Papers
Topics
Authors
Recent
2000 character limit reached

Experimental demonstration of boson sampling as a hardware accelerator for monte carlo integration (2509.25404v1)

Published 29 Sep 2025 in quant-ph, physics.atm-clus, physics.comp-ph, and physics.optics

Abstract: We present an experimental demonstration of boson sampling as a hardware accelerator for Monte Carlo integration. Our approach leverages importance sampling to factorize an integrand into a distribution that can be sampled using quantum hardware and a function that can be evaluated classically, enabling hybrid quantum-classical computation. We argue that for certain classes of integrals, this method offers a quantum advantage by efficiently sampling from probability distributions that are hard to simulate classically. We also identify structural criteria that must be satisfied to preserve computational hardness, notably the sensitivity of the classical post-processing function to high-order quantum correlations. To validate our protocol, we implement a proof-of-principle experiment on a programmable photonic platform to compute the first-order energy correction of a three-boson system in a harmonic trap under an Efimov-inspired three-body perturbation. The experimental results are consistent with theoretical predictions and numerical simulations, with deviations explained by photon distinguishability, discretization, and unitary imperfections. Additionally, we provide an error budget quantifying the impact of these same sources of noise. Our work establishes a concrete use case for near-term photonic quantum devices and highlights a viable path toward practical quantum advantage in scientific computing.

Summary

We haven't generated a summary for this paper yet.

Whiteboard

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.

Tweets

Sign up for free to view the 2 tweets with 0 likes about this paper.