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Paper Citation Record · LEDGER

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

As of 19 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 3 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 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:05:20.964803Z

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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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 2026-08-19T06:32:44.657259+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:58.740293Z digest=sha256:dc2b19e3134cb98d0592ad2072ae1e2291cb4b08cb7a8e49172e28582c2259cd

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:58.781991Z digest=sha256:0134251b512be772630e0fe213833bca505d400995c6b90007ec1f17b279ce38

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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Source-reported events for the cited work

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:58.955195Z digest=sha256:d03faa0b0fe80076ed5a2ccb8058c3d5018866ab7fab5d7d1a3aee6919719ba6

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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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 2026-08-19T06:32:44.657259+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.088651Z digest=sha256:cde25ee2c9aa6eed755fe4838eb901b6a3abbc3408136a716c0f0ed42701fce2

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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local_arxiv, observed 2026-08-06T22:30:00.233844Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.121243Z digest=sha256:a93aaacf4c56215e2dd5410e08839c22224de54e32d205cad2743095f4e04546

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.146253Z digest=sha256:48a7d9c1abacebf66cfe760edd28c0e5d87c78d3be30ee8fff157bb8fd91ecf5

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:29:59.170089Z digest=sha256:d093396919463782ea7c5daae20f3e8f9fa7ca583309a536e64dd0901e5f584a

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.197472Z digest=sha256:fe822cc83d6440f348b6212db34b9f18f1956b024308a0e12cd50ae9fb9a48d5

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

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.215854Z digest=sha256:aa4a985e2440b45096f4fe39c2f5146e1552c52a9ea38f27b46b37e23a82cb3b

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.236980Z digest=sha256:a18a59f6f62bae17713dd122d86cac6a793d1b8ee09ddce9fb81fdbc9b36090c

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

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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 2026-08-19T06:32:44.657259+00:00.

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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

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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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.281949Z digest=sha256:4c2ecdb7e7ae38b1a7c26fd93e6f6b3cd6206770bb7d25a00a52e480cff288a8

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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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

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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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.345360Z digest=sha256:0180eaf51480315468306f30593d27da740dc0e30320c38770ca7fadd0d5ebce

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.372067Z digest=sha256:786467a11f9fe154bb4f7df6767a80c7c97dfd30a34c46f102f93635cf609a2c

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

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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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.391970Z digest=sha256:f34f8f42a3b69b220f9def3be21d5c881b5d4b19bc6e1e4e2d6b4f6c7f9a9e39

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

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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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.411741Z digest=sha256:69df960717f6453b8fe0c235625c15980533487541f57ee02be3ab08ed12793a

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.435251Z digest=sha256:5a7ee5ce287275213381842cfd4b2c7a2e2d0f9c4f5caacb9e41228f517f72f4

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.459065Z digest=sha256:747b874d779c3e89d96ddd9f56cdc5c741f967c758755094b8019ce164b1b5ad

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.

source=pdf_text observed=2026-08-06T22:29:59.481485Z digest=sha256:48876b32f429a2b038898e2a3d86d83aa3ca148ddf9e78fb20276400e5baaf93

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.506430Z digest=sha256:c44335faa69a83c671c2860049010f99b7b1bc93d15616e2e5e998cd07139136

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-06T22:29:59.534826Z digest=sha256:018f9e809ba343a27d50b03845788b01d8e49120a5fe19ebb02eb2afc78f30e0

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.

source=pdf_text observed=2026-08-06T22:29:59.570246Z digest=sha256:c0da08f7bc1a1ccdc582dd6c680392d15125782c3c1c3837e5c55a46e1dbddf5

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.

source=pdf_text observed=2026-08-06T22:29:59.600612Z digest=sha256:fce5488a7729e5f0ee1b54cc7c491e4217c61387cb7cdc22d32d1bc833af94c5

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T18:02:04.838369Z digest=sha256:3f45bf0876f2b054760749897800e7d56776570428c3b34b5d68863ac7ae3a59

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-22T10:54:21.066630Z digest=sha256:555168cab64cee4a294e81597b6a6ce1575284bc9c59e244305a2b8d74f259d1

Observation 15ebaf75-ee07-4acd-8649-be75cc673744 · inbound

PaQit: Energy-Runtime-Fidelity Co-Optimization for Neutral Atom Quantum Computers cites this paper.

PaQit: Energy-Runtime-Fidelity Co-Optimization for Neutral Atom Quantum Computers ResQ: A Novel Framework to Implement Residual Neural Networks on Analog Rydberg Atom Quantum Computers

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T15:05:20.964803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:05:20.964803Z digest=sha256:f1b776c664af9b5eee875b20b0cb323bf9c649eccf4d404edb32125399cd3fdb