Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
LyAl-Net: A high-efficiency Lyman-$\alpha$ forest simulation with a neural network
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2303.17939.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:24:46.747456Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T05:16:38.809917Z
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 4b3f53a3-4823-4307-a0ac-be3cdc251b8d · inbound
An AI super-resolution field emulator for cosmological hydrodynamics: the Lyman-{\alpha} forest cites this paper.
An AI super-resolution field emulator for cosmological hydrodynamics: the Lyman-{\alpha} forest LyAl-Net: A high-efficiency Lyman-$\alpha$ forest simulation with a neural network
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:24:46.747456Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a51b9a25-7f74-4432-bb7d-ea7820a85b41 · inbound
Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest cites this paper.
Machine Learning Techniques for Astrophysics and Cosmology: Lyman-$\alpha$ forest LyAl-Net: A high-efficiency Lyman-$\alpha$ forest simulation with a neural network
Reference 251
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T04:06:02.062455Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation fc2df8c1-0aa8-4d7d-8828-85bdbac42cf6 · inbound
The impact of source and survey modelling on the connection between [O III] emitters and Ly $\alpha$ forest transmission at z ~ 6 cites this paper.
The impact of source and survey modelling on the connection between [O III] emitters and Ly $\alpha$ forest transmission at z ~ 6 LyAl-Net: A high-efficiency Lyman-$\alpha$ forest simulation with a neural network
Reference 76
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T05:16:38.811645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.