{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:JO5FZNUL2X6NYOG2PD6VFL3VFV","short_pith_number":"pith:JO5FZNUL","canonical_record":{"source":{"id":"2605.18170","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-18T10:12:57Z","cross_cats_sorted":["cs.CE","cs.LG"],"title_canon_sha256":"8e4fc00e905a9581a0955bc129e06a984d946323d6119a8650d2f727dbe957e9","abstract_canon_sha256":"cfd0e0057758e80fab7447e91888f6cc5f821617610fc5e1eac1553228150a77"},"schema_version":"1.0"},"canonical_sha256":"4bba5cb68bd5fcdc38da78fd52af752d70c18133a0f1ac5de9b6b01232cf6349","source":{"kind":"arxiv","id":"2605.18170","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.18170","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"arxiv_version","alias_value":"2605.18170v1","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18170","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"pith_short_12","alias_value":"JO5FZNUL2X6N","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"pith_short_16","alias_value":"JO5FZNUL2X6NYOG2","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"pith_short_8","alias_value":"JO5FZNUL","created_at":"2026-05-20T00:05:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:JO5FZNUL2X6NYOG2PD6VFL3VFV","target":"record","payload":{"canonical_record":{"source":{"id":"2605.18170","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-18T10:12:57Z","cross_cats_sorted":["cs.CE","cs.LG"],"title_canon_sha256":"8e4fc00e905a9581a0955bc129e06a984d946323d6119a8650d2f727dbe957e9","abstract_canon_sha256":"cfd0e0057758e80fab7447e91888f6cc5f821617610fc5e1eac1553228150a77"},"schema_version":"1.0"},"canonical_sha256":"4bba5cb68bd5fcdc38da78fd52af752d70c18133a0f1ac5de9b6b01232cf6349","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:05:49.189541Z","signature_b64":"9l2RDwTrNwPa7PvPiEmck+CIKZ5jxi19kO8OCLitxLAyCVPmk1uxXL81mRpbQaGj18DGy17xHLJpZFNgR8tSCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4bba5cb68bd5fcdc38da78fd52af752d70c18133a0f1ac5de9b6b01232cf6349","last_reissued_at":"2026-05-20T00:05:49.188942Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:05:49.188942Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.18170","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":"2026-05-20T00:05:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+988jBcfeBXMTEdSo3L/qY11ZXim+0R03ag2AKzukZspp1mczQfC9JkZ75ejt1jVrjjsfL/H6yAAr/oKJmWPBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T19:29:52.022137Z"},"content_sha256":"ecfffbdadccf3dbf4a2a1477a396924bcf184dae1789c26b0c07616a5cec7e71","schema_version":"1.0","event_id":"sha256:ecfffbdadccf3dbf4a2a1477a396924bcf184dae1789c26b0c07616a5cec7e71"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:JO5FZNUL2X6NYOG2PD6VFL3VFV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Buffer-Parameterized Machine Learning Surrogate Models for Cross-Technology Signal Integrity Analysis and Optimization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CE","cs.LG"],"primary_cat":"eess.SP","authors_text":"Emre Ecik, Julian With\\\"oft, J\\\"urgen G\\\"otze, Ralf Br\\\"uning, Werner John","submitted_at":"2026-05-18T10:12:57Z","abstract_excerpt":"Signal integrity (SI) analysis in printed circuit board (PCB) interconnects faces increasing complexity due to diverse integrated circuit (IC) buffer technologies, varying operating conditions, and manufacturing tolerances. Existing machine learning (ML) surrogate models for predicting SI metrics such as the inner eye contour, eye-height (EH), eye-width (EW), and transient waveform features typically rely on fixed buffer parameters, requiring costly new data generation and retraining cycles for every technology shift. This paper introduces a buffer-parameterized ML surrogate modeling methodolo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18170","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/2605.18170/integrity.json","findings":[],"available":true,"detectors_run":[{"name":"claim_evidence","ran_at":"2026-05-19T23:41:59.048470Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T23:33:35.352881Z","status":"skipped","version":"1.0.0","findings_count":0}],"snapshot_sha256":"a47baeefe88bda1698a7869f8488e071e017080bf34c127297900f23c79ffa62"},"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":"2026-05-20T00:05:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"JXLXMyHWq63EFOY6OmHxB48SGYM+FBSCZdehJ8rJbSWNC9wn7bOnySflV//sL6M/JqNnJ3Byid2K6XWQWZBOBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-06T19:29:52.022722Z"},"content_sha256":"2498cee87452ec448e33a99487bf160d5028d3633b3cb7d242272609e6fd0434","schema_version":"1.0","event_id":"sha256:2498cee87452ec448e33a99487bf160d5028d3633b3cb7d242272609e6fd0434"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JO5FZNUL2X6NYOG2PD6VFL3VFV/bundle.json","state_url":"https://pith.science/pith/JO5FZNUL2X6NYOG2PD6VFL3VFV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JO5FZNUL2X6NYOG2PD6VFL3VFV/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":"2026-06-06T19:29:52Z","links":{"resolver":"https://pith.science/pith/JO5FZNUL2X6NYOG2PD6VFL3VFV","bundle":"https://pith.science/pith/JO5FZNUL2X6NYOG2PD6VFL3VFV/bundle.json","state":"https://pith.science/pith/JO5FZNUL2X6NYOG2PD6VFL3VFV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JO5FZNUL2X6NYOG2PD6VFL3VFV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:JO5FZNUL2X6NYOG2PD6VFL3VFV","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":"cfd0e0057758e80fab7447e91888f6cc5f821617610fc5e1eac1553228150a77","cross_cats_sorted":["cs.CE","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-18T10:12:57Z","title_canon_sha256":"8e4fc00e905a9581a0955bc129e06a984d946323d6119a8650d2f727dbe957e9"},"schema_version":"1.0","source":{"id":"2605.18170","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.18170","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"arxiv_version","alias_value":"2605.18170v1","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.18170","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"pith_short_12","alias_value":"JO5FZNUL2X6N","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"pith_short_16","alias_value":"JO5FZNUL2X6NYOG2","created_at":"2026-05-20T00:05:49Z"},{"alias_kind":"pith_short_8","alias_value":"JO5FZNUL","created_at":"2026-05-20T00:05:49Z"}],"graph_snapshots":[{"event_id":"sha256:2498cee87452ec448e33a99487bf160d5028d3633b3cb7d242272609e6fd0434","target":"graph","created_at":"2026-05-20T00:05:49Z","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":[{"findings_count":0,"name":"claim_evidence","ran_at":"2026-05-19T23:41:59.048470Z","status":"completed","version":"1.0.0"},{"findings_count":0,"name":"ai_meta_artifact","ran_at":"2026-05-19T23:33:35.352881Z","status":"skipped","version":"1.0.0"}],"endpoint":"/pith/2605.18170/integrity.json","findings":[],"snapshot_sha256":"a47baeefe88bda1698a7869f8488e071e017080bf34c127297900f23c79ffa62","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Signal integrity (SI) analysis in printed circuit board (PCB) interconnects faces increasing complexity due to diverse integrated circuit (IC) buffer technologies, varying operating conditions, and manufacturing tolerances. Existing machine learning (ML) surrogate models for predicting SI metrics such as the inner eye contour, eye-height (EH), eye-width (EW), and transient waveform features typically rely on fixed buffer parameters, requiring costly new data generation and retraining cycles for every technology shift. This paper introduces a buffer-parameterized ML surrogate modeling methodolo","authors_text":"Emre Ecik, Julian With\\\"oft, J\\\"urgen G\\\"otze, Ralf Br\\\"uning, Werner John","cross_cats":["cs.CE","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-18T10:12:57Z","title":"Buffer-Parameterized Machine Learning Surrogate Models for Cross-Technology Signal Integrity Analysis and Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.18170","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:ecfffbdadccf3dbf4a2a1477a396924bcf184dae1789c26b0c07616a5cec7e71","target":"record","created_at":"2026-05-20T00:05:49Z","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":"cfd0e0057758e80fab7447e91888f6cc5f821617610fc5e1eac1553228150a77","cross_cats_sorted":["cs.CE","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SP","submitted_at":"2026-05-18T10:12:57Z","title_canon_sha256":"8e4fc00e905a9581a0955bc129e06a984d946323d6119a8650d2f727dbe957e9"},"schema_version":"1.0","source":{"id":"2605.18170","kind":"arxiv","version":1}},"canonical_sha256":"4bba5cb68bd5fcdc38da78fd52af752d70c18133a0f1ac5de9b6b01232cf6349","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4bba5cb68bd5fcdc38da78fd52af752d70c18133a0f1ac5de9b6b01232cf6349","first_computed_at":"2026-05-20T00:05:49.188942Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:05:49.188942Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9l2RDwTrNwPa7PvPiEmck+CIKZ5jxi19kO8OCLitxLAyCVPmk1uxXL81mRpbQaGj18DGy17xHLJpZFNgR8tSCQ==","signature_status":"signed_v1","signed_at":"2026-05-20T00:05:49.189541Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.18170","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ecfffbdadccf3dbf4a2a1477a396924bcf184dae1789c26b0c07616a5cec7e71","sha256:2498cee87452ec448e33a99487bf160d5028d3633b3cb7d242272609e6fd0434"],"state_sha256":"61895cf45ef114bbec58c0581a586f660e3d4b7f73794d813c6a14fb193e9342"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"s+k9Rz+60Zg9U9Jh3MTJOqHAt/y1xOfvOYuJoS5XxTDkEDyLcTpEdMLSbhdH/zuWUbHlTVDTXXIBuM/6zk2qAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-06T19:29:52.026223Z","bundle_sha256":"bf3901692e2228997a0caafb9ca3cf1d6ae91fb3d66443f0ba37fa55c6866bd1"}}