Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Solving two-dimensional quantum eigenvalue problems using physics-informed machine learning
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.01413.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:48:10.443577Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T10:48:11.056024Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 8195cfcd-4331-44ab-ad17-ff16320f19c7 · inbound
Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient cites this paper.
Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient Solving two-dimensional quantum eigenvalue problems using physics-informed machine learning
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T10:48:11.061795Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b692ece7-6a70-44a4-88d0-adc644d94f20 · inbound
Physics-Informed Neural Networks for Complex Eigenfrequency Identification and Mode Structure Reconstruction of the Ground-State ITG Branch cites this paper.
Physics-Informed Neural Networks for Complex Eigenfrequency Identification and Mode Structure Reconstruction of the Ground-State ITG Branch Solving two-dimensional quantum eigenvalue problems using physics-informed machine learning
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T19:44:30.100335Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.