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Main Authors: Zhao, Yukuan, Xu, Xiao-Ye, Li, Chuan-Feng, Guo, Guang-Can
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2512.00753
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author Zhao, Yukuan
Xu, Xiao-Ye
Li, Chuan-Feng
Guo, Guang-Can
author_facet Zhao, Yukuan
Xu, Xiao-Ye
Li, Chuan-Feng
Guo, Guang-Can
contents Gaussian Boson Sampling (GBS) provides a route toward demonstrating quantum computational advantage. However, optical loss, which reduces the entanglement in the system, can render GBS results classically simulable. We propose a nonlinear photonic architecture based on optical parametric amplifiers (OPAs) arranged in an interferometer network. This active configuration amplifies quantum correlations within the circuit while preserving the #P-hard Hafnian structure of the output probabilities. Using logarithmic negativity, we numerically show that entanglement scales linearly with both the OPA gain and network depth in the lossless limit, and maintains linear scaling with the number of modes under realistic loss rate. These scaling behaviors suggest that classical simulation in lossy scenarios remains computationally intractable. Our results demonstrate that OPA-boosted GBS preserves computational hardness in noisy environments, offering a more effective implementations of near-term photonic quantum computers.
format Preprint
id arxiv_https___arxiv_org_abs_2512_00753
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Boosting Gaussian Boson Sampling using Optical Parametric Amplification Networks
Zhao, Yukuan
Xu, Xiao-Ye
Li, Chuan-Feng
Guo, Guang-Can
Quantum Physics
Gaussian Boson Sampling (GBS) provides a route toward demonstrating quantum computational advantage. However, optical loss, which reduces the entanglement in the system, can render GBS results classically simulable. We propose a nonlinear photonic architecture based on optical parametric amplifiers (OPAs) arranged in an interferometer network. This active configuration amplifies quantum correlations within the circuit while preserving the #P-hard Hafnian structure of the output probabilities. Using logarithmic negativity, we numerically show that entanglement scales linearly with both the OPA gain and network depth in the lossless limit, and maintains linear scaling with the number of modes under realistic loss rate. These scaling behaviors suggest that classical simulation in lossy scenarios remains computationally intractable. Our results demonstrate that OPA-boosted GBS preserves computational hardness in noisy environments, offering a more effective implementations of near-term photonic quantum computers.
title Boosting Gaussian Boson Sampling using Optical Parametric Amplification Networks
topic Quantum Physics
url https://arxiv.org/abs/2512.00753