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We address the question of symmetries of an important type of quantum walks. We introduce all the necessary definitions and provide a rigorous formulation of the problem. Using a thorough analysis, we reach the complete answer by presenting…

Quantum Physics · Physics 2012-11-02 Václav Potoček

This work combines three paradigms of image processing: i) the total variation approach to denoising, ii) the superior structure of hexagonal lattices, and iii) fast and exact graph cut optimization techniques. Although isotropic in theory,…

Optimization and Control · Mathematics 2012-04-18 Clemens Kirisits

Asymmetric lineshapes are experimentally observed in Raman spectra of different classes of condensed matter. Determination of the peak parameters, typically done with symmetric pseudo-Voigt functions, in such situations yields unreliable…

Other Condensed Matter · Physics 2018-05-11 Vitaly I. Korepanov , Darya M. Sedlovets

By studying $\mathbb{A}^1$-curves on varieties, we propose a geometric approach to strong approximation problem over function fields of complex curves. We prove that strong approximation holds for smooth, low degree affine complete…

Algebraic Geometry · Mathematics 2015-10-16 Qile Chen , Yi Zhu

We discuss a general parametrization for vertices of quantum graphs and show, in particular, how the $\delta'_s$ and $\delta'$ coupling at an $n$ edge vertex can be approximated by means of $n+1$ couplings of the $\delta$ type provided the…

Quantum Physics · Physics 2009-11-10 Taksu Cheon , Pavel Exner

Graph-based methods have proven to be effective in capturing relationships among points for 3D point cloud analysis. However, these methods often suffer from suboptimal graph structures, particularly due to sparse connections at boundary…

Computer Vision and Pattern Recognition · Computer Science 2026-01-19 Shangbo Yuan , Jie Xu , Ping Hu , Xiaofeng Zhu , Na Zhao

We study spherical, charged and self--similar distributions of matter in the diffusion approximation. We propose a simple, dynamic but physically meaningful solution. For such a solution we obtain a model in which the distribution becomes…

General Relativity and Quantum Cosmology · Physics 2009-11-11 W. Barreto , A. Da Silva

We derive the exact probability density function of the product of $N$ independent variance-gamma random variables with zero location parameter. We then apply this formula to derive formulas for the cumulative distribution function and…

Probability · Mathematics 2025-08-05 Robert E. Gaunt , Siqi Li , Heather Sutcliffe

The aim of the paper is to present numerical results supporting the presence of conformal invariance in three dimensional statistical mechanics models at criticality and to elucidate the geometric aspects of universality. As a case study we…

Statistical Mechanics · Physics 2015-10-05 G. Gori , A. Trombettoni

We show that for every countable group, any sequence of approximate homomorphisms with values in permutations can be realized as the restriction of a sofic approximation of an orbit equivalence relation. Moreover, this orbit equivalence…

Group Theory · Mathematics 2024-11-20 Ben Hayes , Srivatsav Kunnawalkam Elayavalli

We develop unbiased strategies to probabilistic T-wave snowball sampling from graphs, where the interest of estimation may concern finite-order subgraphs such as triangles, cycles or stars. Our approaches encompass also the…

Methodology · Statistics 2023-05-24 Melike Oguz-Alper , Li-Chun Zhang

In this paper, we propose a unified convergence analysis for a class of generic shuffling-type gradient methods for solving finite-sum optimization problems. Our analysis works with any sampling without replacement strategy and covers many…

Optimization and Control · Mathematics 2021-09-21 Lam M. Nguyen , Quoc Tran-Dinh , Dzung T. Phan , Phuong Ha Nguyen , Marten van Dijk

A main task in data analysis is to organize data points into coherent groups or clusters. The stochastic block model is a probabilistic model for the cluster structure. This model prescribes different probabilities for the presence of edges…

Machine Learning · Computer Science 2020-09-24 Alexander Jung

This paper considers a general data-fitting problem over a networked system, in which many computing nodes are connected by an undirected graph. This kind of problem can find many real-world applications and has been studied extensively in…

Machine Learning · Computer Science 2017-04-14 Ying Zhang

The graph is one of the most widely used mathematical structures in engineering and science because of its representational power and inherent ability to demonstrate the relationship between objects. The objective of this work is to…

Data Structures and Algorithms · Computer Science 2021-01-01 Shri Prakash Dwivedi

The purpose of this paper is to analyze the asymptotic behaviour in the spirit of $\Gamma$-convergence of BMO-type functionals related to the total variation of a function $u$. Moreover, we deal with a minimization problem coming from…

Analysis of PDEs · Mathematics 2024-03-04 Serena Guarino Lo Bianco , Roberta Schiattarella

A geometric setup for constrained variational calculus is presented. The analysis deals with the study of the extremals of an action functional defined on piecewise differentiable curves, subject to differentiable, non-holonomic…

Mathematical Physics · Physics 2015-05-08 Enrico Massa , Danilo Bruno , Gianvittorio Luria , Enrico Pagani

In this paper we introduce the notion of second-order total generalized variation (TGV) regularization for manifold-valued data in a discrete setting. We provide an axiomatic approach to formalize reasonable generalizations of TGV to the…

Numerical Analysis · Mathematics 2018-09-17 K. Bredies , M. Holler , M. Storath , A. Weinmann

We study the relationship between discrete analogues of Ricci and scalar curvature that are defined for point clouds and graphs. In the discrete setting, Ricci curvature is replaced by Ollivier-Ricci curvature. Scalar curvature can be…

Discrete Mathematics · Computer Science 2025-10-07 Abigail Hickok , Andrew J. Blumberg

The total variation-based image denoising model has been generalized and extended in numerous ways, improving its performance in different contexts. We propose a new penalty function motivated by the recent progress in the statistical…

Computer Vision and Pattern Recognition · Computer Science 2011-07-28 Aditya Chopra , Heng Lian
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