{"paper":{"title":"Quantum neural computation of entanglement is robust to noise and decoherence","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"E.C. Behrman, J.E. Steck, M. McCann, N.H. Nguyen","submitted_at":"2015-10-30T17:38:15Z","abstract_excerpt":"In previous work, we have proposed an entanglement indicator for a general multiqubit state, which can be \"learned\" by a quantum system, acting as a neural network. The indicator can be used for a pure or a mixed state, and it need not be \"close\" to any particular state; moreover, as the size of the system grows, the amount of additional training necessary diminishes. Here, we show that the indicator is stable to noise and decoherence."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1510.09173","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"}