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Paper Citation Record · LEDGER

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning

As of 13 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2411.15360.

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pith.paper-citation-record.v1
2411.15360 v1

Coverage vector

measured 51 of 51 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:26:41.706482Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

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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

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

Source: cited_works

Reference resolution

51 of 51 outbound references displayed

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External citation measurements

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Outbound references

Observation 204f554f-cc06-4fa2-b59b-4b1257688518 · outbound

This paper cites Counting near-infrared single-photons with 95% efficiency,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Counting near-infrared single-photons with 95% efficiency,

Reference 1

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Observation c465b927-775a-4026-b5cb-0971a50ecdac · outbound

This paper cites Superconducting transition-edge sensors optimized for high- efficiency photon-number resolving detectors,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Superconducting transition-edge sensors optimized for high- efficiency photon-number resolving detectors,

Reference 2

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Observation e1afe05e-fbe2-4486-a26b-b517d5072527 · outbound

This paper cites FirstAstronomicalApplicationofaCryogenicTransitionEdgeSensor Spectrophotometer,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning FirstAstronomicalApplicationofaCryogenicTransitionEdgeSensor Spectrophotometer,

Reference 3

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Observation c58e9b2e-46d7-4f76-82f9-2f202fd03100 · outbound

This paper cites SCUBA-2: the 10 000 pixel bolometer camera on the James Clerk Maxwell Telescope,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning SCUBA-2: the 10 000 pixel bolometer camera on the James Clerk Maxwell Telescope,

Reference 4

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

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Observation e161c4a6-fc8f-46f4-a93c-766bd04eb2cc · outbound

This paper cites A Review of X-ray Microcalorimeters Based on Superconducting Transition Edge Sensors for Astrophysics and Particle Physics,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning A Review of X-ray Microcalorimeters Based on Superconducting Transition Edge Sensors for Astrophysics and Particle Physics,

Reference 5

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Observation b3531a7c-b68b-441a-812b-cd4a9156bf78 · outbound

This paper cites Transition-Edge Sensors,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Transition-Edge Sensors,

Reference 6

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Observation 9fbdd346-3836-407e-836a-e181cddb6894 · outbound

This paper cites Review of superconducting transition-edge sensors for x-ray and gamma-ray spectroscopy,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Review of superconducting transition-edge sensors for x-ray and gamma-ray spectroscopy,

Reference 7

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Observation c0972e07-6e06-4ca5-bfaa-57fa974b086f · outbound

This paper cites Entanglement-enhanced measurement of a completely unknown optical phase,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Entanglement-enhanced measurement of a completely unknown optical phase,

Reference 8

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Observation bfa2d896-372f-4f08-b0c4-ffe3777db11f · outbound

This paper cites Quantum metrology with imperfect states and detectors,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Quantum metrology with imperfect states and detectors,

Reference 9

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Observation 00cdc5ba-8471-4f0e-ae75-6f0038166c4c · outbound

This paper cites Quantum-enhanced interferometry with large heralded photon-number states,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Quantum-enhanced interferometry with large heralded photon-number states,

Reference 10

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Observation 1d7e1cc2-de3c-4a3f-accc-d1ec897a16f9 · outbound

This paper cites Scalable multiphoton quantum metrology with neither pre- nor post-selected measurements,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Scalable multiphoton quantum metrology with neither pre- nor post-selected measurements,

Reference 11

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Observation 2546a949-26b0-44a8-9dbc-4e5244e6db65 · outbound

This paper cites Few-photonspectralconfocalmicroscopyforcellimagingusingsuperconducting transition edge sensor,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Few-photonspectralconfocalmicroscopyforcellimagingusingsuperconducting transition edge sensor,

Reference 12

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Observation 8f2388d1-b5f7-4e20-a875-f3a3360d3f14 · outbound

This paper cites The computational complexity of linear optics,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning The computational complexity of linear optics,

Reference 13

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Observation 60b0826f-6d59-47d5-8fd4-d667853e3466 · outbound

This paper cites Gaussian Boson Sampling,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Gaussian Boson Sampling,

Reference 14

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Observation 3e673cdd-65f3-4ee3-85b2-bde166a55127 · outbound

This paper cites Detailed study of Gaussian boson sampling,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Detailed study of Gaussian boson sampling,

Reference 15

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

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Observation e68a0b4c-31ec-4463-b6ee-61cae2dd84bb · outbound

This paper cites Quantum computational advantage with a programmable photonic processor,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Quantum computational advantage with a programmable photonic processor,

Reference 16

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Source-reported events for the cited work

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Observation 55867c0a-c6c1-4c3b-abb1-642b752a63de · outbound

This paper cites Conclusive quantum steering with superconducting transition-edge sensors,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Conclusive quantum steering with superconducting transition-edge sensors,

Reference 17

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Observation 1b6c1200-432f-4342-ac64-0b83f8ca36b4 · outbound

This paper cites Significant-loophole-free test of bell’s theorem with entangled photons,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Significant-loophole-free test of bell’s theorem with entangled photons,

Reference 18

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Observation bc6ab8c7-8e14-469c-a288-c1ac9b661ebe · outbound

This paper cites Proposal for the distribution of multiphoton entanglement with optimal rate-distance scaling,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Proposal for the distribution of multiphoton entanglement with optimal rate-distance scaling,

Reference 19

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Observation ed2e1f14-b0cc-42bf-b4cb-614c67e39d05 · outbound

This paper cites Generation of optical coherent-state superpositions by number-resolved photon subtraction from the squeezed vacuum,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Generation of optical coherent-state superpositions by number-resolved photon subtraction from the squeezed vacuum,

Reference 20

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Observation f60b3496-14dd-451b-80c3-cb0e09c6a742 · outbound

This paper cites Non-Gaussian operation based on photon subtraction using a photon-number-resolving detector at a telecommunications wavelength,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Non-Gaussian operation based on photon subtraction using a photon-number-resolving detector at a telecommunications wavelength,

Reference 21

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Observation 0d8c0370-1f75-47ca-a54c-8c481b6485a3 · outbound

This paper cites Engineering Schrödinger cat states with a photonic even-parity detector,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Engineering Schrödinger cat states with a photonic even-parity detector,

Reference 22

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Observation 6407e881-446d-46d6-81dd-6f8bb54a6abd · outbound

This paper cites Multiphoton quantum-state engineering using conditional measurements,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Multiphoton quantum-state engineering using conditional measurements,

Reference 23

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Observation 2145df4b-abdb-41fb-9508-22a2ae88b286 · outbound

This paper cites Progress towards practical qubit computation using approximate Gottesman-Kitaev-Preskill codes,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Progress towards practical qubit computation using approximate Gottesman-Kitaev-Preskill codes,

Reference 24

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Observation 30d5fcc8-4506-4f50-849c-9d10517de45c · outbound

This paper cites Non-Gaussian quantum state generation by multi-photon subtraction at the telecommunication wavelength,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Non-Gaussian quantum state generation by multi-photon subtraction at the telecommunication wavelength,

Reference 25

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

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Observation 94e7a735-3400-416b-b253-78aacdcf7d93 · outbound

This paper cites Algorithm for finding clusters with a known distribution and its application to photon-number resolution using a superconducting transition-edge sensor,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Algorithm for finding clusters with a known distribution and its application to photon-number resolution using a superconducting transition-edge sensor,

Reference 26

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

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Observation f3272d71-a38f-4f97-8b44-9ee990ebac58 · outbound

This paper cites Precisely determining photon-number in real time,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Precisely determining photon-number in real time,

Reference 27

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Observation efd0db87-da29-46ca-b5b5-0d1d038620cc · outbound

This paper cites Fast transition-edge sensors suitable for photonic quantum computing,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Fast transition-edge sensors suitable for photonic quantum computing,

Reference 28

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

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Observation 3934cbca-1f62-4751-af4f-c63daf49aff3 · outbound

This paper cites Developmentofsuperconductingsingle-particledetectorTransition-EdgeSensor,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Developmentofsuperconductingsingle-particledetectorTransition-EdgeSensor,

Reference 29

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

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Observation f1b60bcc-5ca5-41d0-a9b9-a7be53614090 · outbound

This paper cites Principal component analysis,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Principal component analysis,

Reference 30

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Source-reported events for the cited work

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

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Observation e82324af-e524-4f3c-af61-b010cf179cdc · outbound

This paper cites Tomography of photon-number resolving continuous-output detectors,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Tomography of photon-number resolving continuous-output detectors,

Reference 31

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Source-reported events for the cited work

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

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Observation 2b213c10-4c39-4d61-81ad-79d62abb73f2 · outbound

This paper cites Nearest neighbor pattern classification,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Nearest neighbor pattern classification,

Reference 32

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Source-reported events for the cited work

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

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Observation 41ffc95f-c3fb-44b3-8f92-ceefb6b9c310 · outbound

This paper cites Scikit-learn: Machine learning in Python,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Scikit-learn: Machine learning in Python,

Reference 33

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation af418877-d8c2-4a00-b103-c1b896116f2f · outbound

This paper cites Random Forests,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Random Forests,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:42.037423Z

Source-reported events for the cited work

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

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Observation 81c472f0-3ab3-487f-be07-302bf27c2a04 · outbound

This paper cites Liblinear: A library for large linear classification,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Liblinear: A library for large linear classification,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:42.021086Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.626776Z digest=sha256:b5737291c0d5a64ae6d340bb18d137f41fdaa50e9248c98c57f49059f6c67389

Observation 6691da8f-a4f8-460b-947f-d663e43a7661 · outbound

This paper cites Libsvm: A library for support vector machines,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Libsvm: A library for support vector machines,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:42.001864Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.631897Z digest=sha256:bac84b4d0efe0c677886fb56fa1e6d2beb4102f9317bc53f1ca3a4f0eba58f87

Observation 537b3f2d-6e55-4da0-8427-a7a1a169c3d5 · outbound

This paper cites Xgboost: A scalable tree boosting system,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Xgboost: A scalable tree boosting system,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.984283Z

Source-reported events for the cited work

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

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Observation 96f1f80a-a37d-4819-866c-462c681f6602 · outbound

This paper cites TensorFlow: Large-scale machine learning on heterogeneous systems,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning TensorFlow: Large-scale machine learning on heterogeneous systems,

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T14:26:41.641668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:26:41.641668Z digest=sha256:f3a3b9ee49876505dd07a8507f49cbbcee92aef7d468698b928e8f541c97e9cb

Observation efde1eb4-127a-43c7-b5d1-27dcd7c4d22a · outbound

This paper cites Network In Network.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Network In Network

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T14:26:41.646522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:26:41.646522Z digest=sha256:439309b948007557d5579f21a5267c05462f244241803acd07a5b75c082c5240

Observation 57263ded-46c4-47c9-866e-b4bcdeedb381 · outbound

This paper cites Timeseriesclassificationfromscratchwithdeepneuralnetworks: Astrongbaseline,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Timeseriesclassificationfromscratchwithdeepneuralnetworks: Astrongbaseline,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.958096Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.652016Z digest=sha256:f54ddcd416188da0835311a16f0e97ae7d155f8eace6751ae6d8e5a0542166f0

Observation b9958a9f-c8c0-4150-a6b6-f06023b2765a · outbound

This paper cites Deep learning for time series classification: a review,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Deep learning for time series classification: a review,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.942619Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.656972Z digest=sha256:6504d85c59fa456e5794bf1694c19b291000848c0d309c3cc09fb04d67d6581d

Observation 2c040619-0474-4792-be11-14080eee05a8 · outbound

This paper cites Density-based clustering based on hierarchical density estimates,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Density-based clustering based on hierarchical density estimates,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.926687Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.661858Z digest=sha256:4f5f5ade24df4af085709861b9591d090789b7da760451588eb036fa55267590

Observation 96178c77-824d-424d-89e6-e6c4dc377062 · outbound

This paper cites hdbscan: Hierarchical density based clustering,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning hdbscan: Hierarchical density based clustering,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.911217Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.666490Z digest=sha256:e631d606a26163536faf3d1811f1de6a1f8d5ad06e9044173ec6132089e4a86d

Observation ee61b9fb-42b2-4b71-8f04-8e6893bf5ea3 · outbound

This paper cites CVXPY: A Python-embedded modeling language for convex optimization,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning CVXPY: A Python-embedded modeling language for convex optimization,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.895004Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.671168Z digest=sha256:d6b1645efa63ef799accd764f7a953e449fb38203b20d95a6a23bbf9f64dbd94

Observation a79baeb2-d93b-477a-9dac-19a8733bf856 · outbound

This paper cites A rewriting system for convex optimization problems,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning A rewriting system for convex optimization problems,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.877160Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.675663Z digest=sha256:92b40e1b153466c272599c3e5ecee72053dad3d4c5c7208602f632685e681755

Observation 674ffd68-42e0-439a-9a80-1ecef5f62b0b · outbound

This paper cites Mapping coherence in measurement via full quantum tomography of a hybrid optical detector,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Mapping coherence in measurement via full quantum tomography of a hybrid optical detector,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.857003Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.680381Z digest=sha256:1ea93c8e741442ba1f1c5c65bb555af316a522b51c239617e356478bbe27b6bc

Observation 14e59753-76c7-4b48-9282-bf756028ffc0 · outbound

This paper cites The simons observatory: large-scale characterization of 90/150 GHz TES detector modules,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning The simons observatory: large-scale characterization of 90/150 GHz TES detector modules,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.840442Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.685609Z digest=sha256:47e2ab781fa6389938c9416adf9b3a3f7f9b53385529331729a09f6d2fc6140e

Observation 54076b6f-00a0-4808-a973-bbd0a1088ddf · outbound

This paper cites High_speed_TES_ML,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning High_speed_TES_ML,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.824241Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.690912Z digest=sha256:e9787387afd878c21b586fa45ce542ab76033a5663430cd5af9f927e17617f35

Observation 98291ffd-5301-4d38-9550-e53e7063f02d · outbound

This paper cites Accurate Unsupervised Photon Counting from Transition Edge Sensor Signals.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning Accurate Unsupervised Photon Counting from Transition Edge Sensor Signals

Reference 49

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verified exact
local_arxiv, observed 2026-08-12T14:26:41.754453Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.695792Z digest=sha256:4b4f4cd2b0240b1b4a9f73f62766413613ba14c6f8810765f0394a566b401062

Observation 8af6e0f8-5955-4f04-8195-64d9ca426a65 · outbound

This paper cites An application of electrothermal feedback for high resolution cryogenic particle detection,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning An application of electrothermal feedback for high resolution cryogenic particle detection,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.808447Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.701054Z digest=sha256:36b33a06c4d131f7bc970b5d4373115d472477125063411d33ebb385322d6cf0

Observation d47537f7-bef1-4c87-ba96-5e8455c18c97 · outbound

This paper cites SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,.

Boosting Photon-Number-Resolved Detection Rates of Transition-Edge Sensors by Machine Learning SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T14:26:41.791179Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-12T14:26:41.706482Z digest=sha256:6ae328d1475fade769385415612af9e756ba22cce2de7c975202062043f687d8

Pith citing papers

No inbound Pith citation observations are available.