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Irreversible aggregation is revisited in view of recent work on renormalization of complex networks. Its scaling laws and phase transitions are related to percolation transitions seen in the latter. We illustrate our points by giving the…

Data Analysis, Statistics and Probability · Physics 2011-08-26 Seung-Woo Son , Golnoosh Bizhani , Claire Christensen , Peter Grassberger , Maya Paczuski

On the topic of probabilistic rewriting, there are several works studying both termination and confluence of different systems. While working with a lambda calculus modelling quantum computation, we found a system with probabilistic…

Logic in Computer Science · Computer Science 2022-04-11 Rafael Romero , Alejandro Díaz-Caro

Data transformation, normalization and handling of batch effect are a key part of data analysis for almost all spectrometry-based omics data. This paper reviews and contrasts these three distinct aspects. We present a systematic overview of…

Methodology · Statistics 2016-06-20 Bart J. A. Mertens

Butcher series appear when Runge-Kutta methods for ordinary differential equations are expanded in power series of the step size parameter. Each term in a Butcher series consists of a weighted elementary differential, and the set of all…

Numerical Analysis · Mathematics 2018-09-05 Robert I McLachlan , Klas Modin , Hans Munthe-Kaas , Olivier Verdier

We review some recent learning approaches in variational imaging, based on bilevel optimisation, and emphasize the importance of their treatment in function space. The paper covers both analytical and numerical techniques. Analytically, we…

Optimization and Control · Mathematics 2016-08-08 Luca Calatroni , Cao Chung , Juan Carlos De Los Reyes , Carola-Bibiane Schönlieb , Tuomo Valkonen

The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability…

Methodology · Statistics 2013-10-15 Mingyuan Zhou , Lawrence Carin

We extend to quenched disordered systems the variational scheme for real space renormalization group calculations that we recently introduced for homogeneous spin Hamiltonians. When disorder is present our approach gives access to the flow…

Statistical Mechanics · Physics 2020-11-11 Yantao Wu , Roberto Car

A distributed-memory parallelization strategy for the density matrix renormalization group is proposed for cases where correlation functions are required. This new strategy has substantial improvements with respect to previous works. A…

Strongly Correlated Electrons · Physics 2010-04-20 Julian Rincon , D. J. Garcia , K. Hallberg

An original regular approach to constructing special type symmetries for boundary value problems, namely renormgroup symmetries, is presented. Different methods of calculating these symmetries, based on modern group analysis are described.…

High Energy Physics - Theory · Physics 2009-10-30 V. F. Kovalev , V. V. Pustovalov , D. V. Shirkov

We investigate to what extent renormalization can be understood as an algebraic manipulation on concatenated one-loop integrals. We find that the resulting algebra indicates a useful connection to knot theory.

High Energy Physics - Theory · Physics 2008-02-03 Dirk Kreimer

We propose an algorithm for evaluation of the cumulative bivariate normal distribution, building upon Marsaglia's ideas for evaluation of the cumulative univariate normal distribution. The algorithm is mathematically transparent, delivers…

Numerical Analysis · Mathematics 2018-09-19 Christian Meyer

As applied to quantum theories, the program of renormalization is successful for `renormalizable models' but fails for `nonrenormalizable models'. After some conceptual discussion and analysis, an enhanced program of renormalization is…

High Energy Physics - Theory · Physics 2009-05-01 John R. Klauder

Reconstructing training data from trained neural networks is an active area of research with significant implications for privacy and explainability. Recent advances have demonstrated the feasibility of this process for several data types.…

Machine Learning · Computer Science 2024-11-26 Ran Elbaz , Gilad Yehudai , Meirav Galun , Haggai Maron

We consider the method of self-similar renormalization for calculating critical temperatures and critical indices. A new optimized variant of the method for an effective summation of asymptotic series is suggested and illustrated by several…

Statistical Mechanics · Physics 2009-10-30 S. Gluzman , V. I. Yukalov

The application of renormalization group methods to microscopic nuclear many-body calculations is discussed. We present the solution of the renormalization group equations in the particle-hole channels for neutron matter and the application…

Nuclear Theory · Physics 2007-05-23 A. Schwenk , B. Friman , G. E. Brown

We present some clues to the study of the renormalization group, at graduate level, as well as some bibliographical pointers to classical resources. Just the kind of things one had liked to hear when starting to study the subject.

High Energy Physics - Theory · Physics 2007-05-23 Alejandro Rivero

Calculating multiple zeta values at arguments of any sign in a way that is compatible with both the quasi-shuffle product as well as meromorphic continuation, is commonly referred to as the renormalisation problem for multiple zeta values.…

Number Theory · Mathematics 2019-01-18 Kurusch Ebrahimi-Fard , Dominique Manchon , Johannes Singer , Jianqiang Zhao

I give an outline of recent applications of the renormalisation group to effective theories of nuclear forces, focussing on the use of a Wilsonian approach to analyse systems of two or three nonrelativistic particles.

Nuclear Theory · Physics 2015-05-20 Michael C. Birse

We extend the classical construction of operator colligations and characteristic functions. Consider the group $G$ of finite block unitary matrices of size $\alpha+\infty+...+\infty$ ($k$ times). Consider the subgroup $K=U(\infty)$, which…

Representation Theory · Mathematics 2017-08-08 Yury A. Neretin

A recently proposed renormalization group approach to dimensional crossover in quasi-one-dimensional quantum antiferromagnets is improved and then shown to give identical results, in some cases, to those obtained earlier.

Condensed Matter · Physics 2008-11-26 Ian Affleck , Bertrand I. Halperin
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