Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T23:33:39.683216Z
Paper Citation Record · LEDGER
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation
As of 10 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2502.04104.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
14 of 14 outbound references displayed
- verified exact5
- verified fuzzy4
- unresolved5
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 29af1c7f-2ea7-4e10-8639-726471637154 · outbound
This paper cites Hubbard,Calculation of Partition Functions,Phys.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Hubbard,Calculation of Partition Functions,Phys
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T23:33:39.921762Z
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 81da5999-f3c4-44ab-9058-03e569341dc5 · outbound
This paper cites Stratonovich,On a Method of Calculating Quantum Distribution Functions, Sov.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Stratonovich,On a Method of Calculating Quantum Distribution Functions, Sov
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T23:33:39.909007Z
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 c1528179-e61d-4072-9930-e06b6c26a0bb · outbound
This paper cites Quantum Monte Carlo Calculations for Carbon Nanotubes.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Quantum Monte Carlo Calculations for Carbon Nanotubes
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T23:33:39.868071Z
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 d54ee132-0cc7-4878-97fa-4bc1e5b5cdf3 · outbound
This paper cites Loh, J.E.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Loh, J.E
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T23:33:39.895337Z
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 20ee1cb0-5671-4e7a-8ae7-29700aa1d876 · outbound
This paper cites Leveraging Machine Learning to Alleviate Hubbard Model Sign Problems.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Leveraging Machine Learning to Alleviate Hubbard Model Sign Problems
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T23:33:39.848837Z
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 ca8f5402-b692-4067-906b-980ece5cf156 · outbound
This paper cites Fermions at Finite Density in (2+1)d with Sign-Optimized Manifolds.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Fermions at Finite Density in (2+1)d with Sign-Optimized Manifolds
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T23:33:39.829754Z
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 421f97e0-a735-4934-b282-b53b4b13ba22 · outbound
This paper cites Monte Carlo simulations on the Lefschetz thimble: taming the sign problem.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Monte Carlo simulations on the Lefschetz thimble: taming the sign problem
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T23:33:39.654802Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b99653f1-9845-4efc-8e7d-e2855aaf2305 · outbound
This paper cites Path integral contour deformations for noisy observables.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Path integral contour deformations for noisy observables
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T23:33:39.658632Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea030acc-59d9-47d6-9bfd-51f6f460a65b · outbound
This paper cites Mitigating the Hubbard Sign Problem with Complex-Valued Neural Networks.
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 599ea3d5-d5f1-4acd-a64d-54930f6b7999 · outbound
This paper cites Lefschetz,On Certain Numerical Invariants of Algebraic Varieties with Application to Abelian Varieties, Trans.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Lefschetz,On Certain Numerical Invariants of Algebraic Varieties with Application to Abelian Varieties, Trans
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T23:33:39.881944Z
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 fd10f3fb-7789-4ad5-a26e-e6182bb58165 · outbound
This paper cites Monte Carlo calculations of the finite density Thirring model.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Monte Carlo calculations of the finite density Thirring model
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T23:33:39.770631Z
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 91a7f2e3-6afa-4652-8d63-d5254b72b110 · outbound
This paper cites Group Equivariant Convolutional Networks.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Group Equivariant Convolutional Networks
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T23:33:39.673947Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 938d19eb-8d2a-4c5e-98c1-b6e831977d9b · outbound
This paper cites Fermionic Sign Problem Minimization by Constant Path Integral Contour Shifts.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Fermionic Sign Problem Minimization by Constant Path Integral Contour Shifts
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T23:33:39.678420Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 10b8ebdb-30cc-40a0-a7c3-7a1265d8670b · outbound
This paper cites Single Particle Spectrum of Doped $\mathrm{C}_{20}\mathrm{H}_{12}$-Perylene.
Exploring Group Convolutional Networks for Sign Problem Mitigation via Contour Deformation Single Particle Spectrum of Doped $\mathrm{C}_{20}\mathrm{H}_{12}$-Perylene
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T23:33:39.724007Z
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.
Pith citing papers
No inbound Pith citation observations are available.