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SummaryIn 2025, machine learning continues to revolutionize various scientific fields, with major implications in physics, particularly photonics. The integration of advanced machine learning algorithms has enabled significant advances in the design and control of photonic systems, improving their efficiency and performance. These advances are essential for the development of communication, imaging and quantum computing technologies. However, physics research presents many challenges that go beyond simple performance measurements: identifying patterns and building analytical models is often just as crucial.In this thesis, we apply computational intelligence tools, in particular heuristic optimization and neural networks, to develop data-driven approaches to solving various tasks in physics. Although data-centric, our approach remains rooted in physics, always seeking to understand the physical phenomena underlying the algorithms. The results of this thesis cover a wide range of applications, from the design of complex metasurfaces and diffraction gratings to the analysis and interpretation of spectral data. We have also successfully developed an optimizer capable of learning and adapting to the problems encountered, particularly in physics. This key tool in our arsenal outperforms state-of-the-art methods in our applications. In particular, it has enabled the design of a coronagraphic phase plate for exoplanet imaging, with a performance 25% better than the best previous solutions.We have also designed a compact, all-dielectric beam deflection device, operating efficiently for all polarizations, reaching a maximum efficiency of 90%. Starting from a purely data-driven design, we were able to extract and validate an analytical model based on the behavior of an echelle lattice, providing a physical understanding of its operation. In addition to simulation-based tasks, we also processed experimental data, developing an animal origin classifier for scrolls, capable of distinguishing three animal species with 90% accuracy. This tool offers a non-invasive method for conservators and historians wishing to analyze fragile historical materials.Jury members Prof. Michaël LOBET (UNamur), PresidentProf. Alexandre MAYER (UNamur), SecretaryDr. Charlotte BEAUTHIER (CENAREO)Prof. Benoît FRENAY (UNamur)Prof. Olivier DEPARIS (UNamur)Prof. Denis LANGEVIN (Université de Clermont Auvergne)Prof. Hai Son NGUYEN (Ecole Centrale de Lyon)

The first global conference of Chinese materials researchers took place from July 22 to 28, 2025, at the University of Namur. Organized by Professor Bao-Lian Su, director of the Inorganic Materials Chemistry Laboratory (CMI) of the Nanomaterials Chemistry Unit (UCNano) in the Chemistry Department at the University of Namur, Belgium, in collaboration with Professor Qing-Jie Zhang of Wuhan University of Technology (China) and Professor Max Gao-Qing Lu of the University of Wollongong (Australia), the event brought together nearly 500 participants. 

A project submitted by Professor Frédéric Silvestre's Laboratoire de Physiologie Évolutive et Adaptative (LEAP) at the University of Namur has been ranked among the top 6 research projects funded by the FNRS and the Fonds de recherche du Québec (FRQ) for scientific collaboration between Wallonia and Quebec. The aim? To understand the impact of human activities on St. Lawrence Estuary (SLE) belugas, using interdisciplinary approaches to help improve conservation strategies for this threatened species..

In early September, the University of Namur hosted the first Main-Group Elements Reactivity Conference (MG-ERC). Over 100 researchers from 12 countries and 32 institutions gathered around Professor Guillaume Berionni. An event hailed as "one of the best chemistry conferences" by its prestigious guests.

SummaryAt a time when a stream of research was striving to reformulate quantum mechanics by abolishing operators and substituting functions, Wigner and Szilard proposed in 1932 a quasi-probability distribution defined on phase space thanks to wave functions. They did not explain its genesis.The first part of our thesis proposes a genesis of this quasi-distribution, based on the natural conditions it must fulfill. It briefly examines a pathology it suffers from: exhibiting negative values in certain subdomains of the phase space (hence the "quasi"), a pathology that does no harm to the calculation of mean values. She then shows how, if we take spin into account, with wave functions giving way to spinners, we are led, thanks to the calculation of mean values of observables, to a generalization of this quasi-distribution in the form of a Hermitian matrix. This approach is extended to the Wigner cross transform, i.e. to weak values.An important theorem, which has been the subject of a publication, is proved in the second part of our thesis. Using harmonic analysis, this result expresses weak values in terms of an integral over a Lie group acting on the Hilbert space under consideration. We give two particular examples: SU(2) and SO(3). The case of a quotient group is briefly discussed.In a third section, we recall the well-known link between Clifford algebras and two important equations of quantum physics: the Klein-Gordon and Dirac equations, and its generalization to Riemannian spacetimes.Finally, in a fourth section we introduce spin groups, and use the spin group Spin(3,2) in the context of the Wigner cross transform discussed in the first section.JuryProf. André FÜZFA (UNamur), PresidentProf. Yves CAUDANO (UNamur), SecretaryDr. Thomas DURT (Institut Fresnel and Ecole Centrale Marseille, Marseille, France)Prof. Romain MURENZI (Worcester Polytecnic Institute)Prof. Dominique LAMBERT (UNamur)Prof. Bertrand HESPEL (UNamur)Prof. André HARDY (UNamur)

A team of American researchers, with the help of Frédérik De Laender, professor in the Department of Biology at UNamur, has just published in the prestigious journal Nature. Their study describes how changing stream temperatures and human introductions of fish can alter river biodiversity in the USA.

Two researchers from the University of Namur's Department of Physics, Professor Michaël Lobet and his PhD student Adrien Debacq, are taking a close look at a subject that fascinates the scientific community : superradiance in media with a refractive index close to zero. In an article published this summer in Nature's prestigious journal Light: science & applications, in collaboration with Harvard University (USA), Michigan Technological University (MTU) and Sparrow Quantum, they contribute to the development of quantum computing.