{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:MG6Q5UP3BF46OR72VEZYFDLXJX","short_pith_number":"pith:MG6Q5UP3","schema_version":"1.0","canonical_sha256":"61bd0ed1fb0979e747faa933828d774dd02a20ddc73596083fbc5f805f3c8424","source":{"kind":"arxiv","id":"1804.07633","version":3},"attestation_state":"computed","paper":{"title":"A Simple Quantum Neural Net with a Periodic Activation Function","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"quant-ph","authors_text":"Ammar Daskin","submitted_at":"2018-04-20T14:16:49Z","abstract_excerpt":"In this paper, we propose a simple neural net that requires only $O(nlog_2k)$ number of qubits and $O(nk)$ quantum gates: Here, $n$ is the number of input parameters, and $k$ is the number of weights applied to these parameters in the proposed neural net. We describe the network in terms of a quantum circuit, and then draw its equivalent classical neural net which involves $O(k^n)$ nodes in the hidden layer. Then, we show that the network uses a periodic activation function of cosine values of the linear combinations of the inputs and weights. The backpropagation is described through the gradi"},"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":"1804.07633","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"quant-ph","submitted_at":"2018-04-20T14:16:49Z","cross_cats_sorted":["cs.LG","cs.NE"],"title_canon_sha256":"daa9236b47e70f725268b00463b1bdfc17536f2557e9e28cbe044294480690f5","abstract_canon_sha256":"71b47bc9888b15f547fee5e4ccbf3ac761a1ae7d36f6497a42b53712ed1ffa48"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:31.227839Z","signature_b64":"jezVdnzG9N5/p+C2+fkHCpxKDdwdlGcjcSzk4Su8vU1zAjSKtmSKf6sH0232mXQqzCSVzVJbRJc8Otu5JW1PDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"61bd0ed1fb0979e747faa933828d774dd02a20ddc73596083fbc5f805f3c8424","last_reissued_at":"2026-05-17T23:47:31.227146Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:31.227146Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Simple Quantum Neural Net with a Periodic Activation Function","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE"],"primary_cat":"quant-ph","authors_text":"Ammar Daskin","submitted_at":"2018-04-20T14:16:49Z","abstract_excerpt":"In this paper, we propose a simple neural net that requires only $O(nlog_2k)$ number of qubits and $O(nk)$ quantum gates: Here, $n$ is the number of input parameters, and $k$ is the number of weights applied to these parameters in the proposed neural net. We describe the network in terms of a quantum circuit, and then draw its equivalent classical neural net which involves $O(k^n)$ nodes in the hidden layer. Then, we show that the network uses a periodic activation function of cosine values of the linear combinations of the inputs and weights. The backpropagation is described through the gradi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1804.07633","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":""},"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":"1804.07633","created_at":"2026-05-17T23:47:31.227229+00:00"},{"alias_kind":"arxiv_version","alias_value":"1804.07633v3","created_at":"2026-05-17T23:47:31.227229+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1804.07633","created_at":"2026-05-17T23:47:31.227229+00:00"},{"alias_kind":"pith_short_12","alias_value":"MG6Q5UP3BF46","created_at":"2026-05-18T12:32:37.024351+00:00"},{"alias_kind":"pith_short_16","alias_value":"MG6Q5UP3BF46OR72","created_at":"2026-05-18T12:32:37.024351+00:00"},{"alias_kind":"pith_short_8","alias_value":"MG6Q5UP3","created_at":"2026-05-18T12:32:37.024351+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/MG6Q5UP3BF46OR72VEZYFDLXJX","json":"https://pith.science/pith/MG6Q5UP3BF46OR72VEZYFDLXJX.json","graph_json":"https://pith.science/api/pith-number/MG6Q5UP3BF46OR72VEZYFDLXJX/graph.json","events_json":"https://pith.science/api/pith-number/MG6Q5UP3BF46OR72VEZYFDLXJX/events.json","paper":"https://pith.science/paper/MG6Q5UP3"},"agent_actions":{"view_html":"https://pith.science/pith/MG6Q5UP3BF46OR72VEZYFDLXJX","download_json":"https://pith.science/pith/MG6Q5UP3BF46OR72VEZYFDLXJX.json","view_paper":"https://pith.science/paper/MG6Q5UP3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1804.07633&json=true","fetch_graph":"https://pith.science/api/pith-number/MG6Q5UP3BF46OR72VEZYFDLXJX/graph.json","fetch_events":"https://pith.science/api/pith-number/MG6Q5UP3BF46OR72VEZYFDLXJX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/MG6Q5UP3BF46OR72VEZYFDLXJX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/MG6Q5UP3BF46OR72VEZYFDLXJX/action/storage_attestation","attest_author":"https://pith.science/pith/MG6Q5UP3BF46OR72VEZYFDLXJX/action/author_attestation","sign_citation":"https://pith.science/pith/MG6Q5UP3BF46OR72VEZYFDLXJX/action/citation_signature","submit_replication":"https://pith.science/pith/MG6Q5UP3BF46OR72VEZYFDLXJX/action/replication_record"}},"created_at":"2026-05-17T23:47:31.227229+00:00","updated_at":"2026-05-17T23:47:31.227229+00:00"}