{"paper":{"title":"Quantifying Uncertainties in Fault Slip Distribution during the T\\=ohoku Tsunami using Polynomial Chaos","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Clint N. Dawson, Ibrahim Hoteit, Ihab Sraj, Kyle T. Mandli, Omar M. Knio","submitted_at":"2016-07-25T19:09:41Z","abstract_excerpt":"An efficient method for inferring Manning's $n$ coefficients using water surface elevation data was presented in Sraj et al. (2014) focusing on a test case based on data collected during the $T\\=ohoku$ earthquake and tsunami. Polynomial chaos expansions were used to build an inexpensive surrogate for the numerical model Geoclaw, which were then used to perform a sensitivity analysis in addition to the inversion. In this paper, a new analysis is performed with the goal of inferring the fault slip distribution of the $T\\=ohoku$ earthquake using a similar problem setup. The same approach to const"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.07414","kind":"arxiv","version":2},"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"}