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Physics for neuromorphic computing [PDF]
Nature Reviews Physics, 2020 Neuromorphic computing takes inspiration from the brain to create energy efficient hardware for information processing, capable of highly sophisticated tasks. In this article, we make the case that building this new hardware necessitates reinventing electronics. We show that research in physics and material science will be key to create artificial nano-
Danijela Marković +3 more
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Applied Sciences, 2022 Prevention of type-1 human immunodeficiency virus (HIV) infections has primarily been through condom usage, abstinence, and behavioral and risk awareness programs.
Jeramy Lewis, Robert E. Camley
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iScience, 2023 Summary: With pre-trained large models and their associated fine-tuning paradigms being constantly applied in deep learning, the performance of large models achieves a dramatic boost, mostly owing to the improvements on both data quantity and quality ...
Xinyu Pan +9 more
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Jurnal Neutrino: Jurnal Fisika dan Aplikasinya, 2021 Neutrino can carry information from places that cannot be reached by the usual detection mechanism because it has a very weak interaction with matter. This can be utilized to study the heat flow process inside the earth by using information carried by ...
Akmal Ferdiyan +1 more
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Smörgåsbords for Physical Computing
Proceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction, 2021 Physical computing concerns the design of systems that can sense and respond to the world around them, which is why it is often used in interaction design projects in educational settings. However, students who encounter physical computing for the first time are typically not aware of the form factors and the potential for interaction of the various ...
Boer, Laurens +3 more
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Transverse confinement of electron beams in a 2D optical lattice for compact coherent x-ray sources
New Journal of Physics, 2021 Compact coherent x-ray sources have been the focus of extensive research efforts over the past decades. As a result, several novel schemes like optical and nano-undulators for generating x-ray emissions in ‘table-top’ setups are proposed, developed, and ...
Arya Fallahi +2 more
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Equivariant neural networks for spin dynamics simulations of itinerant magnets
Machine Learning: Science and Technology, 2023 I present a novel equivariant neural network architecture for the large-scale spin dynamics simulation of the Kondo lattice model. This neural network mainly consists of tensor-product-based convolution layers and ensures two equivariances: translations ...
Yu Miyazaki
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Computability and Physical Theories [PDF]
Foundations of Physics, 1986 The familiar theories of physics have the feature that the application of the theory to make predictions in specific circumstances can be done by means of an algorithm. We propose a more precise formulation of this feature --- one based on the issue of whether or not the physically measurable numbers predicted by the theory are computable in the ...
Geroch, Robert, Hartle, James B.
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Bayesian averaging for ground state masses of atomic nuclei in a Machine Learning approach
Frontiers in Physics, 2023 We present global predictions of the ground state mass of atomic nuclei based on a novel Machine Learning algorithm. We combine precision nuclear experimental measurements together with theoretical predictions of unmeasured nuclei.
Matthew Mumpower +6 more
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Matter and Radiation at Extremes, 2021 We report significant differences in high-pressure properties of vanadium at zero temperature and finite temperature when different projector augmented wave (PAW) potentials are used in simulations based on density functional theory. When a PAW potential
Tingting Zhang +8 more
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