Related papers: Effective Lagrangian of Domain Wall Networks
Interest in the elastic properties of regular lattices constructed from domain walls has recently been motivated by cosmological applications as solid dark energy. This work investigates the particularly simple examples of triangular,…
The analysis of domain wall dynamics is often simplified to one dimensional physics. For domain walls in thin films, more realistic approaches require the description as two dimensional objects. This includes the study of vortices and…
We consider the theories obtained by dimensional reduction to D=1,2,3 of 4D supersymmetric Yang--Mills theories and calculate there the effective low-energy lagrangia describing moduli space dynamics -- the low-dimensional analogs of the…
We have studied the cosmological evolution of domain wall networks in two, three and four spatial dimensions using high-resolution field theory simulations. The dynamical range and number of our simulations is larger than in previous works,…
We develop a new ensemble of modular random graphs in which degree-degree correlations can be different in each module and the inter-module connections are defined by the joint degree-degree distribution of nodes for each pair of modules.…
We propose using the extra dimension separating the domain walls carrying lattice quarks of opposite handedness to gradually filter out the ultraviolet fluctuations of the gauge fields that are felt by the fermionic excitations living in…
Various approaches and measures from network analysis have been applied to granular and particulate networks to gain insights into their structural, transport, failure-propagation and other systems-level properties. In this article, we…
Supersymmetry, like Poincare symmetry, is softly broken at finite lattice spacing provided the gaugino mass term is strongly suppressed. Domain wall fermions provide the mechanism for suppressing this term by approximately imposing chiral…
Based on cluster de-synchronization properties of phase oscillators, we introduce an efficient method for the detection and identification of modules in complex networks. The performance of the algorithm is tested on computer generated and…
We discuss modular domain walls and gravitational waves in a class of supersymmetric models where quark and lepton flavour symmetry emerges from modular symmetry. In such models a single modulus field $\tau$ is often assumed to be…
Supersymmetry, like Poincare symmetry, is softly broken at finite lattice spacing provided the gaugino mass term is strongly suppressed. Domain wall fermions provide the mechanism for suppressing this term by approximately imposing chiral…
We write down the general conditions for N=1 supersymmetric four-dimensional domain walls, deriving them from a ten-dimensional point of view using generalized complex geometry. In cases where the compactification allows for a truncation to…
A novel approach for unsupervised domain adaptation for neural networks is proposed. It relies on metric-based regularization of the learning process. The metric-based regularization aims at domain-invariant latent feature representations…
We discuss algorithms for domain wall fermions focussing on accelerating Hybrid Monte Carlo sampling of gauge configurations. Firstly a new multigrid algorithm for domain wall solvers and secondly a domain decomposed hybrid monte carlo…
Domain wall fermions are defined on a lattice with an extra direction the size of which controls the chiral properties of the theory. When gauge fields are coupled to domain wall fermions the extra direction is treated as an internal flavor…
We address a simple model allowing the existence of domain walls with orientational moduli localized on them. Within this model, we discuss an analytic solution and explore it in the context of previously known results. We discuss the…
We consider the Grand Unified SU(5) model with a small or vanishing cubic term in the adjoint scalar field in the potential. This gives the model an approximate or exact Z$_2$ symmetry whose breaking leads to domain walls. The simplest…
Currently, much interest is drawn to the analysis of optical and matter-wave modes supported by the fractional diffraction in nonlinear media. We predict a new type of such states, in the form of domain walls (DWs) in the two-component…
Deep neural networks (DNNs) are powerful machine learning models and have succeeded in various artificial intelligence tasks. Although various architectures and modules for the DNNs have been proposed, selecting and designing the…
We study current-induced domain-wall dynamics in a thin ferromagnetic nanowire. The domain-wall dynamics is described by simple equations with four parameters. We propose the procedure to determine these parameters by all-electric…