CSIC researchers open the door to revolutionising quantum technologies thanks to artificial intelligence and cold atoms
The CINN, ICMM and INMA institutes are participating alongside the CVC public consortium in a project funded with almost two million euros by the Ministry of Science, Innovation and Universities
The research teams will work on a type of quantum bits called “Rydberg atoms”
The project combines experimental and theoretical approaches.
Zaragoza, 15 December 2025. The quantum technology revolution involves the use of artificial intelligence and machine learning for its development and advancement. This is the idea behind a new project led by the Spanish National Research Council (CSIC) through the Centre for Research in Nanomaterials and Nanotechnology (CINN, CSIC-Uniovi – Principality of Asturias) and involving the participation of the Institute of Materials Science of Madrid (ICMM) and the Institute of Nanoscience and Materials of Aragon (INMA, a joint institute of the CSIC and the University of Zaragoza).
This project, entitled “Machine Learning in Quantum Simulations with Rydberg Atoms” and funded by the Ministry of Science, Innovation and Universities (MCIU), ‘combines quantum computing with artificial intelligence to build an advanced platform where hardware and algorithms work together to solve complex real-world problems more efficiently than classical computers,’ explains Miguel Pruneda, CSIC researcher at CINN and project coordinator. The hardware is based on Rydberg atoms, a type of highly excited atom (i.e., with a higher energy level than others) that presents itself as a promising platform for the development of quantum computing.
‘We know that this type of Rydberg atom has unique properties that make it a very good candidate for scalable quantum computing, as it combines strong interactions between atoms with long coherence times,’ explains Sigmund Kohler, a researcher at ICMM-CSIC and leader of one of the work packages. The challenge with this type of array lies in how to control these atoms. ‘And this is something we can address thanks to artificial intelligence and machine learning,’ adds Yue Ban, also a researcher at ICMM-CSIC.
The experts explain that this project involves ‘disruptive research’ that uses artificial intelligence to control and interpret quantum systems based on Rydberg atoms, which in turn can solve complex optimisation problems using quantum algorithms: ‘This project has the potential to revolutionise both the experimental design and theoretical understanding of complex quantum phenomena,’ adds Jesús Carrete, a CSIC researcher at INMA (CSIC-UNIZAR).
Another interesting aspect of the proposal put forward by these three CSIC centres, together with the Computer Vision Centre (CVC, in Catalonia), is the multidisciplinary approach that combines experimental innovation with computational advances. The project is thus presented as a series of interconnected nodes through which the experimental procedures used to calibrate the systems for the experiments will be optimised, while improving the fidelity and scalability of the computational simulations and designing new quantum algorithms that will, in turn, be specifically optimised for the experimental platform.
Finally, they will also explore the use of these methods in other fields of application, such as quantum chemistry, telecommunications antenna distribution, and electrical grid stability. ‘Together, the synergistic study of quantum software and hardware will contribute to the creation of robust solutions’ that will also be useful in other areas of knowledge.
From the laboratory to the computer, and vice versa
The project has been designed with a multi-node, multi-regional structure that will draw on the expertise of each working team. Coordination will be carried out from the CINN, which already has a laboratory working with Rydberg atoms. This laboratory will serve as the experimental hub of the project, the space where the previously designed quantum simulation protocols will be physically tested.
For its part, the work of INMA in Aragón will focus on the use of neural networks to estimate the properties of many-body quantum systems. These techniques will provide powerful theoretical tools for understanding complex quantum models formed by spins and for optimising the experimental platform. In this way, ‘the quantum simulator itself will be simulated within the project’.
In Madrid, the ICMM team will focus on the development of quantum algorithms, with special emphasis on quantum optimisation methods and novel approaches. ‘This work will result in the creation of high-level quantum applications, linking theoretical development with future hardware implementation,’ Kohler celebrates.
Finally, the CVC in Barcelona will contribute its experience in both classical machine learning and quantum machine learning techniques to support the other nodes in the execution of methodological tasks. Specifically, the CVC will provide advice on the implementation of machine learning and, in turn, will structure the research avenues for technological use cases of quantum machine learning, for example, in artificial vision applications.
INMA, Severo Ochoa Centre of Excellence
The Aragon Nanoscience and Materials Institute (INMA) was the first in our Autonomous Community to obtain Severo Ochoa accreditation of excellence, awarded by the State Research Agency. This recognition entails funding of 4.5 million euros and the provision of five pre-doctoral contracts for the period 2024-2028.
INMA is a joint institute of the CSIC and the University of Zaragoza. With around 300 members, it has more than 40 European projects underway and an annual average of 300 publications and €7 million obtained in competitive public programmes. It also works in collaboration with industry, earning around €1 million per year from contracts and royalties.
Cover photo: Jonathan Castañeda/Unsplash
