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Paper Citation Record · LEDGER

Physics-informed neural network model for quantum impurity problems based on Lehmann representation

As of 14 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2411.18835.

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

pith.paper-citation-record.v1
2411.18835 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:54:51.636388Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T06:23:32.807246Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

  • verified exact1
  • verified fuzzy7
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cc80a048-a720-4c09-9dc4-4617c9118933 · outbound

This paper cites Georges, G.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Georges, G

Reference 1

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Observation 16b545b6-c5cb-4449-b7fc-696af146b5e9 · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 2

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source=pdf_text observed=2026-08-12T10:54:51.446872Z digest=sha256:ae887a7088d0828e6ec6bbf78b05c8c673948f40e5e5502f9fb7042529ff17db

Observation d9db4677-a3b5-4bf2-b01e-addb7fa9231b · outbound

This paper cites Caffarel and W.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Caffarel and W

Reference 3

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source=pdf_text observed=2026-08-12T10:54:51.454529Z digest=sha256:9c5f7bcc6c0c239d7ec542be956e98d724deac438d8ffc5f61e4692f0ef58122

Observation 8c1f0661-86eb-4331-bcd6-87e29d738cc2 · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-12T10:54:51.459569Z digest=sha256:ee6ecd8f56c758efc930398e37f5e94160e25c6adcddb0bdf0cb5ffee5188ed6

Observation 1be88daf-6453-4629-ba9c-61c16257adcb · outbound

This paper cites Werner, A.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Werner, A

Reference 5

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source=pdf_text observed=2026-08-12T10:54:51.464675Z digest=sha256:9a9a568d8c6e6bcdd9b7ad3468d64c5c3656e3aa0ddf9f42bed89384b1a3cbf2

Observation a3b5d4ab-2ccb-4f4f-b94d-7b9d507844cb · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 2885c41e-d4f6-4481-a66e-771e64a9d67a · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 7

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 8a93a221-5d47-4ddd-8211-4a9fc25bc5ef · outbound

This paper cites Bauernfeind, M.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Bauernfeind, M

Reference 8

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source=pdf_text observed=2026-08-12T10:54:51.480426Z digest=sha256:bb03adb2ea989f57476c77d3d7043131327cdf6bcf7a46cfcbe543fcf7c8fbe5

Observation a94e760c-ec36-4f8d-b296-85fca24ce369 · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 9

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 1d30fc2b-afb6-4d50-99e3-ea2b2dce7ef1 · outbound

This paper cites N´ u˜ nez Fern´ andez, M.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation N´ u˜ nez Fern´ andez, M

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation ff8999e3-eb9a-4090-97dc-933ddebb600d · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 11

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 89e86fda-60db-4e9c-bae3-7e06c7dbd3e3 · outbound

This paper cites Sheridan, C.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Sheridan, C

Reference 12

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 56840ae4-5c82-4d63-9471-26ec8b407880 · outbound

This paper cites A language-inspired machine learning approach for solving strongly correlated problems with dynamical mean-field theory.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation A language-inspired machine learning approach for solving strongly correlated problems with dynamical mean-field theory

Reference 13

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local_arxiv, observed 2026-08-12T10:54:51.784725Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 42c134e4-67f2-40c4-81c0-e0fc8de89ecb · outbound

This paper cites Predicting interacting Green's functions with neural networks.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Predicting interacting Green's functions with neural networks

Reference 14

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Source-reported events for the cited work

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Observation 884f5d74-5487-42c2-b81a-40a863c89470 · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 15

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f1edf1aa-893b-4c8c-8bc8-288d4ffa96ed · outbound

This paper cites Ren, R.-S.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Ren, R.-S

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation c5626ab6-0942-435f-befb-95b718cbe5d2 · outbound

This paper cites Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations

Reference 17

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Observation cec622bb-ecdc-429e-b0a9-ba3809568a20 · outbound

This paper cites Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations

Reference 18

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Observation 954e15af-3f29-4b5d-bcfc-1af29a6bd152 · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 19

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 22b20d59-78a3-4085-a61d-92e83c7640bd · outbound

This paper cites Shinaoka, J.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Shinaoka, J

Reference 20

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Observation 098b5dc4-5f93-4697-bdab-ae65d7e114d0 · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:54:51.567152Z digest=sha256:6f68f53c737476d2da29a1ee9ec735b475c2d9f8ada1459945f4c2310ee6f900

Observation 59c57795-5cea-4b7c-990f-5a8a189392cd · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 22

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 202501b2-a6b3-46ba-a1eb-c22ed1cca4f4 · outbound

This paper cites Shinaoka, N.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Shinaoka, N

Reference 23

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 74037a2f-a6d7-4b98-a32e-7860938af864 · outbound

This paper cites Chikano, J.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Chikano, J

Reference 24

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 585ff62c-e064-4cdb-8839-4bce98a191a6 · outbound

This paper cites an unresolved cited work.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Unresolved cited work

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation 12f7b166-8dfa-45e9-bc04-a6f2789a3a78 · outbound

This paper cites For instance, the contribution of a pole with a positive coefficient between two adjacent poles re- quires positive and negative weights on neighboring DLR grid points.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation For instance, the contribution of a pole with a positive coefficient between two adjacent poles re- quires positive and negative weights on neighboring DLR grid points

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-12T10:54:51.823892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation f3245f7e-8d23-4d2e-b4ae-5a05804b015c · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Adam: A Method for Stochastic Optimization

Reference 27

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:54:51.620742Z digest=sha256:0235a67be2437cce55f63d6fb5d85ab9d2b9d94563ea47464e4df076b0e43930

Observation 9e147c52-a919-4abb-bde5-49de46dedc17 · outbound

This paper cites Wallerberger, S.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Wallerberger, S

Reference 28

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Observation dd22b4b6-1fb5-49b5-9469-2bfdf774b637 · outbound

This paper cites Fashionable Modelling with Flux.

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Fashionable Modelling with Flux

Reference 29

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source=pdf_text observed=2026-08-12T10:54:51.631163Z digest=sha256:ccd8a5f2bc252e4e34ee76daad6806d429908505abbe0182dcb0dc84ef3dcd0c

Observation 502de998-fcc8-4af6-909a-cdc59b15d472 · outbound

This paper cites Innes, Flux: Elegant Machine Learning with Julia, Journal of Open Source Software 10.21105/joss.00602 (2018).

Physics-informed neural network model for quantum impurity problems based on Lehmann representation Innes, Flux: Elegant Machine Learning with Julia, Journal of Open Source Software 10.21105/joss.00602 (2018)

Reference 30

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Pith citing papers

Observation 49ef9a07-861d-4700-a29a-1e6823bc89d2 · inbound

Compact and Stable Representation of Real-Frequency Spectral Functions for Machine Learning cites this paper.

Compact and Stable Representation of Real-Frequency Spectral Functions for Machine Learning Physics-informed neural network model for quantum impurity problems based on Lehmann representation

Reference 9

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Unavailable: canonical work link unavailable.

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