{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:7ESM5VHSKQ4MJS7OY6QRLRGATN","short_pith_number":"pith:7ESM5VHS","schema_version":"1.0","canonical_sha256":"f924ced4f25438c4cbeec7a115c4c09b780f08fbe2ed42c2ce5d3223cc5e7ad8","source":{"kind":"arxiv","id":"2506.15060","version":2},"attestation_state":"computed","paper":{"title":"GalaxyGenius: Mock galaxy image generator for various telescopes from hydrodynamical simulations","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["astro-ph.CO","astro-ph.GA"],"primary_cat":"astro-ph.IM","authors_text":"Ayodeji Ibitoye, Chengliang Wei, Furen Deng, Hang Yang, Nan Li, Peng Wei, Qifan Cui, Qi Xiong, Renhao Ye, Shiyin Shen, Xian-Min Meng, Xingchen Zhou, Yuedong Fang, Zizhao He","submitted_at":"2025-06-18T01:57:50Z","abstract_excerpt":"We introduce GalaxyGenius, a Python package designed to produce synthetic galaxy images tailored to different telescopes based on hydrodynamical simulations. Its implementation will support and advance research on galaxies in the era of large-scale sky surveys. The package comprises three main modules: data preprocessing, ideal data cube generation, and mock observation. Specifically, the preprocessing module extracts necessary properties of star and gas particles for a selected subhalo from hydrodynamical simulations and creates the execution file for the following radiative transfer procedur"},"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":"2506.15060","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"astro-ph.IM","submitted_at":"2025-06-18T01:57:50Z","cross_cats_sorted":["astro-ph.CO","astro-ph.GA"],"title_canon_sha256":"f8288f6da18d4a4ea5213f6b43a021c1d9026dc970941154a9ab9b448e48a75f","abstract_canon_sha256":"ecd0752135f8512a08d9000f726eb9351f01fe17e2f026a1dbd24716c2a6a1a5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:52:49.062194Z","signature_b64":"T09VHqySOhl4n3DH4J8CR0etuFDzLGh4wWKLdzWexorILA7r1yEivvL43e57aXURDBG095K2T4TOS3XtyU5KAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f924ced4f25438c4cbeec7a115c4c09b780f08fbe2ed42c2ce5d3223cc5e7ad8","last_reissued_at":"2026-07-05T11:52:49.061619Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:52:49.061619Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"GalaxyGenius: Mock galaxy image generator for various telescopes from hydrodynamical simulations","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["astro-ph.CO","astro-ph.GA"],"primary_cat":"astro-ph.IM","authors_text":"Ayodeji Ibitoye, Chengliang Wei, Furen Deng, Hang Yang, Nan Li, Peng Wei, Qifan Cui, Qi Xiong, Renhao Ye, Shiyin Shen, Xian-Min Meng, Xingchen Zhou, Yuedong Fang, Zizhao He","submitted_at":"2025-06-18T01:57:50Z","abstract_excerpt":"We introduce GalaxyGenius, a Python package designed to produce synthetic galaxy images tailored to different telescopes based on hydrodynamical simulations. Its implementation will support and advance research on galaxies in the era of large-scale sky surveys. The package comprises three main modules: data preprocessing, ideal data cube generation, and mock observation. Specifically, the preprocessing module extracts necessary properties of star and gas particles for a selected subhalo from hydrodynamical simulations and creates the execution file for the following radiative transfer procedur"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.15060","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/2506.15060/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":"2506.15060","created_at":"2026-07-05T11:52:49.061687+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.15060v2","created_at":"2026-07-05T11:52:49.061687+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.15060","created_at":"2026-07-05T11:52:49.061687+00:00"},{"alias_kind":"pith_short_12","alias_value":"7ESM5VHSKQ4M","created_at":"2026-07-05T11:52:49.061687+00:00"},{"alias_kind":"pith_short_16","alias_value":"7ESM5VHSKQ4MJS7O","created_at":"2026-07-05T11:52:49.061687+00:00"},{"alias_kind":"pith_short_8","alias_value":"7ESM5VHS","created_at":"2026-07-05T11:52:49.061687+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.20886","citing_title":"The TNG50-SKIRT Atlas: Multi-wavelength nonparametric galaxy morphology","ref_index":88,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7ESM5VHSKQ4MJS7OY6QRLRGATN","json":"https://pith.science/pith/7ESM5VHSKQ4MJS7OY6QRLRGATN.json","graph_json":"https://pith.science/api/pith-number/7ESM5VHSKQ4MJS7OY6QRLRGATN/graph.json","events_json":"https://pith.science/api/pith-number/7ESM5VHSKQ4MJS7OY6QRLRGATN/events.json","paper":"https://pith.science/paper/7ESM5VHS"},"agent_actions":{"view_html":"https://pith.science/pith/7ESM5VHSKQ4MJS7OY6QRLRGATN","download_json":"https://pith.science/pith/7ESM5VHSKQ4MJS7OY6QRLRGATN.json","view_paper":"https://pith.science/paper/7ESM5VHS","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.15060&json=true","fetch_graph":"https://pith.science/api/pith-number/7ESM5VHSKQ4MJS7OY6QRLRGATN/graph.json","fetch_events":"https://pith.science/api/pith-number/7ESM5VHSKQ4MJS7OY6QRLRGATN/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7ESM5VHSKQ4MJS7OY6QRLRGATN/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7ESM5VHSKQ4MJS7OY6QRLRGATN/action/storage_attestation","attest_author":"https://pith.science/pith/7ESM5VHSKQ4MJS7OY6QRLRGATN/action/author_attestation","sign_citation":"https://pith.science/pith/7ESM5VHSKQ4MJS7OY6QRLRGATN/action/citation_signature","submit_replication":"https://pith.science/pith/7ESM5VHSKQ4MJS7OY6QRLRGATN/action/replication_record"}},"created_at":"2026-07-05T11:52:49.061687+00:00","updated_at":"2026-07-05T11:52:49.061687+00:00"}