{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:C6WPKMW6BAW3S5OLYOEDOGUA44","short_pith_number":"pith:C6WPKMW6","canonical_record":{"source":{"id":"2608.05339","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-08-05T18:56:36Z","cross_cats_sorted":[],"title_canon_sha256":"86cf5fcdba220a2a7310449004857bbcd33edd161cad26c3b80d2d23b5f2e697","abstract_canon_sha256":"5ffd918a9c75473edff641fb098fa01e148361f897f985c7b7ceffa4a6461edd"},"schema_version":"1.0"},"canonical_sha256":"17acf532de082db975cbc388371a80e73e160e36b225473de1a95a588ed4ce19","source":{"kind":"arxiv","id":"2608.05339","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.05339","created_at":"2026-08-07T00:47:02Z"},{"alias_kind":"arxiv_version","alias_value":"2608.05339v1","created_at":"2026-08-07T00:47:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.05339","created_at":"2026-08-07T00:47:02Z"},{"alias_kind":"pith_short_12","alias_value":"C6WPKMW6BAW3","created_at":"2026-08-07T00:47:02Z"},{"alias_kind":"pith_short_16","alias_value":"C6WPKMW6BAW3S5OL","created_at":"2026-08-07T00:47:02Z"},{"alias_kind":"pith_short_8","alias_value":"C6WPKMW6","created_at":"2026-08-07T00:47:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:C6WPKMW6BAW3S5OLYOEDOGUA44","target":"record","payload":{"canonical_record":{"source":{"id":"2608.05339","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-08-05T18:56:36Z","cross_cats_sorted":[],"title_canon_sha256":"86cf5fcdba220a2a7310449004857bbcd33edd161cad26c3b80d2d23b5f2e697","abstract_canon_sha256":"5ffd918a9c75473edff641fb098fa01e148361f897f985c7b7ceffa4a6461edd"},"schema_version":"1.0"},"canonical_sha256":"17acf532de082db975cbc388371a80e73e160e36b225473de1a95a588ed4ce19","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-07T00:47:02.362625Z","signature_b64":"VNOoehZZTeN67wMa5Aptt36CyWj7kgryk9T+6uaq1JhYsZ+hj6ECtWdaVcGXZryy2ONnUBY25tQs21RUzhnPDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"17acf532de082db975cbc388371a80e73e160e36b225473de1a95a588ed4ce19","last_reissued_at":"2026-08-07T00:47:02.361229Z","signature_status":"signed_v1","first_computed_at":"2026-08-07T00:47:02.361229Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2608.05339","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":"2026-08-07T00:47:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"64EpYiBlNXjPX4vGEpziWhnlP3NVJE5XPnklis97iagiFKGt6GNCS1KwkzuYv5QaNx17Hky6Ufevy8LeihJjCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T23:05:18.715386Z"},"content_sha256":"585800eeb1d92256e216b757599f715162a2a3a44e8b4eab4f878d5efa28c0e0","schema_version":"1.0","event_id":"sha256:585800eeb1d92256e216b757599f715162a2a3a44e8b4eab4f878d5efa28c0e0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:C6WPKMW6BAW3S5OLYOEDOGUA44","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PowerScope: ML-based Intra-Cycle Power Estimation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AR","authors_text":"Anand Raghunathan, Jayanth Balasubramanian, Radha Vaidya, Sujay Pandit","submitted_at":"2026-08-05T18:56:36Z","abstract_excerpt":"Power estimation at sub-clock-cycle temporal resolutions is critical for tasks such as power delivery network (PDN) design, dynamic voltage droop analysis, and pre-silicon power side-channel security evaluation. Designers commonly rely on commercial post-layout gate-level power analysis tools for these tasks, but these flows are computationally expensive and scale poorly with design size and workload length. Machine learning (ML)-based power estimation frameworks have shown promise in accelerating power estimation, but prior efforts only address average power or per-cycle power estimation. We "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.05339","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/2608.05339/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":"2026-08-07T00:47:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FOENTT3kUOHc7qPwC2NDYouJA6GbnziovdIJ3iwsJwPz0krFvmpjixS6acmNrxEi5BG0ecaV/us59tfpuSFyAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T23:05:18.715912Z"},"content_sha256":"88cd0e26d481bc371a81f919cb036ed1e33b195cb065ae3d45d35cc501882278","schema_version":"1.0","event_id":"sha256:88cd0e26d481bc371a81f919cb036ed1e33b195cb065ae3d45d35cc501882278"},{"event_type":"integrity_finding","subject_pith_number":"pith:2026:C6WPKMW6BAW3S5OLYOEDOGUA44","target":"integrity","payload":{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1007/978-94-007-0149-6_2) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"Michał Rewiénski. 2011. A Perspective on Fast-SPICE Simulation Technol- ogy. InSimulation and Verification of Electronic and Biological Systems, Peng Li, Luis Miguel Silveira, and Peter Feldmann (Eds.). Springer, 23–42. doi:10.1007/978- 94-","arxiv_id":"2608.05339","detector":"doi_compliance","evidence":{"ref_index":25,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"10.1007/978-","reconstructed_doi":"10.1007/978-94-007-0149-6_2"},"severity":"advisory","ref_index":25,"audited_at":"2026-08-08T15:08:11.059458Z","event_type":"pith.integrity.v1","detected_doi":"10.1007/978-94-007-0149-6_2","detector_url":"https://pith.science/pith-integrity-protocol#doi_compliance","external_url":null,"finding_type":"recoverable_identifier","evidence_hash":"adf2984724cbe81b6c47945fb2bcc915c6bdc244a98c538cbb198f08f6b3c849","paper_version":1,"verdict_class":"incontrovertible","resolved_title":null,"detector_version":"1.1.0","detected_arxiv_id":null,"integrity_event_id":18687,"payload_sha256":"13576e994120a5b5656aab4bb2d5bb9eb67d4339d7843ce05deb42df83beb04a","signature_b64":"xcYGVzuV3HByuAyH4H05w3NPWeteLvkoMDDgSIK9pKxhPDYOJwInbQziOBsMfJCOXvC39BBGC8QQCasA11uJAQ==","signing_key_id":"pith-v1-2026-05"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-08-08T15:08:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gEREu8F/UELV/dNm55bjFX4OkQf0G1ppf/uI8hRkgt607bho817ti/obkj3b6bsps7hskt+9NQDfpOYPX/FxDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-21T23:05:18.719964Z"},"content_sha256":"b04b8cd3f80fe3d4c9de6d60f0eb29abda32bf0356eaafa61ae4e6b3964b87b9","schema_version":"1.0","event_id":"sha256:b04b8cd3f80fe3d4c9de6d60f0eb29abda32bf0356eaafa61ae4e6b3964b87b9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/C6WPKMW6BAW3S5OLYOEDOGUA44/bundle.json","state_url":"https://pith.science/pith/C6WPKMW6BAW3S5OLYOEDOGUA44/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/C6WPKMW6BAW3S5OLYOEDOGUA44/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":"2026-08-21T23:05:18Z","links":{"resolver":"https://pith.science/pith/C6WPKMW6BAW3S5OLYOEDOGUA44","bundle":"https://pith.science/pith/C6WPKMW6BAW3S5OLYOEDOGUA44/bundle.json","state":"https://pith.science/pith/C6WPKMW6BAW3S5OLYOEDOGUA44/state.json","well_known_bundle":"https://pith.science/.well-known/pith/C6WPKMW6BAW3S5OLYOEDOGUA44/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:C6WPKMW6BAW3S5OLYOEDOGUA44","merge_version":"pith-open-graph-merge-v1","event_count":3,"valid_event_count":3,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"5ffd918a9c75473edff641fb098fa01e148361f897f985c7b7ceffa4a6461edd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-08-05T18:56:36Z","title_canon_sha256":"86cf5fcdba220a2a7310449004857bbcd33edd161cad26c3b80d2d23b5f2e697"},"schema_version":"1.0","source":{"id":"2608.05339","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.05339","created_at":"2026-08-07T00:47:02Z"},{"alias_kind":"arxiv_version","alias_value":"2608.05339v1","created_at":"2026-08-07T00:47:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.05339","created_at":"2026-08-07T00:47:02Z"},{"alias_kind":"pith_short_12","alias_value":"C6WPKMW6BAW3","created_at":"2026-08-07T00:47:02Z"},{"alias_kind":"pith_short_16","alias_value":"C6WPKMW6BAW3S5OL","created_at":"2026-08-07T00:47:02Z"},{"alias_kind":"pith_short_8","alias_value":"C6WPKMW6","created_at":"2026-08-07T00:47:02Z"}],"graph_snapshots":[{"event_id":"sha256:88cd0e26d481bc371a81f919cb036ed1e33b195cb065ae3d45d35cc501882278","target":"graph","created_at":"2026-08-07T00:47:02Z","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/2608.05339/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Power estimation at sub-clock-cycle temporal resolutions is critical for tasks such as power delivery network (PDN) design, dynamic voltage droop analysis, and pre-silicon power side-channel security evaluation. Designers commonly rely on commercial post-layout gate-level power analysis tools for these tasks, but these flows are computationally expensive and scale poorly with design size and workload length. Machine learning (ML)-based power estimation frameworks have shown promise in accelerating power estimation, but prior efforts only address average power or per-cycle power estimation. We ","authors_text":"Anand Raghunathan, Jayanth Balasubramanian, Radha Vaidya, Sujay Pandit","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-08-05T18:56:36Z","title":"PowerScope: ML-based Intra-Cycle Power Estimation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.05339","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":"sha256:585800eeb1d92256e216b757599f715162a2a3a44e8b4eab4f878d5efa28c0e0","target":"record","created_at":"2026-08-07T00:47:02Z","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":"5ffd918a9c75473edff641fb098fa01e148361f897f985c7b7ceffa4a6461edd","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-08-05T18:56:36Z","title_canon_sha256":"86cf5fcdba220a2a7310449004857bbcd33edd161cad26c3b80d2d23b5f2e697"},"schema_version":"1.0","source":{"id":"2608.05339","kind":"arxiv","version":1}},"canonical_sha256":"17acf532de082db975cbc388371a80e73e160e36b225473de1a95a588ed4ce19","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"17acf532de082db975cbc388371a80e73e160e36b225473de1a95a588ed4ce19","first_computed_at":"2026-08-07T00:47:02.361229Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-07T00:47:02.361229Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VNOoehZZTeN67wMa5Aptt36CyWj7kgryk9T+6uaq1JhYsZ+hj6ECtWdaVcGXZryy2ONnUBY25tQs21RUzhnPDg==","signature_status":"signed_v1","signed_at":"2026-08-07T00:47:02.362625Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.05339","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:585800eeb1d92256e216b757599f715162a2a3a44e8b4eab4f878d5efa28c0e0","sha256:88cd0e26d481bc371a81f919cb036ed1e33b195cb065ae3d45d35cc501882278","sha256:b04b8cd3f80fe3d4c9de6d60f0eb29abda32bf0356eaafa61ae4e6b3964b87b9"],"state_sha256":"ab728d8ec240426aee39980fea107363e5137cc4be567221abcdaf3c72f2ecac"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1E7I206yTQnbPhpfSslfA+am08rhgyWU5IOkPpQNCGJpClmZg+nlyAB9jtlcd+rao3RtVqfAYooVXSZjriPvBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-21T23:05:18.722427Z","bundle_sha256":"44cd07d753af0066fcb2a6241983f9567c323decf36748ae340a68938b1629da"}}