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arXiv:2505.23860quant-ph

Quantum computing and artificial intelligence: status and perspectives

Giovanni Acampora, Andris Ambainis, Natalia Ares, Leonardo Banchi, Pallavi Bhardwaj, Daniele Binosi, G. Andrew D. Briggs, Tommaso Calarco, Vedran Dunjko, Jens Eisert, Olivier Ezratty, Paul Erker, Federico Fedele, Elies Gil-Fuster, Martin Gärttner, Mats Granath, Markus Heyl, Iordanis Kerenidis, Matthias Klusch, Anton Frisk Kockum, Richard Kueng, Mario Krenn, Jörg Lässig, Antonio Macaluso, Sabrina Maniscalco, Florian Marquardt, Kristel Michielsen, Gorka Muñoz-Gil, Daniel Müssig, Hendrik Poulsen Nautrup, Sophie A. Neubauer, Evert van Nieuwenburg, Roman Orus, Jörg Schmiedmayer, Markus Schmitt, Philipp Slusallek, Filippo Vicentini, Christof Weitenberg, Frank K. Wilhelm

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

This white paper discusses and explores the various points of intersection between quantum computing and artificial intelligence (AI). It describes how quantum computing could support the development of innovative AI solutions. It also examines use cases of classical AI that can empower research and development in quantum technologies, with a focus on quantum computing and quantum sensing. The purpose of this white paper is to provide a long-term research agenda aimed at addressing foundational questions about how AI and quantum computing interact and benefit one another. It concludes with a set of recommendations and challenges, including how to orchestrate the proposed theoretical work, align quantum AI developments with quantum hardware roadmaps, estimate both classical and quantum resources - especially with the goal of mitigating and optimizing energy consumption - advance this emerging hybrid software engineering discipline, and enhance European industrial competitiveness while considering societal implications.

arXiv comments
33 pages, 3 figures
Journal reference
DOI
Subjects
quant-phQuantum Physics cs.AIArtificial Intelligence cs.LGMachine Learning

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Linked by 1 identifiable commenter in 1 comment across 1 thread, from Mar 2026 to Mar 2026. Found in 2 HN submissions from Jun 2025 to Mar 2026. Open submission discussions.

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Discussed in comments1 thread

    • > aaand you entered the "hype and irrational" territory. I dare you to reread your own comment, it is funny You have not understood the first thing about what i had pointed out. > right now QC is 5 orders of magnitude away from practical systems - there's NO profit to invest…

      rramadassView on HNParent context

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