Titlebook: Deep Learning and Physics; Akinori Tanaka,Akio Tomiya,Koji Hashimoto Book 2021 The Editor(s) (if applicable) and The Author(s), under excl

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Dynamical Systems and Neural Networkss. In this chapter, we show that such multi-layer propagation can be interpreted as the time evolution of dynamical systems, and hence of Hamiltonian systems, and look at the close relationship between the fundamental concept of “time evolution” in physics and deep neural networks.

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Application to Superstring Theoryes gravity and other forces, and in recent years, the “holographic principle,” that the world governed by gravity is equivalent to the world of other forces, has been actively studied. We will solve the inverse problem of the emergence of the gravitational world by applying the correspondence to the

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Epilogueoto) are also co-authors of research papers in this interdisciplinary field. Collaborative research is something that is only fun if people who share the same ambition but have different backgrounds gather. We guess that readers have started reading this book with various motivations, but in fact, a

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Application to Superstring Theoryforces, has been actively studied. We will solve the inverse problem of the emergence of the gravitational world by applying the correspondence to the dynamical system seen in Chap. 9, and look at the new relationship between machine learning and spacetime.

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Formal Model for Program Analysisstical mechanics, such as the law of large numbers, the central limit theorem, the Markov chain Monte Carlo method, the principle of detailed balance, the Metropolis method, and the heat bath method, are also used in machine learning. Familiarity with common concepts in physics and machine learning can lead to an understanding of both.

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Workplace: The Office and Beyond the Officeidge between machine learning and physics. Generative adversarial networks are also one of the important topics in deep learning in recent years, and we try to provide an explanation of it from a physical point of view.

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0921-3767 physics problems written so that readers can soon imagine hWhat is deep learning for those who study physics? Is it completely different from physics? Or is it similar??.In recent years, machine learning, including deep learning, has begun to be used in various physics studies. Why is that? Is know