{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:LWN4LQYOKB36KHBAX3T7LXQUOM","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"52ba2b343d099d077ac824eaab295aadb76ee543abf02dc67d92699771869135","cross_cats_sorted":["cond-mat.stat-mech","cs.IT","cs.LG","math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.dis-nn","submitted_at":"2017-04-20T18:02:50Z","title_canon_sha256":"a219b61984efff30fed9e47b623dbbcb375a7f3f94784516622081896f5e6cbc"},"schema_version":"1.0","source":{"id":"1704.06279","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1704.06279","created_at":"2026-05-18T00:05:00Z"},{"alias_kind":"arxiv_version","alias_value":"1704.06279v2","created_at":"2026-05-18T00:05:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1704.06279","created_at":"2026-05-18T00:05:00Z"},{"alias_kind":"pith_short_12","alias_value":"LWN4LQYOKB36","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_16","alias_value":"LWN4LQYOKB36KHBA","created_at":"2026-05-18T12:31:28Z"},{"alias_kind":"pith_short_8","alias_value":"LWN4LQYO","created_at":"2026-05-18T12:31:28Z"}],"graph_snapshots":[{"event_id":"sha256:ee12a9f16beae669234c5f1de4f8316d8e26226c27ae2dfb7b73d60c13ce3b28","target":"graph","created_at":"2026-05-18T00:05:00Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Physical systems differring in their microscopic details often display strikingly similar behaviour when probed at macroscopic scales. Those universal properties, largely determining their physical characteristics, are revealed by the powerful renormalization group (RG) procedure, which systematically retains \"slow\" degrees of freedom and integrates out the rest. However, the important degrees of freedom may be difficult to identify. Here we demonstrate a machine learning algorithm capable of identifying the relevant degrees of freedom and executing RG steps iteratively without any prior knowl","authors_text":"Maciej Koch-Janusz, Zohar Ringel","cross_cats":["cond-mat.stat-mech","cs.IT","cs.LG","math.IT","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.dis-nn","submitted_at":"2017-04-20T18:02:50Z","title":"Mutual Information, Neural Networks and the Renormalization Group"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1704.06279","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:3b4813d95a4b985b5ee5d7fe6a7b1c9ada56d0ed99d42c7c3d5f168ba39c8304","target":"record","created_at":"2026-05-18T00:05:00Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"52ba2b343d099d077ac824eaab295aadb76ee543abf02dc67d92699771869135","cross_cats_sorted":["cond-mat.stat-mech","cs.IT","cs.LG","math.IT","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cond-mat.dis-nn","submitted_at":"2017-04-20T18:02:50Z","title_canon_sha256":"a219b61984efff30fed9e47b623dbbcb375a7f3f94784516622081896f5e6cbc"},"schema_version":"1.0","source":{"id":"1704.06279","kind":"arxiv","version":2}},"canonical_sha256":"5d9bc5c30e5077e51c20bee7f5de1473075678e965bd635f0800c2f046dafd29","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5d9bc5c30e5077e51c20bee7f5de1473075678e965bd635f0800c2f046dafd29","first_computed_at":"2026-05-18T00:05:00.671635Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:05:00.671635Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sKc4jZ0kBWB+Lc/LazuEYWFdj25lYaTUDUD0ph0QosF1EC3AzQK5rSd9h0EwEzfncGtIL9zKI7aeVXiRsdWyDw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:05:00.672345Z","signed_message":"canonical_sha256_bytes"},"source_id":"1704.06279","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3b4813d95a4b985b5ee5d7fe6a7b1c9ada56d0ed99d42c7c3d5f168ba39c8304","sha256:ee12a9f16beae669234c5f1de4f8316d8e26226c27ae2dfb7b73d60c13ce3b28"],"state_sha256":"e18552524c1a22c819c431b3ecf5ec9d0e487979e422318e592254743465a0f8"}