A Fourier analysis framework for approximate classical simulations of quantum circuits
Cristina Cirstoiu

TL;DR
This paper introduces a Fourier analysis framework for classically simulating quantum circuits, leveraging harmonic analysis on groups to efficiently approximate output distributions and expectation values, especially for noisy and structured circuits.
Contribution
It develops a unified harmonic analysis approach that extends existing algorithms for simulating quantum circuits, applicable to noisy, parametrized, and random circuits with theoretical guarantees.
Findings
Efficient algorithms for sampling and expectation estimation in noisy circuits with spectral gap.
Sparse Fourier decompositions enable approximation of noiseless circuit mean values.
Framework generalizes to qudit systems and random circuits via group representation theory.
Abstract
What makes a class of quantum circuits efficiently classically simulable on average? I present a framework that applies harmonic analysis of groups to circuits with a structure encoded by group parameters. Expanding the circuits in a suitable truncated multi-path operator basis gives algorithms to evaluate the Fourier coefficients of output distributions or expectation values that are viewed as functions on the group. Under certain conditions, a truncated Fourier series can be efficiently estimated with guaranteed mean-square convergence. For classes of noisy circuits, it leads to algorithms for sampling and mean value estimation under error models with a spectral gap, where the complexity increases exponentially with the gap's inverse and polynomially with the circuit's size. This approach unifies and extends existing algorithms for noisy parametrised or random circuits using Pauli…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Low-power high-performance VLSI design · Quantum Information and Cryptography
