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Decompositions of networks are useful not only for structural exploration. They also have implications and use in analysis and computational solution of processes (such as the Ising model, percolation, SIR model) running on a given network.…

Disordered Systems and Neural Networks · Physics 2020-04-29 Konstantin Klemm

A new predictor-corrector type incremental algorithm is proposed for the exact construction of weighted straight skeletons of 2D general planar polygons of arbitrary complexity based on the notion of deforming polygon. In the proposed…

Computational Geometry · Computer Science 2020-11-18 Baris Irhan

Trimming is a core technique in geometric modeling. Unfortunately, the resulting objects do not take the requirements of numerical simulations into account and yield various problems. This paper outlines principal issues of trimmed models…

Graphics · Computer Science 2019-02-05 Benjamin Marussig

We propose a method to recover the structure of a compound object from multiple silhouettes. Structure is expressed as a collection of 3D primitives chosen from a pre-defined library, each with an associated pose. This has several…

Computer Vision and Pattern Recognition · Computer Science 2014-02-27 Anton van den Hengel , John Bastian , Anthony Dick , Lachlan Fleming

We derive exact reconstruction methods for cracks consisting of unions of Lipschitz hypersurfaces in the context of Calder\'on's inverse conductivity problem. Our first method obtains upper bounds for the unknown cracks, bounds that can be…

Analysis of PDEs · Mathematics 2024-05-24 Henrik Garde , Michael Vogelius

We consider conformal field theories around points of large twist degeneracy. Examples of this are theories with weakly broken higher spin symmetry and perturbations around generalised free fields. At the degenerate point we introduce twist…

High Energy Physics - Theory · Physics 2017-09-20 Luis F. Alday

The twist construction is a geometric model of T-duality that includes constructions of nilmanifolds from tori. This paper shows how one-dimensional foliations on manifolds may be used in a shear construction, which in algebraic form builds…

Differential Geometry · Mathematics 2018-11-08 Marco Freibert , Andrew Swann

We explore methods for constructing normal forms of indecomposable quiver representations. The first part of the paper develops homological tools for recursively constructing families of indecomposable representations from indecomposables…

Representation Theory · Mathematics 2019-10-29 Ryan Kinser , Thorsten Weist

A refinement of manifold data is a computational process, which produces a denser set of discrete data from a given one. Such refinements are closely related to multiresolution representations of manifold data by pyramid transforms, and…

Numerical Analysis · Mathematics 2016-11-18 Nira Dyn , Nir Sharon

A general reconstruction and calibration procedure for tracking and wire position determination of the OPERA drift tubes is presented. The mathematics of the pattern recognition and the track fit are explained.

Instrumentation and Detectors · Physics 2007-06-07 Raoul Zimmermann

Model calculations of nuclear properties are peformed using quantum computing algorithms on simulated and real quantum computers. The models are a realistic calculation of deuteron binding based on effective field theory, and a simplified…

Nuclear Theory · Physics 2022-05-12 Isaac Hobday , Paul D Stevenson , James Benstead

The Decomposition Problem in the class $LIP(\mathbb{S}^2)$ is to decompose any bi-Lipschitz map $f:\mathbb{S}^2 \to \mathbb{S}^2$ as a composition of finitely many maps of arbitrarily small isometric distortion. In this paper, we construct…

Metric Geometry · Mathematics 2022-02-11 Alastair N. Fletcher , Vyron Vellis

Compacting orthogonal drawings is a challenging task. Usually algorithms try to compute drawings with small area or edge length while preserving the underlying orthogonal shape. We present a one-dimensional compaction algorithm that alters…

Data Structures and Algorithms · Computer Science 2017-06-21 Michael Jünger , Petra Mutzel , Christiane Spisla

Traditional tensor decomposition methods, e.g., two dimensional principal component analysis and two dimensional singular value decomposition, that minimize mean square errors, are sensitive to outliers. To overcome this problem, in this…

Computer Vision and Pattern Recognition · Computer Science 2020-12-30 Miaohua Zhang , Yongsheng Gao , Changming Sun , Michael Blumenstein

Dimensionality reduction is an essential technique for multi-way large-scale data, i.e., tensor. Tensor ring (TR) decomposition has become popular due to its high representation ability and flexibility. However, the traditional TR…

Numerical Analysis · Mathematics 2024-12-20 Longhao Yuan , Chao Li , Jianting Cao , Qibin Zhao

We consider the problem of selecting an optimal mask for an image manifold, i.e., choosing a subset of the pixels of the image that preserves the manifold's geometric structure present in the original data. Such masking implements a form of…

Machine Learning · Statistics 2016-06-16 Hamid Dadkhahi , Marco F. Duarte

The main purpose of this paper is to lay the foundations of a general theory which encompasses the features of the classical Hough transform and extend them to general algebraic objects such as affine schemes. The main motivation comes from…

Commutative Algebra · Mathematics 2012-02-09 Mauro C. Beltrametti , Lorenzo Robbiano

We consider representations of tensors as sums of decomposable tensors or, equivalently, decomposition of multilinear forms into one--forms. In this short note we show that there exists a particular finite strongly orthogonal decomposition…

Numerical Analysis · Mathematics 2014-09-19 Juan Manuel Peña , Tomas Sauer

We consider a strongly heterogeneous medium saturated by an incompressible viscous fluid as it appears in geomechanical modeling. This poroelasticity problem suffers from rapidly oscillating material parameters, which calls for a thorough…

Numerical Analysis · Mathematics 2018-12-27 Robert Altmann , Eric Chung , Roland Maier , Daniel Peterseim , Sai-Mang Pun

Maximum likelihood iteration is one of the most commonly used reconstruction algorithms in quantum tomography. The main appeal of the method is that it is easy to implement and that it converges reliably to a physically meaningful density…

Quantum Physics · Physics 2025-08-21 Florian Oberender
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