AI 中文总结
研究许多相互作用粒子的极端首次通过时间，建立通用框架，证明有界相互作用的时间尺度，识别两种超越对数类别的机制并推导加速极限，区分不同加速来源，加深对相互作用随机系统的理解。
AI 中文摘要
极端首次通过事件与生物、化学和物理过程广泛相关，其中首次成功到达决定结果。现有理论局限于非相互作用搜索者。相互作用的极端统计问题因相关性破坏概率分解而 notoriously 困难。我们建立了相互作用极端搜索的通用框架。一个不可行定理表明，广泛的有界相互作用类别无法超越 N 个独立布朗搜索者的 1/lnN 极端时间尺度，互补的上界证明该尺度对于广泛的排斥相互作用类别是精确的。然后我们识别出超出对数类别的两种尖锐机制，并推导了统一的相互作用驱动加速极限。特别是，确定性成对相互作用最多可将极端搜索时间减少到 1/N 阶，而随机成对强迫达到 1/(NlnN)。我们的结果将由于统计冗余产生的加速与由相干多体输运或放大波动产生的加速分开，加深了我们对相互作用随机系统的理解。
英文摘要
Extreme first-passage events are broadly relevant to biological, chemical, and physical processes in which the first successful arrival determines the outcome. Existing theories are confined to noninteracting searchers. Interacting extreme-statistics problems are notoriously difficult because correlations destroy probability factorization. We establish a general framework for interacting extreme search. A no-go theorem shows that broad classes of bounded interactions cannot beat the $1/\ln N$ extreme timescale of $N$ independent Brownian searchers, and complementary upper bounds prove that this scale is exact for broad classes of repulsive interactions. We then identify two sharp mechanisms beyond the logarithmic class and derive a unified interaction-driven acceleration limit. In particular, deterministic pairwise interaction can at most reduce the extreme search time to order $1/N$, while stochastic pairwise forcing attains $1/(N\ln N)$. Our results separate acceleration due to statistical redundancy from that generated by coherent many-body transport or amplified fluctuations, deepening our understanding of interacting stochastic systems.
Comments6 pages. Comments are highly appreciated. Supplemental Materials will be uploaded prior to the formal submission
