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of superconducting qubits to quantify performance and identify limiting physical mechanisms Perform quantum device calibrations, benchmarking, and run quantum algorithms Presenting and publishing the research
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these micropollutants, per- and polyfluoroalkyl substances (PFAS) are of particular concern. Like microplastics, PFAS are highly persistent, mobile, and widely distributed, even in remote areas. Both substance groups
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Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg | Magdeburg, Sachsen Anhalt | Germany | 2 months ago
used in agriculture and industry, is not only a compelling candidate for storing and distributing H2, but also a potential fuel and a valuable chemical. On the aforementioned ground, recycling oxidized N
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) and the University of California Irvine (UCI). The Research School "Foundations of AI" focuses on advancing AI methods, including energy-efficient and privacy-aware algorithms, fair and explainable
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, economic, secure and socially just energy supply system based on renewable energy sources. We contribute to this through our main research areas of energy provision, energy distribution, energy storage and
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the era of large population size and dense genomic data such as whole-genome sequencing, new algorithms are needed to remove the bottleneck of computational load for such a development. In the frame of a
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Group (EASE IRTG), Empowering Digital Media (EDM), the Research Training Group HEARAZ , the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms
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pair distribution function (PDF) data for structure refinement and modelling of heterogeneous catalysts Publication of results in peer-reviewed scientific journals and presentation at conferences Your
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we
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are using ferroelectric memories, which can calculate AI algorithms from the field of deep learning in resistive crossbar structures with extremely low power consumption and high speed. Furthermore, we