{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:YRQF4O2EQAKWL57XDXQM3SQ2UC","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":"140c6a6481cd13a3c4e6416478d0a5eab0dee1c201097892b2f4350c3f8907a6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-06-11T23:12:09Z","title_canon_sha256":"b283d26d31c9adc5fb4728b8014bf0adb57645c6dbf67b75aba11f1f7790b9eb"},"schema_version":"1.0","source":{"id":"1907.01526","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.01526","created_at":"2026-05-17T23:41:40Z"},{"alias_kind":"arxiv_version","alias_value":"1907.01526v1","created_at":"2026-05-17T23:41:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.01526","created_at":"2026-05-17T23:41:40Z"},{"alias_kind":"pith_short_12","alias_value":"YRQF4O2EQAKW","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_16","alias_value":"YRQF4O2EQAKWL57X","created_at":"2026-05-18T12:33:33Z"},{"alias_kind":"pith_short_8","alias_value":"YRQF4O2E","created_at":"2026-05-18T12:33:33Z"}],"graph_snapshots":[{"event_id":"sha256:b1ca3548037e37dde5da86c4da141558b7f78e3687ac69fc4921b9ad0d26c7f7","target":"graph","created_at":"2026-05-17T23:41:40Z","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"},"paper":{"abstract_excerpt":"The gap between abstraction levels in analog design is a major obstacle for advancing analog and mixed-signal (AMS) design automation and computer-aided design (CAD). Intelligent models for low-level analog building blocks are needed to bridge the accuracy gap between behavioral and transistor-level simulations. The models should be able to accurately estimate the characteristics of the analog block over a large design space. Machine learning (ML) models based on actual silicon have the capabilities of capturing detailed characteristics of complex designs. In this paper, a ML model called Arti","authors_text":"Elias Kougianos, Saraju P. Mohanty","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-06-11T23:12:09Z","title":"iVAMS 2.0: Machine-Learning-Metamodel-Integrated Intelligent Verilog-AMS for Fast and Accurate Mixed-Signal Design Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.01526","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:fb10396085ff5222c0fdc96cf8d9670a712a26cbe7469b88d3ea903f5257fb51","target":"record","created_at":"2026-05-17T23:41:40Z","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":"140c6a6481cd13a3c4e6416478d0a5eab0dee1c201097892b2f4350c3f8907a6","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2019-06-11T23:12:09Z","title_canon_sha256":"b283d26d31c9adc5fb4728b8014bf0adb57645c6dbf67b75aba11f1f7790b9eb"},"schema_version":"1.0","source":{"id":"1907.01526","kind":"arxiv","version":1}},"canonical_sha256":"c4605e3b44801565f7f71de0cdca1aa0b60023312bce8a0f2c7ae4ce6947adc6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c4605e3b44801565f7f71de0cdca1aa0b60023312bce8a0f2c7ae4ce6947adc6","first_computed_at":"2026-05-17T23:41:40.138232Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:41:40.138232Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"60gJZmP7lQFpCkIsK8ps+cS3CLKqtsC7Kmhq4e9Dh/WUf7WDo0FFo+HKj+TEXxYtEb8AnXa6swujhfCNCqNnCg==","signature_status":"signed_v1","signed_at":"2026-05-17T23:41:40.138822Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.01526","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fb10396085ff5222c0fdc96cf8d9670a712a26cbe7469b88d3ea903f5257fb51","sha256:b1ca3548037e37dde5da86c4da141558b7f78e3687ac69fc4921b9ad0d26c7f7"],"state_sha256":"da24e48c3da7fbb1e902e210fe827887689bea1e304f61dcc1a3750d1e58bab0"}