{
  "annotation_id": "ea591494-15e9-44ad-8c62-f46d82e9f9e9",
  "date_created": "2026-02-17T05:53:12.428000Z",
  "date_modified": "2026-02-17T05:53:12.428000Z",
  "file_hash": "c07850270d6c4ab5ac384fa93e5be4aff7f88e56c93342cf3d911f634f585b6a",
  "private": false,
  "record": {
    "abstract": "Search processes are a fundamental part of natural and artificial systems. In such settings, the number of searchers is rarely constant: new agents may be recruited while others can abandon the search. Despite the ubiquity of these dynamics, their combined influence on search efficiency remains unexplored. Here we present a general framework for stochastic search in which independent agents progressively join and leave the process, a mechanism we term \\emph{dynamic redundancy and mortality} (DRM). Under minimal assumptions on the underlying search dynamics, this framework yields exact first-passage time statistics. It further reveals surprising connections to stochastic resetting, including a regime in which the resetting mean first-passage time emerges as a universal lower bound for DRM, as well as regimes in which DRM search is faster. We illustrate our results through a detailed analysis of one-dimensional Brownian DRM search. Altogether, this work provides a rigorous foundation for studying first-passage processes with a fluctuating number of searchers, with direct relevance across physical, biological, and algorithmic systems.",
    "arxiv_id": "2601.07096",
    "authors": [
      "Samantha Linn",
      "Aanjaneya Kumar"
    ],
    "categories": [
      "cond-mat.stat-mech",
      "math.PR",
      "physics.data-an",
      "physics.soc-ph"
    ],
    "license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
    "title": "Dynamic redundancy and mortality in stochastic search",
    "url": "https://arxiv.org/abs/2601.07096",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "bd9293f0-c04d-48cb-b1c2-249e10b95f04",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}