{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:6YLYOEI64OC3XXP5MXGAAM2SNG","short_pith_number":"pith:6YLYOEI6","schema_version":"1.0","canonical_sha256":"f61787111ee385bbddfd65cc003352698ed288e037d0f33d03609fcf68c52d1e","source":{"kind":"arxiv","id":"2305.06347","version":2},"attestation_state":"computed","paper":{"title":"CosmoPower-JAX: high-dimensional Bayesian inference with differentiable cosmological emulators","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM","cs.LG"],"primary_cat":"astro-ph.CO","authors_text":"A. Spurio Mancini, D. Piras","submitted_at":"2023-05-10T17:54:10Z","abstract_excerpt":"We present CosmoPower-JAX, a JAX-based implementation of the CosmoPower framework, which accelerates cosmological inference by building neural emulators of cosmological power spectra. We show how, using the automatic differentiation, batch evaluation and just-in-time compilation features of JAX, and running the inference pipeline on graphics processing units (GPUs), parameter estimation can be accelerated by orders of magnitude with advanced gradient-based sampling techniques. These can be used to efficiently explore high-dimensional parameter spaces, such as those needed for the analysis of n"},"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":"2305.06347","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"astro-ph.CO","submitted_at":"2023-05-10T17:54:10Z","cross_cats_sorted":["astro-ph.IM","cs.LG"],"title_canon_sha256":"5c5f38bd921457509e730438b7d31f5a89c772b61ee0851240934d55d60740fd","abstract_canon_sha256":"eef3789f6a00dddca8139f398457763ac300db50ab8f3a6eecb69fccffb823cf"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:24:29.523553Z","signature_b64":"JxceRJc+/9nIeZ0LW20yWAIk3OAD5/y1F35IjnQH+BQG4wnDZIX5DVNDKr4e/CnddWQN3No1mfwCQyQekHN7DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f61787111ee385bbddfd65cc003352698ed288e037d0f33d03609fcf68c52d1e","last_reissued_at":"2026-07-05T06:24:29.523027Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:24:29.523027Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"CosmoPower-JAX: high-dimensional Bayesian inference with differentiable cosmological emulators","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["astro-ph.IM","cs.LG"],"primary_cat":"astro-ph.CO","authors_text":"A. Spurio Mancini, D. Piras","submitted_at":"2023-05-10T17:54:10Z","abstract_excerpt":"We present CosmoPower-JAX, a JAX-based implementation of the CosmoPower framework, which accelerates cosmological inference by building neural emulators of cosmological power spectra. We show how, using the automatic differentiation, batch evaluation and just-in-time compilation features of JAX, and running the inference pipeline on graphics processing units (GPUs), parameter estimation can be accelerated by orders of magnitude with advanced gradient-based sampling techniques. These can be used to efficiently explore high-dimensional parameter spaces, such as those needed for the analysis of n"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.06347","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/2305.06347/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":"2305.06347","created_at":"2026-07-05T06:24:29.523094+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.06347v2","created_at":"2026-07-05T06:24:29.523094+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.06347","created_at":"2026-07-05T06:24:29.523094+00:00"},{"alias_kind":"pith_short_12","alias_value":"6YLYOEI64OC3","created_at":"2026-07-05T06:24:29.523094+00:00"},{"alias_kind":"pith_short_16","alias_value":"6YLYOEI64OC3XXP5","created_at":"2026-07-05T06:24:29.523094+00:00"},{"alias_kind":"pith_short_8","alias_value":"6YLYOEI6","created_at":"2026-07-05T06:24:29.523094+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":8,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2607.02498","citing_title":"Alleviating prior dependencies for DESI DR1 clustering fits through reparameterization","ref_index":130,"is_internal_anchor":false},{"citing_arxiv_id":"2606.28482","citing_title":"Strongest constraints on dark acoustic oscillations from the Lyman-alpha forest","ref_index":114,"is_internal_anchor":false},{"citing_arxiv_id":"2605.23839","citing_title":"cloelib: A Flexible Python Library for Computing Cosmological Observables in the Euclid Era","ref_index":54,"is_internal_anchor":false},{"citing_arxiv_id":"2605.23841","citing_title":"cloelike: A Python Library for Cosmological Likelihood Inference in the Euclid Era","ref_index":56,"is_internal_anchor":false},{"citing_arxiv_id":"2510.18749","citing_title":"Symbolic Emulators for Cosmology: Accelerating Cosmological Analyses Without Sacrificing Precision","ref_index":8,"is_internal_anchor":false},{"citing_arxiv_id":"2506.20707","citing_title":"SPT-3G D1: CMB temperature and polarization power spectra and cosmology from 2019 and 2020 observations of the SPT-3G Main field","ref_index":36,"is_internal_anchor":false},{"citing_arxiv_id":"2604.25171","citing_title":"Multi-tracers, multi-surveys: a joint Fisher analysis of DESI+PFS","ref_index":47,"is_internal_anchor":false},{"citing_arxiv_id":"2604.25171","citing_title":"Multi-tracers, multi-surveys: a joint Fisher analysis of DESI+PFS","ref_index":47,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/6YLYOEI64OC3XXP5MXGAAM2SNG","json":"https://pith.science/pith/6YLYOEI64OC3XXP5MXGAAM2SNG.json","graph_json":"https://pith.science/api/pith-number/6YLYOEI64OC3XXP5MXGAAM2SNG/graph.json","events_json":"https://pith.science/api/pith-number/6YLYOEI64OC3XXP5MXGAAM2SNG/events.json","paper":"https://pith.science/paper/6YLYOEI6"},"agent_actions":{"view_html":"https://pith.science/pith/6YLYOEI64OC3XXP5MXGAAM2SNG","download_json":"https://pith.science/pith/6YLYOEI64OC3XXP5MXGAAM2SNG.json","view_paper":"https://pith.science/paper/6YLYOEI6","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.06347&json=true","fetch_graph":"https://pith.science/api/pith-number/6YLYOEI64OC3XXP5MXGAAM2SNG/graph.json","fetch_events":"https://pith.science/api/pith-number/6YLYOEI64OC3XXP5MXGAAM2SNG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6YLYOEI64OC3XXP5MXGAAM2SNG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6YLYOEI64OC3XXP5MXGAAM2SNG/action/storage_attestation","attest_author":"https://pith.science/pith/6YLYOEI64OC3XXP5MXGAAM2SNG/action/author_attestation","sign_citation":"https://pith.science/pith/6YLYOEI64OC3XXP5MXGAAM2SNG/action/citation_signature","submit_replication":"https://pith.science/pith/6YLYOEI64OC3XXP5MXGAAM2SNG/action/replication_record"}},"created_at":"2026-07-05T06:24:29.523094+00:00","updated_at":"2026-07-05T06:24:29.523094+00:00"}