{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:WJAHN5Q33UR6CGZTK2YPJN65E3","short_pith_number":"pith:WJAHN5Q3","canonical_record":{"source":{"id":"2002.02481","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.DC","submitted_at":"2020-02-06T19:27:44Z","cross_cats_sorted":["q-fin.CP","stat.CO"],"title_canon_sha256":"fdddcc0b3a566fa9fe88e6b4d3a451a62ab4e14f42415533b272352c97460f3e","abstract_canon_sha256":"2e31bbd33941fbe32822ef63a34bba5ae275483dba2c99dc8d84f0f45d81029e"},"schema_version":"1.0"},"canonical_sha256":"b24076f61bdd23e11b3356b0f4b7dd26c451e805cdcd45ec58cfc9f827210754","source":{"kind":"arxiv","id":"2002.02481","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.02481","created_at":"2026-07-05T00:39:06Z"},{"alias_kind":"arxiv_version","alias_value":"2002.02481v1","created_at":"2026-07-05T00:39:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.02481","created_at":"2026-07-05T00:39:06Z"},{"alias_kind":"pith_short_12","alias_value":"WJAHN5Q33UR6","created_at":"2026-07-05T00:39:06Z"},{"alias_kind":"pith_short_16","alias_value":"WJAHN5Q33UR6CGZT","created_at":"2026-07-05T00:39:06Z"},{"alias_kind":"pith_short_8","alias_value":"WJAHN5Q3","created_at":"2026-07-05T00:39:06Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:WJAHN5Q33UR6CGZTK2YPJN65E3","target":"record","payload":{"canonical_record":{"source":{"id":"2002.02481","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.DC","submitted_at":"2020-02-06T19:27:44Z","cross_cats_sorted":["q-fin.CP","stat.CO"],"title_canon_sha256":"fdddcc0b3a566fa9fe88e6b4d3a451a62ab4e14f42415533b272352c97460f3e","abstract_canon_sha256":"2e31bbd33941fbe32822ef63a34bba5ae275483dba2c99dc8d84f0f45d81029e"},"schema_version":"1.0"},"canonical_sha256":"b24076f61bdd23e11b3356b0f4b7dd26c451e805cdcd45ec58cfc9f827210754","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:39:06.081293Z","signature_b64":"wifjgIuYHjm+sSc+acAK9FiiGHQs3UC4h9KFflxCdBxv+Q+B0WJ4Uy8d8K5qIx3m0CPB09RVMtVatai6JsZVCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b24076f61bdd23e11b3356b0f4b7dd26c451e805cdcd45ec58cfc9f827210754","last_reissued_at":"2026-07-05T00:39:06.080846Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:39:06.080846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.02481","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":"2026-07-05T00:39:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Mr/jBcmeSt5waKbYOABWL9yf2E8YAfry0TtnZ2vWhWP9+xTOUKIOTu62bVvOut8FUHhKp7WnS0mhUS0j3J44CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T21:47:39.326368Z"},"content_sha256":"319dd7d4e41f8e0cb23b87fe0029d0390b1c7917b0286ac8a6dcb34ff9603cbe","schema_version":"1.0","event_id":"sha256:319dd7d4e41f8e0cb23b87fe0029d0390b1c7917b0286ac8a6dcb34ff9603cbe"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:WJAHN5Q33UR6CGZTK2YPJN65E3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sensitivity Analysis in the Dupire Local Volatility Model with Tensorflow","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["q-fin.CP","stat.CO"],"primary_cat":"cs.DC","authors_text":"Davis King, Francois Belletti, James Lottes, John Anderson, Yi-Fan Chen","submitted_at":"2020-02-06T19:27:44Z","abstract_excerpt":"In a recent paper, we have demonstrated how the affinity between TPUs and multi-dimensional financial simulation resulted in fast Monte Carlo simulations that could be setup in a few lines of python Tensorflow code. We also presented a major benefit from writing high performance simulations in an automated differentiation language such as Tensorflow: a single line of code enabled us to estimate sensitivities, i.e. the rate of change in price of financial instrument with respect to another input such as the interest rate, the current price of the underlying, or volatility. Such sensitivities (o"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.02481","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/2002.02481/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":"2026-07-05T00:39:06Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tq3SEBw+/CnZs4vXnWiBTDoIaaXcsFdPZSa1YpIGBNgHAIvZixAMmQpR9XDogcM2feChT/mvJ7NStPkAKFzNCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T21:47:39.326981Z"},"content_sha256":"1970cdb89df45db4cac7686a004e17d29c3ba4b955871db99ada9f23ce43939a","schema_version":"1.0","event_id":"sha256:1970cdb89df45db4cac7686a004e17d29c3ba4b955871db99ada9f23ce43939a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WJAHN5Q33UR6CGZTK2YPJN65E3/bundle.json","state_url":"https://pith.science/pith/WJAHN5Q33UR6CGZTK2YPJN65E3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WJAHN5Q33UR6CGZTK2YPJN65E3/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":"2026-08-22T21:47:39Z","links":{"resolver":"https://pith.science/pith/WJAHN5Q33UR6CGZTK2YPJN65E3","bundle":"https://pith.science/pith/WJAHN5Q33UR6CGZTK2YPJN65E3/bundle.json","state":"https://pith.science/pith/WJAHN5Q33UR6CGZTK2YPJN65E3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WJAHN5Q33UR6CGZTK2YPJN65E3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:WJAHN5Q33UR6CGZTK2YPJN65E3","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":"2e31bbd33941fbe32822ef63a34bba5ae275483dba2c99dc8d84f0f45d81029e","cross_cats_sorted":["q-fin.CP","stat.CO"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.DC","submitted_at":"2020-02-06T19:27:44Z","title_canon_sha256":"fdddcc0b3a566fa9fe88e6b4d3a451a62ab4e14f42415533b272352c97460f3e"},"schema_version":"1.0","source":{"id":"2002.02481","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.02481","created_at":"2026-07-05T00:39:06Z"},{"alias_kind":"arxiv_version","alias_value":"2002.02481v1","created_at":"2026-07-05T00:39:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.02481","created_at":"2026-07-05T00:39:06Z"},{"alias_kind":"pith_short_12","alias_value":"WJAHN5Q33UR6","created_at":"2026-07-05T00:39:06Z"},{"alias_kind":"pith_short_16","alias_value":"WJAHN5Q33UR6CGZT","created_at":"2026-07-05T00:39:06Z"},{"alias_kind":"pith_short_8","alias_value":"WJAHN5Q3","created_at":"2026-07-05T00:39:06Z"}],"graph_snapshots":[{"event_id":"sha256:1970cdb89df45db4cac7686a004e17d29c3ba4b955871db99ada9f23ce43939a","target":"graph","created_at":"2026-07-05T00:39:06Z","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/2002.02481/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In a recent paper, we have demonstrated how the affinity between TPUs and multi-dimensional financial simulation resulted in fast Monte Carlo simulations that could be setup in a few lines of python Tensorflow code. We also presented a major benefit from writing high performance simulations in an automated differentiation language such as Tensorflow: a single line of code enabled us to estimate sensitivities, i.e. the rate of change in price of financial instrument with respect to another input such as the interest rate, the current price of the underlying, or volatility. Such sensitivities (o","authors_text":"Davis King, Francois Belletti, James Lottes, John Anderson, Yi-Fan Chen","cross_cats":["q-fin.CP","stat.CO"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.DC","submitted_at":"2020-02-06T19:27:44Z","title":"Sensitivity Analysis in the Dupire Local Volatility Model with Tensorflow"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.02481","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":"sha256:319dd7d4e41f8e0cb23b87fe0029d0390b1c7917b0286ac8a6dcb34ff9603cbe","target":"record","created_at":"2026-07-05T00:39:06Z","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":"2e31bbd33941fbe32822ef63a34bba5ae275483dba2c99dc8d84f0f45d81029e","cross_cats_sorted":["q-fin.CP","stat.CO"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.DC","submitted_at":"2020-02-06T19:27:44Z","title_canon_sha256":"fdddcc0b3a566fa9fe88e6b4d3a451a62ab4e14f42415533b272352c97460f3e"},"schema_version":"1.0","source":{"id":"2002.02481","kind":"arxiv","version":1}},"canonical_sha256":"b24076f61bdd23e11b3356b0f4b7dd26c451e805cdcd45ec58cfc9f827210754","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b24076f61bdd23e11b3356b0f4b7dd26c451e805cdcd45ec58cfc9f827210754","first_computed_at":"2026-07-05T00:39:06.080846Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:39:06.080846Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wifjgIuYHjm+sSc+acAK9FiiGHQs3UC4h9KFflxCdBxv+Q+B0WJ4Uy8d8K5qIx3m0CPB09RVMtVatai6JsZVCA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:39:06.081293Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.02481","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:319dd7d4e41f8e0cb23b87fe0029d0390b1c7917b0286ac8a6dcb34ff9603cbe","sha256:1970cdb89df45db4cac7686a004e17d29c3ba4b955871db99ada9f23ce43939a"],"state_sha256":"1691d27926bd083a7fa9083e5369a66a92e2baa330f21baeea1bcce0c855d7ab"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5OF3qf5QwookbwV99AcdZWwDL0JW131VD4FhoFpPM16lmjhRHLwh3NFnXzlE8LJPw0nhp2JYJDlxJGih1YoFDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T21:47:39.330754Z","bundle_sha256":"887bacec76f98ff6418989577635a8e71f7bac1ad1b5f6d0cadc8b1c5f69c498"}}