Beyond-classical Machine learning and AI for Quantum Physics

Project Information

BeMAIQuantum

Grant agreement ID: 101124342

DOI

10.3030/101124342

EC signature date 6 February 2024

Start date 1 April 2024

End date 31 March 2029

Funded under

• European Research Council (ERC)

Total cost

€ 1 995 289,00

EU contribution

€ 1 995 289,00

Coordinated by

UNIVERSITEIT LEIDEN
Netherlands

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Peer reviewed articles (10)

Parameterized quantum circuits as universal generative models for continuous multivariate distributions

Author(s): Barthe, A.M.; Grossi, M.; Vallecorsa, S.; Tura Brugués, J.; Dunjko, V.
Published in: npj Quantum Information, 2025, ISSN 2056-6387
Publisher: Springer Nature
DOI: 10.48550/ARXIV.2402.09848

Variational quantum generative modeling by sampling expectation values of tunable observables

Author(s): Shen, Kevin; Kurkin, Andrii; Pérez-Salinas, Adrián; Shishenina, Elvira; Dunjko, Vedran; Wang, Hao
Published in: npj Quantum Information, 2025, ISSN 2056-6387
Publisher: Springer Nature
DOI: 10.48550/ARXIV.2412.17039

Detecting underdetermination in parameterized quantum circuits

Author(s): Marie Kempkes; Jakob Spiegelberg; Evert van Nieuwenburg; Vedran Dunjko
Published in: Machine Learning: Science and Technology, 2026, ISSN 2632-2153
Publisher: IOP
DOI: 10.48550/ARXIV.2504.03315

Error and resource estimates of variational quantum algorithms for solving differential equations based on Runge-Kutta methods

Author(s): David Dechant; Liubov Markovich; Vedran Dunjko; Jordi Tura
Published in: Journal of Mathematical Physics, 2026, ISSN 1089-7658
Publisher: AIP
DOI: 10.48550/ARXIV.2412.12262

Exponential quantum advantages in learning quantum observables from classical data

Author(s): Molteni, Riccardo; Gyurik, Casper; Dunjko, Vedran
Published in: npj Quantum Information, 2026, ISSN 2056-6387
Publisher: Springer Nature
DOI: 10.48550/ARXIV.2405.02027

Quantum generative modeling for financial time series with temporal correlations

Author(s): David Dechant, Eliot Schwander, Lucas van Drooge, Charles Moussa, Diego Garlaschelli, Vedran Dunjko, Jordi Tura
Published in: Machine Learning: Science and Technology, Issue 7, 2026, ISSN 2632-2153
Publisher: IOP Publishing
DOI: 10.1088/2632-2153/AE39A2

Double Descent in Quantum Kernel Methods

Author(s): Marie Kempkes; Aroosa Ijaz; Elies Gil-Fuster; Carlos Bravo-Prieto; Jakob Spiegelberg; Evert van Nieuwenburg; Vedran Dunjko
Published in: PRX Quantum, 2026, ISSN 2691-3399
Publisher: APS
DOI: 10.17169/REFUBIUM-51671

Weighted Approximate Quantum Natural Gradient for Variational Quantum Eigensolver

Author(s): Chenyu Shi, Vedran Dunjko, Hao Wang
Published in: Quantum Science and Technology, 2026, ISSN 2058-9565
Publisher: IOP
DOI: 10.1088/2058-9565/AE3FC8

Trainability maximization using estimation of distribution algorithms assisted by surrogate modelling for quantum architecture search

Author(s): Soliviev, V.P.; Dunjko, V.; Bielza, C.; Larranaga, P.; Wang, H.
Published in: EPJ Quantum Technology, 2024, ISSN 2196-0763
Publisher: Springer Nature
DOI: 10.48550/ARXIV.2407.20091

Universal approximation of continuous functions with minimal quantum circuits

Author(s): Adrián Pérez-Salinas; Mahtab Yaghubi Rad; Alice Barthe; Vedran Dunjko
Published in: Physical Review Research, 2025, ISSN 2643-1564
Publisher: APS
DOI: 10.48550/ARXIV.2411.19152

Conference proceedings (3)

Quantum machine learning advantages beyond hardness of evaluation

Author(s): Riccardo Molteni, Simon C. Marshall, Vedran Dunjko
Published in: International Conference on Learning Representations (ICLR 2025), 2026
Publisher: OpenReview.net

Improved separation between quantum and classical computers for sampling and functional tasks

Author(s): Marshall, Simon C.; Aaronson, Scott; Dunjko, Vedran
Published in: Proceedings of the 40th Computational Complexity Conference (CCC 2025), 2025
Publisher: Schloss Dagstuhl – Leibniz-Zentrum für Informatik
DOI: 10.4230/LIPICS.CCC.2025.5

On the relation between trainability and dequantization of variational quantum learning models

Author(s): Elies Gil-Fuster; Casper Gyurik; Adrián Pérez-Salinas; Vedran Dunjko
Published in: International Conference on Learning Representations (ICLR 2025)., 2024
Publisher: OpenReview.net
DOI: 10.48550/ARXIV.2406.07072