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In a recent paper, a novel surface growth approach for reconstructing bulk geometry and matter fields was proposed, it was shown that this picture can be explicitly realized by the one-shot entanglement distillation tensor network and the…

High Energy Physics - Theory · Physics 2022-08-17 Chao Yu , Fang Zhong Chen , Yi-Yu Lin , Jia-Rui Sun , Yuan Sun

In this paper, we extend the surface growth scheme in AdS spacetime with a boundary in the AdS/BCFT correspondence. We show that the entanglement wedge with a boundary can be constructed from the direct growth of bulk extremal surfaces…

High Energy Physics - Theory · Physics 2024-07-16 Xihao Fang , Fangzhong Chen , Jiarui Sun

In this paper, we study the dynamical connection between the surface growth scheme and the conformal field theory with $T\bar{T}$ deformation. By utilizing the extended one-shot entanglement distillation tensor network, we find that the…

High Energy Physics - Theory · Physics 2025-07-25 Hao-Chun Liang , Jia-Rui Sun , Yuan Sun

The Multi-scale Entanglement Renormalization Ansatz (MERA) is a tensor network that provides an efficient way of variationally estimating the ground state of a critical quantum system. The network geometry resembles a discretization of…

High Energy Physics - Theory · Physics 2015-07-03 Ning Bao , ChunJun Cao , Sean M. Carroll , Aidan Chatwin-Davies , Nicholas Hunter-Jones , Jason Pollack , Grant N. Remmen

Tensor networks are a powerful formalism for transforming one set of degrees of freedom to another. They have been heavily used in analyzing the geometry of bulk/boundary correspondence in conformal field theories. Here we develop a…

Strongly Correlated Electrons · Physics 2019-09-26 Xiongjie Yu , David Pekker , Bryan K. Clark

We investigate a recent conjecture connecting the AdS/CFT correspondence and entanglement renormalization tensor network states (MERA). The proposal interprets the tensor connectivity of the MERA states associated to quantum many body…

High Energy Physics - Theory · Physics 2013-06-27 Javier Molina-Vilaplana

In tensor networks, a geometric operation of pushing a bond cut surface toward a minimal surface corresponds to entanglement distillation. Cutting bonds defines a reduced transition matrix on the bond cut surface and the associated quantum…

High Energy Physics - Theory · Physics 2022-10-17 Takato Mori , Hidetaka Manabe , Hiroaki Matsueda

This paper demonstrates a method for tensorizing neural networks based upon an efficient way of approximating scale invariant quantum states, the Multi-scale Entanglement Renormalization Ansatz (MERA). We employ MERA as a replacement for…

Neural and Evolutionary Computing · Computer Science 2018-12-14 Andrew Hallam , Edward Grant , Vid Stojevic , Simone Severini , Andrew G. Green

A tensor network is a diagram that specifies a way to "multiply" a collection of tensors together to produce another tensor (or matrix). Many existing algorithms for tensor problems (such as tensor decomposition and tensor PCA), although…

Data Structures and Algorithms · Computer Science 2018-11-05 Ankur Moitra , Alexander S. Wein

The AdS/CFT correspondence stipulates a duality between conformal field theories and certain theories of quantum gravity in one higher spatial dimension. However, probing this conjecture on contemporary classical or quantum computers is…

Quantum Physics · Physics 2024-01-25 Rahul Sahay , Mikhail D. Lukin , Jordan Cotler

This paper introduces a novel method for reconstructing meshes from sparse point clouds by predicting edge connection. Existing implicit methods usually produce superior smooth and watertight meshes due to the isosurface extraction…

Computer Vision and Pattern Recognition · Computer Science 2024-07-17 Weimin Wang , Yingxu Deng , Zezeng Li , Yu Liu , Na Lei

Reconstruction of signals from compressively sensed measurements is an ill-posed problem. In this paper, we leverage the recurrent generative model, RIDE, as an image prior for compressive image reconstruction. Recurrent networks can model…

Computer Vision and Pattern Recognition · Computer Science 2017-05-05 Akshat Dave , Anil Kumar Vadathya , Kaushik Mitra

We present an algorithm for supervised learning using tensor networks, employing a step of preprocessing the data by coarse-graining through a sequence of wavelet transformations. We represent these transformations as a set of tensor…

Machine Learning · Statistics 2020-01-24 Justin Reyes , Miles Stoudenmire

In the holographic correspondence of quantum gravity, a global onsite symmetry at the boundary generally translates to a local gauge symmetry in the bulk. We describe one way how the global boundary onsite symmetries can be gauged within…

Strongly Correlated Electrons · Physics 2018-01-31 Sukhwinder Singh , Nathan A. McMahon , Gavin K. Brennen

In this paper, we address the problem of reconstructing an object's surface from a single image using generative networks. First, we represent a 3D surface with an aggregation of dense point clouds from multiple views. Each point cloud is…

Computer Vision and Pattern Recognition · Computer Science 2018-11-26 Jinglu Wang , Bo Sun , Yan Lu

We propose a method for approximating the contraction of a tensor network by partitioning the network into a sum of computationally cheaper networks. This method, which we call a partitioned network expansion (PNE), builds upon recent work…

Quantum Physics · Physics 2025-12-12 Glen Evenbly , Johnnie Gray , Garnet Kin-Lic Chan

We elaborate on a previous proposal by Hartman and Maldacena on a tensor network which accounts for the scaling of the entanglement entropy in a system at a finite temperature. In this construction, the ordinary entanglement renormalization…

High Energy Physics - Theory · Physics 2014-11-04 Javier Molina-Vilaplana , Javier Prior

The multi-scale entanglement renormalization ansatz (MERA) is a tensor network representation for ground states of critical quantum spin chains, with a network that extends in an additional dimension corresponding to scale. Over the years…

High Energy Physics - Theory · Physics 2018-12-04 Ashley Milsted , Guifre Vidal

We use the framework of $\textit{fixed-point BCFT tensor networks}$ to present a microscopic CFT derivation of the correspondence between reflected entropy (RE) and entanglement wedge cross section (EW) in AdS$_3$/CFT$_2$, for both…

High Energy Physics - Theory · Physics 2026-02-17 Ning Bao , Jinwei Chu , Yikun Jiang , Jacob March

We investigate the reconstruction of asymptotically anti-de Sitter (AdS) bulk geometries from boundary entanglement entropy data for ball-shaped entangling regions. By deriving an explicit inversion formula, we relate variations in…

High Energy Physics - Theory · Physics 2025-12-22 Niko Jokela , Tony Liimatainen , Miika Sarkkinen , Leo Tzou
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