Simulating Gaussian boson sampling on graphs in polynomial time
Quantum Physics
2025-11-21 v1 Data Structures and Algorithms
Abstract
We show that a distribution related to Gaussian Boson Sampling (GBS) on graphs can be sampled classically in polynomial time. Graphical applications of GBS typically sample from this distribution, and thus quantum algorithms do not provide exponential speedup for these applications. We also show that another distribution related to Boson sampling can be sampled classically in polynomial time.
Keywords
Cite
@article{arxiv.2511.16558,
title = {Simulating Gaussian boson sampling on graphs in polynomial time},
author = {Konrad Anand and Zongchen Chen and Mary Cryan and Graham Freifeld and Leslie Ann Goldberg and Heng Guo and Xinyuan Zhang},
journal= {arXiv preprint arXiv:2511.16558},
year = {2025}
}
Comments
10 pages, 2 figures