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Persistent homology is a popular tool in Topological Data Analysis. It provides numerical characteristics of data sets which reflect global geometric properties. In order to be useful in practice, for example for feature generation in…

Computational Geometry · Computer Science 2020-02-17 Boris Goldfarb

This is a survey on finite-dimensional integrable dynamical systems related to Hamiltonian $G$-actions. Within a framework of noncommutative integrability we study integrability of $G$-invariant systems, collective motions and reduced…

Symplectic Geometry · Mathematics 2008-12-24 Bozidar Jovanovic

The aim of this paper is to provide a discussion on current directions of research involving typical singularities of 3D nonsmooth vector fields. A brief survey of known results is presented. The main purpose of this work is to describe the…

Dynamical Systems · Mathematics 2019-02-06 Otávio M. L. Gomide , Marco A. Teixeira

The classical Gaussian mixture model assumes homogeneity within clusters, an assumption that often fails in real-world data where observations naturally exhibit varying scales or intensities. To address this, we introduce the…

Machine Learning · Statistics 2026-04-08 Huan Qing

The present paper mainly presents, for example, explicit classifications of compact smooth manifolds having non-empty boundaries and simple structures where the dimensions are general. Studies of this type is fundamental and important. They…

General Topology · Mathematics 2021-06-21 Naoki Kitazawa

Several new combinatorial descriptions of closed 4-manifolds have recently been introduced in the study of smooth maps from 4-manifolds to surfaces. These descriptions consist of simple closed curves in a closed, orientable surface and…

Geometric Topology · Mathematics 2018-05-16 Stefan Behrens , Kenta Hayano

This paper brings together three distinct theories with the goal of quantifying shape textures with complex morphologies. Distance fields are central objects in shape representation, while topological data analysis uses algebraic topology…

Algebraic Topology · Mathematics 2023-07-04 Anna Song , Ka Man Yim , Anthea Monod

In this paper, we investigate the development of generalized synchronization (GS) on typical complex networks, such as scale-free networks, small-world networks, random networks and modular networks. By adopting the auxiliary-system…

Chaotic Dynamics · Physics 2009-11-13 Shuguang Guan , Xingang Wang , Xiaofeng Gong , Kun Li , C. -H. Lai

Though manifold-based clustering has become a popular research topic, we observe that one important factor has been omitted by these works, namely that the defined clustering loss may corrupt the local and global structure of the latent…

Machine Learning · Computer Science 2021-10-12 Lirong Wu , Zicheng Liu , Zelin Zang , Jun Xia , Siyuan Li , Stan. Z Li

We propose a mathematical formalism for discrete multi-scale dynamical systems induced by maps which parallels the established geometric singular perturbation theory for continuous-time fast-slow systems. We identify limiting maps…

Dynamical Systems · Mathematics 2022-11-09 Samuel Jelbart , Christian Kuehn

We consider in this paper a challenging problem of simulating fluid flows, in complex multiscale media possessing multi-continuum background. As an effort to handle this obstacle, model reduction is employed. In \cite{rh2}, homogenization…

Numerical Analysis · Mathematics 2022-05-31 Jun Sur Richard Park , Siu Wun Cheung , Tina Mai , Viet Ha Hoang

Given two discrete Morse functions on a simplicial complex, we introduce the {\em connectedness homomorphism} between the corresponding discrete Morse complexes. This concept leads to a novel framework for studying the connectedness in…

Combinatorics · Mathematics 2024-07-15 Chong Zheng

We introduce two tools, dynamical thickening and flow selectors, to overcome the infamous discontinuity of the gradient flow endpoint map near non-degenerate critical points. More precisely, we interpret the stable fibrations of certain…

Dynamical Systems · Mathematics 2016-07-04 Joa Weber

In this paper we use the gradient flow equation introduced in [10] to construct a Morse complex for the Hamiltonian action $\mathbb A_H$ on a mixed regularity space of loops in the cotangent bundle $T^*M$ of a closed manifold $M$.…

Symplectic Geometry · Mathematics 2025-01-28 L. Asselle , M. Starostka

The computation of homology groups for evolving simplicial complexes often requires repeated reconstruction of boundary operators, resulting in prohibitive costs for large-scale or frequently updated data. This work introduces MMHM, a…

Computational Geometry · Computer Science 2025-08-21 Anqiao Ouyang

We study Morse theory on noncompact manifolds equipped with exhaustions by compact pieces, defining the Morse homology of a pair which consists of the manifold and related geometric/homotopy data. We construct a collection of Morse data…

Geometric Topology · Mathematics 2019-11-12 Taesu Kim

The aim of this paper is to develop a refinement of Forman's discrete Morse theory. To an acyclic partial matching $\mu$ on a finite regular CW complex $X$, Forman introduced a discrete analogue of gradient flows. Although Forman's gradient…

Algebraic Topology · Mathematics 2018-08-27 Vidit Nanda , Dai Tamaki , Kohei Tanaka

We analyze a bifurcation phenomenon associated with critical gravitational collapse in a family of self-gravitating SU(2) $\sigma$-models. As the dimensionless coupling constant decreases, the critical solution changes from discretely…

General Relativity and Quantum Cosmology · Physics 2009-11-07 Christiane Lechner , Jonathan Thornburg , Sascha Husa , Peter C. Aichelburg

A general algebraic approach, incorporating both invariance groups and dynamic symmetry algebras, is developed to reveal hidden coherent structures (closed complexes and configurations) in quantum many-body physics models due to symmetries…

Quantum Physics · Physics 2008-11-26 Valery P. Karassiov

Generative modeling seeks to uncover the underlying factors that give rise to observed data that can often be modeled as the natural symmetries that manifest themselves through invariances and equivariances to certain transformation laws.…

Machine Learning · Computer Science 2022-08-16 Avishek Joey Bose , Marcus Brubaker , Ivan Kobyzev