Quantum Brain
← Back to papers

Simulating Gaussian boson sampling on graphs in polynomial time

Konrad Anand, Zongchen Chen, Mary Cryan, Graham Freifeld, Leslie Ann Goldberg, Heng Guo, Xinyuan Zhang·November 20, 2025
Quantum PhysicsData Structures

AI Breakdown

Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.

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.

Related Research

Quantum Intelligence

Ask about quantum research, companies, or market developments.