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Tensor network (TN), a young mathematical tool of high vitality and great potential, has been undergoing extremely rapid developments in the last two decades, gaining tremendous success in condensed matter physics, atomic physics, quantum…

Computational Physics · Physics 2020-01-31 Shi-Ju Ran , Emanuele Tirrito , Cheng Peng , Xi Chen , Luca Tagliacozzo , Gang Su , Maciej Lewenstein

This article presents the first complete application of a quantum time-marching algorithm for simulating multidimensional linear transport phenomena with arbitrary boundaries, whereby the success probabilities are problem intrinsic. The…

Quantum Physics · Physics 2026-04-13 Sergio Bengoechea , Paul Over , Thomas Rung

The analogy between supersymmetric quantum mechanics and matter-enhanced neutrino oscillations is exploited to obtain exact solutions for a class of electron density profiles. This integrability condition is analogous to the…

High Energy Physics - Phenomenology · Physics 2009-12-30 A. B. Balantekin

Spatially-structured laser beams, eventually carrying orbital angular momentum, affect electronic transitions of atoms and their motional states in a complex way. We present a general framework, based on the spherical tensor decomposition…

Consider the scattering of a time-harmonic elastic plane wave by a bi-periodic rigid surface. The displacement of elastic wave motion is modeled by the three-dimensional Navier equation in an open domain above the surface. Based on the…

Numerical Analysis · Mathematics 2020-07-28 Gang Bao , Xue Jiang , Peijun Li , Xiaokai Yuan

Multichannel Quantum Defect Theory (MQDT) is shown to be capable of producing quantitatively accurate results for low-energy atom-molecule scattering calculations. With a suitable choice of reference potential and short-range matching…

Atomic Physics · Physics 2015-03-19 James F. E. Croft , Alisdair O. G. Wallis , Jeremy M. Hutson , Paul S. Julienne

Relativistic strongly magnetized plasmas are produced in laboratories thanks to state-of-the-art laser technology but can naturally be found around compact objects such as neutron stars and black holes. Detailed studies of the behaviour of…

Plasma Physics · Physics 2017-05-24 J. Pétri

Relating the electromagnetic scattering and absorption properties of an individual particle to the reflection and transmission coefficients of a two-dimensional material composed of these particles is a crucial concept that has driven both…

Optics · Physics 2019-10-02 Romain Dezert , Philippe Richetti , Alexandre Baron

We introduce theoretical methods for describing the optical response of two-dimensional (2D) materials patterned at the nanoscale into both arrays of ribbons along a planar surface and spherical particles. Fourier-Floquet decompositions of…

Mesoscale and Nanoscale Physics · Physics 2025-12-16 Christian Nicolaisen Hansen , Line Jelver , Christos Tserkezis

Neural networks have been demonstrated to be able to accelerate the modeling and inverse design of optical and electromagnetic devices by serving as fast surrogates for electromagnetic solvers. Nevertheless, such neural networks can be…

Dynamic mode decomposition (DMD) has become a powerful data-driven method for analyzing the spatiotemporal dynamics of complex, high-dimensional systems. However, conventional DMD methods are limited to matrix-based formulations, which…

Systems and Control · Electrical Eng. & Systems 2025-08-05 Ziqin He , Mengqi Hu , Yifei Lou , Can Chen

Time-varying nanostructures allow us to control the spatial and temporal properties of light. The temporal modulation of the nanostructures constitutes an additional degree of freedom to control their scattering properties on demand and in…

We introduce and discuss a hybrid quantum-mechanics molecular-mechanics (QM-MM) approach for Car-Parrinello DFT simulations with pseudopotentials and planewaves basis, designed for the treatment of periodic systems. In this implementation…

Materials Science · Physics 2016-07-20 Diego Hunt , Veronica M. Sanchez , Damian A. Scherlis

We assert that the physics underlying the extraordinary light transmission (reflection) in nanostructured materials can be understood from rather general principles based on the formal scattering theory developed in quantum mechanics. The…

Computational Physics · Physics 2016-08-16 A. G. Borisov , F. J. García de Abajo , S. V. Shabanov

Motivated by recent studies of the phenomenon of Coherent Perfect Absorption, we develop the random matrix theory framework for understanding statistics of the zeros of the (subunitary) scattering matrices in the complex energy plane, as…

Disordered Systems and Neural Networks · Physics 2020-07-15 Mohammed Osman , Yan V. Fyodorov

The superior ability of nanostructures to manipulate light has propelled extensive applications in nano-electromagnetic components and devices. Computational electromagnetics plays a critical role in characterizing and optimizing the…

Computational Physics · Physics 2025-01-24 Chengnian Huang , Wei E. I. Sha

We present a density-based topology optimization scheme for locally optimizing the electric power dissipation in nanostructures made of lossy dispersive materials. By using the complex-conjugate pole-residue (CCPR) model, we can accurately…

An adaptive finite element method is presented for the elastic scattering of a time-harmonic plane wave by a periodic surface. First, the unbounded physical domain is truncated into a bounded computational domain by introducing the…

Numerical Analysis · Mathematics 2016-05-30 Xue Jiang , Peijun Li , Junliang Lv , Weiying Zheng

In this work, we derive a multi-fragment real-time extension of projected density matrix embedding theory (pDMET) designed to treat non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static…

Strongly Correlated Electrons · Physics 2023-04-19 Dariia Yehorova , Joshua S. Kretchmer

Nonnegative Tucker decomposition (NTD) is a powerful tool for the extraction of nonnegative parts-based and physically meaningful latent components from high-dimensional tensor data while preserving the natural multilinear structure of…

Machine Learning · Computer Science 2015-09-17 Guoxu Zhou , Andrzej Cichocki , Qibin Zhao , Shengli Xie
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