{"paper":{"title":"Scale-dependent non-Gaussianities in the WMAP data as identified by using surrogates and scaling indices","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.data-an"],"primary_cat":"astro-ph.CO","authors_text":"A. J. Banday, C. Raeth, G. E. Morfill, G. Rossmanith, H. Modest, J. Delabrouille, K. M. Gorski, R. Suetterlin","submitted_at":"2010-12-14T10:30:48Z","abstract_excerpt":"We present a model-independent investigation of the WMAP data with respect to scale- dependent non-Gaussianities (NGs) by employing the method of constrained randomization. For generating so-called surrogate maps a shuffling scheme is applied to the Fourier phases of the original data, which allows to test for the presence of higher order correlations (HOCs) on well-defined scales. Using scaling indices as test statistics we find highly significant signatures for non-Gaussianities when considering all scales. We test for NGs in the bands l = [2,20], l = [20,60], l = [60,120] and l = [120,300]."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1012.2985","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"}