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Related papers: Renormalization Group and Curved Spacetime

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We present a new type of generalization of the Renyi entropy that follows naturally from its representation as a thermodynamic quantity. We apply it to the case of d-dimensional conformal field theories (CFTs) reduced on a region bounded by…

High Energy Physics - Theory · Physics 2019-05-29 Clifford V. Johnson

In this article, we define and study a geometry and an order on the set of partitions of an even number of objects. One of the definitions involves the partition algebra, a structure of algebra on the set of such partitions depending on an…

Combinatorics · Mathematics 2016-11-01 Franck Gabriel

There remains an important need for the development of image reconstruction methods that can produce diagnostically useful images from undersampled measurements. In magnetic resonance imaging (MRI), for example, such methods can facilitate…

Image and Video Processing · Electrical Eng. & Systems 2021-06-28 Varun A. Kelkar , Sayantan Bhadra , Mark A. Anastasio

The exact renormalization group is used to study the RG flow of quantities in field theories. The basic idea is to write an evolution operator for the flow and evaluate it in perturbation theory. This is easier than directly solving the…

High Energy Physics - Theory · Physics 2022-05-18 Prafulla Oak , B. Sathiapalan

When undergraduates ask me what geometric group theorists study, I describe a theorem due to Gromov which relates the groups with an intrinsic geometry like that of the hyperbolic plane to those in which certain computations can be…

Group Theory · Mathematics 2014-12-08 Jon McCammond

We derive the renormalization group equations for a generic nonrenormalizable theory. We show that the equations allow one to derive the structure of the leading divergences at any loop order in terms of one-loop diagrams only. In chiral…

High Energy Physics - Phenomenology · Physics 2009-11-10 Matthias Buchler , Gilberto Colangelo

Neural compression is the application of neural networks and other machine learning methods to data compression. Recent advances in statistical machine learning have opened up new possibilities for data compression, allowing compression…

Machine Learning · Computer Science 2023-08-22 Yibo Yang , Stephan Mandt , Lucas Theis

The physics of complex systems stands to greatly benefit from the qualitative changes in data availability and advances in data-driven computational methods. Many of these systems can be represented by interacting degrees of freedom on…

Statistical Mechanics · Physics 2024-11-27 Doruk Efe Gökmen , Sounak Biswas , Sebastian D. Huber , Zohar Ringel , Felix Flicker , Maciej Koch-Janusz

We study central configurations when the set of positions is symmetric. We use a theorem from representation theory of finite groups to explore the symmetry properties of equations for central configurations. This approach simplifies…

Dynamical Systems · Mathematics 2025-08-06 Marcelo P. Santos , Leon D. da Silva

We develop a holonomy reduction procedure for general Cartan geometries. We show that, given a reduction of holonomy, the underlying manifold naturally decomposes into a disjoint union of initial submanifolds. Each such submanifold…

Differential Geometry · Mathematics 2014-05-08 Andreas Cap , A. Rod Gover , Matthias Hammerl

Refraction is a common physical phenomenon and has long been researched in computer vision. Objects imaged through a refractive object appear distorted in the image as a function of the shape of the interface between the media. This hinders…

Computer Vision and Pattern Recognition · Computer Science 2023-06-01 Antonin Sulc , Imari Sato , Bastian Goldluecke , Tali Treibitz

We develop a method for optimization in shape spaces, i.e., sets of surfaces modulo re-parametrization. Unlike previously proposed gradient flows, we achieve superlinear convergence rates through a subtle approximation of the shape Hessian,…

Computer Vision and Pattern Recognition · Computer Science 2014-04-15 J. Balzer , S. Soatto

The exact renormalization group (ERG) is formulated implementing the decimation of degrees of freedom by means of a particular momentum integration measure. The definition of this measure involves a distribution that links this decimation…

High Energy Physics - Theory · Physics 2023-01-25 Roberto Trinchero

We provide a non-technical overview of recent extensions of renormalization methods and techniques to Group Field Theories (GFTs), a class of combinatorially non-local quantum field theories which generalize matrix models to dimension $d…

General Relativity and Quantum Cosmology · Physics 2016-07-19 Sylvain Carrozza

Graphs are a fundamental abstraction in computer science and discrete mathematics, where information is encoded in their combinatorial structure. Graph-reduction techniques aim at simplifying graphs while preserving selected structural…

Data Structures and Algorithms · Computer Science 2026-03-04 Elia Onofri

Natural images tend to mostly consist of smooth regions with individual pixels having highly correlated spectra. This information can be exploited to recover hyperspectral images of natural scenes from their incomplete and noisy…

Computer Vision and Pattern Recognition · Computer Science 2016-11-03 Reza Arablouei , Frank de Hoog

Renormalization-Group (RG) improvement has been frequently applied to capture the effect of quantum corrections on cosmological and black-hole spacetimes. This work utilizes an algebraically complete set of curvature invariants to establish…

General Relativity and Quantum Cosmology · Physics 2021-05-26 Aaron Held

The renormalization group has proven to be a very powerful tool in physics for treating systems with many length scales. Here we show how it can be adapted to provide a new class of algorithms for discrete optimization. The heart of our…

Disordered Systems and Neural Networks · Physics 2009-10-31 J. Houdayer , O. C. Martin

Renormalization plays an important role in the theoretically and mathematically careful analysis of models in condensed-matter physics. I review selected results about correlated-fermion systems, ranging from mathematical theorems to…

Strongly Correlated Electrons · Physics 2019-05-01 Manfred Salmhofer

In the classical source coding problem, the compressed source is reconstructed at the decoder with respect to some distortion metric. Motivated by settings in which we are interested in more than simply reconstructing the compressed source,…

Information Theory · Computer Science 2023-10-03 Oğuzhan Kubilay Ülger , Elza Erkip