{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:XHAUICGINA3D6ETH7NKPCAXW3J","short_pith_number":"pith:XHAUICGI","schema_version":"1.0","canonical_sha256":"b9c14408c868363f1267fb54f102f6da670bbaf4ff3973aaac88d865f71f4742","source":{"kind":"arxiv","id":"2607.17488","version":1},"attestation_state":"computed","paper":{"title":"Surrogate models for type II supernovae: Probing low-energy explosions and interaction-free regimes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.HE","astro-ph.IM"],"primary_cat":"astro-ph.SR","authors_text":"Bo Wang, Chengyuan Wu, Nikhil Sarin, Shuai Zha, Takashi J. Moriya, Zhengyang Zhang","submitted_at":"2026-07-20T02:24:30Z","abstract_excerpt":"To address the computational bottleneck of analyzing type II supernova samples from surveys such as the Legacy Survey of Space and Time, we present two STELLA-based neural-network surrogates: an interaction model for low-energy explosions with possible circumstellar-material (CSM) interaction and a photospheric model for standard interaction-free SNe IIP. Each uses an autoencoder to compress spectral energy distributions and an emulator to map physical parameters to the latent space. Latent-mixup regularization improves latent-space continuity, with ResNet blocks used for the interaction model"},"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":"2607.17488","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.SR","submitted_at":"2026-07-20T02:24:30Z","cross_cats_sorted":["astro-ph.HE","astro-ph.IM"],"title_canon_sha256":"5c1847bddb73f6f9372756f81ffc93c3d20363446ceb7221a759e8ed45fd7904","abstract_canon_sha256":"13193b47a3efccdd273106c6fdabbac820bca245c9acbc3b8f90ce91d9e3c0da"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-21T01:21:48.185805Z","signature_b64":"5peZ+iy4MXkeDp1vzNZneiq5zo5e2vxouYa5EijxiB10lvxw+q6HGKTr07wUApBckF73IJdFUl77lqnVZk1FDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b9c14408c868363f1267fb54f102f6da670bbaf4ff3973aaac88d865f71f4742","last_reissued_at":"2026-07-21T01:21:48.184917Z","signature_status":"signed_v1","first_computed_at":"2026-07-21T01:21:48.184917Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Surrogate models for type II supernovae: Probing low-energy explosions and interaction-free regimes","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.HE","astro-ph.IM"],"primary_cat":"astro-ph.SR","authors_text":"Bo Wang, Chengyuan Wu, Nikhil Sarin, Shuai Zha, Takashi J. Moriya, Zhengyang Zhang","submitted_at":"2026-07-20T02:24:30Z","abstract_excerpt":"To address the computational bottleneck of analyzing type II supernova samples from surveys such as the Legacy Survey of Space and Time, we present two STELLA-based neural-network surrogates: an interaction model for low-energy explosions with possible circumstellar-material (CSM) interaction and a photospheric model for standard interaction-free SNe IIP. Each uses an autoencoder to compress spectral energy distributions and an emulator to map physical parameters to the latent space. Latent-mixup regularization improves latent-space continuity, with ResNet blocks used for the interaction model"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.17488","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/2607.17488/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":"2607.17488","created_at":"2026-07-21T01:21:48.185385+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.17488v1","created_at":"2026-07-21T01:21:48.185385+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.17488","created_at":"2026-07-21T01:21:48.185385+00:00"},{"alias_kind":"pith_short_12","alias_value":"XHAUICGINA3D","created_at":"2026-07-21T01:21:48.185385+00:00"},{"alias_kind":"pith_short_16","alias_value":"XHAUICGINA3D6ETH","created_at":"2026-07-21T01:21:48.185385+00:00"},{"alias_kind":"pith_short_8","alias_value":"XHAUICGI","created_at":"2026-07-21T01:21:48.185385+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/XHAUICGINA3D6ETH7NKPCAXW3J","json":"https://pith.science/pith/XHAUICGINA3D6ETH7NKPCAXW3J.json","graph_json":"https://pith.science/api/pith-number/XHAUICGINA3D6ETH7NKPCAXW3J/graph.json","events_json":"https://pith.science/api/pith-number/XHAUICGINA3D6ETH7NKPCAXW3J/events.json","paper":"https://pith.science/paper/XHAUICGI"},"agent_actions":{"view_html":"https://pith.science/pith/XHAUICGINA3D6ETH7NKPCAXW3J","download_json":"https://pith.science/pith/XHAUICGINA3D6ETH7NKPCAXW3J.json","view_paper":"https://pith.science/paper/XHAUICGI","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.17488&json=true","fetch_graph":"https://pith.science/api/pith-number/XHAUICGINA3D6ETH7NKPCAXW3J/graph.json","fetch_events":"https://pith.science/api/pith-number/XHAUICGINA3D6ETH7NKPCAXW3J/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XHAUICGINA3D6ETH7NKPCAXW3J/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XHAUICGINA3D6ETH7NKPCAXW3J/action/storage_attestation","attest_author":"https://pith.science/pith/XHAUICGINA3D6ETH7NKPCAXW3J/action/author_attestation","sign_citation":"https://pith.science/pith/XHAUICGINA3D6ETH7NKPCAXW3J/action/citation_signature","submit_replication":"https://pith.science/pith/XHAUICGINA3D6ETH7NKPCAXW3J/action/replication_record"}},"created_at":"2026-07-21T01:21:48.185385+00:00","updated_at":"2026-07-21T01:21:48.185385+00:00"}