Paper Citation Record · LEDGER

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood

As of 14 August 2026, this Paper Citation Record lists 100 of 122 outbound references and 5 inbound Pith citation observations for arXiv:2505.22743.

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

pith.paper-citation-record.v1
2505.22743 v2

Coverage vector

measured 100 of 122 reference resolution

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One-hop event checks from named stored sources.

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measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:24:24.520500Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T22:28:04.003147Z

Reference resolution

100 of 122 outbound references displayed

verified exact11
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External citation measurements

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Outbound references

Observation eb19e3af-246a-4949-802d-f32ba2780501 · outbound

This paper cites Quantum Pseudoentanglement.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Quantum Pseudoentanglement

Reference 1

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Observation 528761d0-395f-418e-9fa1-166a4dd42393 · outbound

This paper cites an unresolved cited work.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 2

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Observation 6196daee-3cd4-4df8-b295-c22bde235baf · outbound

This paper cites an unresolved cited work.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 3

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Observation 1d5cb685-23f5-4030-9bdb-bdd7c0f45b8d · outbound

This paper cites Quantum Algorithmic Measurement.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Quantum Algorithmic Measurement

Reference 4

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Observation 985e3837-17a3-4d34-ade3-aefe012c8892 · outbound

This paper cites 118, Cambridge University Press, 2010.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 118, Cambridge University Press, 2010

Reference 5

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Observation 338f2fd0-c7a8-4538-9d9e-f2ae02b86697 · outbound

This paper cites Sample-efficient learning of quantum many-body systems.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Sample-efficient learning of quantum many-body systems

Reference 6

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Observation 323ef44e-e31c-4066-8539-d2be48a34d9e · outbound

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 7

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Observation 9c37bfa7-f6a5-486b-8cec-bc2f3d980e29 · outbound

This paper cites Quantum statistical query learning.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Quantum statistical query learning

Reference 8

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 9

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 10

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Observation cbcf8698-ef68-4c20-a9ea-c2c811388288 · outbound

This paper cites Learning quantum Hamiltonians at any temperature in polynomial time.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Learning quantum Hamiltonians at any temperature in polynomial time

Reference 11

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Observation 5a2a3cee-5336-49f6-99de-ac2bac3d7130 · outbound

This paper cites Matrix Concentration Inequalities and Free Probability.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Matrix Concentration Inequalities and Free Probability

Reference 12

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Observation a5a09134-7ba7-4590-a8d3-29c6578ea926 · outbound

This paper cites 549–560, 2024.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 549–560, 2024

Reference 13

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Observation 355144f5-8e29-4de9-8b52-191fd6cbbd04 · outbound

This paper cites A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood A Nearly Tight Sum-of-Squares Lower Bound for the Planted Clique Problem

Reference 14

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Observation d83e893b-c9d5-44e0-98be-dd34ecafd76b · outbound

This paper cites 1046–1066, PMLR, 2013.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 1046–1066, PMLR, 2013

Reference 15

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Observation dc7eac2f-a2bd-45bb-a9fc-463acb4399ac · outbound

This paper cites 278–291, 1994.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 278–291, 1994

Reference 16

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Observation 5cefdcd3-4875-4bda-bbcb-02b226149eab · outbound

This paper cites Efficient Quantum Pseudorandomness from Hamiltonian Phase States.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Efficient Quantum Pseudorandomness from Hamiltonian Phase States

Reference 17

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Observation 2cdd9a5a-0be5-4a3e-b500-49ac06af069f · outbound

This paper cites Universality and sharp matrix concentration inequalities.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Universality and sharp matrix concentration inequalities

Reference 18

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Observation 1bc4d476-a5f2-4921-ac0b-8cfb8a639762 · outbound

This paper cites 619–635, Springer, 2019.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 619–635, Springer, 2019

Reference 19

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Observation 2cf28def-8681-442a-ba76-bbd6e69486b9 · outbound

This paper cites Local random quantum circuits are approximate polynomial-designs.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Local random quantum circuits are approximate polynomial-designs

Reference 20

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Observation efb13cb8-7c11-416e-9b5a-78c1f8ff5f96 · outbound

This paper cites 648–847, PMLR, 2020.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 648–847, PMLR, 2020

Reference 21

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Observation 3d5418a8-1ff2-4ee3-8ad5-517a2fa3f5d5 · outbound

This paper cites 48–166, PMLR, 2018.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 48–166, PMLR, 2018

Reference 22

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Observation f1d97f24-88a4-4850-b448-43b88c7f17b4 · outbound

This paper cites Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Statistical Query Algorithms and Low-Degree Tests Are Almost Equivalent

Reference 23

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This paper cites 5850–5889, PMLR, 2023.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 5850–5889, PMLR, 2023

Reference 24

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This paper cites Improved quantum data analysis.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Improved quantum data analysis

Reference 25

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Observation 2193ca07-2d09-4610-a150-f59e7457070a · outbound

This paper cites Entanglement is Necessary for Optimal Quantum Property Testing.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Entanglement is Necessary for Optimal Quantum Property Testing

Reference 26

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Observation 95af7dc7-ac67-40f6-836c-b1cb53cefcb6 · outbound

This paper cites The Quasi-Polynomial Low-Degree Conjecture is False.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood The Quasi-Polynomial Low-Degree Conjecture is False

Reference 27

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Observation c2427783-9508-4166-93d0-2203b7d91e75 · outbound

This paper cites 1193–1203, SIAM, 2014.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 1193–1203, SIAM, 2014

Reference 28

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Observation 56813590-7240-415c-b17d-7c67d073470d · outbound

This paper cites Sparse random Hamiltonians are quantumly easy.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Sparse random Hamiltonians are quantumly easy

Reference 29

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Observation 26e3b953-b642-4632-8fff-164e2cd615cf · outbound

This paper cites Incompressibility and spectral gaps of random circuits.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Incompressibility and spectral gaps of random circuits

Reference 30

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This paper cites Tight bounds on Pauli channel learning without entanglement.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Tight bounds on Pauli channel learning without entanglement

Reference 31

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Observation 4b836214-4939-4130-a41f-52009655b841 · outbound

This paper cites Exponential separations between learning with and without quantum memory.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Exponential separations between learning with and without quantum memory

Reference 32

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This paper cites The Complexity of NISQ.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood The Complexity of NISQ

Reference 33

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 34

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Reference 35

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Observation 711165b3-ea0e-40e8-a27f-574708581957 · outbound

This paper cites Optimal tradeoffs for estimating Pauli observables.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Optimal tradeoffs for estimating Pauli observables

Reference 36

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This paper cites Stabilizer bootstrapping: A recipe for efficient agnostic tomography and magic estimation.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Stabilizer bootstrapping: A recipe for efficient agnostic tomography and magic estimation

Reference 37

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Observation 957ed2aa-e800-4aad-9be1-81be0f93f92a · outbound

This paper cites When Does Adaptivity Help for Quantum State Learning?.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood When Does Adaptivity Help for Quantum State Learning?

Reference 38

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This paper cites Tight Bounds for Quantum State Certification with Incoherent Measurements.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Tight Bounds for Quantum State Certification with Incoherent Measurements

Reference 39

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Optimal high-precision shadow estimation

Reference 41

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood An optimal tradeoff between entanglement and copy complexity for state tomography

Reference 42

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 4764–4781, PMLR, 2022

Reference 43

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Efficient quantum state tomography

Reference 44

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Reference 45

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 4258–4282, PMLR, 2022

Reference 46

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 1514– 1539, PMLR, 2020

Reference 47

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Statistical Query Lower Bounds for Robust Estimation of High-dimensional Gaussians and Gaussian Mixtures

Reference 48

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Subexponential-Time Algorithms for Sparse PCA

Reference 49

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Reference 50

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This paper cites Statistical Algorithms and a Lower Bound for Detecting Planted Clique.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Statistical Algorithms and a Lower Bound for Detecting Planted Clique

Reference 51

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood On the Complexity of Random Satisfiability Problems with Planted Solutions

Reference 52

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 3587–3596, PMLR, 2020

Reference 53

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 54

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood On the sample complexity of purity and inner product estimation

Reference 55

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This paper cites Latorre, Arnau Riera, and Karol Życzkowski,Absolutely maximally entangled states, combinatorial designs, and multiunitary matrices, Phys.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Latorre, Arnau Riera, and Karol Życzkowski,Absolutely maximally entangled states, combinatorial designs, and multiunitary matrices, Phys

Reference 56

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Reference 57

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 58

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Observation 0b4734e7-cb5c-4653-a2da-f9992feac9fb · outbound

This paper cites 1352–1363, 2024, 2304.13915.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 1352–1363, 2024, 2304.13915

Reference 59

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Reference 60

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Simulating quantum chaos without chaos

Reference 61

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Sample-optimal tomography of quantum states

Reference 62

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This paper cites 135–146, IEEE, 2022, 2108.04842.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 135–146, IEEE, 2022, 2108.04842

Reference 63

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Random quantum circuits are approximate unitary $t$-designs in depth $O\left(nt^{5+o(1)}\right)$

Reference 64

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 899–928, PMLR, 2015

Reference 65

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood The Church of the Symmetric Subspace

Reference 66

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 67

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Aspects of generic entanglement

Reference 68

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood A single $T$-gate makes distribution learning hard

Reference 69

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Learnability of the output distributions of local quantum circuits

Reference 70

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Observation f9a5f0cc-79fb-4ce9-be66-2d50b298cdaf · outbound

This paper cites Counterexamples to the Low-Degree Conjecture.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Counterexamples to the Low-Degree Conjecture

Reference 71

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood thesis,CornellUniversity, 2018

Reference 72

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 720–731, IEEE, 2017

Reference 73

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 956–1006, PMLR, 2015

Reference 74

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Bayesian estimation from few samples: community detection and related problems

Reference 75

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 76

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Predicting Many Properties of a Quantum System from Very Few Measurements

Reference 77

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Information-theoretic bounds on quantum advantage in machine learning

Reference 78

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Learning shallow quantum circuits

Reference 79

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Gullans, Sarang Gopalakrishnan, David A

Reference 80

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 81

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 126–152, Springer, 2018

Reference 82

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 83

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This paper cites Learning State Preparation Circuits for Quantum Phases of Matter.

Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Learning State Preparation Circuits for Quantum Phases of Matter

Reference 84

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Triply efficient shadow tomography

Reference 85

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Notes on Computational Hardness of Hypothesis Testing: Predictions using the Low-Degree Likelihood Ratio

Reference 86

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Learning quantum states prepared by shallow circuits in polynomial time

Reference 87

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 511–515, IEEE, 2017

Reference 88

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 672–677, 2022

Reference 89

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood How to Construct Random Unitaries

Reference 90

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Learning $k$-body Hamiltonians via compressed sensing

Reference 91

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 92

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood 3798–3822, PMLR, 2024

Reference 93

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 94

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Learning stabilizer states by Bell sampling

Reference 95

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 96

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Improved algorithms for learning quantum Hamiltonians, via flat polynomials

Reference 97

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Unresolved cited work

Reference 98

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Quantum Spectrum Testing

Reference 99

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Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood Efficient quantum tomography

Reference 100

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Pith citing papers

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Computational Complexity of Statistics: New Insights from Low-Degree Polynomials cites this paper.

Computational Complexity of Statistics: New Insights from Low-Degree Polynomials Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood

Reference 11

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Instance-Optimal Matrix Multiplicative Weight Update and Its Quantum Applications cites this paper.

Instance-Optimal Matrix Multiplicative Weight Update and Its Quantum Applications Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood

Reference 31

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Efficient learning of bosonic Gaussian unitaries Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood

Reference 5

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Learning and Generating Mixed States Prepared by Shallow Channel Circuits cites this paper.

Learning and Generating Mixed States Prepared by Shallow Channel Circuits Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood

Reference 1

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Observation d918f0e4-cfe2-475f-a9ac-65732484aead · inbound

Learning and Generating Mixed States Prepared by Shallow Channel Circuits cites this paper.

Learning and Generating Mixed States Prepared by Shallow Channel Circuits Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood

Reference 1

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