Paper Citation Record · LEDGER

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems

As of 14 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2506.23173.

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

pith.paper-citation-record.v1
2506.23173 v1

Coverage vector

measured 22 of 22 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

22 of 22 outbound references displayed

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Outbound references

Observation de9fb916-147d-43f0-b19d-0bb8ae77a6b5 · outbound

This paper cites Malacara,Optical Shop Testing (John Wiley & Sons, Hoboken, NJ, 2007), 3rd ed.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Malacara,Optical Shop Testing (John Wiley & Sons, Hoboken, NJ, 2007), 3rd ed

Reference 1

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Observation 74e2d50f-793b-4624-87cf-e136e325fa57 · outbound

This paper cites an unresolved cited work.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T21:51:25.625210Z

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Observation 683a7c33-c7ba-4e17-bf50-71f59671325e · outbound

This paper cites Extended hartmann test based on the pseudoguiding property of a hartmann maskcompleted by a phase chessboard,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Extended hartmann test based on the pseudoguiding property of a hartmann maskcompleted by a phase chessboard,

Reference 3

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Observation 01aad398-cb2a-44af-afff-6e98332483c4 · outbound

This paper cites The use of primary mirrors as hartmann masks for in situ alignment of segmented mirror telescopes,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems The use of primary mirrors as hartmann masks for in situ alignment of segmented mirror telescopes,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:25.424025Z

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Observation 5cb5a56a-dd0e-4591-b627-0c37376e4710 · outbound

This paper cites Developments in optical testing technology during the last decade,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Developments in optical testing technology during the last decade,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:25.223841Z

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Observation cfcae713-5991-4abb-92e2-151d727b291c · outbound

This paper cites Telescope alignment by out-of-focus stellar image analysis,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Telescope alignment by out-of-focus stellar image analysis,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:25.073150Z

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Observation e867bcea-ed27-4e32-b781-bfaf31ff785c · outbound

This paper cites Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Neural-network-directed alignment of optical systems using the laser-beam spatial filter as an example,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:24.917459Z

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Observation a173fdd0-7c98-4104-b939-084dff15815a · outbound

This paper cites Deep learning in optical metrology: a review,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Deep learning in optical metrology: a review,

Reference 8

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Observation 1ab25630-c0da-48c7-b4d7-6d21ea35ff5c · outbound

This paper cites Deep learning-enabled framework for automatic lens-design starting-point generation,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Deep learning-enabled framework for automatic lens-design starting-point generation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:24.555498Z

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Observation 3df81789-3881-4854-b76c-af7a21a6bb61 · outbound

This paper cites Accelerating optics-design optimizations with deep learning,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Accelerating optics-design optimizations with deep learning,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:24.376752Z

Source-reported events for the cited work

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Observation 854ad571-cfa6-4c43-bcad-7fb4369007cc · outbound

This paper cites Approach for self-optimising assembly of optical systems,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Approach for self-optimising assembly of optical systems,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:24.177601Z

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Observation 7d979a6d-2558-4044-9432-9bd2f6da9858 · outbound

This paper cites Determining optimal assembly condition for lens module production by combining genetic algorithm and c-blstm,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Determining optimal assembly condition for lens module production by combining genetic algorithm and c-blstm,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:24.002909Z

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Observation e3373286-d706-4e06-a0dc-01e1f59f4b33 · outbound

This paper cites Opticalsystemoptimizationmethodforas-builtperformancebasedonnodalaberration theory,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Opticalsystemoptimizationmethodforas-builtperformancebasedonnodalaberration theory,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:23.784896Z

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Observation ee7dd18a-f8bb-4dc1-a67d-eebee7f992ed · outbound

This paper cites Application of deep learning in active alignment leads to high-efficiency and accurate camera lens assembly,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Application of deep learning in active alignment leads to high-efficiency and accurate camera lens assembly,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:23.571418Z

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Observation 9bee0f05-daf6-4359-bd2d-7ecb2bc262b8 · outbound

This paper cites Pointspreadfunctionestimationforwide-fieldsmall-aperturetelescopeswithdeepneural networks and calibration data,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Pointspreadfunctionestimationforwide-fieldsmall-aperturetelescopeswithdeepneural networks and calibration data,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:23.385091Z

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Observation 6a4eecaa-2268-4b77-abf9-e91da05c8b3d · outbound

This paper cites Improvingneural-network-basedpredictionmodelsformisalignmentinoff-axisthree-mirror anastigmat telescopes,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Improvingneural-network-basedpredictionmodelsformisalignmentinoff-axisthree-mirror anastigmat telescopes,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:23.177991Z

Source-reported events for the cited work

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Observation b84740aa-2556-4097-b886-7c44da6efc5f · outbound

This paper cites Machine learning for improving stellar image-based alignment in wide-field telescopes,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Machine learning for improving stellar image-based alignment in wide-field telescopes,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:23.026403Z

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Observation 8816a980-338b-4248-aefc-5a9bc393ff85 · outbound

This paper cites Perception of misalignment states for sky survey telescopes with digital twin and deep neural networks,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Perception of misalignment states for sky survey telescopes with digital twin and deep neural networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:22.887515Z

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Observation 520b42a7-b08a-47a5-b154-bf2c30505681 · outbound

This paper cites Tolerance-Aware Deep Optics.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Tolerance-Aware Deep Optics

Reference 19

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Source-reported events for the cited work

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Observation 33bf2d73-6d19-47a2-bbaa-5f50d42a5507 · outbound

This paper cites Method for optical adjustment with deep learning to quantitatively predict misalignment in optics,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems Method for optical adjustment with deep learning to quantitatively predict misalignment in optics,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:22.668768Z

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Observation 27b9f032-c4a3-4b54-b878-5ef1d7443099 · outbound

This paper cites GitHub repository.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems GitHub repository

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:22.494219Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 63405391-e464-4637-bdc9-47a90170d976 · outbound

This paper cites 3doptix: Cloud-based optical design and simulation platform,.

Deep Learning for Optical Misalignment Diagnostics in Multi-Lens Imaging Systems 3doptix: Cloud-based optical design and simulation platform,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:51:22.288033Z

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No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

No inbound Pith citation observations are available.