Paper Citation Record · LEDGER

Mitigating the Hubbard Sign Problem with Complex-Valued Neural Networks

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2203.00390.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2203.00390 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:08:39.297801Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-19T03:55:53.912149Z

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 1368b3de-fe4d-45d2-a696-4c916925392a · inbound

Path optimization method for the sign problem caused by fermion determinant cites this paper.

Path optimization method for the sign problem caused by fermion determinant Mitigating the Hubbard Sign Problem with Complex-Valued Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T11:08:39.297801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea030acc-59d9-47d6-9bfd-51f6f460a65b · inbound

Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation cites this paper.

Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Mitigating the Hubbard Sign Problem with Complex-Valued Neural Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T23:33:39.662398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91a110aa-84df-4cff-9428-9ff832cb8ed0 · inbound

Applying the Worldvolume Hybrid Monte Carlo method to the Hubbard model away from half filling cites this paper.

Applying the Worldvolume Hybrid Monte Carlo method to the Hubbard model away from half filling Mitigating the Hubbard Sign Problem with Complex-Valued Neural Networks

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-19T02:11:59.264893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 04769c73-2a7f-4bc6-b8f5-212c63e394e6 · inbound

Analyzing the two-dimensional doped Hubbard model with the Worldvolume HMC method cites this paper.

Analyzing the two-dimensional doped Hubbard model with the Worldvolume HMC method Mitigating the Hubbard Sign Problem with Complex-Valued Neural Networks

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-15T03:09:43.830935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.