aiqbench analysis
This paper establishes new theoretical limits for the classical simulation of lossy Gaussian Boson Sampling, demonstrating that approximation strategies targeting detection events can surpass previous square-root scaling barriers to achieve $N^{2/3}$ and $N^{3/4}$ regimes. By replacing conditional states with Gaussians after photon detections, the authors provide a rigorous framework for estimating quantum advantage thresholds in the presence of realistic optical losses. These findings are critical for defining the operational boundaries where photonic quantum processors maintain their computational hardness against classical algorithms.
Classical Simulation of Lossy Gaussian Boson Sampling beyond Square-Root Regime
arXiv:2610.06526v1 Announce Type: new Abstract: Photon loss makes Gaussian boson sampling easier to simulate classically. A standard approach replaces the lossy input by classical light, and it stays accurate while the mean number of surviving photons grows no faster than the square root of the number $N$ of squeezed inputs at fixed squeezing and accuracy. We prove that this scale is a limit of replacement by classical light. For explicit interferometers, no state with a nonnegative Glauber--Sudarshan $P$ representation, Gaussian or not and however correlated, keeps the error in the photon count distribution small beyond this scale. We then surpass this limit by approximating the detection instead of the input. The sampler evolves the state exactly between detections and, after each detection, replaces the conditional state by a Gaussian with the same covariance. For every interferometer its total variation error is $O(N\eta^3)$ at polynomial expected cost, where $\eta$ is the photon survival probability. The mean surviving photon number can therefore grow as $N^{2/3}$ at fixed accuracy. A separate pair construction reaches $N^{3/4}$ when every input mode is equally squeezed.
Abstract:Photon loss makes Gaussian boson sampling easier to simulate classically. A standard approach replaces the lossy input by classical light, and it stays accurate while the mean number of surviving photons grows no faster than the square root of the number $N$ of squeezed inputs at fixed squeezing and accuracy. We prove that this scale is a limit of replacement by classical light. For explicit interferometers, no state with a nonnegative Glauber--Sudarshan $P$ representation, Gaussian or not and however correlated, keeps the error in the photon count distribution small beyond this scale. We then surpass this limit by approximating the detection instead of the input. The sampler evolves the state exactly between detections and, after each detection, replaces the conditional state by a Gaussian with the same covariance. For every interferometer its total variation error is $O(N\eta^3)$ at polynomial expected cost, where $\eta$ is the photon survival probability. The mean surviving photon number can therefore grow as $N^{2/3}$ at fixed accuracy. A separate pair construction reaches $N^{3/4}$ when every input mode is equally squeezed.
arXiv:2610.06526 [quant-ph]
(or arXiv:2610.06526v1 [quant-ph] for this version)
https://doi.org/10.48550/arXiv.2610.06526 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Full text under the publisher's open licence · 265 words
Related coverage

A brief history of quantum vs classical computational advantage
Quantum Journal · Sep 1, 2026
Matrix product state approach to lossy boson sampling and noisy IQP sampling
arXiv · Jul 22, 2026

Researchers Link Gaussian Matrices to Quantum Sampling Advantage
Quantum Zeitgeist · Aug 5, 2026

The Companies Building Quantum Computing Chips in 2026
The Quantum Insider · Jun 5, 2026