{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5","short_pith_number":"pith:4ZG4MQBK","schema_version":"1.0","canonical_sha256":"e64dc6402af6647b1713ec61b629fa874ef7f3f37bebda7ffac96419d06cc095","source":{"kind":"arxiv","id":"2502.06956","version":2},"attestation_state":"computed","paper":{"title":"Computing Quantum Resources using Tensor Cross Interpolation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.comp-ph"],"primary_cat":"quant-ph","authors_text":"Gianpaolo Torre, Sven Benjamin Ko\\v{z}i\\'c","submitted_at":"2025-02-10T19:00:24Z","abstract_excerpt":"Quantum information quantifiers are indispensable tools for analyzing strongly correlated systems. Consequently, developing efficient and robust numerical methods for their computation is crucial. We propose a general procedure based on the family of Tensor Cross Interpolation (TCI) algorithms to address this challenge in a fully general framework, independent of the system or the quantifier under consideration. To substantiate our approach, we compute the non-stabilizerness R\\'{e}nyi entropy (SRE) and Relative Entropy of Coherence (REC) considering the 1D and 2D ferromagnetic Ising models wit"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2502.06956","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"quant-ph","submitted_at":"2025-02-10T19:00:24Z","cross_cats_sorted":["physics.comp-ph"],"title_canon_sha256":"d43274ec2347482bba2197ac8f2df74de84a90721d902ab534d60a89a8196091","abstract_canon_sha256":"80c599bf5efef26cd46f8bf04276a05b87cb7b49e1788e67dbbd3dc0490c5bf3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:44:22.000727Z","signature_b64":"vjg+TI8+IoItx2GlbggyCZhur09/gciPYuroi9Tv7KLkMoecE0m9HjlWoT0OFxhih4Lz8gp5Oh8qOjOcOq+HDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e64dc6402af6647b1713ec61b629fa874ef7f3f37bebda7ffac96419d06cc095","last_reissued_at":"2026-07-05T10:44:22.000243Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:44:22.000243Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Computing Quantum Resources using Tensor Cross Interpolation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["physics.comp-ph"],"primary_cat":"quant-ph","authors_text":"Gianpaolo Torre, Sven Benjamin Ko\\v{z}i\\'c","submitted_at":"2025-02-10T19:00:24Z","abstract_excerpt":"Quantum information quantifiers are indispensable tools for analyzing strongly correlated systems. Consequently, developing efficient and robust numerical methods for their computation is crucial. We propose a general procedure based on the family of Tensor Cross Interpolation (TCI) algorithms to address this challenge in a fully general framework, independent of the system or the quantifier under consideration. To substantiate our approach, we compute the non-stabilizerness R\\'{e}nyi entropy (SRE) and Relative Entropy of Coherence (REC) considering the 1D and 2D ferromagnetic Ising models wit"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.06956","kind":"arxiv","version":2},"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/2502.06956/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2502.06956","created_at":"2026-07-05T10:44:22.000299+00:00"},{"alias_kind":"arxiv_version","alias_value":"2502.06956v2","created_at":"2026-07-05T10:44:22.000299+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.06956","created_at":"2026-07-05T10:44:22.000299+00:00"},{"alias_kind":"pith_short_12","alias_value":"4ZG4MQBK6ZSH","created_at":"2026-07-05T10:44:22.000299+00:00"},{"alias_kind":"pith_short_16","alias_value":"4ZG4MQBK6ZSHWFYT","created_at":"2026-07-05T10:44:22.000299+00:00"},{"alias_kind":"pith_short_8","alias_value":"4ZG4MQBK","created_at":"2026-07-05T10:44:22.000299+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2507.04262","citing_title":"Solving the Gross-Pitaevskii equation on multiple different scales using the quantics tensor train representation","ref_index":65,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5","json":"https://pith.science/pith/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5.json","graph_json":"https://pith.science/api/pith-number/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5/graph.json","events_json":"https://pith.science/api/pith-number/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5/events.json","paper":"https://pith.science/paper/4ZG4MQBK"},"agent_actions":{"view_html":"https://pith.science/pith/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5","download_json":"https://pith.science/pith/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5.json","view_paper":"https://pith.science/paper/4ZG4MQBK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2502.06956&json=true","fetch_graph":"https://pith.science/api/pith-number/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5/graph.json","fetch_events":"https://pith.science/api/pith-number/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5/action/storage_attestation","attest_author":"https://pith.science/pith/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5/action/author_attestation","sign_citation":"https://pith.science/pith/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5/action/citation_signature","submit_replication":"https://pith.science/pith/4ZG4MQBK6ZSHWFYT5RQ3MKP2Q5/action/replication_record"}},"created_at":"2026-07-05T10:44:22.000299+00:00","updated_at":"2026-07-05T10:44:22.000299+00:00"}