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The density matrix renormalization group (DMRG) is applied to some one-dimensional reaction-diffusion models in the vicinity of and at their critical point. The stochastic time evolution for these models is given in terms of a non-symmetric…

Statistical Mechanics · Physics 2011-10-11 Enrico Carlon , Malte Henkel , Ulrich Schollwoeck

We introduce a perturbation expansion for athermal systems that allows an exact determination of displacement fields away from the crystalline state as a response to disorder. We show that the displacement fields in energy minimized…

Soft Condensed Matter · Physics 2021-09-29 Pappu Acharya , Debankur Das , Kabir Ramola

We review various applications of dispersion relations (DRs) to the electromagnetic structure of hadrons. We discuss the way DRs allow one to extract information on hadron structure constants by connecting information from complementary…

High Energy Physics - Phenomenology · Physics 2018-07-04 B. Pasquini , M. Vanderhaeghen

In this paper, we study the inverse electromagnetic medium scattering problem of estimating the support and shape of medium scatterers from scattered electric or magnetic near-field data. We shall develop a novel direct sampling method…

Numerical Analysis · Mathematics 2015-06-12 Kazufumi Ito , Bangti Jin , Jun Zou

Parity-violating polarized electron scattering from nucleons and nuclei provides an excellent tool to extract valuable information on nuclear and nucleon structure, as well as to determine Standard Model couplings and higher-order radiative…

Nuclear Theory · Physics 2015-04-15 O. Moreno , T. W. Donnelly , R. González-Jiménez , J. A. Caballero

Disordered nanostructures are commonly encountered in many nanophotonic systems, from colloid dispersions for sensing, to heterostructured photocatalysts. Randomness, however, imposes severe challenges for nanophotonics modeling, often…

Many applications require recovering the geometry information of multiple elastic particles based on the scattering information. In this paper, we consider the inverse time-harmonic elastic scattering of multiple rigid particles in three…

Mathematical Physics · Physics 2022-09-21 Jun Lai , Jinrui Zhang

The backscattering of circularly polarized light at normal incidence to a half-space of scattering particles is studied using the Electric Field Monte Carlo (EMC) method. The spatial distribution of the backscattered light intensity is…

Optics · Physics 2009-11-11 Kevin G. Phillips , Min Xu , S. K. Gayen , R. R. Alfano

The multichannel scattering problem in an adiabatic representation is considered. The non-adiabatic coupling matrix is assumed to have a non-trivial constant asymptotic behavior at large internuclear separations. The asymptotic solutions at…

Atomic Physics · Physics 2016-08-30 S L Yakovlev , E A Yarevsky , N Elander , A K Belyaev

X-ray Bragg coherent diffraction imaging has been demonstrated as a powerful three-dimensional (3D) microscopy approach for the investigation of sub-micrometer-scale crystalline particles. It is based on the measurement of a series of…

A framework to calculate two-particle matrix elements for fully antisymmetrized three-cluster configurations is presented. The theory is developed for a scattering situation described in terms of the Algebraic Model. This means that the…

Nuclear Theory · Physics 2009-11-06 V. Vasilevsky , A. V. Nesterov , F. Arickx , J. Broeckhove

How topological defects affect the dynamics of particles hopping between lattice sites of a distorted, two-dimensional crystal is addressed. Perturbation theory and numerical simulations show that weak, short-ranged topological disorder…

Statistical Mechanics · Physics 2007-05-23 Ligang Chen , Michael W. Deem

The compatibility of neutrino-nucleus deep inelastic scattering data within the universal, factorizable nuclear parton distribution functions has been studied independently by several groups in the past few years. The conclusions are…

High Energy Physics - Phenomenology · Physics 2013-07-03 Hannu Paukkunen , Carlos A. Salgado

The multivariate contaminated normal (MCN) distribution represents a simple heavy-tailed generalization of the multivariate normal (MN) distribution to model elliptical contoured scatters in the presence of mild outliers, referred to as…

Methodology · Statistics 2018-10-23 Antonio Punzo , Cristina Tortora

We introduce and analyse ensembles of 2-regular random graphs with a tuneable distribution of short cycles. The phenomenology of these graphs depends critically on the scaling of the ensembles' control parameters relative to the number of…

Disordered Systems and Neural Networks · Physics 2018-02-14 Fabian Aguirre Lopez , Paolo Barucca , Mathilde Fekom , Anthony CC Coolen

Nowadays, massive datasets are typically dispersed across multiple locations, encountering dual challenges of high dimensionality and huge sample size. Therefore, it is necessary to explore sufficient dimension reduction (SDR) methods for…

Methodology · Statistics 2025-09-16 Hongying Li , Minyi Zhu , Yaqi Cao , Xinyi Xu

Robust clustering from incomplete data is an important topic because, in many practical situations, real data sets are heavy-tailed, asymmetric, and/or have arbitrary patterns of missing observations. Flexible methods and algorithms for…

Methodology · Statistics 2018-11-13 Yuhong Wei , Yang Tang , Paul D. McNicholas

Mixtures of bare atomic nuclei on a nearly uniform degenerate electron background are a realistic model of matter in the interior of white dwarfs. Despite tremendous progress in understanding their phase diagrams achieved mainly via…

Solar and Stellar Astrophysics · Physics 2025-04-17 D. A. Baiko

Site-occupancy disorder, defined as the non-periodic occupation of lattice sites in a crystal structure, is a ubiquitous phenomenon in solid-state physics and chemistry. Examples are mineral solid solutions, synthetic non-stoichiometric…

Materials Science · Physics 2016-02-10 Ricardo Grau-Crespo , Said Hamad

Density based representations of atomic environments that are invariant under Euclidean symmetries have become a widely used tool in the machine learning of interatomic potentials, broader data-driven atomistic modelling and the…