Spin-based information processing is a viable alternative to charge-based approaches, enabling low-power devices. In magnetically ordered systems, spin information can be transported via the quantized excitations of the magnetic lattice, called magnons. In an antiferromagnetic system, we generally find two degenerate magnon modes with opposite Néel precession chirality, i.e., opposite spin. These two modes can couple and give rise to complex dynamics and superposition states. I could show that these dynamics can be well described via the pseudospin and its dynamics. My group showed experimentally that electrical pure spin current injection and detection in hematite thin films gives access to the coherent pseudospin dynamics and leads to the manifestation of the magnon Hanle effect. I propose to investigate the coherent spin dynamics induced by pure spin currents in antiferromagnetic insulators, which open up new avenues for energy-efficient information processing beyond von Neumann architectures. The project aims to achieve three main objectives: 1) Establish an experimental platform for pseudospin-based antiferromagnetic magnonics with efficient generation, manipulation, and detection of pseudospin states utilizing antiferromagnetic insulators. This provides the potential for a paradigm shift in magnonics away from wave-based towards spin-based information processing and encoding. 2) Realize pure spin current-driven spin-torque oscillators in antiferromagnetic insulators. This enables the on-chip generation of frequency combs in the microwave and terahertz regime and coherent magnon generation. 3) Explore spiking artificial neurons based on antiferromagnetic spin-torque oscillators. This provides a pathway towards energy-efficient magnonic neural networks and reservoir computing. The successful project will have a transformative effect for energy-efficient information processing, on-chip generation of frequency combs, and hardware for artificial neural networks.

High altitude precipitation and the related accumulation rates on the glaciers are variables with the highest uncertainties, when it comes to assessing the status of the cryosphere in High Mountain Asia (HMA), especially in the poorly documented Pamir Mountains in Central Asia. Within the RECAP project, we propose an integrated study, which combines novel field observations with state of the art analysis of remote sensing observations to feed into regional climate models and detailed modelling of the snow and firn conditions. The central objective of this proposal is to better quantify the spatio-temporal variability of accumulation and precipitation at high elevation in the Pamir Mountains, from local scale (centered on Fedchenko Glacier) to regional scale and assess its evolution over the past century (1900-present). Methodology - During the course of the RECAP project, the Modèle Atmosphérique Régional (MAR) will be configured to produce the first centennial atmospheric reanalysis covering the period 1900-present over the whole Pamir mountains. The model will be calibrated using both local meteorological observations (WP1 and existing data from the past) and remote sensing data (WP2), and testing different global reanalysis as lateral conditions. Finally, we will produce a reanalysis covering the period since 1900, the time span leading from almost natural conditions to a strong increase of anthropogenic impact on the climate and cryospheric system (WP3). The data produced will be used to investigate the variability of both climate and cryosphere from daily to centennial timescales. Snow modelling will help to relate precipitation and accumulation at high elevation (WP4), which is not straightforward considering that surface processes such as sublimation, melt or snow drift may reduce the amount of solid precipitation deposited on glaciers. The synthesis (WP5) will provide an integrated overview of the regional climate changes in the Pamir mountains, and in particular its impact on the cryosphere. Impacts - The climate and surface mass balance reconstruction from the RECAP project is all the most needed and timely as a deep core will be extracted from the accumulation basin of Fedchenko Glacier in 2024 within the funded PAMIR project (funded by the Swiss Polar Institute). The project outcomes will help interpret this ice core, in particular to assess whether the climate conditions and changes from the core are representative of the region, and to assess how surface mass balance processes (melt, sublimation, snow drift) have changed over the last decades in response to the anthropogenic impacts on climate. The collaboration between the Bavarian Academy of Sciences and Humanities and the Institut des Géosciences de l’Environnement will foster rich exchanges, and will complement existing bilateral collaborations with the research teams of Fribourg University and from the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). All the members of the project are engaged in capacity building, which will consist in the development of the collaboration with scientists of Center for the Glaciers Study of the National Academy of Sciences of Tajikistan (CRG) in Dushanbe. Tadjik partners will join the project members in the field and will visit the Bavarian Academy of Science for a training session. Risk assessments - We carefully selected the field sites to offer the best compromise between the feasibility of the measurements and their spatial variability. The PIs of the project have a long standing record of investigating glacier systems in the Alps and HMA. The team is experienced in remote sensing, climate modelling and surface mass balance process modelling, meaning that partial success of the field campaigns will still allow the project to be largely successful in the other aspects.

This project seeks to establish a radically new technology platform for experiments in macroscopic quantum physics and for quantum enabled sensing. We exploit magnetic coupling between superconducting quantum circuits and superconducting mechanical resonators – both levitated and suspended – to enter a hitherto inaccessible parameter regime of both unprecedented force sensitivity and full quantum control of massive, macroscopic objects. Our approach combines, in a new way, techniques from different research areas (magnetic levitation, superconducting circuits, atom-chip technology, cavity optomechanics and quantum optics) and is set up as a joint collaborative effort between expert European teams from academia and industry. Our technology will enable quantum experiments of otherwise unachievable coherence times and masses, which has immediate implications for testing fundamental physical questions, for performing hybrid quantum information processing and, on the applied side, for ultrasensitive force sensing applications.

CLARA, the Center for Artificial Intelligence and Quantum Computing in System Brain Research, represents the interdisciplinary center of excellence focused on the next generation of artificial intelligence/machine learning applications and quantum-centric supercomputing tools to push the frontier of neurodegeneration research, particularly Alzheimer´s disease. The project seeks deep field knowledge and processing of large-scale biological and clinical data that will enrich collective understanding of these emerging technologies, solve real-world challenges, thus accelerating innovations and the future of computing for the benefit of society. Finally, building a domain specific hybrid computing and data infrastructure platform based on emerging EuroHPC Joint Undertaking computing resources, CLARA will significantly contribute to development of the European computing and data ecosystem in the field of system brain research. CLARA will be established as the autonomous division of the International Neurodegenerative Disorders Research Center (INDRC) in Prague, Czech Republic. CLARA is built upon a strong consortium of INDRC as the coordinator (with its affiliated partner VSB-Technical University Ostrava), the Czech Institute of Informatics, Robotics, and Cybernetics of the Czech Technical University in Prague, and the International Clinical Research Center of the St. Anne's University Hospital, all based in the Czech Republic, a low R&I performing country, with two prominent collaborative European research organizations from advanced countries: Paris Brain Institute (France) and Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities (Germany).