# US 2025/0209367 A1 · System and method for simulating quantum computer using tensor networks and related methods

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 2025/0209367 A1
- Document ID: US20250209367A1
- Status: Published application
- Kind: A1
- Application number: 18/399,168
- Filed: 2023-12-28
- Published: 2025-06-26
- Earliest claimed: 2023-12-20
- Assignees: Multiverse Computing S.L.
- Applicants: Multiverse Computing S.L.
- Inventors: Roman ORÚS; Saeed JAHROMI; Sukhbinder SINGH; Siddhartha PATRA
- Web page: https://patentgrep.com/patent/US20250209367A1

## CPC

- G06N 10/80: Quantum programming, e.g. interfaces, languages or software-development kits for creating or handling programs capable of running on quantum computers; Platforms for simulating or accessing quantum computers, e.g. cloud-based quantum computing
- G06N 10/20: Models of quantum computing, e.g. quantum circuits or universal quantum computers
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

A computer-implemented method and system for simulating quantum computations using a lattice-free tensor network simulation that adapts dynamically to an interaction pattern in the quantum computation. The method includes initializing an initial state, applying a quantum gate on two quantum bits, generating a connection in a network structure, truncating numerical values using a mathematical decomposition and an update process, computing an entropy measure for all connections, truncating the connections with the lowest entropy measure to a dimensional parameter, and computing expectation values of observables at the end of the simulation. The system includes modules and submodules for performing these steps.

## Claims

### Claim 1

A computer-implemented method, the method including the following steps:
receiving a quantum computation to be simulated;
implementing a lattice-free tensor network simulation based on the received quantum computation, wherein the tensor network simulation adapts dynamically to an interaction pattern in the quantum computation;
initializing an initial state in the tensor network simulation;
applying a quantum gate on two quantum bits in the tensor network simulation, wherein the application of the quantum gate generates a connection in a network structure and truncates numerical values in the network structure using a mathematical decomposition and an update process such that the number of numerical values is smaller than a numerical parameter D;
computing an entropy measure for all connections in the network structure;
truncating the connections with the lowest entropy measure to a dimensional parameter, such that the number of bond indices in the network structure is always smaller than a numerical parameter K; and
computing expectation values of observables at the end of the simulation of the quantum computation, wherein the computation of the expectation values involves quantum bits determined in a submodule determining the quantum bits and uses an approximation method.

### Claim 2 (depends on 1)

The method of claim 1, wherein the quantum computation is a quantum processing of data.

### Claim 3 (depends on 1)

The method of claim 1, wherein the tensor network simulation is an adaptive simulation approach that does not rely on a geometric assumption.

### Claim 4 (depends on 1)

The method of claim 1, wherein the initial state is an initial product quantum state.

### Claim 5 (depends on 1)

The method of claim 1, wherein the quantum gate is a quantum 2-qubit gate.

### Claim 6 (depends on 1)

The method of claim 1, wherein the quantum bits are arbitrary quantum bits.

### Claim 7 (depends on 1)

The method of claim 1, wherein the connection is a new link in the network structure.

### Claim 8 (depends on 1)

The method of claim 1, wherein the numerical values are the largest singular values of a singular value decomposition.

### Claim 9 (depends on 1)

The method of claim 1, wherein the mathematical decomposition is a singular value decomposition.

### Claim 10 (depends on 1)

The method of claim 1, wherein the update process is a simple tensor update.

### Claim 11 (depends on 1)

The method of claim 1, wherein the entropy measure is a local correlation entropy.

### Claim 12 (depends on 1)

The method of claim 1, wherein the dimensional parameter is bond dimension one.

### Claim 13 (depends on 1)

The method of claim 1, wherein the computation of the expectation values uses a mean-field approximation.

### Claim 14

A computational system, comprising:
a module that receives a quantum computation to be simulated;
a module that implements a lattice-free tensor network simulation based on the received quantum computation, wherein the tensor network simulation adapts dynamically to an interaction pattern in the quantum computation;
an initialization submodule that initializes an initial state in the tensor network simulation;
a gate submodule that applies a quantum gate on two quantum bits in the tensor network simulation, wherein the application of the quantum gate generates a connection in a network structure and truncates numerical values in the network structure using a mathematical decomposition and an update process such that the number of numerical values is smaller than a numerical parameter D;
a submodule that computes an entropy measure for all connections in the network structure;
a submodule that truncates the connections with the lowest entropy measure to a dimensional parameter, such that the number of bond indices in the network structure is always smaller than a numerical parameter K; and
a module that computes expectation values of observables at the end of the simulation of the quantum computation, wherein the computation of the expectation values involves quantum bits determined in a submodule determining the quantum bits and uses an approximation method.

### Claim 15 (depends on 14)

The system of claim 14, wherein the quantum computation is a quantum processing of data.

### Claim 16 (depends on 14)

The system of claim 14, wherein the tensor network simulation is an adaptive simulation approach that does not rely on a geometric assumption.

### Claim 17 (depends on 14)

The system of claim 14, wherein the initial state is an initial product quantum state.

### Claim 18 (depends on 14)

The system of claim 14, wherein the quantum gate is a quantum 2-qubit gate.

### Claim 19 (depends on 14)

The system of claim 14, wherein the quantum bits are arbitrary quantum bits.

### Claim 20 (depends on 14)

The system of claim 14, wherein the computation of the expectation values uses a mean-field approximation.