{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:BGOI3T4WP7NUX3ZCM5O6ZFUMHF","short_pith_number":"pith:BGOI3T4W","canonical_record":{"source":{"id":"2412.18973","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2024-12-25T19:23:29Z","cross_cats_sorted":["cond-mat.str-el","cs.LG"],"title_canon_sha256":"360551d8cbdec34ee4e6a0bd5c983b90587344c5b8e6f25c4ea1ac97ebbd892d","abstract_canon_sha256":"96a848178be7a342c8bd47057f33cfde149fdad7f5174368b533aa94477bcaa0"},"schema_version":"1.0"},"canonical_sha256":"099c8dcf967fdb4bef22675dec968c3953200a1c6d6b5d192b63b977121d3553","source":{"kind":"arxiv","id":"2412.18973","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.18973","created_at":"2026-07-05T09:54:14Z"},{"alias_kind":"arxiv_version","alias_value":"2412.18973v1","created_at":"2026-07-05T09:54:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.18973","created_at":"2026-07-05T09:54:14Z"},{"alias_kind":"pith_short_12","alias_value":"BGOI3T4WP7NU","created_at":"2026-07-05T09:54:14Z"},{"alias_kind":"pith_short_16","alias_value":"BGOI3T4WP7NUX3ZC","created_at":"2026-07-05T09:54:14Z"},{"alias_kind":"pith_short_8","alias_value":"BGOI3T4W","created_at":"2026-07-05T09:54:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:BGOI3T4WP7NUX3ZCM5O6ZFUMHF","target":"record","payload":{"canonical_record":{"source":{"id":"2412.18973","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2024-12-25T19:23:29Z","cross_cats_sorted":["cond-mat.str-el","cs.LG"],"title_canon_sha256":"360551d8cbdec34ee4e6a0bd5c983b90587344c5b8e6f25c4ea1ac97ebbd892d","abstract_canon_sha256":"96a848178be7a342c8bd47057f33cfde149fdad7f5174368b533aa94477bcaa0"},"schema_version":"1.0"},"canonical_sha256":"099c8dcf967fdb4bef22675dec968c3953200a1c6d6b5d192b63b977121d3553","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:54:14.164375Z","signature_b64":"QnjdZP/zNUbvqLXDN6LIxvMInRA81Y2JU13MgPLnNGIvvp8ETZHCwOrsCcw0PPG2YiHLtJBrYcD3tfS7+ljADA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"099c8dcf967fdb4bef22675dec968c3953200a1c6d6b5d192b63b977121d3553","last_reissued_at":"2026-07-05T09:54:14.163932Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:54:14.163932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.18973","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":"2026-07-05T09:54:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IAqR+BUEHTefgaXJdTk/8IN8xI4wAdGRvjRjHt0oEpX8pAhEeO2UBK/QsWJkjNB3XyesRjwZjMMDh8EoLMhDAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T09:12:00.251505Z"},"content_sha256":"aae72eb9d45747a7626385617b2869d43c877733d5c1726aa3745fc3ad9e7591","schema_version":"1.0","event_id":"sha256:aae72eb9d45747a7626385617b2869d43c877733d5c1726aa3745fc3ad9e7591"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:BGOI3T4WP7NUX3ZCM5O6ZFUMHF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Derandomized shallow shadows: Efficient Pauli learning with bounded-depth circuits","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cond-mat.str-el","cs.LG"],"primary_cat":"quant-ph","authors_text":"Christian Kokail, Hannes Pichler, Hong-Ye Hu, Jacob Taylor, Jonathan Kunjummen, Katherine Van Kirk, Madelyn Cain, Mikhail Lukin, Susanne F. Yelin, Yanting Teng","submitted_at":"2024-12-25T19:23:29Z","abstract_excerpt":"Efficiently estimating large numbers of non-commuting observables is an important subroutine of many quantum science tasks. We present the derandomized shallow shadows (DSS) algorithm for efficiently learning a large set of non-commuting observables, using shallow circuits to rotate into measurement bases. Exploiting tensor network techniques to ensure polynomial scaling of classical resources, our algorithm outputs a set of shallow measurement circuits that approximately minimizes the sample complexity of estimating a given set of Pauli strings. We numerically demonstrate systematic improveme"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.18973","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/2412.18973/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":"2026-07-05T09:54:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gMp9sDYSYK9tZTaa59L9Jd337hXC570fX2qSH03EUJRL6kYMpCvlK0BWBaQX0hJLcCdPip6DeMj5+m1P9DLEAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T09:12:00.253098Z"},"content_sha256":"98c33c7a9e1ca2c0623691cefe89023c63a9b87fc3b12139419cc2a2d9e243bb","schema_version":"1.0","event_id":"sha256:98c33c7a9e1ca2c0623691cefe89023c63a9b87fc3b12139419cc2a2d9e243bb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BGOI3T4WP7NUX3ZCM5O6ZFUMHF/bundle.json","state_url":"https://pith.science/pith/BGOI3T4WP7NUX3ZCM5O6ZFUMHF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BGOI3T4WP7NUX3ZCM5O6ZFUMHF/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":"2026-08-06T09:12:00Z","links":{"resolver":"https://pith.science/pith/BGOI3T4WP7NUX3ZCM5O6ZFUMHF","bundle":"https://pith.science/pith/BGOI3T4WP7NUX3ZCM5O6ZFUMHF/bundle.json","state":"https://pith.science/pith/BGOI3T4WP7NUX3ZCM5O6ZFUMHF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BGOI3T4WP7NUX3ZCM5O6ZFUMHF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BGOI3T4WP7NUX3ZCM5O6ZFUMHF","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":"96a848178be7a342c8bd47057f33cfde149fdad7f5174368b533aa94477bcaa0","cross_cats_sorted":["cond-mat.str-el","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2024-12-25T19:23:29Z","title_canon_sha256":"360551d8cbdec34ee4e6a0bd5c983b90587344c5b8e6f25c4ea1ac97ebbd892d"},"schema_version":"1.0","source":{"id":"2412.18973","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.18973","created_at":"2026-07-05T09:54:14Z"},{"alias_kind":"arxiv_version","alias_value":"2412.18973v1","created_at":"2026-07-05T09:54:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.18973","created_at":"2026-07-05T09:54:14Z"},{"alias_kind":"pith_short_12","alias_value":"BGOI3T4WP7NU","created_at":"2026-07-05T09:54:14Z"},{"alias_kind":"pith_short_16","alias_value":"BGOI3T4WP7NUX3ZC","created_at":"2026-07-05T09:54:14Z"},{"alias_kind":"pith_short_8","alias_value":"BGOI3T4W","created_at":"2026-07-05T09:54:14Z"}],"graph_snapshots":[{"event_id":"sha256:98c33c7a9e1ca2c0623691cefe89023c63a9b87fc3b12139419cc2a2d9e243bb","target":"graph","created_at":"2026-07-05T09:54:14Z","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/2412.18973/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Efficiently estimating large numbers of non-commuting observables is an important subroutine of many quantum science tasks. We present the derandomized shallow shadows (DSS) algorithm for efficiently learning a large set of non-commuting observables, using shallow circuits to rotate into measurement bases. Exploiting tensor network techniques to ensure polynomial scaling of classical resources, our algorithm outputs a set of shallow measurement circuits that approximately minimizes the sample complexity of estimating a given set of Pauli strings. We numerically demonstrate systematic improveme","authors_text":"Christian Kokail, Hannes Pichler, Hong-Ye Hu, Jacob Taylor, Jonathan Kunjummen, Katherine Van Kirk, Madelyn Cain, Mikhail Lukin, Susanne F. Yelin, Yanting Teng","cross_cats":["cond-mat.str-el","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2024-12-25T19:23:29Z","title":"Derandomized shallow shadows: Efficient Pauli learning with bounded-depth circuits"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.18973","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:aae72eb9d45747a7626385617b2869d43c877733d5c1726aa3745fc3ad9e7591","target":"record","created_at":"2026-07-05T09:54:14Z","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":"96a848178be7a342c8bd47057f33cfde149fdad7f5174368b533aa94477bcaa0","cross_cats_sorted":["cond-mat.str-el","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2024-12-25T19:23:29Z","title_canon_sha256":"360551d8cbdec34ee4e6a0bd5c983b90587344c5b8e6f25c4ea1ac97ebbd892d"},"schema_version":"1.0","source":{"id":"2412.18973","kind":"arxiv","version":1}},"canonical_sha256":"099c8dcf967fdb4bef22675dec968c3953200a1c6d6b5d192b63b977121d3553","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"099c8dcf967fdb4bef22675dec968c3953200a1c6d6b5d192b63b977121d3553","first_computed_at":"2026-07-05T09:54:14.163932Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:54:14.163932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QnjdZP/zNUbvqLXDN6LIxvMInRA81Y2JU13MgPLnNGIvvp8ETZHCwOrsCcw0PPG2YiHLtJBrYcD3tfS7+ljADA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:54:14.164375Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.18973","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aae72eb9d45747a7626385617b2869d43c877733d5c1726aa3745fc3ad9e7591","sha256:98c33c7a9e1ca2c0623691cefe89023c63a9b87fc3b12139419cc2a2d9e243bb"],"state_sha256":"bef68f89ed97e1d4ad18db423273c0335672152f98be331ce989ca79fb16efee"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lZM1GT3oMR2A3ptcB0oF9ReHt3U1gBUIqLpB+rLhsVeXiJzRREk9Z82t3H2f6haT7SbDuwhr2n37A5PVFj8DCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T09:12:00.259581Z","bundle_sha256":"45b7cdb40172d6f093b0e14b8b801fafd45d39d816be29078b4eaec3d2bde482"}}