Paper Citation Record · LEDGER

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection

As of 10 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 2 inbound Pith citation observations for arXiv:2501.17041.

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

pith.paper-citation-record.v1
2501.17041 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T05:05:36.719817Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:43:16.588321Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T17:38:57.317808Z

Reference resolution

37 of 37 outbound references displayed

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External citation measurements

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Outbound references

Observation a36805ce-ceb0-46fd-b88d-e21e3e0c0adf · outbound

This paper cites an unresolved cited work.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Unresolved cited work

Reference 1

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Observation 1ecc60ff-a27b-470f-9eea-1bce5e6409c5 · outbound

This paper cites Universal quantum simulators.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Universal quantum simulators

Reference 2

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Observation 02e48387-54c5-4040-9b57-62cf32ce91e7 · outbound

This paper cites Harrow, Avinatan Hassidim, and Seth Lloyd.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Harrow, Avinatan Hassidim, and Seth Lloyd

Reference 3

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Observation 298ddac0-1397-4d9a-b00b-b36337eae695 · outbound

This paper cites Quantum Machine Learning: A Review and Case Studies.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Quantum Machine Learning: A Review and Case Studies

Reference 4

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Observation cb33c856-dcc2-498e-961d-7c7441cc7a57 · outbound

This paper cites an unresolved cited work.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Unresolved cited work

Reference 5

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Observation 3d1f645b-2340-4408-b914-007270d0b39b · outbound

This paper cites Quantum Machine Learning in High Energy Physics.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Quantum Machine Learning in High Energy Physics

Reference 6

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Observation fe371a61-ec73-42c1-b265-31559efd37a0 · outbound

This paper cites A quantum-enhanced support vector machine for galaxy classification.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection A quantum-enhanced support vector machine for galaxy classification

Reference 7

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Observation ec74d654-1c3c-4166-bf30-7955080a2441 · outbound

This paper cites Quantum Machine Learning for Radio Astronomy.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Quantum Machine Learning for Radio Astronomy

Reference 8

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This paper cites Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, and Patrick J.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Cerezo, Guillaume Verdon, Hsin-Yuan Huang, Lukasz Cincio, and Patrick J

Reference 9

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Observation 62ef3510-a350-4c1e-9f9f-9f7efd9cba0d · outbound

This paper cites Better than classical? The subtle art of benchmarking quantum machine learning models.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Better than classical? The subtle art of benchmarking quantum machine learning models

Reference 10

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Observation d9c9c387-6e47-49c1-bd5b-fa28ae4b9147 · outbound

This paper cites Parmiggiani et al.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Parmiggiani et al

Reference 11

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This paper cites Parmiggiani, A.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Parmiggiani, A

Reference 12

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This paper cites Parmiggiani, A.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Parmiggiani, A

Reference 13

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Observation b6f75d06-8c56-48c5-a4f0-24cc87499e70 · outbound

This paper cites Tavani et al.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Tavani et al

Reference 14

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Observation 7843aa99-4bd6-4260-a774-8d4543c6b896 · outbound

This paper cites Rizzo et al.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Rizzo et al

Reference 15

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Observation b5555fba-4812-4f6a-b894-bcf2e75518cb · outbound

This paper cites PennyLane: Automatic differentiation of hybrid quantum-classical computations.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection PennyLane: Automatic differentiation of hybrid quantum-classical computations

Reference 16

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Observation fafe270a-092a-4e3e-a190-15b73c7342fc · outbound

This paper cites an unresolved cited work.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Unresolved cited work

Reference 17

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Observation 11e303ae-fc06-4b11-90a4-ccbd0e689ce1 · outbound

This paper cites Mitarai, M.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Mitarai, M

Reference 18

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Observation b1c97278-6564-4f73-8557-b4d4c49e0254 · outbound

This paper cites Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C

Reference 19

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Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Unresolved cited work

Reference 20

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Observation 6b21c01b-a2dd-46f1-8192-e62378837796 · outbound

This paper cites Ghirlanda, L.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Ghirlanda, L

Reference 21

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Observation 653ee1ff-3bb7-4b1d-a27c-31153b6c01fb · outbound

This paper cites an unresolved cited work.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Unresolved cited work

Reference 22

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Observation b2fbb9a7-27eb-4e69-bf8f-a7312f3c3a09 · outbound

This paper cites Stamatikos, N.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Stamatikos, N

Reference 23

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Observation 02475e08-ce53-4cc7-8383-6cc65f6eb168 · outbound

This paper cites Thompson and Colleen A.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Thompson and Colleen A

Reference 24

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Observation 00ea8868-bb9e-4be5-afc6-2a65691ccf82 · outbound

This paper cites von Kienlin, C.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection von Kienlin, C

Reference 25

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Observation ccf420df-2bd1-4017-9e59-dec9c5005ccf · outbound

This paper cites Poolakkil, R.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Poolakkil, R

Reference 26

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This paper cites Gehrels et al.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Gehrels et al

Reference 27

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Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Unresolved cited work

Reference 28

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Observation 4c307967-03b4-49a9-b8bf-f8229c1bfedf · outbound

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Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Unresolved cited work

Reference 29

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Observation 8b3980e4-1792-47be-a6fb-cf2c5f8f1e4e · outbound

This paper cites WORLD SCIENTIFIC, 2019.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection WORLD SCIENTIFIC, 2019

Reference 30

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Observation 08dda860-cccd-4ac1-9f8c-eb2e48c77d95 · outbound

This paper cites Sip”ocz, Tim Unbehaun, Christopher van Eldik, Thomas Vuillaume, and Roberta Zanin.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Sip”ocz, Tim Unbehaun, Christopher van Eldik, Thomas Vuillaume, and Roberta Zanin

Reference 31

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Observation 3a326fe6-500a-4d63-a525-d87f574e229a · outbound

This paper cites Evolution of data formats in very-high-energy gamma-ray astronomy.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Evolution of data formats in very-high-energy gamma-ray astronomy

Reference 32

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Observation 431fb806-be1a-418d-958e-e9fb9d9e3646 · outbound

This paper cites Gammapy: Python toolbox for gamma-ray astronomy, https://doi.org/10.5281/zenodo.10726484, 02 2024.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Gammapy: Python toolbox for gamma-ray astronomy, https://doi.org/10.5281/zenodo.10726484, 02 2024

Reference 33

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Observation 52951c6a-b4d5-49e2-a711-cbbb19f4352c · outbound

This paper cites Patricelli, A.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Patricelli, A

Reference 34

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Observation 161d2a72-6140-488a-b207-7f5345cbb18b · outbound

This paper cites CTAO Instrument Response Functions - prod5 version v0.1, https://doi.org/10.5281/zenodo.5499840, September 2021.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection CTAO Instrument Response Functions - prod5 version v0.1, https://doi.org/10.5281/zenodo.5499840, September 2021

Reference 35

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Observation 5fe20669-1914-47c2-aeb5-23659e39f760 · outbound

This paper cites Johnson, and Al ´an Aspuru-Guzik.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Johnson, and Al ´an Aspuru-Guzik

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:05:36.757570Z

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Observation ae0d6849-bb8e-40e8-88e5-0d782f64d636 · outbound

This paper cites Caro, Hsin-Yuan Huang, M.

Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection Caro, Hsin-Yuan Huang, M

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:05:36.749409Z

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Pith citing papers

Observation 0d510df2-ba74-434c-9d23-cf3aad90197b · inbound

Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators cites this paper.

Qiskit Machine Learning: an open-source library for quantum machine learning tasks at scale on quantum hardware and classical simulators Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection

Reference 31

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Source-reported events for the cited work

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Observation cfff5634-474d-4bea-8c96-ff7cfb1d02eb · inbound

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection cites this paper.

Comparing Quantum Machine Learning Approaches in Astrophysical Signal Detection Benchmarking Quantum Convolutional Neural Networks for Signal Classification in Simulated Gamma-Ray Burst Detection

Reference 7

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