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  "path": "/abs/2604.16074v1",
  "publishedAt": "2026-04-20T00:00:00.000Z",
  "site": "https://arxiv.org",
  "tags": [
    "Stefan Huber",
    "Dominik Kaaser"
  ],
  "textContent": "**Authors:** Stefan Huber, Dominik Kaaser\n\nWe study the patient zero problem in epidemic spreading processes in the independent cascade model and propose a geometric approach for source reconstruction. Using Johnson-Lindenstrauss projections, we embed the contact network into a low-dimensional Euclidean space and estimate the infection source as the node closest to the center of gravity of infected nodes. Simulations on Erdős-Rényi graphs demonstrate that our estimator achieves meaningful reconstruction accuracy despite operating on compressed observations.",
  "title": "Finding Patient Zero via Low-Dimensional Geometric Embeddings"
}