{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:HIETXIMIUTIVOVICFBHSNKTP6E","short_pith_number":"pith:HIETXIMI","canonical_record":{"source":{"id":"1810.01637","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2018-10-03T08:56:30Z","cross_cats_sorted":["physics.optics"],"title_canon_sha256":"6bc376d9abe1cb351c68eab3303a2d80be8896e5b8c680eb5d04f41bbbcc05ff","abstract_canon_sha256":"22787c2c64af37c5e51c1c296d9c7cc3a034d9c313cd6bb5d6e284f2e666a9f3"},"schema_version":"1.0"},"canonical_sha256":"3a093ba188a4d1575502284f26aa6ff11dd65056505d12fc8d0e0d387868de82","source":{"kind":"arxiv","id":"1810.01637","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.01637","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"arxiv_version","alias_value":"1810.01637v2","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.01637","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"pith_short_12","alias_value":"HIETXIMIUTIV","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HIETXIMIUTIVOVIC","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HIETXIMI","created_at":"2026-05-18T12:32:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:HIETXIMIUTIVOVICFBHSNKTP6E","target":"record","payload":{"canonical_record":{"source":{"id":"1810.01637","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2018-10-03T08:56:30Z","cross_cats_sorted":["physics.optics"],"title_canon_sha256":"6bc376d9abe1cb351c68eab3303a2d80be8896e5b8c680eb5d04f41bbbcc05ff","abstract_canon_sha256":"22787c2c64af37c5e51c1c296d9c7cc3a034d9c313cd6bb5d6e284f2e666a9f3"},"schema_version":"1.0"},"canonical_sha256":"3a093ba188a4d1575502284f26aa6ff11dd65056505d12fc8d0e0d387868de82","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:53:57.456169Z","signature_b64":"gJmxrGzawM1LiAGw0DmLh/4iXARBVPUFW1kuIUOCcMCtK5AnjtATPs9CIBZMs13Wsmiq7vudE3M2iMGbrDB5Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3a093ba188a4d1575502284f26aa6ff11dd65056505d12fc8d0e0d387868de82","last_reissued_at":"2026-05-17T23:53:57.455489Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:53:57.455489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1810.01637","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":"2026-05-17T23:53:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8QFqbm0KSufo1Mdv69VNxXFIY8TWrkPNybnBRHphmx5uyEUbcd1jvC/owdflzBn+Xk6RMVHP6YDH8EHaJmHKDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T03:58:59.598969Z"},"content_sha256":"c4afe5d59297893d244642175400fc901220f50e7dabd8b6def4a3d7465d18c5","schema_version":"1.0","event_id":"sha256:c4afe5d59297893d244642175400fc901220f50e7dabd8b6def4a3d7465d18c5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:HIETXIMIUTIVOVICFBHSNKTP6E","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Experimental Realization of a Quantum Autoencoder: The Compression of Qutrits via Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["physics.optics"],"primary_cat":"quant-ph","authors_text":"Alex Pepper, Geoff J. Pryde, Nora Tischler","submitted_at":"2018-10-03T08:56:30Z","abstract_excerpt":"With quantum resources a precious commodity, their efficient use is highly desirable. Quantum autoencoders have been proposed as a way to reduce quantum memory requirements. Generally, an autoencoder is a device that uses machine learning to compress inputs, that is, to represent the input data in a lower-dimensional space. Here, we experimentally realize a quantum autoencoder, which learns how to compress quantum data using a classical optimization routine. We demonstrate that when the inherent structure of the data set allows lossless compression, our autoencoder reduces qutrits to qubits wi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.01637","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":""},"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":"2026-05-17T23:53:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AgBNX7HitjCnCT3kqBwMvE3w3jxar5faFRuRqZYTf9g2ASZrBUufnhnzJGkKI3v1hpNteX5QxQslApXAfn+TDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-04T03:58:59.599356Z"},"content_sha256":"cac6e22ef93b7cb6b2368c3032ec937ba1917f9d54aaa715e078de4893db9197","schema_version":"1.0","event_id":"sha256:cac6e22ef93b7cb6b2368c3032ec937ba1917f9d54aaa715e078de4893db9197"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HIETXIMIUTIVOVICFBHSNKTP6E/bundle.json","state_url":"https://pith.science/pith/HIETXIMIUTIVOVICFBHSNKTP6E/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HIETXIMIUTIVOVICFBHSNKTP6E/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":"2026-06-04T03:58:59Z","links":{"resolver":"https://pith.science/pith/HIETXIMIUTIVOVICFBHSNKTP6E","bundle":"https://pith.science/pith/HIETXIMIUTIVOVICFBHSNKTP6E/bundle.json","state":"https://pith.science/pith/HIETXIMIUTIVOVICFBHSNKTP6E/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HIETXIMIUTIVOVICFBHSNKTP6E/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:HIETXIMIUTIVOVICFBHSNKTP6E","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":"22787c2c64af37c5e51c1c296d9c7cc3a034d9c313cd6bb5d6e284f2e666a9f3","cross_cats_sorted":["physics.optics"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2018-10-03T08:56:30Z","title_canon_sha256":"6bc376d9abe1cb351c68eab3303a2d80be8896e5b8c680eb5d04f41bbbcc05ff"},"schema_version":"1.0","source":{"id":"1810.01637","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1810.01637","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"arxiv_version","alias_value":"1810.01637v2","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1810.01637","created_at":"2026-05-17T23:53:57Z"},{"alias_kind":"pith_short_12","alias_value":"HIETXIMIUTIV","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_16","alias_value":"HIETXIMIUTIVOVIC","created_at":"2026-05-18T12:32:28Z"},{"alias_kind":"pith_short_8","alias_value":"HIETXIMI","created_at":"2026-05-18T12:32:28Z"}],"graph_snapshots":[{"event_id":"sha256:cac6e22ef93b7cb6b2368c3032ec937ba1917f9d54aaa715e078de4893db9197","target":"graph","created_at":"2026-05-17T23:53:57Z","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"},"paper":{"abstract_excerpt":"With quantum resources a precious commodity, their efficient use is highly desirable. Quantum autoencoders have been proposed as a way to reduce quantum memory requirements. Generally, an autoencoder is a device that uses machine learning to compress inputs, that is, to represent the input data in a lower-dimensional space. Here, we experimentally realize a quantum autoencoder, which learns how to compress quantum data using a classical optimization routine. We demonstrate that when the inherent structure of the data set allows lossless compression, our autoencoder reduces qutrits to qubits wi","authors_text":"Alex Pepper, Geoff J. Pryde, Nora Tischler","cross_cats":["physics.optics"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2018-10-03T08:56:30Z","title":"Experimental Realization of a Quantum Autoencoder: The Compression of Qutrits via Machine Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1810.01637","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:c4afe5d59297893d244642175400fc901220f50e7dabd8b6def4a3d7465d18c5","target":"record","created_at":"2026-05-17T23:53:57Z","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":"22787c2c64af37c5e51c1c296d9c7cc3a034d9c313cd6bb5d6e284f2e666a9f3","cross_cats_sorted":["physics.optics"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2018-10-03T08:56:30Z","title_canon_sha256":"6bc376d9abe1cb351c68eab3303a2d80be8896e5b8c680eb5d04f41bbbcc05ff"},"schema_version":"1.0","source":{"id":"1810.01637","kind":"arxiv","version":2}},"canonical_sha256":"3a093ba188a4d1575502284f26aa6ff11dd65056505d12fc8d0e0d387868de82","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3a093ba188a4d1575502284f26aa6ff11dd65056505d12fc8d0e0d387868de82","first_computed_at":"2026-05-17T23:53:57.455489Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:53:57.455489Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gJmxrGzawM1LiAGw0DmLh/4iXARBVPUFW1kuIUOCcMCtK5AnjtATPs9CIBZMs13Wsmiq7vudE3M2iMGbrDB5Dw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:53:57.456169Z","signed_message":"canonical_sha256_bytes"},"source_id":"1810.01637","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c4afe5d59297893d244642175400fc901220f50e7dabd8b6def4a3d7465d18c5","sha256:cac6e22ef93b7cb6b2368c3032ec937ba1917f9d54aaa715e078de4893db9197"],"state_sha256":"8ce660baca303f18529cb64417081b4a5953c0ebd74b8b44453ed62b913114a5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EOL5gQeoHwtp6glEaoNAtEIRa6052tur4IWEzhZ08wlnKfV9wd5XKOJjL34ES5i2U9j+frRKjAItbuNer4f3Cw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-04T03:58:59.602330Z","bundle_sha256":"31adca543dd52253c0dd619478b1c21d5582335ec2982005112b565e1a854338"}}