Machine learning applications in cold atom quantum simulators | Paper Citation Record

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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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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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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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

Resolution: verified exact; doi, observed 2026-08-15T16:18:31.237678Z

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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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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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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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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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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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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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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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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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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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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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This paper cites Machine learning for quantum matter.

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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This paper cites Carvalho, N.

Machine learning applications in cold atom quantum simulators Carvalho, N

Reference 36

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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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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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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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This paper cites Cheuk, Matthew A.

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

Reference 42

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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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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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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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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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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.

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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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Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 48

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Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 49

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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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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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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

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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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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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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

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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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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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This paper cites Di Franco, M.

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

Reference 58

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

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Machine learning applications in cold atom quantum simulators Unresolved cited work

Reference 59

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

This paper cites Endres, M.

Machine learning applications in cold atom quantum simulators Endres, M

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-15T16:17:07.787276Z

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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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-15T16:17:07.810290Z

Source-reported events for the cited work

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

This paper cites RydbergGPT.

Machine learning applications in cold atom quantum simulators RydbergGPT

Reference 67

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

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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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: unresolved; no resolver link, observed 2026-08-15T16:17:07.854936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: 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 2026-08-16T06:30:59.297886+00:00.

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

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

This paper cites Preiss, M.

Machine learning applications in cold atom quantum simulators Preiss, M

Reference 85

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Unavailable: canonical work link unavailable.

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.

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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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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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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

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.

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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

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 2026-08-16T06:30:59.297886+00:00.

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

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