{"paper":{"title":"Identifying Mergers Using Quantitative Morphologies in Zoom Simulations of High-Redshift Galaxies","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"astro-ph.GA","authors_text":"Desika Narayanan, Matthew W. Abruzzo, Robert Thompson, Romeel Dav\\'e","submitted_at":"2018-03-06T19:00:09Z","abstract_excerpt":"Non-parametric morphology measures are a powerful tool for identifying galaxy mergers at low redshifts. We employ cosmological zoom simulations using Gizmo with the Mufasa feedback scheme, post-processed using 3D dust radiative transfer into mock observations, to study whether common morphological measures Gini G, M20, concentration C, and asymmetry A are effective at identifying major galaxy mergers at z ~ 2 - 4, i.e. \"Cosmic Noon\". Our zoom suite covers galaxies with 10^8.6 < M_* < 10^11 M_sun at z ~ 2, and broadly reproduces key global galaxy observations. Our primary result is that these m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1803.02374","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"}