{"paper":{"title":"Parabolic Anderson model in a dynamic random environment: random conductances","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.PR","authors_text":"Dirk Erhard, Frank den Hollander, Gregory Maillard","submitted_at":"2015-07-21T22:45:13Z","abstract_excerpt":"The parabolic Anderson model is defined as the partial differential equation \\partial u(x,t)/\\partial t = \\kappa\\Delta u(x,t) + \\xi(x,t)u(x,t), x\\in\\Z^d, t\\geq 0, where \\kappa \\in [0,\\infty) is the diffusion constant, \\Delta is the discrete Laplacian, and \\xi is a dynamic random environment that drives the equation. The initial condition u(x,0)=u_0(x), x\\in\\Z^d, is taken to be non-negative and bounded. The solution of the parabolic Anderson equation describes the evolution of a field of particles performing independent simple random walks with binary branching: particles jump at rate 2d\\kappa,"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1507.06008","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}