{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:LX7IFR7WYXIQJZWVE5Q25WCG5N","merge_version":"pith-open-graph-merge-v1","event_count":10,"valid_event_count":10,"invalid_event_count":0,"equivocation_count":1,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"231d7e5cdce56e819b12a3e571a80ec2eb040d768cae55f9d399acd406281213","cross_cats_sorted":["cond-mat.dis-nn","cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-30T20:44:57Z","title_canon_sha256":"cd6dcafc862377a7541cbfa6df318aab8eb45c780c82b34e2b8878018ad173bd"},"schema_version":"1.0","source":{"id":"2607.00170","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.00170","created_at":"2026-07-02T00:18:37Z"},{"alias_kind":"arxiv_version","alias_value":"2607.00170v1","created_at":"2026-07-02T00:18:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.00170","created_at":"2026-07-02T00:18:37Z"},{"alias_kind":"pith_short_12","alias_value":"LX7IFR7WYXIQ","created_at":"2026-07-02T00:18:37Z"},{"alias_kind":"pith_short_16","alias_value":"LX7IFR7WYXIQJZWV","created_at":"2026-07-02T00:18:37Z"},{"alias_kind":"pith_short_8","alias_value":"LX7IFR7W","created_at":"2026-07-02T00:18:37Z"}],"graph_snapshots":[{"event_id":"sha256:564f8fa6efb5d0d51f952d1bfc6ee4cf7f97c6c12be4b88735993a6eb2649fe6","target":"graph","created_at":"2026-07-02T00:18:37Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2607.00170/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Thermodynamic computing devices based on the Ising model show great promise for low-power AI inference and edge computing, but scalable methods for training large models for such hardware remain limited. Prior theory shows that the time-averaged behavior of high-temperature Gibbs-sampled Ising systems can implement feed-forward neural inference. We turn this theoretical correspondence into a scalable and purely backpropagation-based algorithm for training deep convolutional networks for thermodynamic inference on Ising machine hardware. Our image classification models achieve accuracies of 94.","authors_text":"Andrew G. Moore","cross_cats":["cond-mat.dis-nn","cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-30T20:44:57Z","title":"Scaling Up Thermodynamic AI Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00170","kind":"arxiv","version":1},"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":"sha256:48efb81e91c3e784bc27544b60e4d6967be4998a45453e71f8b162fc0fde4986","target":"record","created_at":"2026-07-02T00:18:37Z","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":"231d7e5cdce56e819b12a3e571a80ec2eb040d768cae55f9d399acd406281213","cross_cats_sorted":["cond-mat.dis-nn","cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-06-30T20:44:57Z","title_canon_sha256":"cd6dcafc862377a7541cbfa6df318aab8eb45c780c82b34e2b8878018ad173bd"},"schema_version":"1.0","source":{"id":"2607.00170","kind":"arxiv","version":1}},"canonical_sha256":"5dfe82c7f6c5d104e6d52761aed846eb6fccfa65a1703b53f9c014d4807aa71d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5dfe82c7f6c5d104e6d52761aed846eb6fccfa65a1703b53f9c014d4807aa71d","first_computed_at":"2026-07-02T00:18:37.718306Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-02T00:18:37.718306Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MInGP8sJquXGr4YTqYBx2U+d4Ab/QM84H9KqW5XbyefBkecEJf4fY10wfSyYf4q8adfjbzibaQzbDET1oeLqBg==","signature_status":"signed_v1","signed_at":"2026-07-02T00:18:37.719116Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.00170","source_kind":"arxiv","source_version":1}}},"equivocations":[{"signer_id":"pith.science","event_type":"integrity_finding","target":"integrity","event_ids":["sha256:0b80f8321ce2ee8f5aa2d18cf8ab0362bc9abf9b2d8896aefe187647c36721c0","sha256:16ec76ad962c35505fd031d65fc1390492546dc11cbe3267188290f0bc2ec8fb","sha256:295b25a4c626f757a312dd5c4ba0764c1e76e02ffb3f60b5b1883d08190fc752","sha256:3a0678d3d0c7c39a8e84f540e9dd827da395aaba0f9f08a0b0389444ed5a1716","sha256:40270722086f0d758bc3d69d404fba1c047c00c3291d3d8cd10d295585119fc3","sha256:43954f56b340f387866383083d19b042bce3bb1ad23b7e949d411a5d142be017","sha256:8dd7f89936cd199352442d27e7a86477a5c4d8359957c04ca5d4437edd98db09","sha256:c8b758f179daca0faf93530a2fbe9916d4911c55c91ae77da030beabd3157998"]}],"invalid_events":[],"applied_event_ids":["sha256:48efb81e91c3e784bc27544b60e4d6967be4998a45453e71f8b162fc0fde4986","sha256:564f8fa6efb5d0d51f952d1bfc6ee4cf7f97c6c12be4b88735993a6eb2649fe6"],"state_sha256":"714b778e83c742c279c2af3bb1cb8161f1a9c48ebb4a3388ff225c33f02580a0"}