Gate-Based Quantum Simulation of Gaussian Bosonic Circuits on Exponentially Many Modes

We introduce a framework for simulating, on an ( n + 1 )-qubit quantum computer, the action of a Gaussian bosonic (GB) circuit on a state over 2 n modes. Specifically, we encode the initial bosonic state’s expectation values over quadrature operators (and their covariance matrix) as an input qubit s...

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Bibliographic Details
Published in:Physical review letters Vol. 134; no. 7; p. 070604
Main Authors: Barthe, Alice, Cerezo, M., Sornborger, Andrew T., Larocca, Martín, García-Martín, Diego
Format: Journal Article
Language:English
Published: United States American Physical Society (APS) 21.02.2025
Subjects:
bosonic systems
BQP-complete
computational complexity
exponential advantage
quantum algorithms & computation
quantum circuits
quantum harmonic oscillator
quantum simulations
ISSN:0031-9007, 1079-7114, 1079-7114
Online Access:Get full text
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Summary:We introduce a framework for simulating, on an ( n + 1 )-qubit quantum computer, the action of a Gaussian bosonic (GB) circuit on a state over 2 n modes. Specifically, we encode the initial bosonic state’s expectation values over quadrature operators (and their covariance matrix) as an input qubit state. This is then evolved by a quantum circuit that effectively implements the symplectic propagators induced by the GB gates. We find families of GB circuits and initial states leading to efficient quantum simulations. For this purpose, we introduce a dictionary that maps between GB and qubit gates such that particle- (non-particle-) preserving GB gates lead to real- (imaginary-) time evolutions at the qubit level. For the special case of particle-preserving circuits, we present a bounded-error-quantum-polynomial time (BQP)-complete GB decision problem, indicating that GB evolutions of Gaussian states on exponentially many modes are as powerful as universal quantum computers. We also perform numerical simulations of an interferometer on ∼ 8 × 10 9 modes, illustrating the power of our framework.
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89233218CNA000001; 20230049DR; 20230527ECR
USDOE Laboratory Directed Research and Development (LDRD) Program
LA-UR-24-26564
ISSN:0031-9007
1079-7114
1079-7114
DOI:10.1103/PhysRevLett.134.070604