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Related papers: AdS/CFT as a deep Boltzmann machine

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We present a deep neural network representation of the AdS/CFT correspondence, and demonstrate the emergence of the bulk metric function via the learning process for given data sets of response in boundary quantum field theories. The…

High Energy Physics - Theory · Physics 2018-09-12 Koji Hashimoto , Sotaro Sugishita , Akinori Tanaka , Akio Tomiya

We apply the relation between deep learning (DL) and the AdS/CFT correspondence to a holographic model of QCD. Using a lattice QCD data of the chiral condensate at a finite temperature as our training data, the deep learning procedure…

High Energy Physics - Theory · Physics 2020-02-14 Koji Hashimoto , Sotaro Sugishita , Akinori Tanaka , Akio Tomiya

Deep Boltzmann machines (DBMs), one of the first ``deep'' learning methods ever studied, are multi-layered probabilistic models governed by a pairwise energy function that describes the likelihood of all variables/nodes in the network. In…

Machine Learning · Computer Science 2023-07-12 Zhili Feng , Ezra Winston , J. Zico Kolter

The bulk reconstructions in AdS/CFT and its cousins are essential to understand the holographic nature of quantum gravity. In this work, we try to study the bulk reconstruction in the AdS$_3$/WCFT$_2$ correspondence. After deriving the…

High Energy Physics - Theory · Physics 2019-10-30 Yu-han Lin , Bin Chen

According to the AdS/CFT correspondence, the geometries of certain spacetimes are fully determined by quantum states that live on their boundaries -- indeed, by the von Neumann entropies of portions of those boundary states. This work…

Quantum Physics · Physics 2023-04-26 Scott Aaronson , Jason Pollack

The Boltzmann Machine (BM) is a neural network composed of stochastically firing neurons that can learn complex probability distributions by adapting the synaptic interactions between the neurons. BMs represent a very generic class of…

Mesoscale and Nanoscale Physics · Physics 2021-09-16 Brian Kiraly , Elze J. Knol , Hilbert J. Kappen , Alexander A. Khajetoorians

We propose a deep learning method to build an AdS/QCD model from the data of hadron spectra. A major problem of generic AdS/QCD models is that a large ambiguity is allowed for the bulk gravity metric with which QCD observables are…

High Energy Physics - Theory · Physics 2020-07-29 Tetsuya Akutagawa , Koji Hashimoto , Takayuki Sumimoto

We develop a systematic method for renormalizing the AdS/CFT prescription for computing correlation functions. This involves regularizing the bulk on-shell supergravity action in a covariant way, computing all divergences, adding…

High Energy Physics - Theory · Physics 2009-10-31 Sebastian de Haro , Kostas Skenderis , Sergey N. Solodukhin

Motivated by the theory of holographic quantum error correction in the anti-de Sitter/conformal field theory (AdS/CFT) correspondence, together with the kink transform conjecture on the bulk AdS description of boundary cocycle flow, we…

Operator Algebras · Mathematics 2024-12-03 Jason Crann , Monica Jinwoo Kang

In this paper we present a dimensional renormalization scheme suitable for holographic theories. We use the bulk physics in the supergravity limit as a definition of the dual CFT. Similar to the perturbative quantization of a QFT, one is…

High Energy Physics - Theory · Physics 2016-12-14 Adam Bzowski

The deep Boltzmann machine (DBM) has been an important development in the quest for powerful "deep" probabilistic models. To date, simultaneous or joint training of all layers of the DBM has been largely unsuccessful with existing training…

Neural and Evolutionary Computing · Computer Science 2012-03-21 Guillaume Desjardins , Aaron Courville , Yoshua Bengio

Central to the AdS/CFT correspondence is a precise relationship between the curvature of an anti-de Sitter (AdS) spacetime and the central charge of the dual conformal field theory (CFT) on its boundary. Our work shows that such a…

High Energy Physics - Theory · Physics 2020-12-07 Alexander Jahn , Zoltán Zimborás , Jens Eisert

We develop a holographic framework for describing the experience of bulk observers in AdS/CFT, that allows us to compute the proper time and energy distribution measured along any bulk worldline. Our method is formulated directly in the CFT…

High Energy Physics - Theory · Physics 2021-09-01 Daniel Louis Jafferis , Lampros Lamprou

Recent work has shown that entanglement and the structure of spacetime are intimately related. One way to investigate this is to begin with an entanglement entropy in a conformal field theory (CFT) and use the AdS/CFT correspondence to…

High Energy Physics - Theory · Physics 2021-01-13 Ashton Lowenstein , Avik Chakraborty

The AdS/CFT correspondence states an equivalence between a quantum gravitational theory in a (d+1)-dimensional anti-de Sitter spacetime (AdS$_{d+1}$) and a d-dimensional conformal field theory (CFT$_{d}$). The CFT$_{d}$ lives on the…

High Energy Physics - Theory · Physics 2025-12-23 Hao Geng , Daniel Jafferis , Pushkal Shrivastava , Neeraj Tata

The flat/CFT dictionary between the bulk gravitational theory and boundary conformal field theory is systematically developed in this paper. Asymptotically flat spacetime is built up by asymptotically AdS hyperboloid slices in terms of…

High Energy Physics - Theory · Physics 2024-04-02 Zezhuang Hao

We point out a connection between the emergence of bulk locality in AdS/CFT and the theory of quantum error correction. Bulk notions such as Bogoliubov transformations, location in the radial direction, and the holographic entropy bound all…

High Energy Physics - Theory · Physics 2015-07-29 Ahmed Almheiri , Xi Dong , Daniel Harlow

The correlation function in Ads/CFT are correlation of the operator insertions on the boundary (at CFT) through the complete geometry of bulk. These are represented by Witten diagrams which at tree level doesn't have any quantum…

High Energy Physics - Theory · Physics 2024-05-20 Aryaman Mishra

There is a strong interest in studying the correspondence between Euclidean quantum fields and neural networks. This correspondence takes different forms depending on the type of networks considered. In this work, we study this…

High Energy Physics - Theory · Physics 2023-10-30 W. A. Zúñiga-Galindo

According to AdS/DL (Anti de Sitter/ Deep Learning) correspondence given by \cite{Has}, in this paper with a data-driven approach and leveraging holography principle we have designed an artificial neural network architecture to produce…

General Physics · Physics 2024-01-03 Emad Yaraie , Hossein Ghaffarnejad , Mohammad Farsam
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