Spatiotemporal quantum advantages for rare-event sampling

Abstract:In a world fraught with uncertainty, it behooves us to consider the most disastrous possible outcomes, in order that we can best mitigate against them. Often these are extreme risk events -- of high consequence, but low probability. Yet, the rarity of such events limits our ability to study them; there is a paucity of past occurrences to draw upon, and sampling such rare events from models is typically costly in time. Here, we introduce an approach for rare-event sampling based on quantum stochastic models. This integrates the memory advantages of quantum stochastic modelling -- and its associated efficient means of preparing quantum sample states -- with the `speed-ups' of quantum amplitude amplification, to yield simultaneous reductions in spatial and temporal computational complexity compared to classical Monte Carlo-based approaches.

Quantum Physics (quant-ph); Statistical Mechanics (cond-mat.stat-mech)

arXiv:2610.03026 [quant-ph]

(or arXiv:2610.03026v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2610.03026 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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