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Sign-problem free quantum stochastic series expansion algorithm on a quantum computer

Physics

Sign-problem free quantum stochastic series expansion algorithm on a quantum computer

K. C. Tan, D. Bhowmick, et al.

Discover a groundbreaking quantum implementation of the Stochastic Series Expansion Monte Carlo method that transforms the handling of the sign problem, as proposed by Kok Chuan Tan, Dhiman Bhowmick, and Pinaki Sengupta. This innovative approach scales linearly with system size, offering new capabilities even in the absence of the sign problem.

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~3 min • Beginner • English
Abstract
A quantum implementation of the Stochastic Series Expansion (SSE) Monte Carlo method is proposed, and is shown to offer significant advantages over classical implementations of SSE. In particular, for problems where classical SSE encounters the sign problem, the cost of implementing a Monte Carlo iteration scales only linearly with system size in quantum SSE, while it may scale exponentially with system size in classical SSE. In cases where classical SSE can be efficiently implemented, quantum SSE still offers an advantage by allowing for more general observables to be measured.
Publisher
npj Quantum Information
Published On
Apr 26, 2022
Authors
Kok Chuan Tan, Dhiman Bhowmick, Pinaki Sengupta
Tags
Quantum Computing
Stochastic Series Expansion
Monte Carlo Method
Sign Problem
Observables
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