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A new class of neutrino dark energy models is presented. The new models are characterized by the lack of exotic particles or couplings that violate the standard model symmetry. It is shown that these models lead to several concrete…

Cosmology and Nongalactic Astrophysics · Physics 2015-05-19 Ilya Gurwich

A new type of knot energy is presented via real life experiments involving a thin resilient metallic tube. Knotted in different ways, the device mechanically acquires a uniquely determined (up to isometry) normal form at least when the…

Geometric Topology · Mathematics 2015-05-20 A. B. Sossinsky

An abstract 2nd-order evolution equation or inclusion is discretised in time in such a way that the energy is conserved at least in qualified cases, typically in the cases when the governing energy is component-wise quadratic or…

Numerical Analysis · Mathematics 2016-06-01 Tomas Roubicek , Christos G. Panagiotopoulos

Dark energy perturbations are normally either neglected or else included in a purely numerical way, obscuring their dependence on underlying parameters like the equation of state or the sound speed. However, while many different…

Cosmology and Nongalactic Astrophysics · Physics 2009-10-29 Domenico Sapone , Martin Kunz

We derive a discrete spectral representation of the single-particle self-energy using a discrete evaluation of Kugler's symmetric improved estimator. Our construction can be used on both the real and the complex (Matsubara) frequency axis.…

Machine learning is employed to build an energy density functional for self-bound nuclear systems for the first time. By learning the kinetic energy as a functional of the nucleon density alone, a robust and accurate orbital-free density…

Nuclear Theory · Physics 2022-03-21 X. H. Wu , Z. X. Ren , P. W. Zhao

Methods for studying droplets in models with quenched disorder are critically examined. Low energy excitations in two dimensional models are investigated by finding minimal energy interior excitations and by computing the effect of bulk…

Disordered Systems and Neural Networks · Physics 2009-10-31 A. Alan Middleton

The notion of dissipative dynamical systems provides a formal description of processes that cannot generate energy internally. For these systems, changes in energy can only occur due to an external energy supply or dissipation effects.…

Numerical Analysis · Mathematics 2026-02-18 Attila Karsai , Philipp Schulze

Studies on nanoscale materials merit careful development of an electrostatics model concerning discrete point charges within dielectrics. The discrete charge dielectric model treats three unique interaction types derived from an external…

Classical Physics · Physics 2012-03-20 Tim LaFave

We propose nonlinear semi-discrete and discrete models for the elastic energy induced by a finite systems of edge dislocations in two dimensions. Within the dilute regime, we analyze the asymptotic behavior of the nonlinear elastic energy,…

Analysis of PDEs · Mathematics 2023-05-04 Roberto Alicandro , Lucia De Luca , Mariapia Palombaro , Marcello Ponsiglione

The discrete energy-eigenvalues of two nucleons interacting with a finite-range nuclear force and confined to a harmonic potential are used to numerically reconstruct the free-space scattering phase shifts. The extracted phase shifts are…

Nuclear Theory · Physics 2014-11-21 Thomas Luu , Martin Savage , Achim Schwenk , James P. Vary

We establish long-time existence of Banach gradient flows for generalised integral Menger curvatures and tangent-point energies, and for O'Hara's self-repulsive potentials $E^{\alpha,p}$. In order to do so, we employ the theory of curves of…

Classical Analysis and ODEs · Mathematics 2023-04-25 Hannes Matt , Daniel Steenebrügge , Heiko von der Mosel

Discrete gradients (DG) or more exactly discrete gradient methods are time integration schemes that are custom-built to preserve first integrals or Lyapunov functions of a given ordinary differential equation (ODE). In conservative…

Numerical Analysis · Mathematics 2024-01-09 Volker Grimm , Tobias Kliesch , G. R. W. Quispel

In this technical note we give a purely geometric understanding of discrete torsion, as an analogue of orbifold Wilson lines for two-form tensor field potentials. In order to introduce discrete torsion in this context, we describe gerbes…

High Energy Physics - Theory · Physics 2007-05-23 Eric R. Sharpe

Current quadratic smoothness energies for curved surfaces either exhibit distortions near the boundary due to zero Neumann boundary conditions, or they do not correctly account for intrinsic curvature, which leads to unnatural-looking…

Graphics · Computer Science 2020-04-29 Oded Stein , Alec Jacobson , Max Wardetzky , Eitan Grinspun

The M\"obius energy of a curve is a topic of interest to physical knot theorists, harmonic analysts, and geometric analysts. The Gateaux derivative indicates its variation is dependent on curvature and torsion, leading us to consider the…

Differential Geometry · Mathematics 2026-05-14 Max Lipton

Mathematically rigorous inversion method is developed to recover compactly supported potentials from the fixed-energy scattering data in three dimensions. Error estimates are given for the solution. An algorithm for inversion of noisy…

Mathematical Physics · Physics 2007-05-23 A. G. Ramm

When a probe qubit is coupled to a quantum register that represents a physical system, the probe qubit will exhibit a dynamical response only when it is resonant with a transition in the system. Using this principle, we propose a quantum…

Quantum Physics · Physics 2014-02-19 Hefeng Wang , Heng Fan , Fuli Li

The symmetry energy of nuclear matter is a fundamental ingredient in the investigation of exotic nuclei, heavy-ion collisions and astrophysical phenomena. New data from heavy-ion collisions can be used to extract the free symmetry energy…

This paper studies the expressive and computational power of discrete Ordinary Differential Equations (ODEs), a.k.a. (Ordinary) Difference Equations. It presents a new framework using these equations as a central tool for computation and…

Logic in Computer Science · Computer Science 2022-09-27 Olivier Bournez , Arnaud Durand