{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SBSZM3GSYD6RR55MRC2TQJDWI4","short_pith_number":"pith:SBSZM3GS","canonical_record":{"source":{"id":"2405.04363","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2024-05-07T14:44:41Z","cross_cats_sorted":["cs.LG","math.IT"],"title_canon_sha256":"53e0f1e31bee47ae657ff573886a09cdde3f55930c9f6aaeed6fe24e385e8b22","abstract_canon_sha256":"221fc54c364b751d63f91988535e5b1b25e04bfdf0395d65a2f8ed92ccdbb78c"},"schema_version":"1.0"},"canonical_sha256":"9065966cd2c0fd18f7ac88b5382476470cda637629a0f534a78ddf2b94df2d2e","source":{"kind":"arxiv","id":"2405.04363","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.04363","created_at":"2026-07-05T08:19:24Z"},{"alias_kind":"arxiv_version","alias_value":"2405.04363v2","created_at":"2026-07-05T08:19:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.04363","created_at":"2026-07-05T08:19:24Z"},{"alias_kind":"pith_short_12","alias_value":"SBSZM3GSYD6R","created_at":"2026-07-05T08:19:24Z"},{"alias_kind":"pith_short_16","alias_value":"SBSZM3GSYD6RR55M","created_at":"2026-07-05T08:19:24Z"},{"alias_kind":"pith_short_8","alias_value":"SBSZM3GS","created_at":"2026-07-05T08:19:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SBSZM3GSYD6RR55MRC2TQJDWI4","target":"record","payload":{"canonical_record":{"source":{"id":"2405.04363","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2024-05-07T14:44:41Z","cross_cats_sorted":["cs.LG","math.IT"],"title_canon_sha256":"53e0f1e31bee47ae657ff573886a09cdde3f55930c9f6aaeed6fe24e385e8b22","abstract_canon_sha256":"221fc54c364b751d63f91988535e5b1b25e04bfdf0395d65a2f8ed92ccdbb78c"},"schema_version":"1.0"},"canonical_sha256":"9065966cd2c0fd18f7ac88b5382476470cda637629a0f534a78ddf2b94df2d2e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:19:24.837924Z","signature_b64":"nnfbWBkKGOlM/BnQcPR7yywrY0YwDrQ20dqxc23iPiEymVC+3A/0cy9ZRU5H3/Sbjj3EERSJVFTnms84pBaCDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9065966cd2c0fd18f7ac88b5382476470cda637629a0f534a78ddf2b94df2d2e","last_reissued_at":"2026-07-05T08:19:24.837414Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:19:24.837414Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.04363","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:19:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yMAj0AAue3V+MRnAqBLnEgDoVarAyW5eo9dPRbMyAk3g/EjFMWQv0ZQowIl1bW9//NKQnmvp0gI3tys4kODWBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T22:02:32.939683Z"},"content_sha256":"ac216875513c47b9adf0f68f7349d60741219f810391077d950d12a825a9a4ea","schema_version":"1.0","event_id":"sha256:ac216875513c47b9adf0f68f7349d60741219f810391077d950d12a825a9a4ea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SBSZM3GSYD6RR55MRC2TQJDWI4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Some Notes on the Sample Complexity of Approximate Channel Simulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","math.IT"],"primary_cat":"cs.IT","authors_text":"Gergely Flamich, Lennie Wells","submitted_at":"2024-05-07T14:44:41Z","abstract_excerpt":"Channel simulation algorithms can efficiently encode random samples from a prescribed target distribution $Q$ and find applications in machine learning-based lossy data compression. However, algorithms that encode exact samples usually have random runtime, limiting their applicability when a consistent encoding time is desirable. Thus, this paper considers approximate schemes with a fixed runtime instead. First, we strengthen a result of Agustsson and Theis and show that there is a class of pairs of target distribution $Q$ and coding distribution $P$, for which the runtime of any approximate s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.04363","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/2405.04363/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:19:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h3jH5zRVERMFQs15kR/sxZQwEp9TuurJ18bQdmiUwuk1lt2v9GeQ+PYMHVFUgSYxcd7OE24k0Hh89Oe5lK73AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T22:02:32.940226Z"},"content_sha256":"2fe45a7240b3dda1033e5a9a8252d41588850c6eb3f82035583c508cb14effee","schema_version":"1.0","event_id":"sha256:2fe45a7240b3dda1033e5a9a8252d41588850c6eb3f82035583c508cb14effee"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SBSZM3GSYD6RR55MRC2TQJDWI4/bundle.json","state_url":"https://pith.science/pith/SBSZM3GSYD6RR55MRC2TQJDWI4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SBSZM3GSYD6RR55MRC2TQJDWI4/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-16T22:02:32Z","links":{"resolver":"https://pith.science/pith/SBSZM3GSYD6RR55MRC2TQJDWI4","bundle":"https://pith.science/pith/SBSZM3GSYD6RR55MRC2TQJDWI4/bundle.json","state":"https://pith.science/pith/SBSZM3GSYD6RR55MRC2TQJDWI4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SBSZM3GSYD6RR55MRC2TQJDWI4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SBSZM3GSYD6RR55MRC2TQJDWI4","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"221fc54c364b751d63f91988535e5b1b25e04bfdf0395d65a2f8ed92ccdbb78c","cross_cats_sorted":["cs.LG","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2024-05-07T14:44:41Z","title_canon_sha256":"53e0f1e31bee47ae657ff573886a09cdde3f55930c9f6aaeed6fe24e385e8b22"},"schema_version":"1.0","source":{"id":"2405.04363","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.04363","created_at":"2026-07-05T08:19:24Z"},{"alias_kind":"arxiv_version","alias_value":"2405.04363v2","created_at":"2026-07-05T08:19:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.04363","created_at":"2026-07-05T08:19:24Z"},{"alias_kind":"pith_short_12","alias_value":"SBSZM3GSYD6R","created_at":"2026-07-05T08:19:24Z"},{"alias_kind":"pith_short_16","alias_value":"SBSZM3GSYD6RR55M","created_at":"2026-07-05T08:19:24Z"},{"alias_kind":"pith_short_8","alias_value":"SBSZM3GS","created_at":"2026-07-05T08:19:24Z"}],"graph_snapshots":[{"event_id":"sha256:2fe45a7240b3dda1033e5a9a8252d41588850c6eb3f82035583c508cb14effee","target":"graph","created_at":"2026-07-05T08:19:24Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2405.04363/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Channel simulation algorithms can efficiently encode random samples from a prescribed target distribution $Q$ and find applications in machine learning-based lossy data compression. However, algorithms that encode exact samples usually have random runtime, limiting their applicability when a consistent encoding time is desirable. Thus, this paper considers approximate schemes with a fixed runtime instead. First, we strengthen a result of Agustsson and Theis and show that there is a class of pairs of target distribution $Q$ and coding distribution $P$, for which the runtime of any approximate s","authors_text":"Gergely Flamich, Lennie Wells","cross_cats":["cs.LG","math.IT"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2024-05-07T14:44:41Z","title":"Some Notes on the Sample Complexity of Approximate Channel Simulation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.04363","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:ac216875513c47b9adf0f68f7349d60741219f810391077d950d12a825a9a4ea","target":"record","created_at":"2026-07-05T08:19:24Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"221fc54c364b751d63f91988535e5b1b25e04bfdf0395d65a2f8ed92ccdbb78c","cross_cats_sorted":["cs.LG","math.IT"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2024-05-07T14:44:41Z","title_canon_sha256":"53e0f1e31bee47ae657ff573886a09cdde3f55930c9f6aaeed6fe24e385e8b22"},"schema_version":"1.0","source":{"id":"2405.04363","kind":"arxiv","version":2}},"canonical_sha256":"9065966cd2c0fd18f7ac88b5382476470cda637629a0f534a78ddf2b94df2d2e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9065966cd2c0fd18f7ac88b5382476470cda637629a0f534a78ddf2b94df2d2e","first_computed_at":"2026-07-05T08:19:24.837414Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:19:24.837414Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nnfbWBkKGOlM/BnQcPR7yywrY0YwDrQ20dqxc23iPiEymVC+3A/0cy9ZRU5H3/Sbjj3EERSJVFTnms84pBaCDg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:19:24.837924Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.04363","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ac216875513c47b9adf0f68f7349d60741219f810391077d950d12a825a9a4ea","sha256:2fe45a7240b3dda1033e5a9a8252d41588850c6eb3f82035583c508cb14effee"],"state_sha256":"4a81df2bad42d868a28a953b8e4e4853979369686208fdd797310a940b5ae202"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DqIkwtf5VKt+P1X9rEFTqdmGtVUug5U8TtmheW+XZR80/jrl3SsUOEZHfnBfDht203s40JMBLhP5+HZ8DEfGCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T22:02:32.946708Z","bundle_sha256":"b52157db8fb3193eeed666bf27fbf04075933a676d96c36f95997440c43e08a3"}}