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Trapped Ion Quantum Computing Quantum Simulation

Boosting Gaussian Boson Sampling using Optical Parametric Amplification Networks

arXiv
Authors: Yukuan Zhao, Xiao-Ye Xu, Chuan-Feng Li, Guang-Can Guo

Year

2025

Paper ID

16442

Status

Preprint

Abstract Read

~2 min

Abstract Words

134

Citations

N/A

Abstract

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.

Why This Paper Matters

  • This paper contributes to the Quantum Simulation research area in the Quantum Articles archive.
  • It adds a 2025 reference point for readers tracking recent quantum research.
  • Gaussian Boson Sampling (GBS) provides a route toward demonstrating quantum computational advantage.

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