Paper Citation Record · LEDGER

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers

As of 9 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 2 inbound Pith citation observations for arXiv:2506.21537.

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

pith.paper-citation-record.v1
2506.21537 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:29:59.600612Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T10:54:21.066630Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T10:54:47.569194Z

Reference resolution

40 of 40 outbound references displayed

verified exact3
verified fuzzy33
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f8c17d64-fcf4-4c7c-a7c4-0ad8efa9272b · outbound

This paper cites https://www.kaggle.com/datasets/ uciml/pima-indians-diabetes-database, 2024.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers https://www.kaggle.com/datasets/ uciml/pima-indians-diabetes-database, 2024

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:02.601317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 35cc7a40-098b-44da-9d89-7e9a4ebaab11 · outbound

This paper cites Quantum computing optimization technique for iot platform using modified deep residual approach.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Quantum computing optimization technique for iot platform using modified deep residual approach

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:02.530737Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2f48affb-c419-4d15-a2e9-68b906708bde · outbound

This paper cites AWS Aquila Interface.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers AWS Aquila Interface

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:02.445109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation eb198957-40c8-4b67-8fdb-56de9e3f66ef · outbound

This paper cites Qure: Qubit re-allocation in noisy intermediate-scale quan- tum computers.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Qure: Qubit re-allocation in noisy intermediate-scale quan- tum computers

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:02.367608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation aaab24d3-e9f1-45ce-9c27-78016bd8e972 · outbound

This paper cites Measuring analytic gradients of general quantum evolution with the stochastic parameter shift rule.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Measuring analytic gradients of general quantum evolution with the stochastic parameter shift rule

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:02.281561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9bcd7c28-f209-44c5-ab9c-95f9466843a5 · outbound

This paper cites Muqut: Multi-constraint quantum circuit mapping on nisq computers.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Muqut: Multi-constraint quantum circuit mapping on nisq computers

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:02.196558Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 691755d1-c84f-447f-936f-513afe47378b · outbound

This paper cites Quantum ma- chine learning.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Quantum ma- chine learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:02.087348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 35c7ba2b-cb84-4b4e-a5d4-eea42b0f69d2 · outbound

This paper cites Challenges and opportu- nities in quantum machine learning.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Challenges and opportu- nities in quantum machine learning

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.998545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3e23fd59-2ea0-479e-9157-35448de8e537 · outbound

This paper cites Neural ordinary differential equa- tions.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Neural ordinary differential equa- tions

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.870939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a38112dd-2bb1-4b80-99e4-b5b0c2fed1c1 · outbound

This paper cites Learning quantum dynamics with la- tent neural ordinary differential equations.Phys.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Learning quantum dynamics with la- tent neural ordinary differential equations.Phys

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.777428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e7671d90-fa65-46a5-a637-a8ecc353183d · outbound

This paper cites The MNIST Database of Handwritten Digit Images for Machine Learning Research.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers The MNIST Database of Handwritten Digit Images for Machine Learning Research

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.697246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 38945bdd-527b-4fd8-846a-4d08923913a4 · outbound

This paper cites DiBrita, Daniel Leeds, Yuqian Huo, Jason Lud- mir, and Tirthak Patel.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers DiBrita, Daniel Leeds, Yuqian Huo, Jason Lud- mir, and Tirthak Patel

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.662232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1f09567b-8175-461d-8be0-8ef91f5d1d66 · outbound

This paper cites Quantum reinforcement learning.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Quantum reinforcement learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.601277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation de94e98a-4e3c-4654-8217-00b257e0710b · outbound

This paper cites Aug- mented neural odes.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Aug- mented neural odes

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.534989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 47450898-74b7-4d64-adeb-82dd870c8d11 · outbound

This paper cites Deep residual learning in spiking neural networks.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Deep residual learning in spiking neural networks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.466221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 68bf0c13-9804-4f0c-a4d8-e249cf3b8275 · outbound

This paper cites Deep residual learning for image recognition.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Deep residual learning for image recognition

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.371520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 179b7be0-f860-412e-95b1-f7bc3f11699d · outbound

This paper cites Power of data in quantum machine learning.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Power of data in quantum machine learning

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.277887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e98b8989-5262-4e04-8b43-018bbf204fe8 · outbound

This paper cites Learning to predict arbitrary quantum processes.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Learning to predict arbitrary quantum processes

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.225135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c18546ba-f5e4-45e5-81ff-073d9b30c716 · outbound

This paper cites Resqnets: a residual approach for mitigating barren plateaus in quantum neural networks.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Resqnets: a residual approach for mitigating barren plateaus in quantum neural networks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.173642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f4210cc5-6e94-44fe-b543-eca9a2215763 · outbound

This paper cites ResQuNNs: Towards Enabling Deep Learning in Quantum Convolution Neural Networks.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers ResQuNNs: Towards Enabling Deep Learning in Quantum Convolution Neural Networks

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:30:00.233844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a4995be7-39a3-413f-a786-18bde9a0b625 · outbound

This paper cites Continuous-variable quantum neural networks.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Continuous-variable quantum neural networks

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.085809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c0177a28-ad25-48a8-bd2f-35a3bf683b58 · outbound

This paper cites Large-scale quantum reservoir learning with an analog quantum computer.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Large-scale quantum reservoir learning with an analog quantum computer

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T22:29:59.170089Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f85b53d9-3d93-4c5b-be60-19e34d882fd2 · outbound

This paper cites Differentiable analog quantum computing for opti- mization and control.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Differentiable analog quantum computing for opti- mization and control

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:01.000692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 68ec2e52-1a05-4a73-8d32-287fc05385aa · outbound

This paper cites Quantum reinforcement learning during human decision-making.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Quantum reinforcement learning during human decision-making

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.880430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 03b9686a-1dd7-4667-bcb9-83ee6960ac99 · outbound

This paper cites A hybrid quantum–classical neural network with deep residual learning.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers A hybrid quantum–classical neural network with deep residual learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.792301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e3599792-03fc-4115-89d2-2056bca423d2 · outbound

This paper cites Digital-analog quantum learning on Rydberg atom arrays.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Digital-analog quantum learning on Rydberg atom arrays

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:30:00.046484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f82ece69-0fca-4218-94b3-4681c05bae93 · outbound

This paper cites Digital–analog quantum learn- ing on rydberg atom arrays.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Digital–analog quantum learn- ing on rydberg atom arrays

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.728628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c8a6844f-4906-406f-95a0-48204cfd3222 · outbound

This paper cites Opportunities in quantum reservoir com- puting and extreme learning machines.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Opportunities in quantum reservoir com- puting and extreme learning machines

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.656585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2776da7a-66ab-4c8b-8173-3ceb9befd1d8 · outbound

This paper cites Neural schr ¨odinger equation: Physical law as deep neural network.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Neural schr ¨odinger equation: Physical law as deep neural network

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.560108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b6ad2583-f1d3-4a07-8c35-dc5f04efad12 · outbound

This paper cites Disq: a novel quantum output state classification method on ibm quantum comput- ers using openpulse.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Disq: a novel quantum output state classification method on ibm quantum comput- ers using openpulse

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.500779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 83d13c7a-b7c9-4442-a4b5-df912262aba7 · outbound

This paper cites OPTIC: A Practical Quantum Binary Classifier for Near-term Quan- tum Computers.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers OPTIC: A Practical Quantum Binary Classifier for Near-term Quan- tum Computers

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.461804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4c581ebb-b5e0-43de-9b36-d51c8f8a7e4f · outbound

This paper cites Quantum convolutional neural networks (qcnn) using deep learning for computer vision applications.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Quantum convolutional neural networks (qcnn) using deep learning for computer vision applications

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.433197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9f0d88fd-8972-48a6-b4dd-2b0afc6799c5 · outbound

This paper cites ProxiML: Building Machine Learning Classifiers for Photonic Quantum Computing.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers ProxiML: Building Machine Learning Classifiers for Photonic Quantum Computing

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.402374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1b7f2b4f-59e6-40b8-a881-a4fdc6c7d7e4 · outbound

This paper cites MosaiQ: Quantum Generative Adversarial Networks for Image Generation on NISQ Computers.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers MosaiQ: Quantum Generative Adversarial Networks for Image Generation on NISQ Computers

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.360607Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 74827a60-140d-4209-84fb-534eadf229ec · outbound

This paper cites SliQ: Quantum Image Similarity Networks on Noisy Quantum Computers.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers SliQ: Quantum Image Similarity Networks on Noisy Quantum Computers

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.330083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 848f9c15-73f1-45fd-9f5d-3d0864360507 · outbound

This paper cites Quantumnat: quantum noise-aware training with noise injection, quantization and normalization.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Quantumnat: quantum noise-aware training with noise injection, quantization and normalization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T22:29:59.481485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d1544b5-cfe5-4ad9-935e-dbe4d89b3461 · outbound

This paper cites Enhancing the expressivity of quantum neural networks with residual connections.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Enhancing the expressivity of quantum neural networks with residual connections

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T22:30:00.274311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation adddd746-0f55-44ac-9909-e2af2342916e · outbound

This paper cites Non-native Quantum Generative Optimization with Adversarial Autoencoders.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Non-native Quantum Generative Optimization with Adversarial Autoencoders

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-06T22:29:59.949459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0b318420-f4d0-4e94-a70b-460c737110ee · outbound

This paper cites Aquila: QuEra's 256-qubit neutral-atom quantum computer.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Aquila: QuEra's 256-qubit neutral-atom quantum computer

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-06T22:29:59.570246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23e12b9e-6405-4986-bdb2-3e41515df965 · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T22:29:59.600612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation d2c7e231-d0fd-49ba-ac20-d103e6c6ef0a · inbound

A hardware efficient quantum residual neural network without post-selection cites this paper.

A hardware efficient quantum residual neural network without post-selection ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:36:02.786627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a2147a2a-e58a-428c-9177-7aee508c1a90 · inbound

A hardware efficient quantum residual neural network without post-selection cites this paper.

A hardware efficient quantum residual neural network without post-selection ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-22T10:54:47.572608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.