Paper Citation Record · LEDGER

Simulating the Hubbard Model with Equivariant Normalizing Flows

As of 10 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 2 inbound Pith citation observations for arXiv:2501.07371.

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

pith.paper-citation-record.v1
2501.07371 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:48:34.852344Z

measured 41 of 41 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:19:44.545207Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T02:11:59.284972Z

Reference resolution

39 of 39 outbound references displayed

verified exact4
verified fuzzy0
unresolved35
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f682d95-7f94-491b-a24d-68b12183a3a2 · outbound

This paper cites Avoiding Ergodicity Problems in Lattice Discretizations of the Hubbard Model.

Simulating the Hubbard Model with Equivariant Normalizing Flows Avoiding Ergodicity Problems in Lattice Discretizations of the Hubbard Model

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.054859Z

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Observation 4ad08b71-4e21-4389-8759-35e2d7f2a283 · outbound

This paper cites Overcoming Ergodicity Problems of the Hybrid Monte Carlo Method using Radial Updates.

Simulating the Hubbard Model with Equivariant Normalizing Flows Overcoming Ergodicity Problems of the Hybrid Monte Carlo Method using Radial Updates

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.160938Z

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Observation adba8f0a-8db2-4d63-918c-203e295cfdf0 · outbound

This paper cites Variational Inference with Normalizing Flows.

Simulating the Hubbard Model with Equivariant Normalizing Flows Variational Inference with Normalizing Flows

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.203698Z

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Observation c6924b14-ab1f-47e5-a8e3-ca6e4a8f08df · outbound

This paper cites Normalizing Flows: An Introduction and Review of Current Methods.

Simulating the Hubbard Model with Equivariant Normalizing Flows Normalizing Flows: An Introduction and Review of Current Methods

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.250802Z

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Observation c1d837f6-ee0d-4709-b1b1-6dde1ec25850 · outbound

This paper cites Normalizing Flows for Probabilistic Modeling and Inference.

Simulating the Hubbard Model with Equivariant Normalizing Flows Normalizing Flows for Probabilistic Modeling and Inference

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.349456Z

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Observation 69f38a58-4014-485b-9152-e918292faf6d · outbound

This paper cites Pixel Recurrent Neural Networks.

Simulating the Hubbard Model with Equivariant Normalizing Flows Pixel Recurrent Neural Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.421922Z

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Observation e6dc4099-2730-45b8-a75b-10d9ee8cb384 · outbound

This paper cites Conditional Image Generation with PixelCNN Decoders.

Simulating the Hubbard Model with Equivariant Normalizing Flows Conditional Image Generation with PixelCNN Decoders

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.484936Z

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Observation 3343ad54-3980-493f-9835-26cd1a3ab482 · outbound

This paper cites Boltzmann Generators -- Sampling Equilibrium States of Many-Body Systems with Deep Learning.

Simulating the Hubbard Model with Equivariant Normalizing Flows Boltzmann Generators -- Sampling Equilibrium States of Many-Body Systems with Deep Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.594968Z

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Observation df002e6f-fa76-4212-9d4c-4e16bd2f1e3b · outbound

This paper cites Flow-based generative models for Markov chain Monte Carlo in lattice field theory.

Simulating the Hubbard Model with Equivariant Normalizing Flows Flow-based generative models for Markov chain Monte Carlo in lattice field theory

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.704905Z

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Observation a68faed3-7432-4e4d-ad06-dac4d96d43b6 · outbound

This paper cites Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models.

Simulating the Hubbard Model with Equivariant Normalizing Flows Estimation of Thermodynamic Observables in Lattice Field Theories with Deep Generative Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.783736Z

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Observation 6f7acd5c-fd86-4e4f-b717-6ba07a994181 · outbound

This paper cites Stochastic normalizing flows as non-equilibrium transformations.

Simulating the Hubbard Model with Equivariant Normalizing Flows Stochastic normalizing flows as non-equilibrium transformations

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.844768Z

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Observation 341bc7c5-49f8-4afb-9884-79f48b9f9d6f · outbound

This paper cites Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics.

Simulating the Hubbard Model with Equivariant Normalizing Flows Advances in machine-learning-based sampling motivated by lattice quantum chromodynamics

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.924537Z

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Observation e13ff2a1-62ea-4c06-8583-35d26d4d9e30 · outbound

This paper cites Solving Statistical Mechanics Using Variational Autoregressive Networks.

Simulating the Hubbard Model with Equivariant Normalizing Flows Solving Statistical Mechanics Using Variational Autoregressive Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:32.998206Z

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Observation ded9d538-946f-4df0-bd3e-5205718c55d5 · outbound

This paper cites Asymptotically unbiased estimation of physical observables with neural samplers.

Simulating the Hubbard Model with Equivariant Normalizing Flows Asymptotically unbiased estimation of physical observables with neural samplers

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.065066Z

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Observation 4d213c26-ebdf-4518-b7ee-49792ab17d70 · outbound

This paper cites Sampling Nambu-Goto theory using Normalizing Flows.

Simulating the Hubbard Model with Equivariant Normalizing Flows Sampling Nambu-Goto theory using Normalizing Flows

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.124161Z

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Observation 5078abde-6b3e-47c1-a7ce-44742a9417cc · outbound

This paper cites Sampling the lattice Nambu-Goto string using Continuous Normalizing Flows.

Simulating the Hubbard Model with Equivariant Normalizing Flows Sampling the lattice Nambu-Goto string using Continuous Normalizing Flows

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.184933Z

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Observation b5d172f1-0275-42cc-b160-51b1c2ccc7bc · outbound

This paper cites Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules.

Simulating the Hubbard Model with Equivariant Normalizing Flows Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.244889Z

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Observation 326c8cbc-78aa-4f77-a468-cfbc69f4af07 · outbound

This paper cites Gebauer, M.

Simulating the Hubbard Model with Equivariant Normalizing Flows Gebauer, M

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.331035Z

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Observation 1482f3d1-16dd-442f-bf0e-5302cd4a26d3 · outbound

This paper cites R\'enyi entanglement entropy of spin chain with Generative Neural Networks.

Simulating the Hubbard Model with Equivariant Normalizing Flows R\'enyi entanglement entropy of spin chain with Generative Neural Networks

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.404751Z

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Observation 7f8af51c-718e-4dcb-b645-b07450744c0c · outbound

This paper cites Flow-Based Sampling for Entanglement Entropy and the Machine Learning of Defects.

Simulating the Hubbard Model with Equivariant Normalizing Flows Flow-Based Sampling for Entanglement Entropy and the Machine Learning of Defects

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.485171Z

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Observation c153ebfb-4d74-484f-b6ac-0c331ceff414 · outbound

This paper cites Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse.

Simulating the Hubbard Model with Equivariant Normalizing Flows Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:48:36.704754Z

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 981477e0-d829-42c5-8934-cc3d8db7951f · outbound

This paper cites Detecting and Mitigating Mode-Collapse for Flow-based Sampling of Lattice Field Theories.

Simulating the Hubbard Model with Equivariant Normalizing Flows Detecting and Mitigating Mode-Collapse for Flow-based Sampling of Lattice Field Theories

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.605527Z

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Observation 26002e02-64ad-424d-b5d6-f7e584e97480 · outbound

This paper cites Equivariant flow-based sampling for lattice gauge theory.

Simulating the Hubbard Model with Equivariant Normalizing Flows Equivariant flow-based sampling for lattice gauge theory

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.694867Z

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Observation 983a0aed-15e2-4fe3-b1e9-d07083c0fd41 · outbound

This paper cites Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities.

Simulating the Hubbard Model with Equivariant Normalizing Flows Equivariant Flows: Exact Likelihood Generative Learning for Symmetric Densities

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.784857Z

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Observation c5c00377-61a7-4708-a2c0-d06e058a4ee8 · outbound

This paper cites Hubbard,Electron correlations in narrow energy bands, Proceedings of the Royal Society of London.

Simulating the Hubbard Model with Equivariant Normalizing Flows Hubbard,Electron correlations in narrow energy bands, Proceedings of the Royal Society of London

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.834857Z

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Observation 5c1c7fee-446f-4bf6-980c-3bfa1e86e80f · outbound

This paper cites The Hubbard Model.

Simulating the Hubbard Model with Equivariant Normalizing Flows The Hubbard Model

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.884850Z

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Observation 9f0b297e-e8ad-4df4-b2ba-7e61b7f0203d · outbound

This paper cites Trotter,On the product of semi-groups of operators,Proceedings of the American Mathematical Society10(1959) 545.

Simulating the Hubbard Model with Equivariant Normalizing Flows Trotter,On the product of semi-groups of operators,Proceedings of the American Mathematical Society10(1959) 545

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:33.943888Z

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Observation 5967c9a8-a2ff-4912-833d-7c7cd13d289c · outbound

This paper cites an unresolved cited work.

Simulating the Hubbard Model with Equivariant Normalizing Flows Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:34.052567Z

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Observation 593d6c42-7781-49fb-8461-0426f91be578 · outbound

This paper cites Hubbard,Calculation of Partition Functions, Phys.

Simulating the Hubbard Model with Equivariant Normalizing Flows Hubbard,Calculation of Partition Functions, Phys

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:34.095378Z

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Observation 90120ba6-34c5-4be6-8859-1cd4a1f9fd0a · outbound

This paper cites Hybrid Monte Carlo simulation on the graphene hexagonal lattice.

Simulating the Hubbard Model with Equivariant Normalizing Flows Hybrid Monte Carlo simulation on the graphene hexagonal lattice

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:48:35.775237Z

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 158691c2-4076-4e1d-893c-decf0eecb0d1 · outbound

This paper cites Monte-Carlo study of the semimetal-insulator phase transition in monolayer graphene with realistic inter-electron interaction potential.

Simulating the Hubbard Model with Equivariant Normalizing Flows Monte-Carlo study of the semimetal-insulator phase transition in monolayer graphene with realistic inter-electron interaction potential

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:48:35.697572Z

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 adda476c-6a8d-41fd-b832-ac6b8a96d965 · outbound

This paper cites Monte-Carlo simulation of the tight-binding model of graphene with partially screened Coulomb interactions.

Simulating the Hubbard Model with Equivariant Normalizing Flows Monte-Carlo simulation of the tight-binding model of graphene with partially screened Coulomb interactions

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-10T20:48:35.548174Z

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 7b6c70f0-6ce1-4877-9a4e-9e44e9c57e37 · outbound

This paper cites Quantum Monte Carlo Calculations for Carbon Nanotubes.

Simulating the Hubbard Model with Equivariant Normalizing Flows Quantum Monte Carlo Calculations for Carbon Nanotubes

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:34.314865Z

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Observation 246d131d-3d70-4722-8b75-be37dcc34f2c · outbound

This paper cites Duane, A.D.

Simulating the Hubbard Model with Equivariant Normalizing Flows Duane, A.D

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:34.488237Z

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Observation bf4cd771-46fb-44f2-982a-a9c3dc67dd21 · outbound

This paper cites NICE: Non-linear Independent Components Estimation.

Simulating the Hubbard Model with Equivariant Normalizing Flows NICE: Non-linear Independent Components Estimation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:34.544761Z

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Observation fa9f8bb0-2e9d-44f6-839e-1aac46773fa4 · outbound

This paper cites Density estimation using Real NVP.

Simulating the Hubbard Model with Equivariant Normalizing Flows Density estimation using Real NVP

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:34.571230Z

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Observation ec27c0f3-ee1f-41db-b620-e5373d141526 · outbound

This paper cites Kullback and R.A.

Simulating the Hubbard Model with Equivariant Normalizing Flows Kullback and R.A

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:34.766767Z

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Observation 66fbc065-2b22-49fe-9896-c38f05343cef · outbound

This paper cites Sampling using $SU(N)$ gauge equivariant flows.

Simulating the Hubbard Model with Equivariant Normalizing Flows Sampling using $SU(N)$ gauge equivariant flows

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:34.806658Z

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Observation 1e76e2a6-c79e-4875-b8c2-c1bd237364de · outbound

This paper cites Nicoli, C.J.

Simulating the Hubbard Model with Equivariant Normalizing Flows Nicoli, C.J

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T20:48:34.852344Z

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Pith citing papers

Observation 850e0c19-6239-4a11-8fdf-0901aab8e2d0 · inbound

SESaMo: Symmetry-Enforcing Stochastic Modulation for Normalizing Flows cites this paper.

SESaMo: Symmetry-Enforcing Stochastic Modulation for Normalizing Flows Simulating the Hubbard Model with Equivariant Normalizing Flows

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T14:19:44.545207Z

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Observation c2030065-863d-47ff-844d-9bc69e9820e2 · 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 Simulating the Hubbard Model with Equivariant Normalizing Flows

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-19T02:11:59.287152Z

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.