# Simulating Large Quantum Circuits on a Small Quantum Computer.

@article{Peng2020SimulatingLQ, title={Simulating Large Quantum Circuits on a Small Quantum Computer.}, author={Tianyi Peng and Aram Wettroth Harrow and Maris A. Ozols and Xiaodi Wu}, journal={Physical review letters}, year={2020}, volume={125 15}, pages={ 150504 } }

Limited quantum memory is one of the most important constraints for near-term quantum devices. Understanding whether a small quantum computer can simulate a larger quantum system, or execute an algorithm requiring more qubits than available, is both of theoretical and practical importance. In this Letter, we introduce cluster parameters K and d of a quantum circuit. The tensor network of such a circuit can be decomposed into clusters of size at most d with at most K qubits of inter-cluster…

## 44 Citations

Cutting Quantum Circuits to Run on Quantum and Classical Platforms

- Computer Science
- 2022

CutQC is introduced, a scalable hybrid computing approach that distributes a large quantum circuit onto quantum (QPU) and classical platforms (CPU or GPU) for co-processing and demonstrates evaluation of quantum circuits that are larger than the limit of QPU or classical simulation.

High Dimensional Quantum Learning With Small Quantum Computers

- Computer ScienceArXiv
- 2022

A machine learning model is constructed that may be capable of approximating the outputs of the larger circuit with much fewer circuit evaluations, and is applied to the task of digit recognition, using simulated quantum computers much smaller than the data dimension.

Deep Variational Quantum Eigensolver: a divide-and-conquer method for solving a larger problem with smaller size quantum computers

- Physics
- 2020

A divide-and-conquer method for the quantum-classical hybrid algorithm to solve larger problems with small-scale quantum computers, and concatenate variational quantum eigensolver (VQE) with reducing the dimensions of the system.

Quantum Divide and Compute: Exploring the Effect of Different Noise Sources

- Computer Science, PhysicsSN Comput. Sci.
- 2021

This article investigates the impact of different noise sources— readout error, gate error and decoherence—on the success probability of the QDC procedure, and performs detailed noise modeling on the Atos Quantum Learning Machine, allowing to understand tradeoffs and formulate recommendations about which hardware noise sources should be preferentially optimized.

Qurzon: A Prototype for a Divide and Conquer Based Quantum Compiler

- Computer Science
- 2021

When working with algorithms on quantum devices, quantum memory becomes a crucial bottleneck due to low qubit count in NISQ era devices. In this context, the concept of ‘divide and compute’, wherein…

Automatic decomposition of quantum circuits onto small quantum machines

- Physics
- 2019

In the last few years, there has been a great deal of progress in making real world quantum computers, but the number of physical qubits is remains too small to run larger problem sizes on these…

A hybrid algorithm framework for small quantum computers with application to finding Hamiltonian cycles

- Computer ScienceJournal of Mathematical Physics
- 2020

This work presents a framework for hybrid quantum-classical algorithms which utilise quantum computers significantly smaller than the problem size and demonstrates how this approach can be used to enhance Eppstein's algorithm for the cubic Hamiltonian cycle problem, and achieve a polynomial speedup for any ratio of the number of qubits to the size of the graph.

Circuit knitting with classical communication

- Computer Science
- 2022

A positive answer is provided by showing that for circuits containing n nonlocal CNOT gates connecting two circuit parts, the simulation overhead can be reduced from O (9 n) to O (4 n) if one allows for classical information exchange.

Qubit-efficient entanglement spectroscopy using qubit resets

- Computer ScienceQuantum
- 2021

Algorithms for computing the trace of the n-th power of the density operator of a quantum system, Tr(ρn), are developed that use fewer qubits than any previous efficient algorithm while achieving similar performance in the presence of noise, thus enabling spectroscopy of larger quantum systems on NISQ devices.

Parallel quantum simulation of large systems on small NISQ computers

- Computer Science
- 2020

This work provides Cirq and Qiskit code that translates infinite, translationally invariant matrix product state (iMPS) algorithms to finite-depth quantum circuit machines, allowing the representation, optimisation and evolution of arbitrary one-dimensional systems.

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