Results 11 to 20 of about 114,088 (215)
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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Computational Complexity in Physics [PDF]
, 2001 This is a brief review paper summarizing talks at the NATO school on Complexity and Large Deviations in Geilo, Norway, 2001.
Cristopher Moore
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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 ...
James B. Hartle, Robert Geroch
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Polymer Physics by Quantum Computing [PDF]
Physical Review Letters, 2021 Supplementary Material ...
Micheletti, Cristian +2 more
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Morphological Computation: Nothing but Physical Computation [PDF]
Entropy, 2018 The purpose of this paper is to argue against the claim that morphological computation is substantially different from other kinds of physical computation. I show that some (but not all) purported cases of morphological computation do not count as specifically computational, and that those that do are solely physical computational systems. These latter
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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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Physics-Informed Deep Learning for Traffic State Estimation: A Survey and the Outlook
Algorithms, 2023 For its robust predictive power (compared to pure physics-based models) and sample-efficient training (compared to pure deep learning models), physics-informed deep learning (PIDL), a paradigm hybridizing physics-based models and deep neural networks ...
Xuan Di +3 more
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Quantum physics and computers [PDF]
Contemporary Physics, 1996 27 pages, LaTeX, 8 PostScript figures embedded. A bug in one of the postscript files has been fixed. Reprints available from the author.
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Dual-Antenna Microwave Ablation of Liver Tumor from the 3D-IRCADb-01 Database [PDF]
International Journal of BiomedicineMicrowave ablation (MWA) is a minimally invasive energy-based thermal ablative technique designed to destroy tumor cells using microwave energy. Each tumor indeed has unique characteristics, including size, shape, and location, which significantly ...
Nikola Bošković +2 more
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Unifying projected entangled pair state contractions
New Journal of Physics, 2014 The approximate contraction of a tensor network of projected entangled pair states (PEPS) is a fundamental ingredient of any PEPS algorithm, required for the optimization of the tensors in ground state search or time evolution, as well as for the ...
Michael Lubasch +2 more
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