{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:LZPU6QNHSFXDX3GWWYBKD63BGA","short_pith_number":"pith:LZPU6QNH","canonical_record":{"source":{"id":"2507.06644","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2025-07-09T08:17:03Z","cross_cats_sorted":["physics.data-an"],"title_canon_sha256":"31fd6007242f2d040dd27c9a9f85d2281b117520256737e2054e2730dd4e0ae6","abstract_canon_sha256":"fbf3bb890ad2a4f9dd349e3b58421520e9e8b5e3fd4e6516a385ef7943f9bd20"},"schema_version":"1.0"},"canonical_sha256":"5e5f4f41a7916e3becd6b602a1fb613011e25aa02726b86d4d5a14b9cfcb57f2","source":{"kind":"arxiv","id":"2507.06644","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.06644","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"arxiv_version","alias_value":"2507.06644v1","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.06644","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_12","alias_value":"LZPU6QNHSFXD","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_16","alias_value":"LZPU6QNHSFXDX3GW","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_8","alias_value":"LZPU6QNH","created_at":"2026-07-05T11:34:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:LZPU6QNHSFXDX3GWWYBKD63BGA","target":"record","payload":{"canonical_record":{"source":{"id":"2507.06644","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2025-07-09T08:17:03Z","cross_cats_sorted":["physics.data-an"],"title_canon_sha256":"31fd6007242f2d040dd27c9a9f85d2281b117520256737e2054e2730dd4e0ae6","abstract_canon_sha256":"fbf3bb890ad2a4f9dd349e3b58421520e9e8b5e3fd4e6516a385ef7943f9bd20"},"schema_version":"1.0"},"canonical_sha256":"5e5f4f41a7916e3becd6b602a1fb613011e25aa02726b86d4d5a14b9cfcb57f2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:34:20.135631Z","signature_b64":"Xrs+VHoxzcWnXqbu0pugI8rGU4vINffpn9zdF4EuGmILJV0y2oYw3rJhas21R3WPRZvhk9SEVB+hBtMtdCqLDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5e5f4f41a7916e3becd6b602a1fb613011e25aa02726b86d4d5a14b9cfcb57f2","last_reissued_at":"2026-07-05T11:34:20.135050Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:34:20.135050Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.06644","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":"2026-07-05T11:34:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MV7Bv6lMmh64e2ls5YXZnpBYQLz6Z1Kar/0KCndjjqUt8yF6YxpC594+e98wLDtv+4Xnrvh95G3WCpY+XYbDCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-02T22:39:14.985176Z"},"content_sha256":"fab6d6de4817d1b4623bf2c1cfd9d90ab737d2827f6d2db752ddc3c0106b81ea","schema_version":"1.0","event_id":"sha256:fab6d6de4817d1b4623bf2c1cfd9d90ab737d2827f6d2db752ddc3c0106b81ea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:LZPU6QNHSFXDX3GWWYBKD63BGA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["physics.data-an"],"primary_cat":"cond-mat.mtrl-sci","authors_text":"Clement Atlan, Ewen Bellec, Marie-Ingrid Richard, Matteo Masto, Steven Leake, Tobias Sch\\\"ulli, Vincent Favre-Nicolin","submitted_at":"2025-07-09T08:17:03Z","abstract_excerpt":"In Bragg Coherent Diffraction Imaging (BCDI), Phase Retrieval of highly strained crystals is often challenging with standard iterative algorithms. This computational obstacle limits the potential of the technique as it precludes the reconstruction of physically interesting highly-strained particles. Here, we propose a novel approach to this problem using a supervised Convolutional Neural Network (CNN) trained on 3D simulated diffraction data to predict the corresponding reciprocal space phase. This method allows to fully exploit the potential of the CNN by mapping functions within the same spa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.06644","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/2507.06644/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":"2026-07-05T11:34:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Xst23bWVfXhxd4YgjnxdW81W0EA48IT2bsvbnGh2YaruThvwdWmLGpS2/IWgThmz1Mc0LORFym9trXcPdbR4CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-02T22:39:14.985877Z"},"content_sha256":"516840ac359c0a54a2a2cde480d1981c8dada3eef89bd3b168f1e811e91eaeab","schema_version":"1.0","event_id":"sha256:516840ac359c0a54a2a2cde480d1981c8dada3eef89bd3b168f1e811e91eaeab"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LZPU6QNHSFXDX3GWWYBKD63BGA/bundle.json","state_url":"https://pith.science/pith/LZPU6QNHSFXDX3GWWYBKD63BGA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LZPU6QNHSFXDX3GWWYBKD63BGA/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":"2026-08-02T22:39:14Z","links":{"resolver":"https://pith.science/pith/LZPU6QNHSFXDX3GWWYBKD63BGA","bundle":"https://pith.science/pith/LZPU6QNHSFXDX3GWWYBKD63BGA/bundle.json","state":"https://pith.science/pith/LZPU6QNHSFXDX3GWWYBKD63BGA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LZPU6QNHSFXDX3GWWYBKD63BGA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LZPU6QNHSFXDX3GWWYBKD63BGA","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":"fbf3bb890ad2a4f9dd349e3b58421520e9e8b5e3fd4e6516a385ef7943f9bd20","cross_cats_sorted":["physics.data-an"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2025-07-09T08:17:03Z","title_canon_sha256":"31fd6007242f2d040dd27c9a9f85d2281b117520256737e2054e2730dd4e0ae6"},"schema_version":"1.0","source":{"id":"2507.06644","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.06644","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"arxiv_version","alias_value":"2507.06644v1","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.06644","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_12","alias_value":"LZPU6QNHSFXD","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_16","alias_value":"LZPU6QNHSFXDX3GW","created_at":"2026-07-05T11:34:20Z"},{"alias_kind":"pith_short_8","alias_value":"LZPU6QNH","created_at":"2026-07-05T11:34:20Z"}],"graph_snapshots":[{"event_id":"sha256:516840ac359c0a54a2a2cde480d1981c8dada3eef89bd3b168f1e811e91eaeab","target":"graph","created_at":"2026-07-05T11:34:20Z","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/2507.06644/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In Bragg Coherent Diffraction Imaging (BCDI), Phase Retrieval of highly strained crystals is often challenging with standard iterative algorithms. This computational obstacle limits the potential of the technique as it precludes the reconstruction of physically interesting highly-strained particles. Here, we propose a novel approach to this problem using a supervised Convolutional Neural Network (CNN) trained on 3D simulated diffraction data to predict the corresponding reciprocal space phase. This method allows to fully exploit the potential of the CNN by mapping functions within the same spa","authors_text":"Clement Atlan, Ewen Bellec, Marie-Ingrid Richard, Matteo Masto, Steven Leake, Tobias Sch\\\"ulli, Vincent Favre-Nicolin","cross_cats":["physics.data-an"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2025-07-09T08:17:03Z","title":"Phase Retrieval of Highly Strained Bragg Coherent Diffraction Patterns using Supervised Convolutional Neural Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.06644","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:fab6d6de4817d1b4623bf2c1cfd9d90ab737d2827f6d2db752ddc3c0106b81ea","target":"record","created_at":"2026-07-05T11:34:20Z","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":"fbf3bb890ad2a4f9dd349e3b58421520e9e8b5e3fd4e6516a385ef7943f9bd20","cross_cats_sorted":["physics.data-an"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cond-mat.mtrl-sci","submitted_at":"2025-07-09T08:17:03Z","title_canon_sha256":"31fd6007242f2d040dd27c9a9f85d2281b117520256737e2054e2730dd4e0ae6"},"schema_version":"1.0","source":{"id":"2507.06644","kind":"arxiv","version":1}},"canonical_sha256":"5e5f4f41a7916e3becd6b602a1fb613011e25aa02726b86d4d5a14b9cfcb57f2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5e5f4f41a7916e3becd6b602a1fb613011e25aa02726b86d4d5a14b9cfcb57f2","first_computed_at":"2026-07-05T11:34:20.135050Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:34:20.135050Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Xrs+VHoxzcWnXqbu0pugI8rGU4vINffpn9zdF4EuGmILJV0y2oYw3rJhas21R3WPRZvhk9SEVB+hBtMtdCqLDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:34:20.135631Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.06644","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fab6d6de4817d1b4623bf2c1cfd9d90ab737d2827f6d2db752ddc3c0106b81ea","sha256:516840ac359c0a54a2a2cde480d1981c8dada3eef89bd3b168f1e811e91eaeab"],"state_sha256":"23a7d1bdaa3866ba710b6e807cef4fc6cc0e3f258242a55ca2b42ef40ce94f66"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZjLxYM4z4cXFt5mQwgNny5+X5klteQCbnCn0FPVgBIHhWlpWLOM5nZd9XGkP3QErXN3E7xxIZaPm65/8wNo+Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-02T22:39:14.991315Z","bundle_sha256":"aae05fea1ee7743d5b67eda64bf55ffc4dd3b8a3f618bc54dcf6fa06b1813d8d"}}