Restricted Modulation Freedom Enhances Noise Robustness in Coherent Diffractive Optical Networks

[2605.30820] Restricted Modulation Freedom Enhances Noise Robustness in Coherent Diffractive Optical Networks Skip to main content Search Submit Donate Log in Physics > Optics arXiv:2605.30820 (physics) [Submitted on 29 May 2026 ( v1 ), last revised 28 Aug 2026 (this version, v2)] Title: Restricted Modulation Freedom Enhances Noise Robustness in Coherent Diffractive Optical Networks Authors: Hyuntae Lim , Kyoungsik Kim View PDF Abstract: In coherent diffractive optical networks, greater modulation freedom allows more flexible optimization for clean inputs, but its effect on noise robustness and its physical origin remain unclear. We derive an analytical framework that identifies the physical mechanism linking modulation freedom to noise robustness. To establish this connection, we compare a continuous DDNN (C-DDNN) with continuous amplitude and phase modulation and a binary-mask DDNN (BM-DDNN) with binary amplitude modulation. Trained only on clean MNIST data, the seven-layer BM-DDNN has 1.83 percentage points lower clean test accuracy but 32.82 percentage points higher noisy test accuracy under pixel-wise Gaussian noise. This robustness advantage cannot be explained by lower total noise-only intensity at the imaging plane: the BM-DDNN has 3.22 times the noise-only intensity but 8.64 times the clean-signal intensity of the C-DDNN, reducing noise contamination relative to the clean signal. We show that this difference arises from a clean-signal transmission bias generated by spatial correlations between the structured clean-signal field and learned modulation patterns. We quantify this mechanism with a cumulative transmission-bias factor K, linking modulation freedom to relative noise contamination and robustness. The C-DDNN exhibits a stronger suppressive bias (more negative K), whereas the BM-DDNN exhibits a weaker bias (less negative K^{\tilde}), yielding the consistent ordering K<K^{\tilde}. Because K requires only clean-data forward passes, it serves as a robustness screening metric before noisy-input simulations. Comments: 17 pages, 5 figures Subjects: Optics (physics.optics) ; Applied Physics (physics.app-ph) Cite as: arXiv:2605.30820 [physics.optics] (or arXiv:2605.30820v2 [physics.optics] for this version) https://doi.org/10.48550/arXiv.2605.30820 Focus to learn more arXiv-issued DOI via DataCite Submission history From: Kyoungsik Kim [ view email ] [v1] Fri, 29 May 2026 04:11:23 UTC (848 KB) [v2] Fri, 28 Aug 2026 04:59:27 UTC (1,158 KB) Full-text links: Access Paper: View PDF view license Current browse context: physics.optics < prev | next > new | recent | 2026-05 Change to browse by: physics physics.app-ph References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab) Major funding support from

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