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  Quantum fields as deep learning

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Referee this paper: arXiv:1708.07408 by Jae-Weon Lee

Please use comments to point to previous work in this direction, and reviews to referee the accuracy of the paper. Feel free to edit this submission to summarise the paper (just click on edit, your summary will then appear under the horizontal line)

(Is this your paper?)

requested Feb 25, 2018 by Giulio Prisco (190 points)
submission not yet summarized

paper authored Aug 18, 2017 to physics by  (no author on PO assigned yet) 
  • [ no revision ]

    Abstract: "In this essay we conjecture that quantum fields such as the Higgs field is related to a restricted Boltzmann machine for deep neural networks. An accelerating Rindler observer in a flat spacetime sees the quantum fields having a thermal distribution from the quantum entanglement, and a renormalization group process for the thermal fields on a lattice is similar to a deep learning algorithm. This correspondence can be generalized for the KMS states of quantum fields in a curved spacetime like a black hole.

    In Conclusions: "Our conjecture also implies a surprising possibility that the quantum fields, and hence matter in the universe, can memorize information and even can perform self-learning to some extend like DNN in a way consistent with the Strong Church-Turing thesis."

    I'm a little afraid when I read "quantum entanglement is suggested to be a source of dark energy, gravity and the spacetime itself.". But, surprisingly, there is a full compatible Bohr entanglement and at the same time hidden variables. I'm hungry of a good review.

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