{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:PTM5ZM4OGVHGB2DMKYMHQG4NCR","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":"0f6bed316f447cef40867c491e3fd9ab53c8bcb86ecbf202ad08f393c553a074","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.SP","submitted_at":"2026-06-22T19:10:22Z","title_canon_sha256":"1f0572d646dfefb924355f282227c29ae36805fd32ba5857d920befe18b9ea1f"},"schema_version":"1.0","source":{"id":"2606.23868","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.23868","created_at":"2026-06-24T00:14:28Z"},{"alias_kind":"arxiv_version","alias_value":"2606.23868v1","created_at":"2026-06-24T00:14:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.23868","created_at":"2026-06-24T00:14:28Z"},{"alias_kind":"pith_short_12","alias_value":"PTM5ZM4OGVHG","created_at":"2026-06-24T00:14:28Z"},{"alias_kind":"pith_short_16","alias_value":"PTM5ZM4OGVHGB2DM","created_at":"2026-06-24T00:14:28Z"},{"alias_kind":"pith_short_8","alias_value":"PTM5ZM4O","created_at":"2026-06-24T00:14:28Z"}],"graph_snapshots":[{"event_id":"sha256:4a007db6f8c66adb0a49cef3c5a8e541dafc29dfe2a5ceca511df726e441723b","target":"graph","created_at":"2026-06-24T00:14:28Z","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/2606.23868/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, machine learning (ML) methods have become increasingly popular for wireless communication systems. These require large amounts of data reflecting the behavior of realistic channels with high fidelity. However, sampling over-the-air (OTA) channel data is an extremely resource-intensive process which cannot accurately represent the variety of real world channels. This results in the need for realistic training data for ML systems. To this end, generative models have been proposed to synthesize channel data. However,(i) the outputs produced by such methods may not correspond to p","authors_text":"Aditya Sant, Akshay Malhotra, Christopher G. Brinton, David J. Love, Satyavrat Wagle, Shahab Hamidi-Rad","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.SP","submitted_at":"2026-06-22T19:10:22Z","title":"Unlocking Realism and Interpretability in Wireless Channel Synthesis: A Physics-Guided Generative Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.23868","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:ceeb245b6222ac90b4e890043df3fbbcfc93c4bdfb7234ed1ae33b901c455d5b","target":"record","created_at":"2026-06-24T00:14:28Z","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":"0f6bed316f447cef40867c491e3fd9ab53c8bcb86ecbf202ad08f393c553a074","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.SP","submitted_at":"2026-06-22T19:10:22Z","title_canon_sha256":"1f0572d646dfefb924355f282227c29ae36805fd32ba5857d920befe18b9ea1f"},"schema_version":"1.0","source":{"id":"2606.23868","kind":"arxiv","version":1}},"canonical_sha256":"7cd9dcb38e354e60e86c5618781b8d146735b09122790357263178c311b5a9f8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7cd9dcb38e354e60e86c5618781b8d146735b09122790357263178c311b5a9f8","first_computed_at":"2026-06-24T00:14:28.959540Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-24T00:14:28.959540Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"IBVGZhG9Uksw7siDYlVQmLNH86JWw0O9UFGpDgryuGWUnCTE8w3b791NwpbDnRY0SmhzgcHYfgpH3SBoxHxuCQ==","signature_status":"signed_v1","signed_at":"2026-06-24T00:14:28.959927Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.23868","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ceeb245b6222ac90b4e890043df3fbbcfc93c4bdfb7234ed1ae33b901c455d5b","sha256:4a007db6f8c66adb0a49cef3c5a8e541dafc29dfe2a5ceca511df726e441723b"],"state_sha256":"567ec05776ce7f554d2465d98d94da643b48d5adee91e07f56fb14c641f198fa"}