{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:P7MNHH367PIZUHT35PUTBMNSGG","short_pith_number":"pith:P7MNHH36","schema_version":"1.0","canonical_sha256":"7fd8d39f7efbd19a1e7bebe930b1b231b1b577d3690016d93aa003b325dc1545","source":{"kind":"arxiv","id":"2311.01171","version":1},"attestation_state":"computed","paper":{"title":"Memristor-based hardware and algorithms for higher-order Hopfield optimization solver outperforming quadratic Ising machines","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AR"],"primary_cat":"cs.ET","authors_text":"Adrien Renaudineau, Arne Heittmann, Dmitrii Dobrynin, Dmitri Strukov, George Hutchinson, John Paul Strachan, Mohammad Hizzani, Thomas Van Vaerenbergh, Tinish Bhattacharya","submitted_at":"2023-11-02T12:09:20Z","abstract_excerpt":"Ising solvers offer a promising physics-based approach to tackle the challenging class of combinatorial optimization problems. However, typical solvers operate in a quadratic energy space, having only pair-wise coupling elements which already dominate area and energy. We show that such quadratization can cause severe problems: increased dimensionality, a rugged search landscape, and misalignment with the original objective function. Here, we design and quantify a higher-order Hopfield optimization solver, with 28nm CMOS technology and memristive couplings for lower area and energy computations"},"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":"2311.01171","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.ET","submitted_at":"2023-11-02T12:09:20Z","cross_cats_sorted":["cs.AR"],"title_canon_sha256":"a9f5979ac433ee0104e367237d175e56ece072fd461c40d089417c268446aa55","abstract_canon_sha256":"d653c1d271786c65bc3065e1c30b49a18fd0022812444cb31eb0f51fe392ab66"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:23:45.485882Z","signature_b64":"s9Lp2rhyNVz3jC0wVM+VIWZP3ncJrZ86Xm1HmRNcJWQ3XNHPWaKy/zl5JyS2BcuLIV8sRRaBSMDP0om8Tu/9AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7fd8d39f7efbd19a1e7bebe930b1b231b1b577d3690016d93aa003b325dc1545","last_reissued_at":"2026-07-05T09:23:45.485440Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:23:45.485440Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Memristor-based hardware and algorithms for higher-order Hopfield optimization solver outperforming quadratic Ising machines","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AR"],"primary_cat":"cs.ET","authors_text":"Adrien Renaudineau, Arne Heittmann, Dmitrii Dobrynin, Dmitri Strukov, George Hutchinson, John Paul Strachan, Mohammad Hizzani, Thomas Van Vaerenbergh, Tinish Bhattacharya","submitted_at":"2023-11-02T12:09:20Z","abstract_excerpt":"Ising solvers offer a promising physics-based approach to tackle the challenging class of combinatorial optimization problems. However, typical solvers operate in a quadratic energy space, having only pair-wise coupling elements which already dominate area and energy. We show that such quadratization can cause severe problems: increased dimensionality, a rugged search landscape, and misalignment with the original objective function. Here, we design and quantify a higher-order Hopfield optimization solver, with 28nm CMOS technology and memristive couplings for lower area and energy computations"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.01171","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2311.01171/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2311.01171","created_at":"2026-07-05T09:23:45.485502+00:00"},{"alias_kind":"arxiv_version","alias_value":"2311.01171v1","created_at":"2026-07-05T09:23:45.485502+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.01171","created_at":"2026-07-05T09:23:45.485502+00:00"},{"alias_kind":"pith_short_12","alias_value":"P7MNHH367PIZ","created_at":"2026-07-05T09:23:45.485502+00:00"},{"alias_kind":"pith_short_16","alias_value":"P7MNHH367PIZUHT3","created_at":"2026-07-05T09:23:45.485502+00:00"},{"alias_kind":"pith_short_8","alias_value":"P7MNHH36","created_at":"2026-07-05T09:23:45.485502+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/P7MNHH367PIZUHT35PUTBMNSGG","json":"https://pith.science/pith/P7MNHH367PIZUHT35PUTBMNSGG.json","graph_json":"https://pith.science/api/pith-number/P7MNHH367PIZUHT35PUTBMNSGG/graph.json","events_json":"https://pith.science/api/pith-number/P7MNHH367PIZUHT35PUTBMNSGG/events.json","paper":"https://pith.science/paper/P7MNHH36"},"agent_actions":{"view_html":"https://pith.science/pith/P7MNHH367PIZUHT35PUTBMNSGG","download_json":"https://pith.science/pith/P7MNHH367PIZUHT35PUTBMNSGG.json","view_paper":"https://pith.science/paper/P7MNHH36","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2311.01171&json=true","fetch_graph":"https://pith.science/api/pith-number/P7MNHH367PIZUHT35PUTBMNSGG/graph.json","fetch_events":"https://pith.science/api/pith-number/P7MNHH367PIZUHT35PUTBMNSGG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/P7MNHH367PIZUHT35PUTBMNSGG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/P7MNHH367PIZUHT35PUTBMNSGG/action/storage_attestation","attest_author":"https://pith.science/pith/P7MNHH367PIZUHT35PUTBMNSGG/action/author_attestation","sign_citation":"https://pith.science/pith/P7MNHH367PIZUHT35PUTBMNSGG/action/citation_signature","submit_replication":"https://pith.science/pith/P7MNHH367PIZUHT35PUTBMNSGG/action/replication_record"}},"created_at":"2026-07-05T09:23:45.485502+00:00","updated_at":"2026-07-05T09:23:45.485502+00:00"}