{"as_of":"2026-08-07T15:21:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a250eb55249aadda13d25c395fe36bb823565d227854039645c748eca56ce0bc","coverage":[{"denominator":31,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-02T23:06:37.495844Z","state":"measured"},{"denominator":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2602.14947/citation-record","integrity":"/paper/2602.14947/integrity","json":"/paper/2602.14947/citation-record.json","paper":"/paper/2602.14947"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:34.033394Z","title":null,"venue":null,"work_id":null,"year":1968},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:34.033394Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:f4da1eb97349a1e9cf3e0874246578ac8a59b7434cb15057505a2754c94f0690","observation_id":"3cd70969-a0b5-480b-bdeb-34d5d741018b","resolution":{"observed_at":"2026-08-02T23:06:34.033394Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:34.156265Z","title":null,"venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:34.156265Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:1ec51cf3b1ea01b12d6e452f06e710a94e21c3f34585a729c04a0602426cf739","observation_id":"b1820388-f284-4588-a7b4-ab8c5bda412a","resolution":{"observed_at":"2026-08-02T23:06:34.156265Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:34.255465Z","title":"Die Nachbildung von Magnetisierungskurven durch einfache algebraische oder transzendente Funktionen,","venue":null,"work_id":null,"year":1956},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:34.255465Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:4db48a6bc221744f38518e861e0fc36dd0cfa86bf8423c5ad26f97d394b1c59f","observation_id":"5089c96a-2904-4b81-af92-b117416d971f","resolution":{"observed_at":"2026-08-02T23:06:34.255465Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:34.323697Z","title":"Inclusion of magnetic saturation in dynamic models of synchronous reluctance motors,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:34.323697Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:0d17b3225254fdc71455ce17f13c0cec455b2354fad6a9ef2c03494f97c5ae21","observation_id":"e0f32cc8-caf0-411b-806d-76c40f2d28d5","resolution":{"observed_at":"2026-08-02T23:06:34.323697Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:34.423882Z","title":"Analytical modeling and simulation of highly utilized electrical machines considering nonlinear effects,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:34.423882Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:4cbafd2b28a1349dc46713e48a585ff515874335ee131c33d11df951e9be2921","observation_id":"4f6811cf-5107-4727-b4ea-30c79c0ba184","resolution":{"observed_at":"2026-08-02T23:06:34.423882Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:34.595250Z","title":"Flux maps spatial harmonic modeling and measurement in synchronous reluctance motors,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:34.595250Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:7011a9435b4cac3d0de06bd724d677782fc39fc82f9384f7f97996a424587c83","observation_id":"4d83367a-eb87-4129-abcf-2b4ab638e602","resolution":{"observed_at":"2026-08-02T23:06:34.595250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:34.734464Z","title":"A saturation model based on a simplified equivalent magnetic circuit for permanent magnet machines,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:34.734464Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:5d3474b3de0d32903984441b8bca9a6e8f92268cd162dd5bd6e611118e8cf019","observation_id":"6cf7f778-0f0d-4c44-ae65-2a1cfb6c6ad7","resolution":{"observed_at":"2026-08-02T23:06:34.734464Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:34.828091Z","title":"Flux- observer-based high-performance control of synchronous reluctance mo- tors by including cross saturation,","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:34.828091Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:0ff64efa9f75d12cb0d1f380a582420d1c01678cb04821383a11b1a7e6ce3c9e","observation_id":"463a7981-a2a7-4656-bfe1-bb530b2f9494","resolution":{"observed_at":"2026-08-02T23:06:34.828091Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:34.969265Z","title":"A high-fidelity and computationally efficient model for interior permanent-magnet machines considering the magnetic saturation, spatial harmonics, and iron loss effect,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:34.969265Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:312da933218799c970b0bf04b22f01ade7584d834b6d7ccd889c7b48d14665ce","observation_id":"9ca4ea17-fdd8-443d-98ca-a93e4a165f86","resolution":{"observed_at":"2026-08-02T23:06:34.969265Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:35.098962Z","title":"Modeling of interior permanent magnet machine considering saturation, cross coupling, spatial harmonics, and temperature effects,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:35.098962Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:acad4ece3641ccf1573308c00ff2fee536ed8e92494372afce2df311a1199e38","observation_id":"5cefbcb6-ebd7-4a82-974b-9aa87fc855b3","resolution":{"observed_at":"2026-08-02T23:06:35.098962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:35.216769Z","title":"Identification of IPMSM flux-linkage map for high-accuracy simulation of IPMSM drives,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:35.216769Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:9b0c32cd911d9f0abbb4d5d465e66425a309a017f506072f0d380770950efa43","observation_id":"9142aae9-74b6-4682-b3d3-4e1502fce8dc","resolution":{"observed_at":"2026-08-02T23:06:35.216769Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:35.320963Z","title":"The dq-theta flux map model of synchronous machines,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:35.320963Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:b286be5f069f7c7087289d9ae5bc6110ecef637fa81a3f95239af346a867fbbd","observation_id":"2711c2d9-4fab-4973-8ff4-ddfdb48cc19b","resolution":{"observed_at":"2026-08-02T23:06:35.320963Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:35.383057Z","title":"Experimental identification of the dq𝜃flux maps of synchronous machines,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:35.383057Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:3b45b73c12e615bce85bf2d7daa45d74067f21b410ca59352f1fdf214f512862","observation_id":"b6614e37-3a45-4aed-8152-eb33783173a6","resolution":{"observed_at":"2026-08-02T23:06:35.383057Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:35.442705Z","title":"Sensorless speed control of synchronous reluctance motor drives based on extended kalman filter and neural magnetic model,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:35.442705Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:d67f47241ef84d84a2ed31d5759c03e112087407a2a505f4ca7722d7e2935d9f","observation_id":"4727353a-9d2e-4fa3-907c-21d90cd3eeb3","resolution":{"observed_at":"2026-08-02T23:06:35.442705Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:35.551249Z","title":"RNN-based high fidelity permanent magnet synchronous motor emulator considering driving inverter switching faults,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:35.551249Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:3d5bef2cd308dd45068b9a46c98d962f2dd43bac7fe879f08e7cb4267957c3b0","observation_id":"d4e1c06d-2c6e-4d79-9bc6-5ad01bfecb26","resolution":{"observed_at":"2026-08-02T23:06:35.551249Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:35.559798Z","title":"A neural-network-based electric machine emulator using neuro- fuzzy controller for power-hardware-in-the-loop testing,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:35.559798Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:e37cb3a6a10dad235f20e964513ce15742c0e43207cfe1d6967a0d99d35d89bc","observation_id":"df661008-ae81-4dba-ba0a-ce67c9a08ef5","resolution":{"observed_at":"2026-08-02T23:06:35.559798Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:35.666752Z","title":"Estimation of flux saturation model for SynRMs using artificial neural network,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:35.666752Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:777b8c96731735de2e8952f8ed2b94b23e474d276410fa3326d76dd83631daec","observation_id":"fd07a1a3-f2d7-43a1-9f37-5490dee27748","resolution":{"observed_at":"2026-08-02T23:06:35.666752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:35.824516Z","title":"Fast flux mapping technique for synchronous reluctance machines: Method description and comparison with full FEA and measurements,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:35.824516Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:f463484371a831aa31480d76f826e0d35a9ca37b59179f720c264f98ff65d04a","observation_id":"1f9ecbe3-8493-4994-a7b3-d0a2a226db49","resolution":{"observed_at":"2026-08-02T23:06:35.824516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:35.989968Z","title":"Experimental identification of the magnetic model of synchronous machines,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:35.989968Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:f21b5e2894f0a3b600d6f4451e87bcb03dfec4d1b97adc64e0483dd9f2a071f2","observation_id":"9781e1c0-7d42-4587-aebd-2a16915dbeb7","resolution":{"observed_at":"2026-08-02T23:06:35.989968Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:36.076787Z","title":"Sensorless self-commissioning of synchronous reluctance motors at standstill without rotor locking,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:36.076787Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:879714ec3bc1809322a56c34a6c91b261c33d31fcf05a83eb0b5f99012b4b060","observation_id":"3b7fb974-fd61-4532-a905-0fc205c422f1","resolution":{"observed_at":"2026-08-02T23:06:36.076787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:36.228295Z","title":"Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:36.228295Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:aca5234f5b0a2936f0e92048ebeda64258d71fa96855846631e9c1baad62510e","observation_id":"6446340f-9f28-42c1-9235-144a68fdc6c7","resolution":{"observed_at":"2026-08-02T23:06:36.228295Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2003.04630","last_updated":"2020-07-30T05:22:58Z","snapshot_observed_at":"2026-08-04T10:05:44.957260Z","submitted_at":"2020-03-10T10:55:25Z","title":"Lagrangian Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2003.04630","snapshot_observed_at":"2026-08-02T23:06:36.443571Z","title":"Lagrangian neural networks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:36.443571Z"},"links":{"cited_paper":"/paper/2003.04630","citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:5cb029bd70f55ea8e2cf048449d6a6ed2001161ced1a113777d4a5933f1b92bd","observation_id":"4799b1bd-c5df-46f9-8854-836f120892d3","resolution":{"observed_at":"2026-08-02T23:06:36.443571Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:36.577853Z","title":"Hamiltonian neural networks,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:36.577853Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:86f756c938b8bbc4f6abda7a2847429281d9aa0a6af41217598257cadbe56aa1","observation_id":"f7dc39ba-b038-46bc-8055-893b3ed1dee8","resolution":{"observed_at":"2026-08-02T23:06:36.577853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:36.915677Z","title":"Port-Hamiltonian neural networks for learning explicit time-dependent dynamical systems,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:36.915677Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:db10d0836d8f6542324df6b443d49c7e7996b87b3cdc09ba549c30bf622524a7","observation_id":"1b6b4709-92c5-4350-940e-aa3d34e4b91c","resolution":{"observed_at":"2026-08-02T23:06:36.915677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:37.084185Z","title":"van der Schaft and D","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:37.084185Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:c305fb85507970776aec709c6ee44c17930b24feb623fafb13d81c296cb762e5","observation_id":"0608a3d5-be26-40d2-8a69-9359d10b44f4","resolution":{"observed_at":"2026-08-02T23:06:37.084185Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:37.181646Z","title":"Gradient networks,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:37.181646Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:f8ac99b235b27adbf142c61764dbdc27de842f27d12cb87901310efdb1d5ebfc","observation_id":"44dfcc4a-9e54-46d3-8fad-d67d75346605","resolution":{"observed_at":"2026-08-02T23:06:37.181646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.10739","last_updated":"2020-06-18T17:59:11Z","snapshot_observed_at":"2026-07-06T09:30:32.320227Z","submitted_at":"2020-06-18T17:59:11Z","title":"Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domains","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.10739","snapshot_observed_at":"2026-08-02T23:06:37.242148Z","title":"Fourier features let networks learn high frequency functions in low dimensional domains,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:37.242148Z"},"links":{"cited_paper":"/paper/2006.10739","citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:3966eef67f372612e7d067fa57ec7e3785a96812482598cd439e2865d4c44ccc","observation_id":"c379969f-36c2-4d5d-9911-ccdab21c2050","resolution":{"observed_at":"2026-08-02T23:06:37.242148Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.11687","last_updated":"2021-12-22T06:20:27Z","snapshot_observed_at":"2026-07-06T12:21:24.416553Z","submitted_at":"2021-12-22T06:20:27Z","title":"Squareplus: A Softplus-Like Algebraic Rectifier","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.11687","snapshot_observed_at":"2026-08-02T23:06:37.340462Z","title":"Squareplus: A softplus-like algebraic rectifier,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:37.340462Z"},"links":{"cited_paper":"/paper/2112.11687","citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:661d01432e995d27c5b11835711db729680b5ab6a5eb6fbe2bf0d2f33390053f","observation_id":"24d52ee1-1117-43c9-8b24-d9e431c8c452","resolution":{"observed_at":"2026-08-02T23:06:37.340462Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:37.436636Z","title":"Design framework for sensorless control of synchronous machine drives,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:37.436636Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:7645b67bd51c0fdeffbff90ffc98a6652a20c5e78472d816d6c87a9758c5278e","observation_id":"d3f0555c-ad29-41a2-bccf-4cae849c0a5d","resolution":{"observed_at":"2026-08-02T23:06:37.436636Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-02T23:06:37.495844Z","title":"Direct flux vector control of synchronous motor drives: Accurate decoupled control with online adaptive maximum torque per ampere and maximum torque per volts evaluation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:37.495844Z"},"links":{"citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:a7e39007b8a2d9dd842ec06a0f13ebaa476a36c1fe7f605c5f3bb3dab6fc50b5","observation_id":"2afaf0bf-cbd0-4aa1-9d99-3f7b6e4be2d0","resolution":{"observed_at":"2026-08-02T23:06:37.495844Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.01563","last_updated":"2019-09-05T04:20:28Z","snapshot_observed_at":"2026-08-02T00:19:27.415872Z","submitted_at":"2019-06-04T16:27:55Z","title":"Hamiltonian Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.01563","snapshot_observed_at":"2026-08-02T23:06:36.748661Z","title":"Available: https://arxiv.org/abs/1906.01563","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines","version":3},"reference_index":2019,"source":"pdf_text","source_observed_at":"2026-08-02T23:06:36.748661Z"},"links":{"cited_paper":"/paper/1906.01563","citing_paper":"/paper/2602.14947"},"observation_digest":"sha256:8e14a5dedbff55e1aae26c9673ecedae954ed054976160c7525e4931e07aae29","observation_id":"7fe8304a-a9c9-4f86-917b-f390081cfa4c","resolution":{"observed_at":"2026-08-02T23:06:36.748661Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2602.14947","last_updated":"2026-07-28T07:14:02Z","latest_version":3,"primary_category":"eess.SY","snapshot_observed_at":"2026-08-06T11:26:19.536946Z","submitted_at":"2026-02-16T17:28:42Z","title":"Gradient Networks for Universal Magnetic Modeling of Synchronous Machines"},"reference_resolution":{"displayed":31,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":31,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":31},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2602.14947."}