{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:U2QLGBZI6OUXOONRWFG4TOV7LC","short_pith_number":"pith:U2QLGBZI","canonical_record":{"source":{"id":"2205.02191","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2022-05-04T17:13:59Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"128520e2b53126a359c855dcc1a7c89b9a77b3ff6ba75467045e52ae67d2f03d","abstract_canon_sha256":"0989c0c33e7b90b4f21b7e831a031ea26d791aec4a427ec6333e85dd04a5ac5d"},"schema_version":"1.0"},"canonical_sha256":"a6a0b30728f3a97739b1b14dc9babf58aa3e36b198bfcb9ef514cf99bda100da","source":{"kind":"arxiv","id":"2205.02191","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.02191","created_at":"2026-07-05T04:20:25Z"},{"alias_kind":"arxiv_version","alias_value":"2205.02191v1","created_at":"2026-07-05T04:20:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.02191","created_at":"2026-07-05T04:20:25Z"},{"alias_kind":"pith_short_12","alias_value":"U2QLGBZI6OUX","created_at":"2026-07-05T04:20:25Z"},{"alias_kind":"pith_short_16","alias_value":"U2QLGBZI6OUXOONR","created_at":"2026-07-05T04:20:25Z"},{"alias_kind":"pith_short_8","alias_value":"U2QLGBZI","created_at":"2026-07-05T04:20:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:U2QLGBZI6OUXOONRWFG4TOV7LC","target":"record","payload":{"canonical_record":{"source":{"id":"2205.02191","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2022-05-04T17:13:59Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"128520e2b53126a359c855dcc1a7c89b9a77b3ff6ba75467045e52ae67d2f03d","abstract_canon_sha256":"0989c0c33e7b90b4f21b7e831a031ea26d791aec4a427ec6333e85dd04a5ac5d"},"schema_version":"1.0"},"canonical_sha256":"a6a0b30728f3a97739b1b14dc9babf58aa3e36b198bfcb9ef514cf99bda100da","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:20:25.950852Z","signature_b64":"qaqWlkeNMAYrPvFenwOj8c2Yyq2622Mv3l0iUFerpIDCFyzWWm5WSm5aY7GEXAcMzbNjxQj3YEl2afE0VueMAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a6a0b30728f3a97739b1b14dc9babf58aa3e36b198bfcb9ef514cf99bda100da","last_reissued_at":"2026-07-05T04:20:25.950420Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:20:25.950420Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.02191","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":"2026-07-05T04:20:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cXe5eY3/mH/Cj3GiWL6tacOknMl7XT97PzTehK+w3WuE97QdRS2EvdfmXs6CTrxVkwAFG5rLI3qTOGaV3H/NDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T09:15:34.207225Z"},"content_sha256":"10e383ce488b185989b7988e450771b28ddb21815ab453d1f3a4e109bc50e43d","schema_version":"1.0","event_id":"sha256:10e383ce488b185989b7988e450771b28ddb21815ab453d1f3a4e109bc50e43d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:U2QLGBZI6OUXOONRWFG4TOV7LC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Wavelet neural operator: a neural operator for parametric partial differential equations","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"physics.comp-ph","authors_text":"Souvik Chakraborty, Tapas Tripura","submitted_at":"2022-05-04T17:13:59Z","abstract_excerpt":"With massive advancements in sensor technologies and Internet-of-things, we now have access to terabytes of historical data; however, there is a lack of clarity in how to best exploit the data to predict future events. One possible alternative in this context is to utilize operator learning algorithm that directly learn nonlinear mapping between two functional spaces; this facilitates real-time prediction of naturally arising complex evolutionary dynamics. In this work, we introduce a novel operator learning algorithm referred to as the Wavelet Neural Operator (WNO) that blends integral kernel"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.02191","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/2205.02191/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":"2026-07-05T04:20:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SOVSHV6t3rhO+UiaXAt6gR6itiY3oKEFsUBjIxzys/lFkCVRwlK96fKBMbmt3cn05Z739FxTpftJjbGjm0a1Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T09:15:34.207748Z"},"content_sha256":"6506f6a5ae12779a19b11d19ca88434b10b1b80e77a0214509f172bb63511f36","schema_version":"1.0","event_id":"sha256:6506f6a5ae12779a19b11d19ca88434b10b1b80e77a0214509f172bb63511f36"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/U2QLGBZI6OUXOONRWFG4TOV7LC/bundle.json","state_url":"https://pith.science/pith/U2QLGBZI6OUXOONRWFG4TOV7LC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/U2QLGBZI6OUXOONRWFG4TOV7LC/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":"2026-08-08T09:15:34Z","links":{"resolver":"https://pith.science/pith/U2QLGBZI6OUXOONRWFG4TOV7LC","bundle":"https://pith.science/pith/U2QLGBZI6OUXOONRWFG4TOV7LC/bundle.json","state":"https://pith.science/pith/U2QLGBZI6OUXOONRWFG4TOV7LC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/U2QLGBZI6OUXOONRWFG4TOV7LC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:U2QLGBZI6OUXOONRWFG4TOV7LC","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":"0989c0c33e7b90b4f21b7e831a031ea26d791aec4a427ec6333e85dd04a5ac5d","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2022-05-04T17:13:59Z","title_canon_sha256":"128520e2b53126a359c855dcc1a7c89b9a77b3ff6ba75467045e52ae67d2f03d"},"schema_version":"1.0","source":{"id":"2205.02191","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.02191","created_at":"2026-07-05T04:20:25Z"},{"alias_kind":"arxiv_version","alias_value":"2205.02191v1","created_at":"2026-07-05T04:20:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.02191","created_at":"2026-07-05T04:20:25Z"},{"alias_kind":"pith_short_12","alias_value":"U2QLGBZI6OUX","created_at":"2026-07-05T04:20:25Z"},{"alias_kind":"pith_short_16","alias_value":"U2QLGBZI6OUXOONR","created_at":"2026-07-05T04:20:25Z"},{"alias_kind":"pith_short_8","alias_value":"U2QLGBZI","created_at":"2026-07-05T04:20:25Z"}],"graph_snapshots":[{"event_id":"sha256:6506f6a5ae12779a19b11d19ca88434b10b1b80e77a0214509f172bb63511f36","target":"graph","created_at":"2026-07-05T04:20:25Z","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/2205.02191/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With massive advancements in sensor technologies and Internet-of-things, we now have access to terabytes of historical data; however, there is a lack of clarity in how to best exploit the data to predict future events. One possible alternative in this context is to utilize operator learning algorithm that directly learn nonlinear mapping between two functional spaces; this facilitates real-time prediction of naturally arising complex evolutionary dynamics. In this work, we introduce a novel operator learning algorithm referred to as the Wavelet Neural Operator (WNO) that blends integral kernel","authors_text":"Souvik Chakraborty, Tapas Tripura","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2022-05-04T17:13:59Z","title":"Wavelet neural operator: a neural operator for parametric partial differential equations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.02191","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":"sha256:10e383ce488b185989b7988e450771b28ddb21815ab453d1f3a4e109bc50e43d","target":"record","created_at":"2026-07-05T04:20:25Z","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":"0989c0c33e7b90b4f21b7e831a031ea26d791aec4a427ec6333e85dd04a5ac5d","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"physics.comp-ph","submitted_at":"2022-05-04T17:13:59Z","title_canon_sha256":"128520e2b53126a359c855dcc1a7c89b9a77b3ff6ba75467045e52ae67d2f03d"},"schema_version":"1.0","source":{"id":"2205.02191","kind":"arxiv","version":1}},"canonical_sha256":"a6a0b30728f3a97739b1b14dc9babf58aa3e36b198bfcb9ef514cf99bda100da","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a6a0b30728f3a97739b1b14dc9babf58aa3e36b198bfcb9ef514cf99bda100da","first_computed_at":"2026-07-05T04:20:25.950420Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:20:25.950420Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"qaqWlkeNMAYrPvFenwOj8c2Yyq2622Mv3l0iUFerpIDCFyzWWm5WSm5aY7GEXAcMzbNjxQj3YEl2afE0VueMAw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:20:25.950852Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.02191","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:10e383ce488b185989b7988e450771b28ddb21815ab453d1f3a4e109bc50e43d","sha256:6506f6a5ae12779a19b11d19ca88434b10b1b80e77a0214509f172bb63511f36"],"state_sha256":"c61e9fcd0c92ee328e6cf614a2c5f44c17e4672fe332ec2b4dafdbd4120eb08d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oF/O/fNzSfqhRHyZUiVLsMfUI4v4cZlCyLjSbKlaXUO0dwfJRU11XTRbyflUt+3C+fNlkLyp9kka3bIiDUfJBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T09:15:34.211229Z","bundle_sha256":"2b3e3646b61037257078cbd6317b119e5b84ebb01fac8364e0c01873b2943460"}}