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Related papers: Defect relation of $n+1$ components through the GC…

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The generator coordinate (GC) method is a variational approach to the quantum many-body problem in which interacting many-body wave functions are constructed as superpositions of (generally nonorthogonal) eigenstates of auxiliary…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 E. Orestes , K. Capelle , A. B. F. da Silva , C. A. Ullrich

We have parameterized the degeneracy factor in terms of temperature and using this we have tried to compare and study the LQCD(Lattice Quantum Chromodynamics) data with our data.

Nuclear Theory · Physics 2020-01-17 Ranjesh Kumar , Ankit Anand , Souvik Paul , Sarthak Satapathy , Sabyasachi Ghosh

Conformal defects -- extended objects in conformal field theories -- carry localised excitations inherited from symmetry currents, known as the displacements and tilts. They capture the linear response of the defect to deformations of its…

High Energy Physics - Theory · Physics 2025-12-19 Nadav Drukker , Ziwen Kong , Petr Kravchuk

We formulate and analyze an optimization-based Atomistic-to-Continuum (AtC) coupling method for problems with point defects. Near the defect core the method employs a potential-based atomistic model, which enables accurate simulation of the…

Numerical Analysis · Mathematics 2014-11-17 Derek Olson , Alexander V. Shapeev , Pavel Bochev , Mitchell Luskin

We consider the problem of learning distance-based Graph Convolutional Networks (GCNs) for relational data. Specifically, we first embed the original graph into the Euclidean space $\mathbb{R}^m$ using a relational density estimation…

Machine Learning · Computer Science 2021-10-14 Devendra Singh Dhami , Siwen Yan , Sriraam Natarajan

The degeneracy of central configurations in the planar $N$-body problem makes their enumeration problem hard and the related dynamics appealing. To truly understand the bifurcations of central configurations, we should work in the FULL…

Dynamical Systems · Mathematics 2026-02-12 Shanzhong Sun , Zhifu Xie , Peng You

We review our recent works on tests of perturbative QCD, inspired by the relation between the hadronic decay of the tau lepton and the e+ e- annihilation into hadrons. First, we present a set of commensurate scale relations that probe the…

High Energy Physics - Phenomenology · Physics 2009-09-11 J. R. Pelaez , S. J. Brodsky , C. Merino , N. Toumbas

The statistical correlations between defects in the two dimensional complex Ginsburg-Landau model are studied in the defect-coarsening regime. In particular the defect-velocity probability distribution is determined and has the same high…

Statistical Mechanics · Physics 2013-05-29 Gene F. Mazenko

We consider decentralized machine learning over a network where the training data is distributed across $n$ agents, each of which can compute stochastic model updates on their local data. The agent's common goal is to find a model that…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-09 Anastasia Koloskova , Tao Lin , Sebastian U. Stich

We consider coordinate descent (CD) methods with exact line search on convex quadratic problems. Our main focus is to study the performance of the CD method that use random permutations in each epoch and compare it to the performance of the…

Optimization and Control · Mathematics 2018-03-23 Mert Gurbuzbalaban , Asuman Ozdaglar , Nuri Denizcan Vanli , Stephen J. Wright

We present a systematic methodology for the accurate calculation of defect structures in supercells which we illustrate with a study of the neutral vacancy in silicon. This is a prototypical defect which has been studied extensively using…

Materials Science · Physics 2009-11-10 M. I. J. Probert , M. C. Payne

The coupling between defects and extended critical degrees of freedom gives rise to the intriguing theory known as defect conformal field theory (CFT). In this work, we introduce a novel family of boundary and interface CFTs by coupling $N$…

Statistical Mechanics · Physics 2024-12-30 Yang Ge , Shao-Kai Jian

In machine-learning-assisted high-throughput defect studies, a defect-aware latent representation of the supercell structure is crucial to the accurate prediction of defect properties. The performance of current graph neural network (GNN)…

Materials Science · Physics 2024-11-01 Zhenyao Fang , Qimin Yan

The defect of valued field extensions is a major obstacle in open problems in resolution of singularities and in the model theory of valued fields, whenever positive characteristic is involved. We continue the detailed study of defect…

Commutative Algebra · Mathematics 2017-05-29 Anna Blaszczok , Franz-Viktor Kuhlmann

The nonlinear Klein-Gordon equation with a different potential that satisfies the degeneracy properties discussed in this paper possesses solitonic solutions that interact with long-range forces. We generalize the Ginzburg-Landau equation…

patt-sol · Physics 2021-01-01 L. E. Guerrero , J. A. Gonzalez

Causal discovery from data affected by latent confounders is an important and difficult challenge. Causal functional model-based approaches have not been used to present variables whose relationships are affected by latent confounders,…

Machine Learning · Computer Science 2020-11-05 Takashi Nicholas Maeda , Shohei Shimizu

We formulate a model for a point defect embedded in a homogeneous multilattice crystal with an empirical interatomic potential interaction. Under a natural, phonon stability assumption we quantify the decay of the long-range elastic fields…

Analysis of PDEs · Mathematics 2016-10-03 Derek Olson , Christoph Ortner

Statistics and thermally activated dynamics of crack nucleation and propagation in a two-dimensional heterogeneous material containing quenched randomly distributed defects are studied theoretically. Using the generalized Griffith criterion…

Disordered Systems and Neural Networks · Physics 2010-10-28 J. Kierfeld , V. M. Vinokur

We present a global fit of current available experimental results on $\chi_c$ decays within next-to-leading-order perturbative QCD. The quality and reduced errors of recent data improve the agreement between theory and experiment.

High Energy Physics - Phenomenology · Physics 2009-10-28 M. L. Mangano , A. Petrelli

Understanding causal dependencies in observational data is critical for informing decision-making. These relationships are often modeled as Bayesian Networks (BNs) and Directed Acyclic Graphs (DAGs). Existing methods, such as NOTEARS and…

Machine Learning · Computer Science 2026-04-03 Hao Zhu , Di Zhou , Donna Slonim