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We introduce Cubical Ripser for computing persistent homology of image and volume data (more precisely, weighted cubical complexes). To our best knowledge, Cubical Ripser is currently the fastest and the most memory-efficient program for…

Computer Vision and Pattern Recognition · Computer Science 2020-06-15 Shizuo Kaji , Takeki Sudo , Kazushi Ahara

Peptide sequencing from mass spectrometry data is a key step in proteome research. Especially de novo sequencing, the identification of a peptide from its spectrum alone, is still a challenge even for state-of-the-art algorithmic…

Data Structures and Algorithms · Computer Science 2011-03-29 Sandro Andreotti , Gunnar W. Klau , Knut Reinert

The concept of k-spectrum for genomes is here investigated as a basic tool to analyze genomes. Related spectral notions based on k-mers are introduced with some related mathematical properties which are relevant for informational analysis…

Computational Engineering, Finance, and Science · Computer Science 2021-06-30 Vincenzo Bonnici , Giuditta Franco , Vincenzo Manca

We present an interactive IDL program for viewing and analyzing astronomical spectra in the context of modern imaging surveys. SpecPro's interactive design lets the user simultaneously view spectroscopic, photometric, and imaging data,…

Instrumentation and Methods for Astrophysics · Physics 2015-05-27 Daniel Masters , Peter Capak

We define for every dendroidal set X a chain complex and show that this assignment determines a left Quillen functor. Then we define the homology groups $H_n(X)$ as the homology groups of this chain complex. This generalizes the homology of…

Algebraic Topology · Mathematics 2016-08-07 Matija Bašić , Thomas Nikolaus

Computing spectra is a central problem in computational mathematics with an abundance of applications throughout the sciences. However, in many applications gaining an approximation of the spectrum is not enough. Often it is vital to…

Spectral Theory · Mathematics 2022-09-20 Matthew J. Colbrook

Semidefinite programming (SDP) is a powerful tool for tackling a wide range of computationally hard problems such as clustering. Despite the high accuracy, semidefinite programs are often too slow in practice with poor scalability on large…

Machine Learning · Statistics 2022-02-10 Yubo Zhuang , Xiaohui Chen , Yun Yang

The spherical harmonic transform is a powerful tool in the analysis of spherical data sets, such as the cosmic microwave background data. In this work, we present a new scheme for the spherical harmonic transforms that supports both CPU and…

Instrumentation and Methods for Astrophysics · Physics 2022-11-18 Chi Tian , Siyu Li , Hao Liu

Simplicial complexes can be viewed as high dimensional generalizations of graphs that explicitly encode multi-way ordered relations between vertices at different resolutions, all at once. This concept is central towards detection of higher…

Machine Learning · Computer Science 2022-07-05 Alexandros Dimitrios Keros , Vidit Nanda , Kartic Subr

We consider a finite group acting on a vector space and the corresponding skew group algebra generated by the group and the symmetric algebra of the space. This skew group algebra illuminates the resulting orbifold and serves as a…

Rings and Algebras · Mathematics 2009-11-05 Anne V. Shepler , Sarah Witherspoon

Persistent homology is a popular computational tool for analyzing the topology of point clouds, such as the presence of loops or voids. However, many real-world datasets with low intrinsic dimensionality reside in an ambient space of much…

Machine Learning · Computer Science 2024-11-01 Sebastian Damrich , Philipp Berens , Dmitry Kobak

A Mathematica based program has been elaborated in order to determine the symmetry group of a finite difference equation, by means of its differential representation. The package provides functions which enable us to solve the determining…

Numerical Analysis · Mathematics 2007-05-23 Emma Hoarau , Claire David

Let $G$ be a group and $S$ a unital epsilon-strongly $G$-graded algebra. We construct spectral sequences converging to the Hochschild (co)homology of $S$. Each spectral sequence is expressed in terms of the partial group (co)homology of $G$…

K-Theory and Homology · Mathematics 2025-07-23 Emmanuel Jerez

The completely bounded trace and spectral norms, for finite-dimensional spaces, are known to be efficiently expressible by semidefinite programs (J. Watrous, Theory of Computing 5: 11, 2009). This paper presents two new, and arguably much…

Quantum Physics · Physics 2012-08-03 John Watrous

While several feature embedding models have been developed in the literature, comparisons of these embeddings have largely focused on their numerical performance in classification-related downstream applications. However, an interpretable…

Machine Learning · Computer Science 2025-08-19 Mohammad Jalali , Bahar Dibaei Nia , Farzan Farnia

Recently developed quantum algorithms address computational challenges in numerical analysis by performing linear algebra in Hilbert space. Such algorithms can produce a quantum state proportional to the solution of a $d$-dimensional system…

Quantum Physics · Physics 2021-10-19 Andrew M. Childs , Jin-Peng Liu

In this paper, we develop Leray-Serre-type spectral sequences to compute the intersection homology of the regular neighborhood and deleted regular neighborhood of the bottom stratum of a stratified PL-pseudomanifold. The E^2 terms of the…

Geometric Topology · Mathematics 2011-03-31 Greg Friedman

The Boolean algebra of regular closed sets is prominent in topology, particularly as a dual for the Stone-Cech compactification. This algebra is also central for the theory of geometric computation, as a representation for combinatorial…

We study the homology groups of the complement of a complexified real line arrangement with coefficients in complex rank-one local systems. Using Borel--Moore homology, we establish an algorithm computing their dimensions via the real…

Algebraic Geometry · Mathematics 2026-04-29 Baiting Xie , Chenglong Yu

We consider the solution of nonlinear programs with nonlinear semidefiniteness constraints. The need for an efficient exploitation of the cone of positive semidefinite matrices makes the solution of such nonlinear semidefinite programs more…

Optimization and Control · Mathematics 2007-05-23 Roland W. Freund , Florian Jarre , Christoph Vogelbusch
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