{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:OCBJRK4U5EH3CUG4SF47U5NJPY","short_pith_number":"pith:OCBJRK4U","schema_version":"1.0","canonical_sha256":"708298ab94e90fb150dc9179fa75a97e3363d0da555b3c6b9fe3c0262a695b82","source":{"kind":"arxiv","id":"1906.10467","version":3},"attestation_state":"computed","paper":{"title":"Analysis and synthesis of feature map for kernel-based quantum classifier","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Hiroshi Yano, Manato Akiyama, Naoki Yamamoto, Qi Gao, Shumpei Uno, Tomoki Tanaka, Yudai Suzuki","submitted_at":"2019-06-25T12:11:09Z","abstract_excerpt":"A method for analyzing the feature map for the kernel-based quantum classifier is developed; that is, we give a general formula for computing a lower bound of the exact training accuracy, which helps us to see whether the selected feature map is suitable for linearly separating the dataset. We show a proof of concept demonstration of this method for a class of 2-qubit classifier, with several 2-dimensional dataset. Also, a synthesis method, that combines different kernels to construct a better-performing feature map in a lager feature space, is presented."},"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":"1906.10467","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2019-06-25T12:11:09Z","cross_cats_sorted":[],"title_canon_sha256":"ecd04be9a988d8823cf540b1132a536350402ad599927c48e0e5499d17d1517a","abstract_canon_sha256":"92c8d94b030ef6da49a0cf734e88fc2734a7df27c86a239eea937bb7ad5d6f7d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:27:18.500200Z","signature_b64":"t5GzeZUgWvaHpnP1cNaH3iyEMBpw6o+9Kvp5OaN+mPEVRR1vWM3rfMCvPYMTYvzXEgEKILaP0pgxmB8W+SLGBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"708298ab94e90fb150dc9179fa75a97e3363d0da555b3c6b9fe3c0262a695b82","last_reissued_at":"2026-07-05T01:27:18.499656Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:27:18.499656Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Analysis and synthesis of feature map for kernel-based quantum classifier","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"quant-ph","authors_text":"Hiroshi Yano, Manato Akiyama, Naoki Yamamoto, Qi Gao, Shumpei Uno, Tomoki Tanaka, Yudai Suzuki","submitted_at":"2019-06-25T12:11:09Z","abstract_excerpt":"A method for analyzing the feature map for the kernel-based quantum classifier is developed; that is, we give a general formula for computing a lower bound of the exact training accuracy, which helps us to see whether the selected feature map is suitable for linearly separating the dataset. We show a proof of concept demonstration of this method for a class of 2-qubit classifier, with several 2-dimensional dataset. Also, a synthesis method, that combines different kernels to construct a better-performing feature map in a lager feature space, is presented."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1906.10467","kind":"arxiv","version":3},"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/1906.10467/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":"1906.10467","created_at":"2026-07-05T01:27:18.499719+00:00"},{"alias_kind":"arxiv_version","alias_value":"1906.10467v3","created_at":"2026-07-05T01:27:18.499719+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1906.10467","created_at":"2026-07-05T01:27:18.499719+00:00"},{"alias_kind":"pith_short_12","alias_value":"OCBJRK4U5EH3","created_at":"2026-07-05T01:27:18.499719+00:00"},{"alias_kind":"pith_short_16","alias_value":"OCBJRK4U5EH3CUG4","created_at":"2026-07-05T01:27:18.499719+00:00"},{"alias_kind":"pith_short_8","alias_value":"OCBJRK4U","created_at":"2026-07-05T01:27:18.499719+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/OCBJRK4U5EH3CUG4SF47U5NJPY","json":"https://pith.science/pith/OCBJRK4U5EH3CUG4SF47U5NJPY.json","graph_json":"https://pith.science/api/pith-number/OCBJRK4U5EH3CUG4SF47U5NJPY/graph.json","events_json":"https://pith.science/api/pith-number/OCBJRK4U5EH3CUG4SF47U5NJPY/events.json","paper":"https://pith.science/paper/OCBJRK4U"},"agent_actions":{"view_html":"https://pith.science/pith/OCBJRK4U5EH3CUG4SF47U5NJPY","download_json":"https://pith.science/pith/OCBJRK4U5EH3CUG4SF47U5NJPY.json","view_paper":"https://pith.science/paper/OCBJRK4U","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1906.10467&json=true","fetch_graph":"https://pith.science/api/pith-number/OCBJRK4U5EH3CUG4SF47U5NJPY/graph.json","fetch_events":"https://pith.science/api/pith-number/OCBJRK4U5EH3CUG4SF47U5NJPY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/OCBJRK4U5EH3CUG4SF47U5NJPY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/OCBJRK4U5EH3CUG4SF47U5NJPY/action/storage_attestation","attest_author":"https://pith.science/pith/OCBJRK4U5EH3CUG4SF47U5NJPY/action/author_attestation","sign_citation":"https://pith.science/pith/OCBJRK4U5EH3CUG4SF47U5NJPY/action/citation_signature","submit_replication":"https://pith.science/pith/OCBJRK4U5EH3CUG4SF47U5NJPY/action/replication_record"}},"created_at":"2026-07-05T01:27:18.499719+00:00","updated_at":"2026-07-05T01:27:18.499719+00:00"}