Conférences - Physique de la matière condensée et des matériaux - Suède

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Machine Learning for Quantum Matter
26 aou 2019 - 28 aou 2019 • Stockholm, Suède
Machine learning has entered the field of quantum matter with applications covering quantum materials and the many-body problem. For example, interpretable and computationally-efficient machine learning models are able to capture the structure-property relationship in materials science. In case of the many-body problem, machine learning architectures provide versatile wavefunctions that lead to accurate results and prove to be more flexible than traditional methods. Conversely, methods in physics have also influenced the development of machine learning methods in the case of tensor networks. The workshop will feature talks by leading experts combined with the talks of younger participants to present a broad picture of the activities and best ideas on the use of ML methods in quantum matter.
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Quantum Materials for Dark Matter Detection
09 sep 2019 - 13 sep 2019 • Stockholm, Suède
In the search for dark matter (DM), one particular focus is on light and ultra-light dark matter, i.e. sub-GeV mass dark matter from a hidden dark sector with a new force interacting with the standard model or ultra-light DM with mass range from 10-22 eV to keV. The arguably most popular example of the latter class is the axion, invoked to solve the apparent absence of CP violation in Quantum Chromo Dynamics. Detection of these particles poses new challenges to potential sensor materials: very small energy depositions, magnetic properties and anisotropic response to particle interactions for example become crucial requirements. The challenge of finding suitable materials fits well with recent developments in solid state physics: Motivated by the exponential growth of computational power and the resulting data, we witness the rapid adoption of functional materials prediction within the framework of materials informatics. Here, methods adapted from computer science based on data-mining and machine learning are applied to identify materials with requested target properties.
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Sujets apparentés:
SXNS16 — 16th International Conference on Surface X-ray and Neutron Scattering
23 jui 2020 - 26 jui 2020 • Lund, Suède
European Spallation Source and Max IV Laboratory
The conference is co-organized by the European Spallation Source and Max IV Laboratory and will emphasize novel techniques for surface x-ray and neutron scattering including instrumentation and source development.
in-situ and in-operando surface studies, nanostructured surfaces and interfaces, surface and interfaces in soft matter, biological interfaces, emergent interfacial materials, and dynamics of surfaces, interfaces and nanostructures
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Dernière mise à jour: 30 Juillet 2019