the quantum computation is received, the quantum state initiator (202-a) sets the initial state in the tensor network simulation. After the initialization of the initial state, the quantum gate operator (202-b) applies a quantum gate to two qubits in the tensor network simulation. By applying this quantum gate, connections are generated within the network structure, and a mathematical decomposition and update process is used to truncate the numerical values within the network structure.
[0041] Next, the tensor network simulator (204) performs a lattice-free tensor network simulation based on the received quantum computation. The network structure manager (204-a) manages the connections within the network structure, calculates the entropy measurement quantity for all connections, and truncates the connection with the lowest entropy measurement quantity to the dimensional parameter. Finally, the expected value calculator (204-b) calculates the expected value of the observable at the end of the simulation of the quantum computation. The calculation of these expected values requires the qubits determined within the sub-module and uses an approximation method.
[0042] The quantum processor numbered 202 is part of a quantum computing simulation system. It is responsible for receiving and processing quantum computations. This component consists of two sub-components. The quantum state initiator (202-a) sets the initial state in the tensor network simulation. This initial state is the initial generated quantum state. The quantum gate operator (202-b) applies quantum gates to two qubits in the tensor network simulation. By applying this quantum gate, connections are generated within the network structure, and mathematical decomposition and update processes are used to truncate the numerical values within the network structure.
[0043] The quantum processor (202) begins its operation by receiving the quantum computation to be simulated. When the quantum computation is received, the quantum state initiator (202-a) sets the initial state in the tensor network simulation. After the initialization of the initial state, the quantum gate operator (202-b) applies quantum gates to two qubits in the tensor network simulation. By applying this quantum gate, connections are generated within the network structure, and mathematical decomposition and update processes are used to truncate the numerical values within the network structure.
[0044] In summary, the quantum processor (202) is responsible for receiving and processing quantum computations. It consists of a quantum state initiator (202-a) that sets the initial state and a quantum gate operator (202-b) that applies quantum gates to two qubits. These sub-components cooperate to ensure the simulation of quantum computations.
[0045] The tensor network simulator numbered 204 is part of a quantum computing simulation system. It performs a lattice-free tensor network simulation based on the received quantum computation. The tensor network simulation dynamically adapts to the interaction pattern in the quantum computation.
[0046] This component includes two sub-components. The network structure manager (204-a) manages the connections within the network structure, calculates an entropy measure for all connections, and truncates the connection with the lowest entropy measure to the dimensional parameter. This process ensures that the number of coupling indices within the network structure is always smaller than the numerical parameter K.
[0047] The expected value calculator (204-b) calculates the expected value of the observable at the end of the quantum calculation simulation. The calculation of these expected values requires qubits determined within the sub-module and uses an approximation method.
[0048] The tensor network simulator (204) performs a lattice-free tensor network simulation based on the received quantum calculation. The network structure manager (204-a) manages the connections within the network structure, calculates an entropy measure for all connections, and truncates the connection with the lowest entropy measure to the dimensional parameter. Finally, the expected value calculator (204-b) calculates the expected value of the observable at the end of the quantum calculation simulation. The calculation of these expected values requires qubits determined within the sub-module and uses an approximation method.
[0049] In summary, the tensor network simulator (204) is responsible for performing the lattice-free tensor network simulation. It consists of a network structure manager (204-a) that manages the connections within the network structure and an expected value calculator (204-b) that calculates the expected value of the observable at the end of the simulation.
Claims
1. 1. A computer-implemented method comprising: receiving a quantum computation to be simulated; performing a lattice-free tensor network simulation based on the received quantum computation, the tensor network simulation dynamically adapting to interaction patterns in the quantum computation; initializing an initial state in the tensor network simulation; applying a quantum gate to two qubits in the tensor network simulation, the application of the quantum gate generating connections in a network structure and using a mathematical decomposition and update process to truncate numerical values in the network structure such that the number of numerical values is less than a numerical parameter D; calculating an entropy measure for every connection in the network structure; truncating the connections with the lowest entropy measures to a dimension parameter K such that the number of connection indices in the network structure is always smaller than a numerical parameter K; and at the end of the simulation of the quantum computation, calculating an expectation value of an observable, the calculation of the expectation value requiring the quantum bit determined in a submodule that determines a quantum bit and using an approximation method.
2. 2. The method of claim 1, wherein the quantum computation is a quantum processing of data.
3. 2. The method of claim 1, wherein the tensor network simulation is an adaptive simulation technique that is independent of geometric assumptions.
4. 2. The method of claim 1, wherein the initial state is an initially generated quantum state.
5. 2. The method of claim 1, wherein the quantum gate is a quantum two-qubit gate.
6. 2. The method of claim 1, wherein the quantum bit is an arbitrary quantum bit.
7. 2. The method of claim 1, wherein the connection is a new link within the network structure.
8. 2. The method of claim 1, wherein the numerical value is a maximum singular value of a singular value decomposition.
9. 2. The method of claim 1, wherein the mathematical decomposition is a singular value decomposition.
10. 2. The method of claim 1, wherein the update process is a simple tensor update.
11. 2. The method of claim 1, wherein the entropy measure is local correlation entropy.
12. 2. The method of claim 1, wherein the dimensional parameters are joint dimensional parameters.
13. 2. The method of claim 1, wherein said calculation of said expectation value uses a mean field approximation.
14. a module for receiving a quantum computation to be simulated; a module for performing a lattice-free tensor network simulation based on the received quantum computation, the tensor network simulation dynamically adapting to interaction patterns in the quantum computation; an initialization submodule for initializing an initial state in the tensor network simulation; a gating submodule that applies a quantum gate to two qubits in the tensor network simulation, the application of the quantum gate generating connections in a network structure and using a mathematical decomposition and update process to truncate numerical values in the network structure such that the number of numerical values is less than a numerical parameter D; a sub-module for calculating an entropy measure for every connection in said network structure; a submodule for truncating the connections having the lowest entropy measures to a dimension parameter K such that the number of connection indices in the network structure is always smaller than a numerical parameter K; and a module for calculating an expectation value of an observable at the end of the simulation of the quantum computation, the calculation of the expectation value requiring the quantum bits determined in a submodule for determining quantum bits and using an approximation method.
15. 15. The system of claim 14, wherein the quantum computation is quantum processing of data.
16. 15. The system of claim 14, wherein the tensor network simulation is an adaptive simulation technique that is independent of geometric assumptions.
17. 15. The system of claim 14, wherein the initial state is an initially generated quantum state.
18. 15. The system of claim 14, wherein the quantum gate is a quantum two-qubit gate.
19. 15. The system of claim 14, wherein the quantum bit is an arbitrary quantum bit.
20. 15. The system of claim 14, wherein the calculation of the expectation value uses a mean field approximation.