Paper Citation Record · LEDGER

Path optimization method for the sign problem: Insights from random matrix models

As of 9 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2607.15742.

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

pith.paper-citation-record.v1
2607.15742 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T22:29:30.815339Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

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Outbound references

Observation b428e1ea-b7cd-41d3-a552-8ca41a0a227f · outbound

This paper cites Simulating QCD at finite density.

Path optimization method for the sign problem: Insights from random matrix models Simulating QCD at finite density

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:25.835977Z

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Observation 2fd27b10-966c-40c6-91df-dfca1fd2a930 · outbound

This paper cites Finite-density lattice QCD and sign problem: current status and open problems.

Path optimization method for the sign problem: Insights from random matrix models Finite-density lattice QCD and sign problem: current status and open problems

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:25.957599Z

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Observation 5c393cac-64ae-434e-bd9d-39efd27af7ed · outbound

This paper cites Analytic Continuation Of Chern-Simons Theory.

Path optimization method for the sign problem: Insights from random matrix models Analytic Continuation Of Chern-Simons Theory

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:26.085195Z

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Observation 27696562-c1ed-48e6-86a9-09c6ae2c50c4 · outbound

This paper cites Duane, A.

Path optimization method for the sign problem: Insights from random matrix models Duane, A

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:26.239300Z

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Observation f0fa24eb-b7ea-4179-bfa1-6734aac2f56e · outbound

This paper cites Toward solving the sign problem with path optimization method.

Path optimization method for the sign problem: Insights from random matrix models Toward solving the sign problem with path optimization method

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:26.386248Z

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Observation 2a02fdb9-28a3-40b8-adb2-05ea57824211 · outbound

This paper cites Application of neural network to sign problem via path optimization method.

Path optimization method for the sign problem: Insights from random matrix models Application of neural network to sign problem via path optimization method

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:26.565930Z

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Observation ddb4abc1-24d6-4883-a5eb-57218b15772c · outbound

This paper cites Deep Learning Beyond Lefschetz Thimbles.

Path optimization method for the sign problem: Insights from random matrix models Deep Learning Beyond Lefschetz Thimbles

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:26.740864Z

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Observation ecc97f71-deaf-4bf3-8f97-19d13e33bc7e · outbound

This paper cites Complex Paths Around The Sign Problem.

Path optimization method for the sign problem: Insights from random matrix models Complex Paths Around The Sign Problem

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:26.896153Z

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Observation e177c512-82be-4040-8aac-a25b62522c67 · outbound

This paper cites Random matrix model of QCD at finite density and the nature of the quenched limit.

Path optimization method for the sign problem: Insights from random matrix models Random matrix model of QCD at finite density and the nature of the quenched limit

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:27.039056Z

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Observation 6648395d-be7f-4460-a2f1-f5952366c9d9 · outbound

This paper cites On the Phase Diagram of QCD.

Path optimization method for the sign problem: Insights from random matrix models On the Phase Diagram of QCD

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:27.140666Z

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Observation 2b76bf39-8988-45f1-bf02-6619e077fdd9 · outbound

This paper cites Complex Langevin Simulation of a Random Matrix Model at Nonzero Chemical Potential.

Path optimization method for the sign problem: Insights from random matrix models Complex Langevin Simulation of a Random Matrix Model at Nonzero Chemical Potential

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:27.265195Z

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Observation 88b5dff2-7476-42fe-a045-7adf2f59e979 · outbound

This paper cites Worldvolume approach to the tempered Lefschetz thimble method.

Path optimization method for the sign problem: Insights from random matrix models Worldvolume approach to the tempered Lefschetz thimble method

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:27.426975Z

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Observation c5890a68-ba8d-4a5e-a630-ae6c001ae9de · outbound

This paper cites Fighting the sign problem in a chiral random matrix model with contour deformations.

Path optimization method for the sign problem: Insights from random matrix models Fighting the sign problem in a chiral random matrix model with contour deformations

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:27.590320Z

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Observation af31518c-82b5-48b2-96d3-0fb13780d865 · outbound

This paper cites Complex Langevin Dynamics for chiral Random Matrix Theory.

Path optimization method for the sign problem: Insights from random matrix models Complex Langevin Dynamics for chiral Random Matrix Theory

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:27.737609Z

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Observation 4fe398f0-8e72-48bb-bb21-4fd1be90ee18 · outbound

This paper cites Full simulation of chiral Random Matrix Theory at non-zero chemical potential by Complex Langevin.

Path optimization method for the sign problem: Insights from random matrix models Full simulation of chiral Random Matrix Theory at non-zero chemical potential by Complex Langevin

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:27.858414Z

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Observation 6696f4cb-0ed7-4727-a575-508b55ba1e1f · outbound

This paper cites Test for a universal behavior of Dirac eigenvalues in the complex Langevin method.

Path optimization method for the sign problem: Insights from random matrix models Test for a universal behavior of Dirac eigenvalues in the complex Langevin method

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:27.955301Z

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Observation c1b9b05d-0438-441e-bc6b-5544206f3db3 · outbound

This paper cites Phase diagram of a generalized Stephanov model for finite-density QCD.

Path optimization method for the sign problem: Insights from random matrix models Phase diagram of a generalized Stephanov model for finite-density QCD

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:28.038855Z

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Observation 5c090443-9ec0-4250-b862-8f4d951b8c95 · outbound

This paper cites Subsets and the canonical partition functions.

Path optimization method for the sign problem: Insights from random matrix models Subsets and the canonical partition functions

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:28.207978Z

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Observation 2aeda101-09d4-4112-854d-4d1add897e36 · outbound

This paper cites Finite-Density Monte Carlo Calculations on Sign-Optimized Manifolds.

Path optimization method for the sign problem: Insights from random matrix models Finite-Density Monte Carlo Calculations on Sign-Optimized Manifolds

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:28.375417Z

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Observation f54ca6d5-94a3-408f-ae0e-6124e3f88d79 · outbound

This paper cites Szandała, in Bio-inspired neurocomputing (Springer,.

Path optimization method for the sign problem: Insights from random matrix models Szandała, in Bio-inspired neurocomputing (Springer,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:28.515536Z

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Observation e8b6e399-ac9a-48cc-b099-a0f1b74cd4d2 · outbound

This paper cites an unresolved cited work.

Path optimization method for the sign problem: Insights from random matrix models Unresolved cited work

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:28.656911Z

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Observation 15f35860-4bd5-4e0b-923e-43f9e6bc8c13 · outbound

This paper cites Improving efficiency of the path optimization method for a gauge theory.

Path optimization method for the sign problem: Insights from random matrix models Improving efficiency of the path optimization method for a gauge theory

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:28.768309Z

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Observation 7b15542e-6f39-47aa-94ad-3c1e2fe6e454 · outbound

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

Path optimization method for the sign problem: Insights from random matrix models Path optimization method for the sign problem caused by fermion determinant

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:28.914765Z

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Observation aebef0e0-dacd-471a-a14a-5355b1e7555e · outbound

This paper cites an unresolved cited work.

Path optimization method for the sign problem: Insights from random matrix models Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:29.053752Z

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Observation 0ad95d9e-6c9e-4eb3-9eeb-e85f3bedf761 · outbound

This paper cites an unresolved cited work.

Path optimization method for the sign problem: Insights from random matrix models Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:29.180949Z

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Observation 3c42f858-cae3-4463-9de1-058b15954336 · outbound

This paper cites Hukushima and K.

Path optimization method for the sign problem: Insights from random matrix models Hukushima and K

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:29.336572Z

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Observation 98e6db1f-8bab-4d0d-b5cb-60e321c96970 · outbound

This paper cites Path optimization for $U(1)$ gauge theory with complexified parameters.

Path optimization method for the sign problem: Insights from random matrix models Path optimization for $U(1)$ gauge theory with complexified parameters

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:29.492190Z

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Observation fba1f28a-91b7-48f1-98b0-86113ad4c083 · outbound

This paper cites Paszke, S.

Path optimization method for the sign problem: Insights from random matrix models Paszke, S

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:29.630476Z

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Observation ec98a2f6-0353-4e26-ac15-6e1eb717126f · outbound

This paper cites Mish: A Self Regularized Non-Monotonic Activation Function.

Path optimization method for the sign problem: Insights from random matrix models Mish: A Self Regularized Non-Monotonic Activation Function

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:29.740549Z

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Observation b1b37898-e1d8-44dc-9fff-b7da44524ad9 · outbound

This paper cites Glorot and Y.

Path optimization method for the sign problem: Insights from random matrix models Glorot and Y

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:29.865573Z

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Observation 6b564e75-7dfc-423f-8885-b58a648f0e12 · outbound

This paper cites Decoupled Weight Decay Regularization.

Path optimization method for the sign problem: Insights from random matrix models Decoupled Weight Decay Regularization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:29.985423Z

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Observation 6006b382-1d48-4f9e-a0a2-85928852702d · outbound

This paper cites An Exponential Learning Rate Schedule for Deep Learning.

Path optimization method for the sign problem: Insights from random matrix models An Exponential Learning Rate Schedule for Deep Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:30.146859Z

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Observation 87f24f94-cbf3-4143-a90e-1c7b4137c382 · outbound

This paper cites Bottou, Online learning in neural networks (1998).

Path optimization method for the sign problem: Insights from random matrix models Bottou, Online learning in neural networks (1998)

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:30.284048Z

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Observation 63ad1c8f-9dd6-4e26-be72-b32d0724e7c0 · outbound

This paper cites Functional integrals for QCD at nonzero chemical potential and zero density.

Path optimization method for the sign problem: Insights from random matrix models Functional integrals for QCD at nonzero chemical potential and zero density

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:30.445615Z

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Observation 48aabdec-5851-4d0b-a3a9-dc1b9c978aef · outbound

This paper cites Modifying partition functions: a way to solve the sign problem.

Path optimization method for the sign problem: Insights from random matrix models Modifying partition functions: a way to solve the sign problem

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:30.564096Z

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Observation c919fc1a-7826-4030-a8cd-131189b1f4b3 · outbound

This paper cites Parallel tempering algorithm for integration over Lefschetz thimbles.

Path optimization method for the sign problem: Insights from random matrix models Parallel tempering algorithm for integration over Lefschetz thimbles

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:30.702080Z

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Observation ad2003cc-c048-40c5-b25f-b597079bca24 · outbound

This paper cites Deep Learning of Fermion Sign Fluctuations.

Path optimization method for the sign problem: Insights from random matrix models Deep Learning of Fermion Sign Fluctuations

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-01T22:29:30.815339Z

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Pith citing papers

No inbound Pith citation observations are available.