Quantum enhanced rare event discovery and sampling 文章

ArXiv CS.AI2026-06-06NEWSen作者: Naixu Guo, Po-Wei Huang, Qisheng Wang, Jayne Thompson, Patrick Rebentrost, Mile Gu, Chengran Yang

摘要

arXiv:2606.06316v1 Announce Type: cross Abstract: Financial crashes, cascading failures in infrastructure, and critical errors in AI systems are frequently triggered by events that occur with extremely small probability. Efficiently discovering and sampling events with probability below a threshold is therefore of critical interest. Yet this task is highly non-trivial using existing classical or quantum methods. Being rare, such events require an immense sampling overhead to collect sufficient data samples. Moreover, because the rare events are not known in advance, they cannot be flagged for amplification using standard techniques. Here, we introduce a quantum algorithm for rare-event discovery and sampling without first learning which events are rare. The algorithm achieves the optimal quantum scaling with the rarity threshold.

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Quantum enhanced rare event discovery and sampling
2026-06-06PRODUCT_LAUNCH影响: MEDIUM

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