{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:HZ3OCEO22KCIV2J2MXOMY3QB3F","short_pith_number":"pith:HZ3OCEO2","canonical_record":{"source":{"id":"2506.14138","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-06-17T03:02:04Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"22c5849c66e2fa5b40eeb731dadf8a578c34063710db9753018d228881f2e075","abstract_canon_sha256":"7a5ebc669b8e24cd191ad3aa80d031c09448d4ac312a668ab229c47e7431432a"},"schema_version":"1.0"},"canonical_sha256":"3e76e111dad2848ae93a65dccc6e01d973de8ee857e99436fd518edad336a2f3","source":{"kind":"arxiv","id":"2506.14138","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.14138","created_at":"2026-07-05T11:22:49Z"},{"alias_kind":"arxiv_version","alias_value":"2506.14138v1","created_at":"2026-07-05T11:22:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.14138","created_at":"2026-07-05T11:22:49Z"},{"alias_kind":"pith_short_12","alias_value":"HZ3OCEO22KCI","created_at":"2026-07-05T11:22:49Z"},{"alias_kind":"pith_short_16","alias_value":"HZ3OCEO22KCIV2J2","created_at":"2026-07-05T11:22:49Z"},{"alias_kind":"pith_short_8","alias_value":"HZ3OCEO2","created_at":"2026-07-05T11:22:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:HZ3OCEO22KCIV2J2MXOMY3QB3F","target":"record","payload":{"canonical_record":{"source":{"id":"2506.14138","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-06-17T03:02:04Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"22c5849c66e2fa5b40eeb731dadf8a578c34063710db9753018d228881f2e075","abstract_canon_sha256":"7a5ebc669b8e24cd191ad3aa80d031c09448d4ac312a668ab229c47e7431432a"},"schema_version":"1.0"},"canonical_sha256":"3e76e111dad2848ae93a65dccc6e01d973de8ee857e99436fd518edad336a2f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:22:49.777130Z","signature_b64":"yJMmAjNuvHuyP1NX/GSG8Vi/CebJYjkx1sOExPQpUYYlR+F9UTX26TGax+ch3IdxRfgu2i/09cANj/th2okLBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3e76e111dad2848ae93a65dccc6e01d973de8ee857e99436fd518edad336a2f3","last_reissued_at":"2026-07-05T11:22:49.776582Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:22:49.776582Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.14138","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:22:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rBg7Rk0OyK9Cp1wHGAV1VmEApo6fPz8gIdiRbFevdOAAp4wwPUfNfmQqnd8vSUVwzB9U3rH0g0mYZY6Lm8gmCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T04:26:27.663961Z"},"content_sha256":"4e1ca4911f0ae689bf92e7d3fa53ec812df4f759f3a90314265a7d822462db85","schema_version":"1.0","event_id":"sha256:4e1ca4911f0ae689bf92e7d3fa53ec812df4f759f3a90314265a7d822462db85"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:HZ3OCEO22KCIV2J2MXOMY3QB3F","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.NE","authors_text":"Ashish Gautam, Prasanna Date, Robert Patton, Shruti Kulkarni, Thomas Potok","submitted_at":"2025-06-17T03:02:04Z","abstract_excerpt":"Spiking Neural Networks (SNNs) are computational models inspired by the structure and dynamics of biological neuronal networks. Their event-driven nature enables them to achieve high energy efficiency, particularly when deployed on neuromorphic hardware platforms. Unlike conventional Artificial Neural Networks (ANNs), which primarily rely on layered architectures, SNNs naturally support a wide range of connectivity patterns, from traditional layered structures to small-world graphs characterized by locally dense and globally sparse connections. In this work, we introduce NeuroCoreX, an FPGA-ba"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.14138","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/2506.14138/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:22:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EtfxItuSxRoQQrIpqnpaqxCKIm6515RnsBIFdnfh9kxHUEggg1YU42hy0FyJyTOBYuagGq0nWESxZ9YE44KKCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-19T04:26:27.664333Z"},"content_sha256":"2e86a9ca73b9c2c1a2554d8656e05cb887d778bd2594821a3e6c86612c519353","schema_version":"1.0","event_id":"sha256:2e86a9ca73b9c2c1a2554d8656e05cb887d778bd2594821a3e6c86612c519353"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HZ3OCEO22KCIV2J2MXOMY3QB3F/bundle.json","state_url":"https://pith.science/pith/HZ3OCEO22KCIV2J2MXOMY3QB3F/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HZ3OCEO22KCIV2J2MXOMY3QB3F/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-07-19T04:26:27Z","links":{"resolver":"https://pith.science/pith/HZ3OCEO22KCIV2J2MXOMY3QB3F","bundle":"https://pith.science/pith/HZ3OCEO22KCIV2J2MXOMY3QB3F/bundle.json","state":"https://pith.science/pith/HZ3OCEO22KCIV2J2MXOMY3QB3F/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HZ3OCEO22KCIV2J2MXOMY3QB3F/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:HZ3OCEO22KCIV2J2MXOMY3QB3F","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":"7a5ebc669b8e24cd191ad3aa80d031c09448d4ac312a668ab229c47e7431432a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-06-17T03:02:04Z","title_canon_sha256":"22c5849c66e2fa5b40eeb731dadf8a578c34063710db9753018d228881f2e075"},"schema_version":"1.0","source":{"id":"2506.14138","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.14138","created_at":"2026-07-05T11:22:49Z"},{"alias_kind":"arxiv_version","alias_value":"2506.14138v1","created_at":"2026-07-05T11:22:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.14138","created_at":"2026-07-05T11:22:49Z"},{"alias_kind":"pith_short_12","alias_value":"HZ3OCEO22KCI","created_at":"2026-07-05T11:22:49Z"},{"alias_kind":"pith_short_16","alias_value":"HZ3OCEO22KCIV2J2","created_at":"2026-07-05T11:22:49Z"},{"alias_kind":"pith_short_8","alias_value":"HZ3OCEO2","created_at":"2026-07-05T11:22:49Z"}],"graph_snapshots":[{"event_id":"sha256:2e86a9ca73b9c2c1a2554d8656e05cb887d778bd2594821a3e6c86612c519353","target":"graph","created_at":"2026-07-05T11:22:49Z","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/2506.14138/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Spiking Neural Networks (SNNs) are computational models inspired by the structure and dynamics of biological neuronal networks. Their event-driven nature enables them to achieve high energy efficiency, particularly when deployed on neuromorphic hardware platforms. Unlike conventional Artificial Neural Networks (ANNs), which primarily rely on layered architectures, SNNs naturally support a wide range of connectivity patterns, from traditional layered structures to small-world graphs characterized by locally dense and globally sparse connections. In this work, we introduce NeuroCoreX, an FPGA-ba","authors_text":"Ashish Gautam, Prasanna Date, Robert Patton, Shruti Kulkarni, Thomas Potok","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-06-17T03:02:04Z","title":"NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.14138","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":"sha256:4e1ca4911f0ae689bf92e7d3fa53ec812df4f759f3a90314265a7d822462db85","target":"record","created_at":"2026-07-05T11:22:49Z","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":"7a5ebc669b8e24cd191ad3aa80d031c09448d4ac312a668ab229c47e7431432a","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.NE","submitted_at":"2025-06-17T03:02:04Z","title_canon_sha256":"22c5849c66e2fa5b40eeb731dadf8a578c34063710db9753018d228881f2e075"},"schema_version":"1.0","source":{"id":"2506.14138","kind":"arxiv","version":1}},"canonical_sha256":"3e76e111dad2848ae93a65dccc6e01d973de8ee857e99436fd518edad336a2f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3e76e111dad2848ae93a65dccc6e01d973de8ee857e99436fd518edad336a2f3","first_computed_at":"2026-07-05T11:22:49.776582Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:22:49.776582Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yJMmAjNuvHuyP1NX/GSG8Vi/CebJYjkx1sOExPQpUYYlR+F9UTX26TGax+ch3IdxRfgu2i/09cANj/th2okLBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:22:49.777130Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.14138","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e1ca4911f0ae689bf92e7d3fa53ec812df4f759f3a90314265a7d822462db85","sha256:2e86a9ca73b9c2c1a2554d8656e05cb887d778bd2594821a3e6c86612c519353"],"state_sha256":"4877b9f95c132c00cdcc46e54761c7254e4166a03751dfedf06fe1e5e9509309"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZjRvcKrva2ykoO5m2zq5uEy70E8W01jFGMfX4EaWzzU15GqvxBkNeVZm+PnovkD8+gc/WXKnrlWh2rzHGfpzDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-19T04:26:27.666347Z","bundle_sha256":"954307f2a86a255ecf43e66354f241dd247d7928f692092ae978d979d522a8da"}}