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We propose a hybrid model of simplicial quantum gravity by performing at once dynamical triangulations and Regge calculus. A motive for the hybridization is to give a dynamical description of topology-changing processes of Euclidean…

High Energy Physics - Lattice · Physics 2007-05-23 Hiroyuki Hagura

Tensor network algorithms have been remarkably successful solving a variety of problems in quantum many-body physics. However, algorithms to optimize two-dimensional tensor networks known as PEPS lack many of the aspects that make the…

Strongly Correlated Electrons · Physics 2020-04-22 Katharine Hyatt , E. M. Stoudenmire

Consider the partition function of a classical system in two spatial dimensions, or the Euclidean path integral of a quantum system in two space-time dimensions, both on a lattice. We show that the tensor network renormalization (TNR)…

Strongly Correlated Electrons · Physics 2016-01-29 Glen Evenbly , Guifre Vidal

We review some recent attempts to extract information about the nature of quantum gravity, with and without matter, by quantum field theoretical methods. More specifically, we work within a covariant lattice approach where the individual…

High Energy Physics - Theory · Physics 2007-05-23 J. Ambjorn , J. Jurkiewicz , R. Loll

Searching for new non-perturbatively renormalizable quantum gravity theories, functional renormalization group (RG) flows are studied on a theory space of action functionals depending on the metric and the torsion tensor, the latter…

High Energy Physics - Theory · Physics 2016-03-23 Martin Reuter , Gregor M. Schollmeyer

We develop a density matrix renormalization group (DMRG) algorithm for constrained quantum lattice models that successfully {\it{implements the local constraints as symmetries in the contraction of the matrix product states and matrix…

Strongly Correlated Electrons · Physics 2025-08-11 Ting-Tung Wang , Xiaoxue Ran , Zi Yang Meng

We apply Monte Carlo Renormalization group to the crumpling transition in random surface models of fixed connectivity. This transition is notoriously difficult to treat numerically. We employ here a Fourier accelerated Langevin algorithm in…

High Energy Physics - Lattice · Physics 2009-10-28 D. Espriu , A. Travesset

We report recent progress on the application of the tensor renormalization group (TRG) to quantum field theories pursued by the Tsukuba group. We explain how to treat the scalar, fermion, and gauge theories with the TRG method presenting…

High Energy Physics - Lattice · Physics 2022-09-21 Shinichiro Akiyama , Yoshinobu Kuramashi , Yusuke Yoshimura

We study the logarithmic correction to the scaling of the first Lee-Yang (LY) zero in the classical $XY$ model on square lattices by using tensor renormalization group methods. In comparing the higher-order tensor renormalization group…

Statistical Mechanics · Physics 2022-07-28 Seongpyo Hong , Dong-Hee Kim

In this thesis, we present a novel method combining energy-based finite-size scaling with tensor network renormalization (TNR) to study phase transitions in lattice models. This approach effectively calculates running coupling constants and…

Statistical Mechanics · Physics 2024-02-01 Atsushi Ueda

Segre-Veronese manifolds are smooth submanifolds of tensors comprising the partially symmetric rank-1 tensors. We investigate a one-parameter family of warped geometries of Segre-Veronese manifolds, which includes the standard Euclidean…

Numerical Analysis · Mathematics 2026-01-27 Simon Jacobsson , Lars Swijsen , Joeri Van der Veken , Nick Vannieuwenhoven

Low-rank tensor completion recovers missing entries based on different tensor decompositions. Due to its outstanding performance in exploiting some higher-order data structure, low rank tensor ring has been applied in tensor completion. To…

Machine Learning · Computer Science 2020-07-14 Huyan Huang , Yipeng Liu , Ce Zhu

We show that the numerical strong disorder renormalization group algorithm (SDRG) of Hikihara et. al. [Phys. Rev. B 60, 12116 (1999)] for the one-dimensional disordered Heisenberg model naturally describes a tree tensor network (TTN) with…

Disordered Systems and Neural Networks · Physics 2014-07-01 Andrew M. Goldsborough , Rudolf A. Römer

In 1961 Tullio Regge provided us with a beautiful lattice representation of Einstein's geometric theory of gravity. This Regge Calculus (RC) is strikingly different from the more usual finite difference and finite element discretizations of…

General Relativity and Quantum Cosmology · Physics 2008-04-03 Jonathan R. McDonald , Warner A. Miller

Robust tensor completion (RTC) aims to recover a low-rank tensor from its incomplete observation with outlier corruption. The recently proposed tensor ring (TR) model has demonstrated superiority in solving the RTC problem. However, the…

Machine Learning · Computer Science 2023-02-16 Zhenhao Huang , Yuning Qiu , Xinqi Chen , Weijun Sun , Guoxu Zhou

Although tensor networks are powerful tools for simulating low-dimensional quantum physics, tensor network algorithms are very computationally costly in higher spatial dimensions. We introduce quantum gauge networks: a different kind of…

Quantum Physics · Physics 2023-09-20 Kevin Slagle

We study 2D quantum gravity on spherical topologies using the Regge calculus approach. Our goal is to shed new light upon the validity of the Regge approach to quantum gravity, which has recently been questioned in the literature. We…

High Energy Physics - Lattice · Physics 2009-10-28 Christian Holm , Wolfhard Janke

The phase structure of the two dimensional lattice CP(1) model in the presence of the $\theta$ term is analyzed by tensor network methods. The tensor renormalization group, which is a standard renormalization method of tensor networks, is…

High Energy Physics - Lattice · Physics 2018-04-18 Hikaru Kawauchi , Shinji Takeda

This article presents detailed discussions and calculations of the recent paper "Quantum Regge calculus of Einstein-Cartan theory" in Phys. Lett. B682 (2009) 300. The Euclidean space-time is discretized by a four-dimensional simplicial…

High Energy Physics - Theory · Physics 2010-10-08 She-Sheng Xue

We propose a second renormalization group method to handle the tensor-network states or models. This method reduces dramatically the truncation error of the tensor renormalization group. It allows physical quantities of classical…

Strongly Correlated Electrons · Physics 2024-06-26 Z. Y. Xie , H. C. Jiang , Q. N. Chen , Z. Y. Weng , T. Xiang