{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:4WM2ZY3VRBZSJYECZXHTDV5E44","short_pith_number":"pith:4WM2ZY3V","schema_version":"1.0","canonical_sha256":"e599ace375887324e082cdcf31d7a4e73678f02877eb5a579ebf97319847b753","source":{"kind":"arxiv","id":"2605.28922","version":1},"attestation_state":"computed","paper":{"title":"Photometry is all you need: supernova classification as a mixing problem","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.CO"],"primary_cat":"astro-ph.IM","authors_text":"Ana Sof\\'ia M. Uzsoy, V. Ashley Villar","submitted_at":"2026-05-27T18:00:00Z","abstract_excerpt":"In the era of large-scale photometric surveys, scalable and robust methods for classifying supernova (SN) populations are increasingly necessary. Often, spectroscopy is essential in addition to photometry to reliably classify SNe; however, complete spectroscopic follow-up is infeasible for all of the millions of transient light curves being collected by facilities such as the Vera C. Rubin Observatory. Using light curves of SNe Ia and Ibc observed with the Zwicky Transient Facility, we frame the classification of large SN populations as a mixing problem. We fit all objects using a semi-analyti"},"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":"2605.28922","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.IM","submitted_at":"2026-05-27T18:00:00Z","cross_cats_sorted":["astro-ph.CO"],"title_canon_sha256":"86a98cfc8d64d2cc8817485c4fc000b714616b41f1f8ad4f5c70ca2b68381a02","abstract_canon_sha256":"0569209995500bc7aa7436ec4dcc692e0404984117548338dd8ce4e5285072c2"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T00:04:16.666210Z","signature_b64":"csEuSalcj8YSvNWUkZ02UafKkYY9TRyxqc8A4jttaKkvn5B72zWxuXCxNfSSczsI5mToJgmtWca2seJcTXWJBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e599ace375887324e082cdcf31d7a4e73678f02877eb5a579ebf97319847b753","last_reissued_at":"2026-05-29T00:04:16.665632Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T00:04:16.665632Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Photometry is all you need: supernova classification as a mixing problem","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.CO"],"primary_cat":"astro-ph.IM","authors_text":"Ana Sof\\'ia M. Uzsoy, V. Ashley Villar","submitted_at":"2026-05-27T18:00:00Z","abstract_excerpt":"In the era of large-scale photometric surveys, scalable and robust methods for classifying supernova (SN) populations are increasingly necessary. Often, spectroscopy is essential in addition to photometry to reliably classify SNe; however, complete spectroscopic follow-up is infeasible for all of the millions of transient light curves being collected by facilities such as the Vera C. Rubin Observatory. Using light curves of SNe Ia and Ibc observed with the Zwicky Transient Facility, we frame the classification of large SN populations as a mixing problem. We fit all objects using a semi-analyti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.28922","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/2605.28922/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":"2605.28922","created_at":"2026-05-29T00:04:16.665716+00:00"},{"alias_kind":"arxiv_version","alias_value":"2605.28922v1","created_at":"2026-05-29T00:04:16.665716+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.28922","created_at":"2026-05-29T00:04:16.665716+00:00"},{"alias_kind":"pith_short_12","alias_value":"4WM2ZY3VRBZS","created_at":"2026-05-29T00:04:16.665716+00:00"},{"alias_kind":"pith_short_16","alias_value":"4WM2ZY3VRBZSJYEC","created_at":"2026-05-29T00:04:16.665716+00:00"},{"alias_kind":"pith_short_8","alias_value":"4WM2ZY3V","created_at":"2026-05-29T00:04:16.665716+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/4WM2ZY3VRBZSJYECZXHTDV5E44","json":"https://pith.science/pith/4WM2ZY3VRBZSJYECZXHTDV5E44.json","graph_json":"https://pith.science/api/pith-number/4WM2ZY3VRBZSJYECZXHTDV5E44/graph.json","events_json":"https://pith.science/api/pith-number/4WM2ZY3VRBZSJYECZXHTDV5E44/events.json","paper":"https://pith.science/paper/4WM2ZY3V"},"agent_actions":{"view_html":"https://pith.science/pith/4WM2ZY3VRBZSJYECZXHTDV5E44","download_json":"https://pith.science/pith/4WM2ZY3VRBZSJYECZXHTDV5E44.json","view_paper":"https://pith.science/paper/4WM2ZY3V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2605.28922&json=true","fetch_graph":"https://pith.science/api/pith-number/4WM2ZY3VRBZSJYECZXHTDV5E44/graph.json","fetch_events":"https://pith.science/api/pith-number/4WM2ZY3VRBZSJYECZXHTDV5E44/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/4WM2ZY3VRBZSJYECZXHTDV5E44/action/timestamp_anchor","attest_storage":"https://pith.science/pith/4WM2ZY3VRBZSJYECZXHTDV5E44/action/storage_attestation","attest_author":"https://pith.science/pith/4WM2ZY3VRBZSJYECZXHTDV5E44/action/author_attestation","sign_citation":"https://pith.science/pith/4WM2ZY3VRBZSJYECZXHTDV5E44/action/citation_signature","submit_replication":"https://pith.science/pith/4WM2ZY3VRBZSJYECZXHTDV5E44/action/replication_record"}},"created_at":"2026-05-29T00:04:16.665716+00:00","updated_at":"2026-05-29T00:04:16.665716+00:00"}