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Callias-type (or Dirac-Schr\"odinger) operators associated to abstract semifinite spectral triples are introduced and their indices are computed in terms of an associated index pairing derived from the spectral triple. The result is then…

Mathematical Physics · Physics 2022-03-30 Hermann Schulz-Baldes , Tom Stoiber

Solving discretized versions of the Dirac equation represents a large share of execution time in lattice Quantum Chromodynamics (QCD) simulations. Many high-performance computing (HPC) clusters use graphics processing units (GPUs) to offer…

High Energy Physics - Lattice · Physics 2024-07-02 Tilmann Matthaei

We obtain a class of adiabatic solutions of Dirac equation for the charged massless relativistic quasi-particles that arise from the low-energy excitations \cite{foot-1} in a 2D graphene sheet, interacting with an electromagnetic field. The…

Mesoscale and Nanoscale Physics · Physics 2011-03-02 F. H. M. Faisal

Modern data introduces new challenges to classic signal processing approaches, leading to a growing interest in the field of graph signal processing. A powerful and well established model for real world signals in various domains is sparse…

Machine Learning · Computer Science 2019-03-27 Yael Yankelevsky , Michael Elad

This paper reviews recent results on the classification of partial differential operators modeling bulk and interface topological insulators in Euclidean spaces. Our main objective is the mathematical analysis of the unusual,…

Mathematical Physics · Physics 2025-10-22 Guillaume Bal

Let $(M_i, g_i)_{i \in \mathbb{N}}$ be a sequence of spin manifolds with uniform bounded curvature and diameter that converges to a lower dimensional Riemannian manifold $(B,h)$ in the Gromov-Hausdorff topology. Lott showed that the…

Spectral Theory · Mathematics 2019-05-08 Saskia Roos

We propose principled Gaussian processes (GPs) for modeling functions defined over the edge set of a simplicial 2-complex, a structure similar to a graph in which edges may form triangular faces. This approach is intended for learning…

Machine Learning · Statistics 2024-03-05 Maosheng Yang , Viacheslav Borovitskiy , Elvin Isufi

An integer valued topological index of a Dirac operator is introduced for a pair of a 4n+2 dimensional open Spin^c manifold and a section of the determinant line bundle satisfying some property. We show a relation between the index and an…

Differential Geometry · Mathematics 2014-01-22 Shin Hayashi

In this tutorial, we pedagogically review recent developments in the field of non-interacting fermionic phases of matter, focussing on the low energy description of higher-order topological insulators in terms of the Dirac equation. Our aim…

Mesoscale and Nanoscale Physics · Physics 2021-06-14 Frank Schindler

We first develop a general framework for Laplace operators defined in terms of the combinatorial structure of a simplicial complex. This includes, among others, the graph Laplacian, the combinatorial Laplacian on simplicial complexes, the…

Algebraic Topology · Mathematics 2011-11-09 Danijela Horak , Jürgen Jost

Bistatic integrated sensing and communication (ISAC) enables efficient reuse of the existing cellular infrastructure and is likely to play an important role in future sensing networks. In this context, ISAC using the data channel is a…

Signal Processing · Electrical Eng. & Systems 2026-01-19 Marcus Henninger , Lucas Giroto , Ahmed Elkelesh , Silvio Mandelli

Given a bounded smooth domain $\Omega\subset\mathbb{R}^3$, we explore the relation between couplings of the free Dirac operator $-i\alpha\cdot\nabla+m\beta$ with pure electrostatic shell potentials $\lambda\delta_{\partial\Omega}$…

Mathematical Physics · Physics 2015-12-14 Albert Mas

The overlap operator is a lattice discretization of the Dirac operator of quantum chromodynamics, the fundamental physical theory of the strong interaction between the quarks. As opposed to other discretizations it preserves the important…

High Energy Physics - Lattice · Physics 2014-10-28 James Brannick , Andreas Frommer , Karsten Kahl , Björn Leder , Matthias Rottmann , Artur Strebel

The closed loops or cycles in a brain network embeds higher order signal transmission paths, which provide fundamental insights into the functioning of the brain. In this work, we propose an efficient algorithm for systematic identification…

Neurons and Cognition · Quantitative Biology 2023-01-04 D. Vijay Anand , Moo K. Chung

In the past decade, significant progress has been made to generalize classical tools from Fourier analysis to analyze and process signals defined on networks. In this paper, we propose a new framework for constructing Gabor-type frames for…

Functional Analysis · Mathematics 2021-02-16 Mahya Ghandehari , Dominique Guillot , Kris Hollingsworth

The lattice studies in QCD demonstrate the nontrivial localization behavior of the eigenmodes of the 4D Euclidean Dirac operator considered as Hamiltonian of $4+1$ dimensional disordered system. We use the holographic viewpoint to provide…

High Energy Physics - Theory · Physics 2019-07-04 A. Gorsky , M. Litvinov

Topological nodal superconductors possess gapless low energy excitations that are characterized by point or line nodal Fermi surfaces. In this work, using a coupled wire construction, we study topological nodal superconductors that have…

Strongly Correlated Electrons · Physics 2018-11-28 Moon Jip Park , Syed Raza , Matthew J. Gilbert , Jeffrey C. Y. Teo

$p$-Adic divergence and gradient operators are constructed giving rise to $p$-adic vertex Laplacian operators used by Z\'u\~niga in order to study Turing patterns on graphs, as well as their edge Laplacian counterparts. It is shown that the…

Analysis of PDEs · Mathematics 2024-06-21 Patrick Erik Bradley

We use the Dirac operator technique to establish sharp distance estimates for compact spin manifolds under lower bounds on the scalar curvature in the interior and on the mean curvature of the boundary. In the situations we consider, we…

Differential Geometry · Mathematics 2024-05-22 Simone Cecchini , Rudolf Zeidler

In this paper, we propose a framework for graph signal processing using category theory. The aim is to generalize a few recent works on probabilistic approaches to graph signal processing, which handle signal and graph uncertainties.

Signal Processing · Electrical Eng. & Systems 2023-02-27 Feng Ji , Xingchao Jian , Wee Peng Tay
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