{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:KMRAPDSHWQJRI5DSJFRD7M362U","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":"d9b21be21bf06b564f9359faee8f2214af9752e556a1e937937e575b03b0466a","cross_cats_sorted":["cs.AI","cs.AR","cs.NE"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.SP","submitted_at":"2024-12-05T09:41:33Z","title_canon_sha256":"0ce943dd35fedbaa3b174b167eb964502538c3dff7a1bb0bf574881ec8565b7c"},"schema_version":"1.0","source":{"id":"2412.04008","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.04008","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"arxiv_version","alias_value":"2412.04008v1","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.04008","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"pith_short_12","alias_value":"KMRAPDSHWQJR","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"pith_short_16","alias_value":"KMRAPDSHWQJRI5DS","created_at":"2026-07-05T09:44:57Z"},{"alias_kind":"pith_short_8","alias_value":"KMRAPDSH","created_at":"2026-07-05T09:44:57Z"}],"graph_snapshots":[{"event_id":"sha256:04332c80161e230ca7dc96a9904b18623f84000b9ac95cab6f07a9325ce45572","target":"graph","created_at":"2026-07-05T09:44:57Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2412.04008/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper explores the potential of conversion-based neuromorphic algorithms for highly accurate and energy-efficient single-snapshot multidimensional harmonic retrieval (MHR). By casting the MHR problem as a sparse recovery problem, we devise the currently proposed, deep-unrolling-based Structured Learned Iterative Shrinkage and Thresholding (S-LISTA) algorithm to solve it efficiently using complex-valued convolutional neural networks with complex-valued activations, which are trained using a supervised regression objective. Afterward, a novel method for converting the complex-valued convolu","authors_text":"Alexandru P. Dr\\u{a}gu\\c{t}oiu, Gabriel B\\'ena, Holger Boche, Mahmoud Akl, Matthias Lohrmann, Ullrich J. M\\\"onich, Vlad C. Andrei, Yin Li","cross_cats":["cs.AI","cs.AR","cs.NE"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.SP","submitted_at":"2024-12-05T09:41:33Z","title":"Deep-Unrolling Multidimensional Harmonic Retrieval Algorithms on Neuromorphic Hardware"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.04008","kind":"arxiv","version":1},"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:d270f1e48d65f01878c5e6172fec350e73f9b6df045eb96a1730d5325e0759e2","target":"record","created_at":"2026-07-05T09:44:57Z","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":"d9b21be21bf06b564f9359faee8f2214af9752e556a1e937937e575b03b0466a","cross_cats_sorted":["cs.AI","cs.AR","cs.NE"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"eess.SP","submitted_at":"2024-12-05T09:41:33Z","title_canon_sha256":"0ce943dd35fedbaa3b174b167eb964502538c3dff7a1bb0bf574881ec8565b7c"},"schema_version":"1.0","source":{"id":"2412.04008","kind":"arxiv","version":1}},"canonical_sha256":"5322078e47b41314747249623fb37ed5097f37d5b0960d6ea3c3338bb0a1f240","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5322078e47b41314747249623fb37ed5097f37d5b0960d6ea3c3338bb0a1f240","first_computed_at":"2026-07-05T09:44:57.957835Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:44:57.957835Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Qq/X0nPg7RgSjrEqdp5PGDrIpsOO2/buL0xjCiBAEZEr1Q+UgCRQgsKOufkxHxbDrb6hK0MRqaShIcmRQHm6Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:44:57.958254Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.04008","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d270f1e48d65f01878c5e6172fec350e73f9b6df045eb96a1730d5325e0759e2","sha256:04332c80161e230ca7dc96a9904b18623f84000b9ac95cab6f07a9325ce45572"],"state_sha256":"30e88c429a7ce65a41e08eefb67cb832eab0411815df7de624854f3b3b15f161"}