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Paper Citation Record · LEDGER

Machine learning applications in cold atom quantum simulators

As of 19 August 2026, this Paper Citation Record lists 100 of 184 outbound references and 1 inbound Pith citation observation for arXiv:2509.08011.

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

pith.paper-citation-record.v1
2509.08011 v1

Coverage vector

measured 100 of 184 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:17:08.006379Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T18:08:27.633335Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T16:16:09.935247Z

Reference resolution

100 of 184 outbound references displayed

  • verified exact30
  • verified fuzzy0
  • unresolved70
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8643b6de-4a15-4d04-bcb7-adca7bf025ae · outbound

This paper cites Williams.

Machine learning applications in cold atom quantum simulators Williams

Reference 1

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Observation 55f0a2a4-b8ea-4e11-ac0b-03e1175993de · outbound

This paper cites Sample-efficient learning of interacting quantum systems.

Machine learning applications in cold atom quantum simulators Sample-efficient learning of interacting quantum systems

Reference 2

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Observation a20ebbf7-f011-4b9c-a677-bd4301414414 · outbound

This paper cites Replacing Neural Networks by Optimal Analytical Predictors for the Detection of Phase Transitions.

Machine learning applications in cold atom quantum simulators Replacing Neural Networks by Optimal Analytical Predictors for the Detection of Phase Transitions

Reference 3

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Observation 547061ea-65ef-4c98-9429-559ab1767695 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 4

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Observation 7761fbf3-f75b-490a-a14a-1a0f762ae967 · outbound

This paper cites Machine learning phase transitions: Connections to the Fisher information.

Machine learning applications in cold atom quantum simulators Machine learning phase transitions: Connections to the Fisher information

Reference 5

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Observation a4005e17-cc1d-4327-a36b-94a6ec53203b · outbound

This paper cites Fast Detection of Phase Transitions with Multi-Task Learning-by-Confusion.

Machine learning applications in cold atom quantum simulators Fast Detection of Phase Transitions with Multi-Task Learning-by-Confusion

Reference 6

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Observation afe5c6b4-10cd-4013-9588-cf9abc74dea3 · outbound

This paper cites Mapping Out Phase Diagrams with Generative Classifiers.

Machine learning applications in cold atom quantum simulators Mapping Out Phase Diagrams with Generative Classifiers

Reference 7

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Observation bb767aac-0db7-457c-bdd4-6cc7615f6752 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 8

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Observation ac250eb1-b783-48c4-9453-cf653f033af1 · outbound

This paper cites Applying machine learning optimization methods to the production of a quantum gas.

Machine learning applications in cold atom quantum simulators Applying machine learning optimization methods to the production of a quantum gas

Reference 9

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Observation 03d8d72f-b251-46cd-b2c0-4ee0b250791b · outbound

This paper cites An atom-by-atom assembler of defect-free arbitrary two-dimensional atomic arrays.

Machine learning applications in cold atom quantum simulators An atom-by-atom assembler of defect-free arbitrary two-dimensional atomic arrays

Reference 10

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Observation 02b5ffa4-b901-4422-947e-d01bd7f6ffa5 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 11

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Observation f1ff86f5-1c45-4a0c-8991-02b5b6953928 · outbound

This paper cites Robust quantum reservoir learning for molecular property prediction.

Machine learning applications in cold atom quantum simulators Robust quantum reservoir learning for molecular property prediction

Reference 12

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Observation fc3e915b-7c6a-4f00-8700-da0a90fbd3c7 · outbound

This paper cites Bennewitz, Florian Hopfmueller, Bohdan Kulchytskyy, Juan Carrasquilla, and Pooya Ronagh.

Machine learning applications in cold atom quantum simulators Bennewitz, Florian Hopfmueller, Bohdan Kulchytskyy, Juan Carrasquilla, and Pooya Ronagh

Reference 13

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Observation 5b75de9a-abf4-47a9-80aa-54fdb35e1402 · outbound

This paper cites Zibrov, Manuel Endres, Markus Greiner, Vladan Vuleti \'c , and Mikhail D.

Machine learning applications in cold atom quantum simulators Zibrov, Manuel Endres, Markus Greiner, Vladan Vuleti \'c , and Mikhail D

Reference 14

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Observation e3545641-fbfb-4db3-8c00-2d7c66cb0a1e · outbound

This paper cites Diagnosing quantum transport from wave function snapshots.

Machine learning applications in cold atom quantum simulators Diagnosing quantum transport from wave function snapshots

Reference 15

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Observation eeae2a9e-adf3-4ec4-a875-8bca2e7d62d6 · outbound

This paper cites Bayesian Optimization for Robust State Preparation in Quantum Many-Body Systems.

Machine learning applications in cold atom quantum simulators Bayesian Optimization for Robust State Preparation in Quantum Many-Body Systems

Reference 16

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Observation 3092af85-4edd-4214-9d9a-470613a4cd12 · outbound

This paper cites Many-body physics with ultracold gases.

Machine learning applications in cold atom quantum simulators Many-body physics with ultracold gases

Reference 17

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Observation d183bd31-81cd-4096-ad2d-774e63551e9c · outbound

This paper cites Quantum simulations with ultracold quantum gases.

Machine learning applications in cold atom quantum simulators Quantum simulations with ultracold quantum gases

Reference 18

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Observation 6a93e426-4a7d-49ef-852b-5bee1389627c · outbound

This paper cites Bluvstein, A.

Machine learning applications in cold atom quantum simulators Bluvstein, A

Reference 19

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Observation 8e733bb6-cf66-4bb7-b6b5-5166fb86feef · outbound

This paper cites Bohrdt, S.

Machine learning applications in cold atom quantum simulators Bohrdt, S

Reference 20

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Observation bddc982f-3335-4309-80cc-53f8fdc50ef7 · outbound

This paper cites Chiu, Geoffrey Ji, Muqing Xu, Daniel Greif, Markus Greiner, Eugene Demler, Fabian Grusdt, and Michael Knap.

Machine learning applications in cold atom quantum simulators Chiu, Geoffrey Ji, Muqing Xu, Daniel Greif, Markus Greiner, Eugene Demler, Fabian Grusdt, and Michael Knap

Reference 21

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Observation 7ddaa02d-b27a-47bc-92dc-5705b18b26b6 · outbound

This paper cites Exploration of doped quantum magnets with ultracold atoms.

Machine learning applications in cold atom quantum simulators Exploration of doped quantum magnets with ultracold atoms

Reference 22

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Observation 0aded364-f87a-4080-91c3-b1e248cb202a · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 23

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Observation 4210c6c0-a70a-41c0-a63a-43014eea9ebc · outbound

This paper cites Quantum phase recognition via unsupervised machine learning.

Machine learning applications in cold atom quantum simulators Quantum phase recognition via unsupervised machine learning

Reference 24

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Observation 11648c1e-97ab-4e8d-a205-2ae61d969b86 · outbound

This paper cites Melko, and Simon Trebst.

Machine learning applications in cold atom quantum simulators Melko, and Simon Trebst

Reference 25

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Observation a2f94899-cb22-4647-9695-4370ce9d91ae · outbound

This paper cites Lanyon, Peter Zoller, Rainer Blatt, and Christian F.

Machine learning applications in cold atom quantum simulators Lanyon, Peter Zoller, Rainer Blatt, and Christian F

Reference 26

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Observation f00c92db-caee-4899-9d32-f8e4254e89a0 · outbound

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Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 27

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Observation 09cde35a-b0f5-42cd-81d3-a1f99858f92b · outbound

This paper cites Intrinsic dimension estimation: Advances and open problems.

Machine learning applications in cold atom quantum simulators Intrinsic dimension estimation: Advances and open problems

Reference 28

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Observation 10662089-3409-47c6-bb0e-7ad2f570a771 · outbound

This paper cites Supervised learning in Hamiltonian reconstruction from local measurements on eigenstates.

Machine learning applications in cold atom quantum simulators Supervised learning in Hamiltonian reconstruction from local measurements on eigenstates

Reference 29

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation e9230808-60cc-41ce-b0fa-aeac332ff5a0 · outbound

This paper cites Solving the quantum many-body problem with artificial neural networks.

Machine learning applications in cold atom quantum simulators Solving the quantum many-body problem with artificial neural networks

Reference 30

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Observation 1f3c42e4-872d-4e35-b3af-2b3665cc38ad · outbound

This paper cites Machine learning and the physical sciences.

Machine learning applications in cold atom quantum simulators Machine learning and the physical sciences

Reference 31

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Observation c069be85-0211-4f93-81cf-66262ba58544 · outbound

This paper cites Theoretical and experimental perspectives of quantum verification.

Machine learning applications in cold atom quantum simulators Theoretical and experimental perspectives of quantum verification

Reference 32

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Observation c342cefd-2f9c-4c98-ac7c-a72faee8a19b · outbound

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Machine learning applications in cold atom quantum simulators Machine learning for quantum matter

Reference 33

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Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 34

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Observation f9d7612b-3b45-484d-b167-51ea86dbb2ad · outbound

This paper cites How To Use Neural Networks To Investigate Quantum Many-Body Physics.

Machine learning applications in cold atom quantum simulators How To Use Neural Networks To Investigate Quantum Many-Body Physics

Reference 35

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Observation 3244ff77-ee01-4cac-b6c5-a937306bbcb2 · outbound

This paper cites Carvalho, N.

Machine learning applications in cold atom quantum simulators Carvalho, N

Reference 36

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Observation 92fd2603-5793-4d66-8ff3-a6e367e260b9 · outbound

This paper cites Casert, T.

Machine learning applications in cold atom quantum simulators Casert, T

Reference 37

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Observation 4c01f62e-bde0-4f5c-bb3f-0d7737a148d7 · outbound

This paper cites Attention-based quantum tomography.

Machine learning applications in cold atom quantum simulators Attention-based quantum tomography

Reference 38

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Observation 699a30a9-9d7b-46b5-895e-c4ba9446dfe0 · outbound

This paper cites Recent progress on quantum simulations of non-standard Bose--Hubbard models.

Machine learning applications in cold atom quantum simulators Recent progress on quantum simulations of non-standard Bose--Hubbard models

Reference 39

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 21b1c22f-110e-477e-8552-4054906707ba · outbound

This paper cites Topological quantum phase transitions retrieved through unsupervised machine learning.

Machine learning applications in cold atom quantum simulators Topological quantum phase transitions retrieved through unsupervised machine learning

Reference 40

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source=arxiv_source observed=2026-08-15T16:17:07.658285Z digest=sha256:7df300a65085a98230b991159db88d99102107a19eb6ff0f7f644bf6c86d58b0

Observation 8ab6516f-7897-4326-acaf-ad040790c007 · outbound

This paper cites Liu, Pascal Scholl, Daniel Barredo, Johannes Hauschild, Shubhayu Chatterjee, Michael Schuler, Andreas M.

Machine learning applications in cold atom quantum simulators Liu, Pascal Scholl, Daniel Barredo, Johannes Hauschild, Shubhayu Chatterjee, Michael Schuler, Andreas M

Reference 41

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doi, observed 2026-08-15T16:18:31.036966Z

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source=arxiv_source observed=2026-08-15T16:17:07.664389Z digest=sha256:505604ec8786030df4c12bfe3e2e9109575b1dcdca3c73b655b60cc8247577fb

Observation d01bf123-4276-4937-8030-17ae1c4b6553 · outbound

This paper cites Cheuk, Matthew A.

Machine learning applications in cold atom quantum simulators Cheuk, Matthew A

Reference 42

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source=arxiv_source observed=2026-08-15T16:17:07.670097Z digest=sha256:5abebe6ad943c1f11a051d3038fdcc0aa73d3807ecb4b1c46a2480d248be22ce

Observation 5bebda59-3e92-4a14-a5b1-390707eb71f5 · outbound

This paper cites Chiu, Geoffrey Ji, Annabelle Bohrdt, Muqing Xu, Michael Knap, Eugene Demler, Fabian Grusdt, Markus Greiner, and Daniel Greif.

Machine learning applications in cold atom quantum simulators Chiu, Geoffrey Ji, Annabelle Bohrdt, Muqing Xu, Michael Knap, Eugene Demler, Fabian Grusdt, Markus Greiner, and Daniel Greif

Reference 43

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source=arxiv_source observed=2026-08-15T16:17:07.675680Z digest=sha256:ee7a07eb3e29d03698a637f38334a00758e853cb20b36d23fda67d97663ec2b3

Observation b5cf4626-4b4a-4de0-8400-19b10df297c6 · outbound

This paper cites Melko, and Ehsan Khatami.

Machine learning applications in cold atom quantum simulators Melko, and Ehsan Khatami

Reference 44

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source=arxiv_source observed=2026-08-15T16:17:07.680912Z digest=sha256:20f4d1d53dcfed41f2679a302d8440bb9073eeb3f80f10dd5ff8a6472391d3ff

Observation 8d1e7770-efa9-413c-a553-eaf2cbbe468d · outbound

This paper cites Unsupervised machine learning account of magnetic transitions in the Hubbard model.

Machine learning applications in cold atom quantum simulators Unsupervised machine learning account of magnetic transitions in the Hubbard model

Reference 45

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source=arxiv_source observed=2026-08-15T16:17:07.686874Z digest=sha256:b4a77de018d9713b50075928b71a62b4812abee0f5c5dee12bbcf8c09cfad690

Observation b1083411-e580-4cde-a45c-9c3a81078529 · outbound

This paper cites Machine learning identification of symmetrized base states of Rydberg atoms.

Machine learning applications in cold atom quantum simulators Machine learning identification of symmetrized base states of Rydberg atoms

Reference 46

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verified exact
doi, observed 2026-08-15T16:18:31.003655Z

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correction dated 2021-10-20. Source: crossref record 10.1007/s11467-021-1118-1->10.1007/s11467-021-1099-0:correction, observed 2026-07-11T03:13:12.022914+00:00. This notice travels one citation hop only.

source=arxiv_source observed=2026-08-15T16:17:07.692329Z digest=sha256:cc01fd82f30a84994c2d8230a2062d4b98b298a2ef87fe3cb88bb31108762c09

Observation 3ef3b531-89a7-4d28-b0e4-20ee6c099474 · outbound

This paper cites The Enigma of the Pseudogap Phase of the Cuprate Superconductors , pages 1--43.

Machine learning applications in cold atom quantum simulators The Enigma of the Pseudogap Phase of the Cuprate Superconductors , pages 1--43

Reference 47

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source=arxiv_source observed=2026-08-15T16:17:07.697346Z digest=sha256:f7274c3423802f52a36bcd63537907e8853e92587546c0e3d433be602c85a056

Observation 6aa2716c-2335-4572-8ead-9da924153f3b · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 48

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source=arxiv_source observed=2026-08-15T16:17:07.702638Z digest=sha256:9fb1ba52d6bd0999e18c2aad6d51e348412348f1fdccf9307dc6bafdc7b5f519

Observation fcc68ccc-1cde-4f9b-a2e5-ac227d8e9a12 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 49

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source=arxiv_source observed=2026-08-15T16:17:07.708375Z digest=sha256:dd6a197c3ab75ddfbab1de79cd7072a7e31aeeb25271c88150795dd0710e7ca4

Observation 7a2f9e35-0054-41a7-9712-4989d9ef9a93 · outbound

This paper cites Costa, Wenjian Hu, Z.

Machine learning applications in cold atom quantum simulators Costa, Wenjian Hu, Z

Reference 50

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no resolver link, observed 2026-08-15T16:17:07.714885Z

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source=arxiv_source observed=2026-08-15T16:17:07.714885Z digest=sha256:6f665262ddc1116a03214e0928de2a6b6eb098a239b64e44c814360115bc5b27

Observation 47bafba5-4bb8-48fe-961c-9667683f709b · outbound

This paper cites Speak so a physicist can understand you! TetrisCNN for detecting phase transitions and order parameters.

Machine learning applications in cold atom quantum simulators Speak so a physicist can understand you! TetrisCNN for detecting phase transitions and order parameters

Reference 51

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no resolver link, observed 2026-08-15T16:17:07.720348Z

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source=arxiv_source observed=2026-08-15T16:17:07.720348Z digest=sha256:7f105c64c861afc9664c350d89673d112eecc093573846bbf048bb66f78cbd87

Observation ee68155d-b722-4067-840f-6882aa51a361 · outbound

This paper cites Schuyler Moss, Matthew Radzihovsky, Ejaaz Merali, and Roger G.

Machine learning applications in cold atom quantum simulators Schuyler Moss, Matthew Radzihovsky, Ejaaz Merali, and Roger G

Reference 52

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.970610Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.726155Z digest=sha256:638d00e3fb37feefc0362c8db89ca056150228ccca351cec9cff3a814c18d131

Observation 6c7b9575-2029-4b52-be07-af8bea0fbbf1 · outbound

This paper cites Daley, Immanuel Bloch, Christian Kokail, Stuart Flannigan, Natalie Pearson, Matthias Troyer, and Peter Zoller.

Machine learning applications in cold atom quantum simulators Daley, Immanuel Bloch, Christian Kokail, Stuart Flannigan, Natalie Pearson, Matthias Troyer, and Peter Zoller

Reference 53

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no resolver link, observed 2026-08-15T16:17:07.732140Z

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source=arxiv_source observed=2026-08-15T16:17:07.732140Z digest=sha256:2df0a29ff3c6e412d8587dece516cef6b5dedd70d9d33012a549c49c1d486730

Observation 457bd528-d308-4e5a-94ae-6d66a0de0b81 · outbound

This paper cites Colloquium: Artificial gauge potentials for neutral atoms.

Machine learning applications in cold atom quantum simulators Colloquium: Artificial gauge potentials for neutral atoms

Reference 54

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no resolver link, observed 2026-08-15T16:17:07.737619Z

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source=arxiv_source observed=2026-08-15T16:17:07.737619Z digest=sha256:388238e32391d6fdaaac4d7d3a2a4e1bb335ca2cc5c0737e72de0b05f75638dd

Observation 781dc96a-cd34-4b91-9e4b-ebd2a527e68a · outbound

This paper cites Phase detection with neural networks: interpreting the black box.

Machine learning applications in cold atom quantum simulators Phase detection with neural networks: interpreting the black box

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-15T16:17:07.743041Z

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source=arxiv_source observed=2026-08-15T16:17:07.743041Z digest=sha256:bb10566b7b48b8f2e6bc0a2a4988f8eda36c7a64c123bb64c22f6e07365b6fff

Observation 175e654e-f105-48fa-966f-9cdeec795f9f · outbound

This paper cites Hessian-based toolbox for reliable and interpretable machine learning in physics.

Machine learning applications in cold atom quantum simulators Hessian-based toolbox for reliable and interpretable machine learning in physics

Reference 56

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.897383Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.748948Z digest=sha256:bb8f11aa69060ac1bb35c0b6eb007e293c77c4b83e627383a3b131956ddfd1e0

Observation a09c4a35-0fa5-4a98-953d-2abc5f83d3db · outbound

This paper cites Nicoli, Paolo Stornati, Rouven Koch, Miriam Büttner, Robert Okuła, Gorka Muñoz-Gil, Rodrigo A.

Machine learning applications in cold atom quantum simulators Nicoli, Paolo Stornati, Rouven Koch, Miriam Büttner, Robert Okuła, Gorka Muñoz-Gil, Rodrigo A

Reference 57

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no resolver link, observed 2026-08-15T16:17:07.754640Z

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source=arxiv_source observed=2026-08-15T16:17:07.754640Z digest=sha256:b5f3ede5f642ea9a0ec313c31ef5818f951774948d6733b29728c80146f28516

Observation 7f368689-64e1-4f81-ab8c-96b36beaa7ba · outbound

This paper cites Di Franco, M.

Machine learning applications in cold atom quantum simulators Di Franco, M

Reference 58

Resolution
verified exact
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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.760482Z digest=sha256:2f2c8af4ece009f4f555e6ee2db9f801a55ed59768f0bf143645d3fef2af6487

Observation fb6d7430-9ab6-493e-a212-9720ed646fa4 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 59

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no resolver link, observed 2026-08-15T16:17:07.768167Z

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source=arxiv_source observed=2026-08-15T16:17:07.768167Z digest=sha256:1fd7e758e4f4d9386f74693d9dba785773b2b6466fabadcff166f7bd0bea0c4f

Observation da5ca3ca-6082-4b26-bf8c-ef31d937a6fa · outbound

This paper cites Colloquium: Atomic quantum gases in periodically driven optical lattices.

Machine learning applications in cold atom quantum simulators Colloquium: Atomic quantum gases in periodically driven optical lattices

Reference 60

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no resolver link, observed 2026-08-15T16:17:07.774159Z

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source=arxiv_source observed=2026-08-15T16:17:07.774159Z digest=sha256:1b35a8bf414355123b749f6b015943e4b7581d83e9f92154fb6d12f47509c90e

Observation f7000afb-48d2-430d-841b-211842699ccc · outbound

This paper cites Mixed-state entanglement from local randomized measurements.

Machine learning applications in cold atom quantum simulators Mixed-state entanglement from local randomized measurements

Reference 61

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source=arxiv_source observed=2026-08-15T16:17:07.780703Z digest=sha256:7410a619051907689e392a0eed2236c0e90931e82e758b801e93072bf79fb5cf

Observation d51f0709-27ef-49d9-83cd-c3a65a427960 · outbound

This paper cites Endres, M.

Machine learning applications in cold atom quantum simulators Endres, M

Reference 62

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source=arxiv_source observed=2026-08-15T16:17:07.787276Z digest=sha256:139c3712a02a52e71ba3cd798ce7ea75983866437674811e6d54fd1deefd4190

Observation 941f6f47-cc81-45b2-acf4-5be94c38448f · outbound

This paper cites Anschuetz, Alexandre Krajenbrink, Crystal Senko, Vladan Vuletic, Markus Greiner, and Mikhail D.

Machine learning applications in cold atom quantum simulators Anschuetz, Alexandre Krajenbrink, Crystal Senko, Vladan Vuletic, Markus Greiner, and Mikhail D

Reference 63

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no resolver link, observed 2026-08-15T16:17:07.793642Z

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source=arxiv_source observed=2026-08-15T16:17:07.793642Z digest=sha256:b6248a0bb96e523c0329381ae88b226ca85a6a8f44ec3cf1b87eab6fbc33afd7

Observation 27ec08f0-4909-4522-8938-91bc23d35e33 · outbound

This paper cites Fermi-Hubbard Physics with Atoms in an Optical Lattice.

Machine learning applications in cold atom quantum simulators Fermi-Hubbard Physics with Atoms in an Optical Lattice

Reference 64

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.660661Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.799310Z digest=sha256:3bb79859aa033eb445ffbfef27e137efe0b8439cccd56a65f483753ebfe8ae25

Observation 7a680bab-1c8c-4437-9ec9-a15916f41e97 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 65

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.650797Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.804647Z digest=sha256:5281ec83e29906a92d8db7aa0961f228c1c3d9a6e8f3f174c675a8f0ff6044e4

Observation 0ac1fac1-f66f-4003-b7a1-6d680703917c · outbound

This paper cites Sengupta, and Subir Sachdev.

Machine learning applications in cold atom quantum simulators Sengupta, and Subir Sachdev

Reference 66

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source=arxiv_source observed=2026-08-15T16:17:07.810290Z digest=sha256:41f50f34cba082bff2d434cdf6a54863b5b7ba2c71bf79192a1608deff64691e

Observation 57245483-b205-4a63-bcd8-7b45fb946da9 · outbound

This paper cites RydbergGPT.

Machine learning applications in cold atom quantum simulators RydbergGPT

Reference 67

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no resolver link, observed 2026-08-15T16:17:07.815758Z

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source=arxiv_source observed=2026-08-15T16:17:07.815758Z digest=sha256:d73a0fed5e0ef5d904c4af50ca4909c68516531f9a3fdc487049a3210927d09e

Observation 758c84d0-7f1d-482f-8609-0b581cbb5f9a · outbound

This paper cites Harnessing Disordered-Ensemble Quantum Dynamics for Machine Learning.

Machine learning applications in cold atom quantum simulators Harnessing Disordered-Ensemble Quantum Dynamics for Machine Learning

Reference 68

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no resolver link, observed 2026-08-15T16:17:07.821119Z

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source=arxiv_source observed=2026-08-15T16:17:07.821119Z digest=sha256:ee18f64c10087a74f75490925c9fe54e5a81e65d38f61c5cf8883d9b301e9a66

Observation 003bffb8-de3e-4f0b-b525-b94585969cea · outbound

This paper cites Quantum Reservoir Computing: A Reservoir Approach Toward Quantum Machine Learning on Near-Term Quantum Devices , pages 423--450.

Machine learning applications in cold atom quantum simulators Quantum Reservoir Computing: A Reservoir Approach Toward Quantum Machine Learning on Near-Term Quantum Devices , pages 423--450

Reference 69

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unresolved
no resolver link, observed 2026-08-15T16:17:07.826623Z

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source=arxiv_source observed=2026-08-15T16:17:07.826623Z digest=sha256:09d484c26c9505ff9595ca522b6249ab289bed70d78bae50475356441e9e0bd0

Observation 6843c4f5-3ee2-40cb-bc63-2bfbd220e748 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 70

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.621686Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.832005Z digest=sha256:dff710f9c63dc1ce18b543d83cfbba63ad5326a632d59535812a2d1f69437168

Observation a5cdf396-9456-4bf8-9d7f-adfc09c01297 · outbound

This paper cites Probing hidden spin order with interpretable machine learning.

Machine learning applications in cold atom quantum simulators Probing hidden spin order with interpretable machine learning

Reference 71

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.611312Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.837487Z digest=sha256:962640d8da2a73fb10bd1e1d864ea496b88eed78a0558fc01f0803913fbcbeab

Observation 1fe4d917-31dd-4361-aca8-b58fcf6a5f7d · outbound

This paper cites The view of TK-SVM on the phase hierarchy in the classical kagome Heisenberg antiferromagnet.

Machine learning applications in cold atom quantum simulators The view of TK-SVM on the phase hierarchy in the classical kagome Heisenberg antiferromagnet

Reference 72

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.601360Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.843815Z digest=sha256:feb7d81d2bd5035692715b824cbdd8b600b2a3bfe7823bac5c0579eb41b6b52d

Observation e94bf709-18f7-45b8-aeb6-32b8fb49d8b9 · outbound

This paper cites a fer, Niels L \.

Machine learning applications in cold atom quantum simulators a fer, Niels L \

Reference 73

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no resolver link, observed 2026-08-15T16:17:07.849590Z

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source=arxiv_source observed=2026-08-15T16:17:07.849590Z digest=sha256:2f821f0b7ecf8d9fcd8dabe38cae85f3b61d08503b7d112caf1cc95574c37c68

Observation e06be324-1bb3-44a3-9984-a648c4ecd699 · outbound

This paper cites Quantum simulations with ultracold atoms in optical lattices.

Machine learning applications in cold atom quantum simulators Quantum simulations with ultracold atoms in optical lattices

Reference 74

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source=arxiv_source observed=2026-08-15T16:17:07.854936Z digest=sha256:88ca961ef5a9484ed5cf6fba5ead680bafb4d92992abc72e50afdb7c214b48b4

Observation 60a1d1ed-5616-44d0-ab15-58985edf4677 · outbound

This paper cites Learning phase transitions from regression uncertainty: a new regression-based machine learning approach for automated detection of phases of matter.

Machine learning applications in cold atom quantum simulators Learning phase transitions from regression uncertainty: a new regression-based machine learning approach for automated detection of phases of matter

Reference 75

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.467064Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.860398Z digest=sha256:83d0978812422897f79d22e5d05d4f01adc61df9c4fcf40c05ac7b4a59774206

Observation 9bf4369d-9066-46f4-bee4-285173fb3f8a · outbound

This paper cites Cotta, Bruno Peaudecerf, Graham D.

Machine learning applications in cold atom quantum simulators Cotta, Bruno Peaudecerf, Graham D

Reference 76

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no resolver link, observed 2026-08-15T16:17:07.866324Z

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source=arxiv_source observed=2026-08-15T16:17:07.866324Z digest=sha256:f2c293c25dd9270cb39d72d76197be1c05b0a958d3548bab581d73b824099d26

Observation 4d778221-7222-45d3-8fb3-840ef2854639 · outbound

This paper cites Hilker, Guillaume Salomon, Fabian Grusdt, Ahmed Omran, Martin Boll, Eugene Demler, Immanuel Bloch, and Christian Gross.

Machine learning applications in cold atom quantum simulators Hilker, Guillaume Salomon, Fabian Grusdt, Ahmed Omran, Martin Boll, Eugene Demler, Immanuel Bloch, and Christian Gross

Reference 77

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no resolver link, observed 2026-08-15T16:17:07.872101Z

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source=arxiv_source observed=2026-08-15T16:17:07.872101Z digest=sha256:208fb6a6bad55c0fed2da1190f8bfe7d27ae480d724abb1e1637b0765f2ea6ef

Observation 3628d6b6-d095-4501-add4-187a3125b4c7 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 78

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verified exact
doi, observed 2026-08-15T16:18:30.363618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.877686Z digest=sha256:32ac3bf1434982ec6df32e953c58ec513c1eabeed7b45eb948a500b267061857

Observation ab2f2b3c-a9ca-4d9b-8048-a040bcb80972 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 79

Resolution
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no resolver link, observed 2026-08-15T16:17:07.883400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:17:07.883400Z digest=sha256:ffd7b7f5328e5e269ce8964b07562a4b93f70ef69a126d846d40159b1666e947

Observation 27a2d03d-862e-4852-9147-b330404aad94 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-15T16:17:07.889117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:17:07.889117Z digest=sha256:5c3a7a997b6a0ab50b0d00fcac0fee3a4c5fd3d1cfbe4e37eafa8c8c0ceed5df

Observation c86029ae-6e06-4f08-8a8d-7b4791e0cef4 · outbound

This paper cites Albert, and John Preskill.

Machine learning applications in cold atom quantum simulators Albert, and John Preskill

Reference 81

Resolution
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no resolver link, observed 2026-08-15T16:17:07.894542Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T16:17:07.894542Z digest=sha256:9d9913d5c53525e93a0438fd918cb0e5175e0e942e2d287856fb152382e4ed81

Observation f859a1db-2f6d-4ab2-9dfd-5aaf895d7f1d · outbound

This paper cites Identifying quantum phase transitions with adversarial neural networks.

Machine learning applications in cold atom quantum simulators Identifying quantum phase transitions with adversarial neural networks

Reference 82

Resolution
unresolved
no resolver link, observed 2026-08-15T16:17:07.900188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:17:07.900188Z digest=sha256:05d8293c35d9df21fca51a91fbfe79846c4798f2ff707eacf3786c947347c470

Observation 77bfbccd-44df-4c3d-9508-ff10e1eac149 · outbound

This paper cites Scalettar, and Ehsan Khatami.

Machine learning applications in cold atom quantum simulators Scalettar, and Ehsan Khatami

Reference 83

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.285091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.906443Z digest=sha256:44e710e42703738358b23a0b47486e19ed9f57c97fe61c72f0786e34242241a1

Observation 4cc8f985-e559-46ae-83a1-7986ef1afe20 · outbound

This paper cites Wienand, Sophie Häfele, Hendrik von Raven, Scott Hubele, Till Klostermann, Cesar R.

Machine learning applications in cold atom quantum simulators Wienand, Sophie Häfele, Hendrik von Raven, Scott Hubele, Till Klostermann, Cesar R

Reference 84

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.272925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.912030Z digest=sha256:553376b3e4671923c4fa57916a213815605c832c1655f5f14486738e97567841

Observation b59eae83-c450-44b1-933c-c4bdabda3eef · outbound

This paper cites Preiss, M.

Machine learning applications in cold atom quantum simulators Preiss, M

Reference 85

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no resolver link, observed 2026-08-15T16:17:07.917673Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T16:17:07.917673Z digest=sha256:38f70293dabac64c333541c06e2e8af47e1dbf7ef7d36bebb3fa4f71c2860220

Observation 0ad63d43-c18b-4ed6-96b6-35aab38eb25f · outbound

This paper cites A perspective on machine learning and data science for strongly correlated electron problems.

Machine learning applications in cold atom quantum simulators A perspective on machine learning and data science for strongly correlated electron problems

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-15T16:17:07.923616Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T16:17:07.923616Z digest=sha256:860d00c206da4282af9b25e9f64e16e98ece509c61efb25503cc19364b449b4a

Observation 88d4005d-a21d-472d-9a1a-fd80c0cd7fc4 · outbound

This paper cites Joshi, Christian Kokail, Rick van Bijnen, Florian Kranzl, Torsten V.

Machine learning applications in cold atom quantum simulators Joshi, Christian Kokail, Rick van Bijnen, Florian Kranzl, Torsten V

Reference 87

Resolution
unresolved
no resolver link, observed 2026-08-15T16:17:07.931521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:17:07.931521Z digest=sha256:f8ee23e1c67f0173b39b000b23800f9c5a502a700b1818c50830a65a859e4119

Observation f81fd1f9-8890-47b5-9442-62c0f24b4072 · outbound

This paper cites Unsupervised machine learning of topological phase transitions from experimental data.

Machine learning applications in cold atom quantum simulators Unsupervised machine learning of topological phase transitions from experimental data

Reference 88

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.245754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.936947Z digest=sha256:8775ebe2083fe92ff0839f2048f5532a099e0ebcae5e968c34f870c0dafec507

Observation c571a368-0119-431d-86fa-99b58e62df00 · outbound

This paper cites Phase transition encoded in neural network.

Machine learning applications in cold atom quantum simulators Phase transition encoded in neural network

Reference 89

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.234516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.942274Z digest=sha256:f0aed588e49290098f560c12c78fa38435032fdb7e0efbeda60cde3a691bbf49

Observation 90b79be4-e95e-4d63-ad3f-40414c795cd2 · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 90

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unresolved
no resolver link, observed 2026-08-15T16:17:07.948175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:17:07.948175Z digest=sha256:0d1ee240ddfdf76b604f91753b4479946fcd09b10895921bfa5500e7fcb0e5bd

Observation 4fb7e072-9d7b-440b-baac-2a531cfa62cf · outbound

This paper cites Spar, Juan Felipe Carrasquilla, Waseem S.

Machine learning applications in cold atom quantum simulators Spar, Juan Felipe Carrasquilla, Waseem S

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-15T16:17:07.954004Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T16:17:07.954004Z digest=sha256:26dabc34903df10fd5415a24016bbfd06468eeb05018d615ad0168094ec67ca5

Observation 4f4a7c06-7564-4e8c-bfe4-2b11122eb99c · outbound

This paper cites Smallest neural network to learn the Ising criticality.

Machine learning applications in cold atom quantum simulators Smallest neural network to learn the Ising criticality

Reference 92

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.112372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.959812Z digest=sha256:34681dd442d30b589012cd9cce1e08eb217d8458efd644545739b0a94b553284

Observation d65997ac-1b4c-45d5-b762-b2b69f25336f · outbound

This paper cites Zache, Andreas Elben, Benot Vermersch, Marcello Dalmonte, Rick van Bijnen, and Peter Zoller.

Machine learning applications in cold atom quantum simulators Zache, Andreas Elben, Benot Vermersch, Marcello Dalmonte, Rick van Bijnen, and Peter Zoller

Reference 93

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.050825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.965280Z digest=sha256:abe6039dcdc5238416c371b46f15a691167870e587c81f57970be2580f70e3d6

Observation 34517751-020e-4476-af62-5ab01d6ba9e6 · outbound

This paper cites Entanglement hamiltonian tomography in quantum simulation.

Machine learning applications in cold atom quantum simulators Entanglement hamiltonian tomography in quantum simulation

Reference 94

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.038857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.971672Z digest=sha256:ec7977c18aba5cacaff50509234009900b58e80f284adcb8304386f30e5492f6

Observation b60d22a5-4d53-4e62-ac77-16d7c5663e77 · outbound

This paper cites Large-scale quantum reservoir learning with an analog quantum computer.

Machine learning applications in cold atom quantum simulators Large-scale quantum reservoir learning with an analog quantum computer

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-15T16:17:07.978011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:17:07.978011Z digest=sha256:d13903c5066d1763f0316387a153c38f506d98667d8deb3433c5bde94190266d

Observation 7e99b227-560e-4d08-bae7-b10c3b90ea00 · outbound

This paper cites Unsupervised Phase Discovery with Deep Anomaly Detection.

Machine learning applications in cold atom quantum simulators Unsupervised Phase Discovery with Deep Anomaly Detection

Reference 96

Resolution
verified exact
doi, observed 2026-08-15T16:18:30.026914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.983708Z digest=sha256:13525e0227e727cb3e35b9983fcad4133c5f74e4de41c8e6833bc3e9ad8aa90d

Observation b6af2e24-c1a7-4e4a-8baf-4f306f35f43c · outbound

This paper cites Automated Search for new Quantum Experiments.

Machine learning applications in cold atom quantum simulators Automated Search for new Quantum Experiments

Reference 97

Resolution
verified exact
doi, observed 2026-08-15T16:18:29.998233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.989266Z digest=sha256:b2ca27ec5771fc28671a8fa7426b355215f6f619460e78d2f39d0e6f3b2a2267

Observation 946f6dfd-341c-417f-a87c-1cc4c22580fb · outbound

This paper cites an unresolved cited work.

Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 98

Resolution
verified exact
doi, observed 2026-08-15T16:17:09.790679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:07.995190Z digest=sha256:ada1faa220c082c8527fb6735db73a4cb177920485bf0721d6d3aeb03f2cef8f

Observation eeb6417c-9473-4e54-98fc-4d1851e5e3c8 · outbound

This paper cites Adaptive Q uantum S tate T omography with A ctive L earning.

Machine learning applications in cold atom quantum simulators Adaptive Q uantum S tate T omography with A ctive L earning

Reference 99

Resolution
verified exact
doi, observed 2026-08-15T16:17:09.773674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-15T16:17:08.000715Z digest=sha256:8e9d030f5e0900f63b400685a64323f4061a0c946eaab3efc2d40da85df1f27c

Observation 49c6ba3a-0f2a-43e3-8516-b95de3802469 · outbound

This paper cites From architectures to applications: a review of neural quantum states.

Machine learning applications in cold atom quantum simulators From architectures to applications: a review of neural quantum states

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-15T16:17:08.006379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:17:08.006379Z digest=sha256:af75f7fd42cc15e5e9eb290b4caa5240794b021c3001414b0d5006f8cb113f8f

Pith citing papers

Observation 6b50552f-16a2-4daa-bed6-47711cfd8354 · inbound

Model-agnostic cooling algorithms for strongly interacting fermions cites this paper.

Model-agnostic cooling algorithms for strongly interacting fermions Machine learning applications in cold atom quantum simulators

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:16:09.940306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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