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Paper Citation Record · LEDGER

Classifying single-qubit noise using machine learning

As of 16 August 2026, this Paper Citation Record lists 100 of 113 outbound references and 0 inbound Pith citation observations for arXiv:1908.11762.

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

pith.paper-citation-record.v1
1908.11762 v1

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measured 100 of 113 reference resolution

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measured 100 of 100 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

100 of 113 outbound references displayed

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  • verified fuzzy16
  • unresolved70
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

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Outbound references

Observation 8eb09f80-413f-4395-9c30-f56ce8d88555 · outbound

This paper cites Are the gate errors coherent or stochastic?.

Classifying single-qubit noise using machine learning Are the gate errors coherent or stochastic?

Reference 1

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Observation 9a8358cb-edff-4e07-9ad7-304081486594 · outbound

This paper cites coherent vs. stochastic.

Classifying single-qubit noise using machine learning coherent vs. stochastic

Reference 2

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Observation d5debbaa-af16-47f7-b6e6-57560d7cf8c1 · outbound

This paper cites The em- bedding is described by a feature map, φ, mapping each QCVV data setD to a feature vector f (i.e.,φ :D→ f∈ F).

Classifying single-qubit noise using machine learning The em- bedding is described by a feature map, φ, mapping each QCVV data setD to a feature vector f (i.e.,φ :D→ f∈ F)

Reference 3

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Observation a56c1cf4-112d-4e77-8d6f-3e20ce92ea4a · outbound

This paper cites For example, properties that are categorical would re- quire classification algorithms, whereas properties that are continuous would require regression algorithms.

Classifying single-qubit noise using machine learning For example, properties that are categorical would re- quire classification algorithms, whereas properties that are continuous would require regression algorithms

Reference 4

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Observation adc2cc5d-7362-4220-9617-e13336c0ddf4 · outbound

This paper cites It measures the quality of fθ’s predictions.

Classifying single-qubit noise using machine learning It measures the quality of fθ’s predictions

Reference 5

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Observation dc82953c-d32f-4ff0-a039-ca80fda11936 · outbound

This paper cites In simple cases the hyperparameters can be specified a priori.

Classifying single-qubit noise using machine learning In simple cases the hyperparameters can be specified a priori

Reference 6

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This paper cites Estimate the coherence of noise.

Classifying single-qubit noise using machine learning Estimate the coherence of noise

Reference 7

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Observation 874debbb-e1d9-4599-babe-3e1dc38c710d · outbound

This paper cites L =l GST feature vector.

Classifying single-qubit noise using machine learning L =l GST feature vector

Reference 8

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Observation eb5eb9e7-d1f6-4c82-863a-6d0655d4487b · outbound

This paper cites Given a collection of feature vectors C = {(fj,yj)}N j=1, with yj ∈ {±1} indicating which class the feature vector fj∈F belongs to, learn a classifier c :F→{± 1}.

Classifying single-qubit noise using machine learning Given a collection of feature vectors C = {(fj,yj)}N j=1, with yj ∈ {±1} indicating which class the feature vector fj∈F belongs to, learn a classifier c :F→{± 1}

Reference 9

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Observation 97f8e03d-78e6-4324-848b-5435b3e7ac1a · outbound

This paper cites 0/1 loss.

Classifying single-qubit noise using machine learning 0/1 loss

Reference 10

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Observation 38bc39e5-494f-4fbb-984b-8f5ec3b64442 · outbound

This paper cites For each algorithm, we performed hyperparameter tuning using brute-force grid search over the values listed in Table II; see Appendix C for details.

Classifying single-qubit noise using machine learning For each algorithm, we performed hyperparameter tuning using brute-force grid search over the values listed in Table II; see Appendix C for details

Reference 11

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Observation c7b792c3-62a7-4cfe-b4ec-a9c76ffa20c5 · outbound

This paper cites stochas- tic.

Classifying single-qubit noise using machine learning stochas- tic

Reference 12

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Observation af13dce3-cfba-4386-8387-b959ba4c7da4 · outbound

This paper cites linear GST.

Classifying single-qubit noise using machine learning linear GST

Reference 13

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This paper cites uninformative.

Classifying single-qubit noise using machine learning uninformative

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This paper cites Hero test.

Classifying single-qubit noise using machine learning Hero test

Reference 15

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Observation d846b45b-197a-4590-81cf-484c917e2729 · outbound

This paper cites Quantum Computing in the NISQ era and beyond.

Classifying single-qubit noise using machine learning Quantum Computing in the NISQ era and beyond

Reference 16

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Observation 2855b13f-3063-4d37-98b1-c86a1a3cc03b · outbound

This paper cites A Preview of Bristlecone, Google’s New Quan- tum Processor,.

Classifying single-qubit noise using machine learning A Preview of Bristlecone, Google’s New Quan- tum Processor,

Reference 17

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Observation 111fb4de-b373-4c20-b79e-d913c0af6f0d · outbound

This paper cites IBM Announces Advances to IBM Quantum Sys- tems & Ecosystem,.

Classifying single-qubit noise using machine learning IBM Announces Advances to IBM Quantum Sys- tems & Ecosystem,

Reference 18

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Observation cafa1954-1e7a-496e-951c-4dbc271b6b9e · outbound

This paper cites Benchmarking an 11-qubit quantum computer.

Classifying single-qubit noise using machine learning Benchmarking an 11-qubit quantum computer

Reference 19

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Observation 5f0d878a-93ca-48a0-b057-ec67c61595bc · outbound

This paper cites Unsupervised Machine Learning on Rigetti 19Q with Forest 1.2,.

Classifying single-qubit noise using machine learning Unsupervised Machine Learning on Rigetti 19Q with Forest 1.2,

Reference 20

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Observation 779dc01a-9688-4698-8832-7fc9870e8ff2 · outbound

This paper cites Robust, self-consistent, closed-form tomography of quantum logic gates on a trapped ion qubit.

Classifying single-qubit noise using machine learning Robust, self-consistent, closed-form tomography of quantum logic gates on a trapped ion qubit

Reference 21

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Observation b8214921-ad4a-4938-aad1-a60272b7fe4c · outbound

This paper cites Magesan, J.

Classifying single-qubit noise using machine learning Magesan, J

Reference 22

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This paper cites Robust randomized benchmarking of quantum processes.

Classifying single-qubit noise using machine learning Robust randomized benchmarking of quantum processes

Reference 23

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This paper cites Validating quantum computers using randomized model circuits.

Classifying single-qubit noise using machine learning Validating quantum computers using randomized model circuits

Reference 24

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Observation 26541d51-8404-464f-bc9b-c3d6a837e8c0 · outbound

This paper cites A volumetric framework for quantum computer benchmarks.

Classifying single-qubit noise using machine learning A volumetric framework for quantum computer benchmarks

Reference 25

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Classifying single-qubit noise using machine learning Unresolved cited work

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This paper cites Hastie, R.

Classifying single-qubit noise using machine learning Hastie, R

Reference 27

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Observation e86a517c-b8f4-4779-acc8-57c8975beb46 · outbound

This paper cites Goodfellow, Y.

Classifying single-qubit noise using machine learning Goodfellow, Y

Reference 28

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Classifying single-qubit noise using machine learning James, D

Reference 29

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Classifying single-qubit noise using machine learning Quantum Recommendation Systems

Reference 30

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Classifying single-qubit noise using machine learning Unresolved cited work

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This paper cites Wasserman, All of Statistics: A Concise Course in Statistical Inference (Springer New York, 2004).

Classifying single-qubit noise using machine learning Wasserman, All of Statistics: A Concise Course in Statistical Inference (Springer New York, 2004)

Reference 32

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Classifying single-qubit noise using machine learning Unresolved cited work

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Classifying single-qubit noise using machine learning Unresolved cited work

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Classifying single-qubit noise using machine learning Unresolved cited work

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Classifying single-qubit noise using machine learning Farley and W

Reference 36

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Classifying single-qubit noise using machine learning Unresolved cited work

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This paper cites Estimating the Coherence of Noise.

Classifying single-qubit noise using machine learning Estimating the Coherence of Noise

Reference 38

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Observation e4d1109d-a84a-4c77-8bf0-c0444dc6aecc · outbound

This paper cites Estimating the coherence of noise in quantum control of a solid-state qubit.

Classifying single-qubit noise using machine learning Estimating the coherence of noise in quantum control of a solid-state qubit

Reference 39

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Observation 76ddb7e0-e007-4b21-9d44-78c5137fbea9 · outbound

This paper cites An introduction to quantum machine learning.

Classifying single-qubit noise using machine learning An introduction to quantum machine learning

Reference 40

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source=pdf_text observed=2026-08-14T10:13:15.376358Z digest=sha256:e80b2bfbe820770f0ac57041b83e110f6b13218c4d22d5f9952476f5ce00ad22

Observation 4ce930c3-0c32-498b-a51d-bf5974d86ca4 · outbound

This paper cites Quantum Machine Learning.

Classifying single-qubit noise using machine learning Quantum Machine Learning

Reference 41

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source=pdf_text observed=2026-08-14T10:13:15.380576Z digest=sha256:0bf2c6eadeae342fcce636b4fb4fecbdc22aaa5d2fba15599b6e04aed3f11016

Observation 78321069-b3e6-4671-915c-b3dcf9e1342f · outbound

This paper cites Papers - Physics & Machine Learning,.

Classifying single-qubit noise using machine learning Papers - Physics & Machine Learning,

Reference 42

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source=pdf_text observed=2026-08-14T10:13:15.385208Z digest=sha256:a4c25b83b9d46437627f4ee1fc19dd341da321f2f2f469139f6390412a5c2132

Observation fcc5c7b0-5263-4c97-91e9-e7ad89a73952 · outbound

This paper cites Dunjko and H.

Classifying single-qubit noise using machine learning Dunjko and H

Reference 43

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source=pdf_text observed=2026-08-14T10:13:15.389476Z digest=sha256:4258da1f07f8e153a4431f37fbdc6e269e9e3853879b85a9cff2d0819b1c87fc

Observation 5756eede-b2b8-4b6e-a063-1e33cf164fce · outbound

This paper cites Quantum algorithm for solving linear systems of equations.

Classifying single-qubit noise using machine learning Quantum algorithm for solving linear systems of equations

Reference 44

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source=pdf_text observed=2026-08-14T10:13:15.397000Z digest=sha256:1ce7290e6b021f61b30b877e6863d8da8dc4fa006f203f3abbf0c3be9f03ae2d

Observation 3a6b13e4-9588-4bbb-a09e-47020740ba04 · outbound

This paper cites Torlai, G.

Classifying single-qubit noise using machine learning Torlai, G

Reference 45

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source=pdf_text observed=2026-08-14T10:13:15.472799Z digest=sha256:814df80975f72f311dfcae7d83acdab5e5fce975baa1ae77f8a797bb05299a24

Observation d26cbd65-0241-4fba-86fd-4499359c1d88 · outbound

This paper cites Tang, arXiv (2019), 10.1145/3313276.3316310, arXiv:arXiv:1807.04271v3.

Classifying single-qubit noise using machine learning Tang, arXiv (2019), 10.1145/3313276.3316310, arXiv:arXiv:1807.04271v3

Reference 46

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source=pdf_text observed=2026-08-14T10:13:15.405435Z digest=sha256:4a6f3e71075e4d92d3ac17c5978b944fefe72e05ce851b8ae635a5b0834679ba

Observation 3dc09641-c48a-4d00-861b-958bbff5fdd9 · outbound

This paper cites Quantum principal component analysis only achieves an exponential speedup because of its state preparation assumptions.

Classifying single-qubit noise using machine learning Quantum principal component analysis only achieves an exponential speedup because of its state preparation assumptions

Reference 47

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source=pdf_text observed=2026-08-14T10:13:15.410091Z digest=sha256:0313e4cb0af4acbd08d8b6525230f2d6aab0298304764283d4fcddcdfc856323

Observation 40f737bf-26dc-49a5-bc12-61e8b61ae47e · outbound

This paper cites Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension.

Classifying single-qubit noise using machine learning Quantum-inspired low-rank stochastic regression with logarithmic dependence on the dimension

Reference 48

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source=pdf_text observed=2026-08-14T10:13:15.415562Z digest=sha256:782ddf305788a0fc1516b2991a17a8c12dca117f55925e58e5b0493c5c6b885e

Observation a52de8d3-15fb-42be-8d81-034d09185996 · outbound

This paper cites Automated discovery of characteristic features of phase transitions in many-body localization.

Classifying single-qubit noise using machine learning Automated discovery of characteristic features of phase transitions in many-body localization

Reference 49

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source=pdf_text observed=2026-08-14T10:13:15.420406Z digest=sha256:1b689a6fe73a76187b6da8ac2046716440889f2ca148d2d3d5315c0147d6f844

Observation 9e77452f-85f8-4f80-9c57-02d219d2834d · outbound

This paper cites Learning phase transitions by confusion.

Classifying single-qubit noise using machine learning Learning phase transitions by confusion

Reference 50

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source=pdf_text observed=2026-08-14T10:13:15.425325Z digest=sha256:2bcfd8d4ecc433e030a998610e306f9763783a00322db87c3037befaccc1d998

Observation 4e52d6df-754f-4109-90d8-4c887ef23466 · outbound

This paper cites Machine learning phases of matter.

Classifying single-qubit noise using machine learning Machine learning phases of matter

Reference 51

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source=pdf_text observed=2026-08-14T10:13:15.430306Z digest=sha256:cb117893f88ce06b3fdc203bd4a47ff4e153b8c7bb3372cda0f5164a9eef5c2b

Observation fdbb1c1a-8201-485e-86b4-d31c04eb4db8 · outbound

This paper cites Machine Learning Phases of Strongly Correlated Fermions.

Classifying single-qubit noise using machine learning Machine Learning Phases of Strongly Correlated Fermions

Reference 52

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source=pdf_text observed=2026-08-14T10:13:15.435142Z digest=sha256:9f1552eca96068f8a232a79f2a8e13a5ef89cf0d6b7271ff38a241d617f77126

Observation 4a97350a-e202-424c-a3e1-9a471017f926 · outbound

This paper cites Unsupervised learning of phase transitions: from principal component analysis to variational autoencoders.

Classifying single-qubit noise using machine learning Unsupervised learning of phase transitions: from principal component analysis to variational autoencoders

Reference 53

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local_arxiv, observed 2026-08-14T10:13:15.995377Z

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source=pdf_text observed=2026-08-14T10:13:15.440301Z digest=sha256:d5fdf432cb98314849f8814956bd08947d0a3703349ef5c4a14d5452fd5853c8

Observation ee27362b-bad4-4af0-9815-baed41cad074 · outbound

This paper cites Machine Learning Topological Invariants with Neural Networks.

Classifying single-qubit noise using machine learning Machine Learning Topological Invariants with Neural Networks

Reference 54

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source=pdf_text observed=2026-08-14T10:13:15.444753Z digest=sha256:91f5b26c016f7b712185e2643dd4f55a261d946d6b255bd4f2b307b1aadb2f87

Observation aad6484e-e900-4cf8-b4dd-648272a748d3 · outbound

This paper cites Robust Online Hamiltonian Learning.

Classifying single-qubit noise using machine learning Robust Online Hamiltonian Learning

Reference 55

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source=pdf_text observed=2026-08-14T10:13:15.449580Z digest=sha256:96b2f84c51656f48d6ccb50d1ce13e9323367ed386847a2eb581b74ae8417513

Observation 17f0aeb9-b2f3-4a24-a6d9-535f95580f08 · outbound

This paper cites Efficient online quantum state estimation using a matrix-exponentiated gradient method.

Classifying single-qubit noise using machine learning Efficient online quantum state estimation using a matrix-exponentiated gradient method

Reference 56

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source=pdf_text observed=2026-08-14T10:13:15.454242Z digest=sha256:b5da1f551e61189a9719aaa9d9d0914ffeb6d734f731f81a58027a1f26317684

Observation 14b70dac-32ab-4081-8555-2194969fc573 · outbound

This paper cites Machine learning for predictive estimation of qubit dynamics subject to dephasing.

Classifying single-qubit noise using machine learning Machine learning for predictive estimation of qubit dynamics subject to dephasing

Reference 57

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local_arxiv, observed 2026-08-14T10:13:15.939644Z

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

source=pdf_text observed=2026-08-14T10:13:15.459280Z digest=sha256:b6eb4be68e17adfd25cfce2826ef92c5b0d60b2183eba6ce380b04cd01fa02f1

Observation 893687bc-76e0-4a0a-989f-33013a5b170a · outbound

This paper cites Machine learning for discriminating quantum measurement trajectories and improving readout.

Classifying single-qubit noise using machine learning Machine learning for discriminating quantum measurement trajectories and improving readout

Reference 58

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source=pdf_text observed=2026-08-14T10:13:15.463852Z digest=sha256:319700b9f4916fe730ef9aa7c9f7b41829f27d6f3a87622552ad9f4cd5c20e56

Observation a78d3fcc-0d8e-4b09-b465-cb20de6f4c50 · outbound

This paper cites Discovering physical concepts with neural networks.

Classifying single-qubit noise using machine learning Discovering physical concepts with neural networks

Reference 59

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source=pdf_text observed=2026-08-14T10:13:15.468369Z digest=sha256:85ba37865a368200deb76c9e41ea4f7b0c9c399aa89b5e0cb294f298439d79f6

Observation 7974c3a4-af8a-4ce9-8940-0c44c2dea202 · outbound

This paper cites Pedregosa, G.

Classifying single-qubit noise using machine learning Pedregosa, G

Reference 60

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source=pdf_text observed=2026-08-14T10:13:15.542196Z digest=sha256:87a7909b18cc6852fab266b4a01438564d09e570b46de97f2d3f1f05cbe8a5d8

Observation 8f0442a2-a487-427c-8bc4-7228c2bfd40f · outbound

This paper cites The canonical QCVV task is to estimate a specific property, so supervised learning is more relevant.

Classifying single-qubit noise using machine learning The canonical QCVV task is to estimate a specific property, so supervised learning is more relevant

Reference 61

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source=pdf_text observed=2026-08-14T10:13:15.476386Z digest=sha256:c5d2a9b631cfefa14c03698716c38ee0ae921a1e2ca15ae4160544db2ccc00ec

Observation 79abe12d-1601-4021-9a9f-1559c00baae6 · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 62

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source=pdf_text observed=2026-08-14T10:13:15.479970Z digest=sha256:ea7acecb4c74ab1a779b66316d243bd467c66c53f7402fbabd395d114d8a66f8

Observation cc9b21e2-2020-4983-8684-05bd41f9d92e · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 63

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source=pdf_text observed=2026-08-14T10:13:15.484477Z digest=sha256:78ae595b77849e5479a078fe9cbe173dac8ea3bb40a4e8313fdf9d687cc4db0f

Observation cac5c873-5dcc-42c3-bf49-fad42b99ab74 · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 64

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source=pdf_text observed=2026-08-14T10:13:15.489516Z digest=sha256:acd69618b4ce0c539c0f79260cfd8cdabeb1ece3b364a7738605f2e7dbe5e138

Observation 10c31703-dd8d-4bdb-9ec7-d8844c4edd2c · outbound

This paper cites Bergstra, D.

Classifying single-qubit noise using machine learning Bergstra, D

Reference 65

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source=pdf_text observed=2026-08-14T10:13:15.495538Z digest=sha256:e32666fade71f5797a5f042ce6f08357ad1c470e1554b58b65cba69d43d31c30

Observation a553f596-c8c5-46fe-834f-ad07cf70debb · outbound

This paper cites Comparing Experiments to the Fault-Tolerance Threshold.

Classifying single-qubit noise using machine learning Comparing Experiments to the Fault-Tolerance Threshold

Reference 66

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source=pdf_text observed=2026-08-14T10:13:15.499795Z digest=sha256:f3eb2e2edba5f47642035a1fb555966abf3afb6ae5c4946fe054303e04372287

Observation 974c01b2-3a4c-41bd-be2d-21a952dad49d · outbound

This paper cites Quantum error correction failure distributions: comparison of coherent and stochastic error models.

Classifying single-qubit noise using machine learning Quantum error correction failure distributions: comparison of coherent and stochastic error models

Reference 67

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local_arxiv, observed 2026-08-14T10:13:15.872878Z

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source=pdf_text observed=2026-08-14T10:13:15.505239Z digest=sha256:f12b4006e7c7ba752a0e002c7b37c0d98293428ce5ef1d1dc3303b60c9f7f504

Observation 619739fa-fd68-4f14-8670-a20864749ab5 · outbound

This paper cites Tensor-Network Simulations of the Surface Code under Realistic Noise.

Classifying single-qubit noise using machine learning Tensor-Network Simulations of the Surface Code under Realistic Noise

Reference 68

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source=pdf_text observed=2026-08-14T10:13:15.509805Z digest=sha256:15b2073639d24f12d36539b1c18ecd207a404eba3e1c801946dc3cc8e2575567

Observation 765ae8f7-dfde-4b6b-8868-19110db708fa · outbound

This paper cites Noise tailoring for scalable quantum computation via randomized compiling.

Classifying single-qubit noise using machine learning Noise tailoring for scalable quantum computation via randomized compiling

Reference 69

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source=pdf_text observed=2026-08-14T10:13:15.516103Z digest=sha256:bf56b09a69529e44fc511d35c417238c7229ea253ad7a353a90d309a41f98274

Observation 56ffd470-92ec-4b1d-8f15-d8bcac24b7b5 · outbound

This paper cites Errors and pseudo-thresholds for incoherent and coherent noise.

Classifying single-qubit noise using machine learning Errors and pseudo-thresholds for incoherent and coherent noise

Reference 70

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source=pdf_text observed=2026-08-14T10:13:15.521307Z digest=sha256:248d659c4045e44a28161b2f3a30377e084348ba31b4d4b40774b3e4401eb24f

Observation ff15c46d-cc43-45e2-84b3-6f71ee9d0f49 · outbound

This paper cites Characterizing errors on qubit operations via iterative randomized benchmarking.

Classifying single-qubit noise using machine learning Characterizing errors on qubit operations via iterative randomized benchmarking

Reference 71

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

source=pdf_text observed=2026-08-14T10:13:15.527157Z digest=sha256:5f7a4bead07d26c154ebf482a79bc7741cb458cffbdaf48ba6492613dc5f920b

Observation 0f9797b3-8c2d-42af-b30f-f8b3facc6fe7 · outbound

This paper cites Introduction to Quantum Gate Set Tomography.

Classifying single-qubit noise using machine learning Introduction to Quantum Gate Set Tomography

Reference 72

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source=pdf_text observed=2026-08-14T10:13:15.532268Z digest=sha256:30613210191a6e977a9b2cd88cfa8531bcacfc96482064f62fe25eb34fe547e4

Observation 972e4be1-0649-4be5-aebd-b0e072de88f8 · outbound

This paper cites Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography.

Classifying single-qubit noise using machine learning Demonstration of qubit operations below a rigorous fault tolerance threshold with gate set tomography

Reference 73

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local_arxiv, observed 2026-08-14T10:13:15.783051Z

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

source=pdf_text observed=2026-08-14T10:13:15.537060Z digest=sha256:d8438c2188acb127225f9b0162fd46e6bc426b026d21a59c12169de28ba9e329

Observation 6e1fe2cf-fb33-463c-9917-ab877928919b · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 74

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

source=pdf_text observed=2026-08-14T10:13:15.600924Z digest=sha256:f661b013ac56eb713d8f63c462fc9779130dae6e054cb6f10edbc2756feab1c9

Observation add63a7a-9235-403e-898a-2dcedf4aa0c0 · outbound

This paper cites Rosenblatt, Psychological Review 65, 386 (1958).

Classifying single-qubit noise using machine learning Rosenblatt, Psychological Review 65, 386 (1958)

Reference 75

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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.

source=pdf_text observed=2026-08-14T10:13:15.546896Z digest=sha256:908ad88deae0a7b5567a9b45489fb5bfb8ca6515dde8db94dffd45e8131985f4

Observation 3c838135-60cf-4a7d-8a4c-dc7f834c92d6 · outbound

This paper cites Rosenblatt, The Perceptron - A Perceiving and Rec- ognizing Automaton , Tech.

Classifying single-qubit noise using machine learning Rosenblatt, The Perceptron - A Perceiving and Rec- ognizing Automaton , Tech

Reference 76

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raw_fallback, observed 2026-08-14T10:13:16.915385Z

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source=pdf_text observed=2026-08-14T10:13:15.551085Z digest=sha256:f7747135565a3f0a0ca919f8e25ff2f032048581350be05334204c6594eef744

Observation be9432e7-99e8-488b-bc27-34c531b2fe66 · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 77

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

source=pdf_text observed=2026-08-14T10:13:15.555296Z digest=sha256:21c9aa6bfdadb521fa4c2ccb2d2d26eb08bb57ca1c0f19807804d162f89fc6dc

Observation 5fcd0381-9467-4d5f-9fdb-31bdfb9d4c8d · outbound

This paper cites Hofmann, B.

Classifying single-qubit noise using machine learning Hofmann, B

Reference 78

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source=pdf_text observed=2026-08-14T10:13:15.559053Z digest=sha256:19047d47ce57bf8151f265fa8e90894f92d2d2af16a57d95cbf3c3b47af80780

Observation 62ef0c5e-d43e-45d8-a695-fc8a58f85029 · outbound

This paper cites Guyon, B.

Classifying single-qubit noise using machine learning Guyon, B

Reference 79

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raw_fallback, observed 2026-08-14T10:13:16.875076Z

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.

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Observation d9c5d0bc-7ad5-4442-b2d0-dd418140c003 · outbound

This paper cites pyGSTio/pyGSTi,.

Classifying single-qubit noise using machine learning pyGSTio/pyGSTi,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:13:16.861506Z

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.

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Observation 2f579bb0-54f8-4713-a428-a9ce78e5c9bd · outbound

This paper cites Polyglot: Distributed Word Representations for Multilingual NLP.

Classifying single-qubit noise using machine learning Polyglot: Distributed Word Representations for Multilingual NLP

Reference 81

Resolution
verified exact
local_arxiv, observed 2026-08-14T10:13:15.765056Z

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.

source=pdf_text observed=2026-08-14T10:13:15.571210Z digest=sha256:a18bc017a49426b5c61945eaacc445aa208559776e159dfa277ed10f78ad7375

Observation 6c74a336-6e97-400c-8786-71ed820a0065 · outbound

This paper cites Jolliffe, Principal Component Analysis , 2nd ed.

Classifying single-qubit noise using machine learning Jolliffe, Principal Component Analysis , 2nd ed

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:13:16.847911Z

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.

source=pdf_text observed=2026-08-14T10:13:15.575705Z digest=sha256:3b42d180a6e5b33916062a97aa9f0f071ca73132ed2b9bdfd22ab485e9b90114

Observation c9977cac-710d-4d3f-8e30-f321f49dc5db · outbound

This paper cites Hotelling, Journal of Educational Psychology 24, 417 (1933).

Classifying single-qubit noise using machine learning Hotelling, Journal of Educational Psychology 24, 417 (1933)

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:13:16.833014Z

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.

source=pdf_text observed=2026-08-14T10:13:15.579530Z digest=sha256:a93a3f314c328e908211be0aa574f1007ee10b7b779f154d52696bc43fcb6745

Observation 14d09871-fd6c-41b0-946c-7d722d84736f · outbound

This paper cites Pearson, The London, Edinburgh, and Dublin Philo- sophical Magazine and Journal of Science 2, 559 (1901).

Classifying single-qubit noise using machine learning Pearson, The London, Edinburgh, and Dublin Philo- sophical Magazine and Journal of Science 2, 559 (1901)

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:13:16.818670Z

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.

source=pdf_text observed=2026-08-14T10:13:15.583211Z digest=sha256:5f06ff5ee0157b4a6e1cb41015301a43b64b47ab47a5550658e89b22a30096fa

Observation 2aaf1b6f-27d2-41bd-9de9-014fa789fc6e · outbound

This paper cites Borg and P.

Classifying single-qubit noise using machine learning Borg and P

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:13:16.802281Z

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.

source=pdf_text observed=2026-08-14T10:13:15.587217Z digest=sha256:a9b6a220d20dabd2131e3a874481f01aeb988050a037f0291d301222e8e21f6b

Observation 3809e3ad-2bc5-4860-a676-18bd9b699db8 · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 86

Resolution
unresolved
raw_fallback, observed 2026-08-14T10:13:16.787172Z

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.

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Observation 90b7f70b-280b-49f8-95f2-04fd9b30c118 · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 87

Resolution
unresolved
raw_fallback, observed 2026-08-14T10:13:16.773604Z

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.

source=pdf_text observed=2026-08-14T10:13:15.596904Z digest=sha256:a184e601c5837f2a0c8e3bca535434378c925e07af30cc18ee4af3d6c9a78488

Observation e6502d0f-9bcd-4683-8c14-140ee0215b3d · outbound

This paper cites McKinney, in Proceedings of the 9th Python in Sci- ence Conference, edited by S.

Classifying single-qubit noise using machine learning McKinney, in Proceedings of the 9th Python in Sci- ence Conference, edited by S

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:13:16.559647Z

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.

source=pdf_text observed=2026-08-14T10:13:15.663173Z digest=sha256:a31cfa3c5111177124f6a6810bf8a599bd0743a6706e7f2ef6ae80023f4c2778

Observation e086f330-9c4b-469e-bcef-29e3193689c0 · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 89

Resolution
unresolved
raw_fallback, observed 2026-08-14T10:13:16.736611Z

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.

source=pdf_text observed=2026-08-14T10:13:15.604893Z digest=sha256:8c3a897b1fcdef5e03010fa9ba0e291ecf8aaf8a0e182a96429840cef587a89d

Observation 5115db76-e697-41c2-891b-f5069a1d925e · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 90

Resolution
unresolved
raw_fallback, observed 2026-08-14T10:13:16.705620Z

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.

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Observation 7435b678-508e-456b-9e1c-7f178976cd1f · outbound

This paper cites Jamio lkowski, Reports on Mathematical Physics 3, 275 (1972).

Classifying single-qubit noise using machine learning Jamio lkowski, Reports on Mathematical Physics 3, 275 (1972)

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-14T10:13:15.612592Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:13:15.612592Z digest=sha256:a52c4d04836be422c0ce22dff762163c8bc71074ab5f0d391bac27918fcfc4d5

Observation 86df1b92-a366-42d0-9e11-9dd745b793c6 · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 92

Resolution
unresolved
raw_fallback, observed 2026-08-14T10:13:16.675386Z

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.

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Observation fee8f27d-a890-41b0-b562-61f125629287 · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 93

Resolution
unresolved
raw_fallback, observed 2026-08-14T10:13:16.662590Z

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.

source=pdf_text observed=2026-08-14T10:13:15.622186Z digest=sha256:bf44bba9a3daba4ee20533e50258fafeb58580141c124125e233ad70a7819f05

Observation 825dfa29-f1fb-4f91-a732-77c53d84e47a · outbound

This paper cites F¨ osel, P.

Classifying single-qubit noise using machine learning F¨ osel, P

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:13:16.649925Z

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.

source=pdf_text observed=2026-08-14T10:13:15.627161Z digest=sha256:bfca04c03900e94db5e9470da165a3f78450690ed89954643a472f1fbe791da3

Observation 055fc5f5-787f-428b-b5ad-423569ce2fa8 · outbound

This paper cites Gatti, Design of Experiments for Reinforcement Learning, 1st ed.

Classifying single-qubit noise using machine learning Gatti, Design of Experiments for Reinforcement Learning, 1st ed

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:13:16.635431Z

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.

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Observation f519737d-54d5-4a42-b67f-30664e1eee02 · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 96

Resolution
unresolved
raw_fallback, observed 2026-08-14T10:13:16.620724Z

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.

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Observation e63e0c7e-375b-445a-9bfe-768c33fff27a · outbound

This paper cites Diamond and S.

Classifying single-qubit noise using machine learning Diamond and S

Reference 97

Resolution
unresolved
no resolver link, observed 2026-08-14T10:13:15.640775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:13:15.640775Z digest=sha256:ab68be833fda35cb4dfc0019582a2d16c49643bb1b277e552ae8207daab90472

Observation 2dfebc08-ea28-4d6d-aae6-a0224b48855b · outbound

This paper cites Agrawal, R.

Classifying single-qubit noise using machine learning Agrawal, R

Reference 98

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:13:16.594662Z

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.

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Observation fd84e85b-57cd-4911-9522-c0bbd8ee9e47 · outbound

This paper cites P´ erez and B.

Classifying single-qubit noise using machine learning P´ erez and B

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T10:13:16.580789Z

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.

source=pdf_text observed=2026-08-14T10:13:15.650691Z digest=sha256:ab108e1cc30593e90c8d13e5cbff8cb3b733a35733b78ecbe9adef4cf86f9a39

Observation a11b8371-ed61-4b60-9201-a82522847c9e · outbound

This paper cites an unresolved cited work.

Classifying single-qubit noise using machine learning Unresolved cited work

Reference 100

Resolution
unresolved
no resolver link, observed 2026-08-14T10:13:15.654703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:13:15.654703Z digest=sha256:6555d43318db3403b992f99be8fcdb0127ba77737516064df3ecbbfa138cec96

Pith citing papers

No inbound Pith citation observations are available.