{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:RYYDOE25YKW53VDKYDYWU4DZKY","short_pith_number":"pith:RYYDOE25","schema_version":"1.0","canonical_sha256":"8e3037135dc2adddd46ac0f16a70795633ca6a57cefe64f769bdab62c0df0d8f","source":{"kind":"arxiv","id":"1709.09447","version":1},"attestation_state":"computed","paper":{"title":"Information processing features can detect behavioral regimes of dynamical systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","physics.soc-ph"],"primary_cat":"cs.IT","authors_text":"Alexandre Dupuis, Alfons G. Hoekstra, Bastien Chopard, Gregor Chliamovitch, Jean-Luc Falcone, Peter M.A. Sloot, Rick Quax","submitted_at":"2017-09-27T11:04:02Z","abstract_excerpt":"In dynamical systems, local interactions between dynamical units generate correlations which are stored and transmitted throughout the system, generating the macroscopic behavior. However a framework to quantify and study this at the microscopic scale is missing. Here we propose an 'information processing' framework based on Shannon mutual information quantities between the initial and future states. We apply it to the 256 elementary cellular automata (ECA), which are the simplest possible dynamical systems exhibiting behaviors ranging from simple to complex. Our main finding for ECA is that o"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1709.09447","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2017-09-27T11:04:02Z","cross_cats_sorted":["math.IT","physics.soc-ph"],"title_canon_sha256":"a2c118895f38fd025613295d10411878db2aaebe13c6557964686bc33fce7e2a","abstract_canon_sha256":"cb5854ecbee935f891cd57b1740ed319f87895fe32ccf3e8c7e3b9a90dea3c4a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:34:11.705729Z","signature_b64":"CZHjnCJLPkLGCM8d48FAB1KW+tU/AEnqMTg30MxqBVjThijZGCc6VslS1eAen2/x4nkFLP+zg212TRbluUzVDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e3037135dc2adddd46ac0f16a70795633ca6a57cefe64f769bdab62c0df0d8f","last_reissued_at":"2026-05-18T00:34:11.705232Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:34:11.705232Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Information processing features can detect behavioral regimes of dynamical systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","physics.soc-ph"],"primary_cat":"cs.IT","authors_text":"Alexandre Dupuis, Alfons G. Hoekstra, Bastien Chopard, Gregor Chliamovitch, Jean-Luc Falcone, Peter M.A. Sloot, Rick Quax","submitted_at":"2017-09-27T11:04:02Z","abstract_excerpt":"In dynamical systems, local interactions between dynamical units generate correlations which are stored and transmitted throughout the system, generating the macroscopic behavior. However a framework to quantify and study this at the microscopic scale is missing. Here we propose an 'information processing' framework based on Shannon mutual information quantities between the initial and future states. We apply it to the 256 elementary cellular automata (ECA), which are the simplest possible dynamical systems exhibiting behaviors ranging from simple to complex. Our main finding for ECA is that o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1709.09447","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1709.09447","created_at":"2026-05-18T00:34:11.705296+00:00"},{"alias_kind":"arxiv_version","alias_value":"1709.09447v1","created_at":"2026-05-18T00:34:11.705296+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1709.09447","created_at":"2026-05-18T00:34:11.705296+00:00"},{"alias_kind":"pith_short_12","alias_value":"RYYDOE25YKW5","created_at":"2026-05-18T12:31:43.269735+00:00"},{"alias_kind":"pith_short_16","alias_value":"RYYDOE25YKW53VDK","created_at":"2026-05-18T12:31:43.269735+00:00"},{"alias_kind":"pith_short_8","alias_value":"RYYDOE25","created_at":"2026-05-18T12:31:43.269735+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/RYYDOE25YKW53VDKYDYWU4DZKY","json":"https://pith.science/pith/RYYDOE25YKW53VDKYDYWU4DZKY.json","graph_json":"https://pith.science/api/pith-number/RYYDOE25YKW53VDKYDYWU4DZKY/graph.json","events_json":"https://pith.science/api/pith-number/RYYDOE25YKW53VDKYDYWU4DZKY/events.json","paper":"https://pith.science/paper/RYYDOE25"},"agent_actions":{"view_html":"https://pith.science/pith/RYYDOE25YKW53VDKYDYWU4DZKY","download_json":"https://pith.science/pith/RYYDOE25YKW53VDKYDYWU4DZKY.json","view_paper":"https://pith.science/paper/RYYDOE25","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1709.09447&json=true","fetch_graph":"https://pith.science/api/pith-number/RYYDOE25YKW53VDKYDYWU4DZKY/graph.json","fetch_events":"https://pith.science/api/pith-number/RYYDOE25YKW53VDKYDYWU4DZKY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RYYDOE25YKW53VDKYDYWU4DZKY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RYYDOE25YKW53VDKYDYWU4DZKY/action/storage_attestation","attest_author":"https://pith.science/pith/RYYDOE25YKW53VDKYDYWU4DZKY/action/author_attestation","sign_citation":"https://pith.science/pith/RYYDOE25YKW53VDKYDYWU4DZKY/action/citation_signature","submit_replication":"https://pith.science/pith/RYYDOE25YKW53VDKYDYWU4DZKY/action/replication_record"}},"created_at":"2026-05-18T00:34:11.705296+00:00","updated_at":"2026-05-18T00:34:11.705296+00:00"}