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Paper Citation Record · LEDGER

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments

As of 12 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 2 inbound Pith citation observations for arXiv:2411.16052.

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

pith.paper-citation-record.v1
2411.16052 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:41:29.678783Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:15:51.293779Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T11:15:10.658470Z

Reference resolution

36 of 36 outbound references displayed

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External citation measurements

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Outbound references

Observation f4265787-befa-48f9-944a-db1ae4e7110b · outbound

This paper cites Spacetime-emergent ring toward tabletop quantum gravity experiments.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Spacetime-emergent ring toward tabletop quantum gravity experiments

Reference 1

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Observation da253edd-5d5d-4e07-91b3-38e9991eeb05 · outbound

This paper cites The large-n limit of superconformal field theorie s and supergravity.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments The large-n limit of superconformal field theorie s and supergravity

Reference 2

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Observation ff60a461-e07b-477f-8641-7d96d154df66 · outbound

This paper cites Inverse problem of correlation fu nctions in holography.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Inverse problem of correlation fu nctions in holography

Reference 3

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Observation 2317febe-10aa-413e-a95c-95ee0c2e6fa8 · outbound

This paper cites Deep learning and the ads/cft correspondence.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Deep learning and the ads/cft correspondence

Reference 4

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Observation 5d41353d-bc39-4761-98bc-3a26022a5083 · outbound

This paper cites Machine learning spa tial geometry from entanglement features.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Machine learning spa tial geometry from entanglement features

Reference 5

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Observation 9515c6f3-73a1-4fb2-8ae1-52cf0a996935 · outbound

This paper cites Deep learning and holographic qcd.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Deep learning and holographic qcd

Reference 6

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Observation 235c6d4c-906e-4265-968f-a181bfb3bdb0 · outbound

This paper cites Ads/cft correspondence as a deep boltzmann machine.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Ads/cft correspondence as a deep boltzmann machine

Reference 7

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Observation 2ae4d506-e460-4438-a796-a2549a5eaa33 · outbound

This paper cites Entanglement transitions from holographic random tensor networks.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Entanglement transitions from holographic random tensor networks

Reference 8

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Observation 10321a02-d3c3-43ae-ac47-ff44cfaf0701 · outbound

This paper cites Deep learning the holographic black h ole with charge.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Deep learning the holographic black h ole with charge

Reference 9

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Observation 8d2bac49-63b8-438c-8654-5d691f2fd999 · outbound

This paper cites Deep learning and ads/qcd.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Deep learning and ads/qcd

Reference 10

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Observation b015e456-a6b5-44af-bcf6-bbdd07ab862b · outbound

This paper cites Machin e learning holographic mapping by neural network renormalization group.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Machin e learning holographic mapping by neural network renormalization group

Reference 11

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Observation cee7689e-82fd-4e1c-8169-86cf504a8962 · outbound

This paper cites Deep lear ning black hole metrics from shear viscosity.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Deep lear ning black hole metrics from shear viscosity

Reference 12

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Observation 1cbc8ea8-2ee4-4274-95a2-5709ccb0c655 · outbound

This paper cites Neural ordin ary differential equation and holographic quantum chromodynamics.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Neural ordin ary differential equation and holographic quantum chromodynamics

Reference 13

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Observation c2a0ee69-6b2a-49df-a64f-3b78c41dc2c2 · outbound

This paper cites Machine learning statistical g ravity from multi-region entanglement entropy.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Machine learning statistical g ravity from multi-region entanglement entropy

Reference 14

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Observation 22f0a6b2-f1e4-472b-91be-48ac0043ee63 · outbound

This paper cites Ads/deep-learning made easy: simple examples.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Ads/deep-learning made easy: simple examples

Reference 15

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Observation 453a063a-64cc-41c6-85de-7577f8cce799 · outbound

This paper cites Ph ysics-informed deep learning for three dimensional black holes.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Ph ysics-informed deep learning for three dimensional black holes

Reference 16

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Observation 066c46c0-29d5-4f5f-a2c5-db43cbf7cfb9 · outbound

This paper cites Learning the black hole metric from holographic conductivity.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Learning the black hole metric from holographic conductivity

Reference 17

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Observation 574ece73-5a67-4066-a945-6192c3757750 · outbound

This paper cites Deep learning bulk spacetime from boundary optical conductivity.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Deep learning bulk spacetime from boundary optical conductivity

Reference 18

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Observation 4caf330e-fc15-4798-8b6c-3dfa5b32d1e1 · outbound

This paper cites Holographic complex potential of a quarkonium from deep learning.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Holographic complex potential of a quarkonium from deep learning

Reference 19

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Observation 65ff35cc-4cbe-473d-be6e-c8b3c1968a4b · outbound

This paper cites Machine learning holographic black hole f rom lattice qcd equation of state.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Machine learning holographic black hole f rom lattice qcd equation of state

Reference 20

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Observation b7cd49a1-790c-4beb-a215-d388ee4d0e20 · outbound

This paper cites Neural Network Modeling of Heavy-Quark Potential from Holography.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Neural Network Modeling of Heavy-Quark Potential from Holography

Reference 21

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Observation 42598c68-e2dd-41ed-b140-01a00dba0bdf · outbound

This paper cites Flavor dependent Critical endpoint from holographic QCD through machine learning.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Flavor dependent Critical endpoint from holographic QCD through machine learning

Reference 22

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Observation 03cf449e-78d4-40eb-9a52-227b9efad79d · outbound

This paper cites Holographic reconstruction of black hole spacetime: machine learning and entanglement entropy.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Holographic reconstruction of black hole spacetime: machine learning and entanglement entropy

Reference 23

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Observation c9a59698-89e6-42ec-9bb5-a21173561726 · outbound

This paper cites Neural ODEs for holographic transport models without translation symmetry.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Neural ODEs for holographic transport models without translation symmetry

Reference 24

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Observation 25d6441f-2d18-44ea-8339-c1cc90a24391 · outbound

This paper cites Gravitational Duals from Equations of State.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Gravitational Duals from Equations of State

Reference 25

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Observation bbc03b6e-f486-4e3d-903a-97ad1b9bafd1 · outbound

This paper cites Anti-de Sitter space, thermal phase transitio n, and confinement in gauge theories.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Anti-de Sitter space, thermal phase transitio n, and confinement in gauge theories

Reference 26

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Observation e768fd8b-40cd-47a2-9a38-fa39d1419379 · outbound

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Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Neural ordinary differential equations

Reference 27

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Observation 6b5aa469-a45e-46aa-b229-d84510eed68d · outbound

This paper cites KAN: Kolmogorov-Arnold Networks.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments KAN: Kolmogorov-Arnold Networks

Reference 28

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Observation abb2817d-0142-43c8-8976-07b26e5fa80e · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 29

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Observation 60477596-29c5-4d10-b791-f4912c61bbed · outbound

This paper cites End-to- end symbolic regression with transformers.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments End-to- end symbolic regression with transformers

Reference 30

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Observation 94e80303-e667-4eb1-930e-f87ea26c8ee1 · outbound

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Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Linear algebra with transformers

Reference 31

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Observation f594680e-7526-47b8-9f06-9b34fa6d5f41 · outbound

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Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Deep Learning for Symbolic Mathematics

Reference 32

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Observation d946458d-3de7-44ea-bbf7-82b3bb7cfd86 · outbound

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Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Holography Transformer

Reference 33

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local_arxiv, observed 2026-08-12T13:41:29.722847Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 47ec5b28-8d19-4540-835f-51b1c21bcdcc · outbound

This paper cites Transforming the Bootstrap: Using Transformers to Compute Scattering Amplitudes in Planar N = 4 Super Yang-Mills Theory.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Transforming the Bootstrap: Using Transformers to Compute Scattering Amplitudes in Planar N = 4 Super Yang-Mills Theory

Reference 34

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Observation 2e47661d-56d2-4838-afbb-824241aced4a · outbound

This paper cites Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE

Reference 35

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local_arxiv, observed 2026-08-12T13:41:29.703762Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 28c7f3bb-a6f4-4dcd-baf2-27175f8799fa · outbound

This paper cites Boundary Terms of the Einstein–Hilbert Action , pages 43–59.

Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments Boundary Terms of the Einstein–Hilbert Action , pages 43–59

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:41:29.794768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T13:41:29.678783Z digest=sha256:8a8535277051577fe90736db4fa912a327cc6a52d76637e42b68e4a3b2ccb872

Pith citing papers

Observation 54896d8b-3a91-4aab-86b4-78447192dbd6 · inbound

Heat and work in black hole thermodynamics via holography cites this paper.

Heat and work in black hole thermodynamics via holography Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-11T11:15:51.293779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:15:51.293779Z digest=sha256:6f3bd2d799a785565091da7fb4986685ae7cac1a085c782381672daa776e41a5

Observation 9299d2c5-c8cf-42bf-a16c-69113a97cbef · inbound

Probing bulk geometry via pole skipping: from static to rotating spacetimes cites this paper.

Probing bulk geometry via pole skipping: from static to rotating spacetimes Machine-learning emergent spacetime from linear response in future tabletop quantum gravity experiments

Reference 109

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:15:10.660844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T11:12:50.614044Z digest=sha256:8c8350e0293dc4be76b682070a4bfeba8fb126bcc12f0707b96b3ce9f8a994b4