{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:FIOPFQILJSLCH2V3QI7MPKUAHR","short_pith_number":"pith:FIOPFQIL","canonical_record":{"source":{"id":"2309.15747","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2023-09-27T16:02:32Z","cross_cats_sorted":["cs.IT","math.IT"],"title_canon_sha256":"445b177068834780e48a977204ba7678b363d8d95626eb2e47a64f00b88c4bcf","abstract_canon_sha256":"cabb2aef324e3386da2ecf5476df8bb3a8b81e3c60fe2fb3b978830f105d5399"},"schema_version":"1.0"},"canonical_sha256":"2a1cf2c10b4c9623eabb823ec7aa803c5d45ea855d38180cdde044e638c48411","source":{"kind":"arxiv","id":"2309.15747","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.15747","created_at":"2026-07-05T08:20:51Z"},{"alias_kind":"arxiv_version","alias_value":"2309.15747v2","created_at":"2026-07-05T08:20:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.15747","created_at":"2026-07-05T08:20:51Z"},{"alias_kind":"pith_short_12","alias_value":"FIOPFQILJSLC","created_at":"2026-07-05T08:20:51Z"},{"alias_kind":"pith_short_16","alias_value":"FIOPFQILJSLCH2V3","created_at":"2026-07-05T08:20:51Z"},{"alias_kind":"pith_short_8","alias_value":"FIOPFQIL","created_at":"2026-07-05T08:20:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:FIOPFQILJSLCH2V3QI7MPKUAHR","target":"record","payload":{"canonical_record":{"source":{"id":"2309.15747","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2023-09-27T16:02:32Z","cross_cats_sorted":["cs.IT","math.IT"],"title_canon_sha256":"445b177068834780e48a977204ba7678b363d8d95626eb2e47a64f00b88c4bcf","abstract_canon_sha256":"cabb2aef324e3386da2ecf5476df8bb3a8b81e3c60fe2fb3b978830f105d5399"},"schema_version":"1.0"},"canonical_sha256":"2a1cf2c10b4c9623eabb823ec7aa803c5d45ea855d38180cdde044e638c48411","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:20:51.118023Z","signature_b64":"LudVwJoYKhOVUHMd/Jwn47daHgSOLKpQT1852mVN1BP5liOpEP/LgUxu+wBXiue21hqKczgpbFelZGdIG5UVDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2a1cf2c10b4c9623eabb823ec7aa803c5d45ea855d38180cdde044e638c48411","last_reissued_at":"2026-07-05T08:20:51.117586Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:20:51.117586Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.15747","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:20:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jfTuB65OT3jGkxGNaGEWJS0X8IGYB8F7EuQO1IkosL5PvHWxdxGWE3D0LwL0jhn9UmtXLcQiJvF3gGLEmv2yDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T20:08:44.794350Z"},"content_sha256":"b2eaa1df008281fa47beda549dbecab2ca917de05eac600e02cf80891ef67b48","schema_version":"1.0","event_id":"sha256:b2eaa1df008281fa47beda549dbecab2ca917de05eac600e02cf80891ef67b48"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:FIOPFQILJSLCH2V3QI7MPKUAHR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Differentiable Machine Learning-Based Modeling for Directly-Modulated Lasers","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.IT","math.IT"],"primary_cat":"eess.SP","authors_text":"Christophe Peucheret, Darko Zibar, Francesco Da Ros, Ognjen Jovanovic, Sergio Hernandez","submitted_at":"2023-09-27T16:02:32Z","abstract_excerpt":"End-to-end learning has become a popular method for joint transmitter and receiver optimization in optical communication systems. Such approach may require a differentiable channel model, thus hindering the optimization of links based on directly modulated lasers (DMLs). This is due to the DML behavior in the large-signal regime, for which no analytical solution is available. In this paper, this problem is addressed by developing and comparing differentiable machine learning-based surrogate models. The models are quantitatively assessed in terms of root mean square error and training/testing t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.15747","kind":"arxiv","version":2},"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/2309.15747/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":"2026-07-05T08:20:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v1TYb04JSQ3pb9kbAG2Fl5GjPVnHJyRnsZW23wcb0TMXkDMzamVDQp7ARJMqDT17JcasTT0fjx6eHRCsVfmeCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T20:08:44.794735Z"},"content_sha256":"1ee52f4534f50c479ae511de5176f7b8696ec0079b7e74256572335a2b7f5299","schema_version":"1.0","event_id":"sha256:1ee52f4534f50c479ae511de5176f7b8696ec0079b7e74256572335a2b7f5299"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FIOPFQILJSLCH2V3QI7MPKUAHR/bundle.json","state_url":"https://pith.science/pith/FIOPFQILJSLCH2V3QI7MPKUAHR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FIOPFQILJSLCH2V3QI7MPKUAHR/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":"2026-07-28T20:08:44Z","links":{"resolver":"https://pith.science/pith/FIOPFQILJSLCH2V3QI7MPKUAHR","bundle":"https://pith.science/pith/FIOPFQILJSLCH2V3QI7MPKUAHR/bundle.json","state":"https://pith.science/pith/FIOPFQILJSLCH2V3QI7MPKUAHR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FIOPFQILJSLCH2V3QI7MPKUAHR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:FIOPFQILJSLCH2V3QI7MPKUAHR","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":"cabb2aef324e3386da2ecf5476df8bb3a8b81e3c60fe2fb3b978830f105d5399","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2023-09-27T16:02:32Z","title_canon_sha256":"445b177068834780e48a977204ba7678b363d8d95626eb2e47a64f00b88c4bcf"},"schema_version":"1.0","source":{"id":"2309.15747","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.15747","created_at":"2026-07-05T08:20:51Z"},{"alias_kind":"arxiv_version","alias_value":"2309.15747v2","created_at":"2026-07-05T08:20:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.15747","created_at":"2026-07-05T08:20:51Z"},{"alias_kind":"pith_short_12","alias_value":"FIOPFQILJSLC","created_at":"2026-07-05T08:20:51Z"},{"alias_kind":"pith_short_16","alias_value":"FIOPFQILJSLCH2V3","created_at":"2026-07-05T08:20:51Z"},{"alias_kind":"pith_short_8","alias_value":"FIOPFQIL","created_at":"2026-07-05T08:20:51Z"}],"graph_snapshots":[{"event_id":"sha256:1ee52f4534f50c479ae511de5176f7b8696ec0079b7e74256572335a2b7f5299","target":"graph","created_at":"2026-07-05T08:20:51Z","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/2309.15747/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"End-to-end learning has become a popular method for joint transmitter and receiver optimization in optical communication systems. Such approach may require a differentiable channel model, thus hindering the optimization of links based on directly modulated lasers (DMLs). This is due to the DML behavior in the large-signal regime, for which no analytical solution is available. In this paper, this problem is addressed by developing and comparing differentiable machine learning-based surrogate models. The models are quantitatively assessed in terms of root mean square error and training/testing t","authors_text":"Christophe Peucheret, Darko Zibar, Francesco Da Ros, Ognjen Jovanovic, Sergio Hernandez","cross_cats":["cs.IT","math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2023-09-27T16:02:32Z","title":"Differentiable Machine Learning-Based Modeling for Directly-Modulated Lasers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.15747","kind":"arxiv","version":2},"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:b2eaa1df008281fa47beda549dbecab2ca917de05eac600e02cf80891ef67b48","target":"record","created_at":"2026-07-05T08:20:51Z","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":"cabb2aef324e3386da2ecf5476df8bb3a8b81e3c60fe2fb3b978830f105d5399","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SP","submitted_at":"2023-09-27T16:02:32Z","title_canon_sha256":"445b177068834780e48a977204ba7678b363d8d95626eb2e47a64f00b88c4bcf"},"schema_version":"1.0","source":{"id":"2309.15747","kind":"arxiv","version":2}},"canonical_sha256":"2a1cf2c10b4c9623eabb823ec7aa803c5d45ea855d38180cdde044e638c48411","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2a1cf2c10b4c9623eabb823ec7aa803c5d45ea855d38180cdde044e638c48411","first_computed_at":"2026-07-05T08:20:51.117586Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:20:51.117586Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LudVwJoYKhOVUHMd/Jwn47daHgSOLKpQT1852mVN1BP5liOpEP/LgUxu+wBXiue21hqKczgpbFelZGdIG5UVDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:20:51.118023Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.15747","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b2eaa1df008281fa47beda549dbecab2ca917de05eac600e02cf80891ef67b48","sha256:1ee52f4534f50c479ae511de5176f7b8696ec0079b7e74256572335a2b7f5299"],"state_sha256":"df459a221b7b269e0dbf88db2c1e86172d55159545537181f84e97e79bdfd750"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jU6l64fKeJStAg5/+PeFLR5hH6y5eyqZCEEKRCTuwdw1kMrcTq8BiGrJiQUqvtPm7nzqvtsRLn3KqMzCFfKVDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-28T20:08:44.797081Z","bundle_sha256":"9cbb6563d1d3a079004b1e8b8f4d91f9c33ef9d27edf8fe6ff377376fba42f66"}}