Sequence and Image Transformations with Monarq: Quantum Implementations for NISQ Devices
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Quantum Physics arXiv:2603.03582 (quant-ph) [Submitted on 3 Mar 2026] Title:Sequence and Image Transformations with Monarq: Quantum Implementations for NISQ Devices Authors:Jan Balewski, Roel Van Beeumen, E. Wes Bethel, Talita Perciano View a PDF of the paper titled Sequence and Image Transformations with Monarq: Quantum Implementations for NISQ Devices, by Jan Balewski and 3 other authors View PDF HTML (experimental) Abstract:We introduce Monarq, a unified quantum data processing framework that combines QCrank encoding with the EHands protocol for polynomial transformations, and demonstrate its implementation on noisy intermediate-scale quantum (NISQ) hardware. This framework provides fundamental quantum building blocks for signal and image processing tasks, including convolution, discrete-time Fourier transform (DFT), squared gradient computation, and edge detection, serving as a reference for a broad class of data processing applications on near-term quantum devices. Comments: Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2603.03582 [quant-ph] (or arXiv:2603.03582v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2603.03582 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Talita Perciano PhD [view email] [v1] Tue, 3 Mar 2026 23:19:34 UTC (872 KB) Full-text links: Access Paper: View a PDF of the paper titled Sequence and Image Transformations with Monarq: Quantum Implementations for NISQ Devices, by Jan Balewski and 3 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-03 References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: 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?) Links to Code Toggle Papers with Code (What is Papers with Code?) 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?)