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We present a novel framework for the study of disclinations in two-dimensional active nematic liquid crystals, and topological defects in general. The order tensor formalism is used to calculate exact multi-particle solutions of the…

Soft Condensed Matter · Physics 2018-02-28 Dario Cortese , Jens Eggers , Tanniemola B. Liverpool

We present a quantum algorithm based on repeated measurement to solve initial-value problems for nonlinear ordinary differential equations (ODEs), which may be generated from partial differential equations in plasma physics. We map a…

Quantum Physics · Physics 2025-04-30 Joseph Andress , Alexander Engel , Yuan Shi , Scott Parker

Time- and frequency resolved optical signals provide insights into the properties of light harvesting molecular complexes, including excitation energies, dipole strengths and orientations, as well as in the exciton energy flow through the…

Chemical Physics · Physics 2018-06-15 Tobias Kramer , Matthias Noack , Alexander Reinefeld , Mirta Rodriguez , Yaroslav Zelinskyy

Controllable arrays of ions and ultra-cold atoms can simulate complex many-body phenomena and may provide insights into unsolved problems in modern science. To this end, experimentally feasible protocols for quantifying the buildup of…

This research demonstrates analytical time-dependent non-equilibrium green function (TD-NEGF) algorithms to investigate dynamical functionalities of quantum devices, especially for photon-assisted transports. Together with the lumped…

Mesoscale and Nanoscale Physics · Physics 2021-06-08 I-Lin Ho

We present a novel technique to significantly reduce the offline cost associated to non-intrusive nonlinear tensors identification in reduced order models (ROMs) of geometrically nonlinear, finite elements (FE)-discretized structural…

Numerical Analysis · Mathematics 2024-11-22 Alexander Saccani , Paolo Tiso

The nonlinear, or warped, resolvent recently explored by Giselsson and B\`ui-Combettes has been used to model a large set of existing and new monotone inclusion algorithms. To establish convergent algorithms based on these resolvents,…

Optimization and Control · Mathematics 2023-10-02 Martin Morin , Sebastian Banert , Pontus Giselsson

We develop a new paradigm for finding bifurcations of solutions of nonlinear problems, which is based on the detection of extreme values of new type of variational functional associated with the considering problem. The variational…

Analysis of PDEs · Mathematics 2014-11-11 Yavdat Il'yasov , Alexsandr Ivanov

This paper constructs a semi-discrete tight frame of tensor needlets associated with a quadrature rule for tangent vector fields on the unit sphere $\mathbb{S}^2$ of $\mathbb{R}^3$ --- tensor needlets. The proposed tight tensor needlets…

Numerical Analysis · Mathematics 2019-08-01 Ming Li , Philip Broadbridge , Andriy Olenko , Yu Guang Wang

We consider an application of variational-wavelet approach to nonlinear collective models of beam/plasma physics: Vlasov/Boltzmann-like reduction from general BBGKY hierachy. We obtain fast convergent multiresolution representations for…

Plasma Physics · Physics 2009-11-07 Antonina N. Fedorova , Michael G. Zeitlin

We propose a deep probabilistic-neural-network architecture for learning a minimal and near-orthogonal set of non-linear modes from high-fidelity turbulent-flow-field data useful for flow analysis, reduced-order modeling, and flow control.…

Fluid Dynamics · Physics 2021-09-06 Hamidreza Eivazi , Soledad Le Clainche , Sergio Hoyas , Ricardo Vinuesa

We present an improved system for orbit and betatron phase measurement utilizing nonlinear models of BPM pickup response. We first describe the calculation of the BPM pickup signals as nonlinear functions of beam position using Green's…

Accelerator Physics · Physics 2010-11-15 Richard W. Helms , Georg H. Hoffstaetter

This paper proposes a multivariate nonlinear function-on-function regression model, which allows both the response and the covariates can be multi-dimensional functions. The model is built upon the multivariate functional reproducing kernel…

Methodology · Statistics 2024-06-28 Xu Haijie , Zhang Chen

We recently proposed a new variational theory of "tensor-optimized antisymmetrized molecular dynamics" (TOAMD), which treats the strong interaction explicitly for finite nuclei [T. Myo et al., Prog. Theor. Exp. Phys. 2015, 073D02 (2015)].…

Nuclear Theory · Physics 2017-09-05 Takayuki Myo , Hiroshi Toki , Kiyomi Ikeda , Hisashi Horiuchi , Tadahiro Suhara

We introduce new methods for integrating nonlinear differential equations on low-rank manifolds. These methods rely on interpolatory projections onto the tangent space, enabling low-rank time integration of vector fields that can be…

Numerical Analysis · Mathematics 2024-11-05 Alec Dektor

Snapping beams enable rapid geometric transitions through nonlinear instability, offering an efficient means of generating motion in soft robotic systems. In this study, a tendon-driven mechanism consisting of spiral-based metabeams was…

Robotics · Computer Science 2026-02-23 Mohsen Jafarpour , Ayberk Yüksek , Shahab Eshghi , Stanislav Gorb , Edoardo Milana

The implementation of optimal statistical inference protocols for high-dimensional quantum systems is often computationally expensive. To avoid the difficulties associated with optimal techniques, here I propose an alternative approach to…

Quantum Physics · Physics 2015-12-23 Mankei Tsang

It has been argued by Grigoriev and Rubakov that one can simulate real time processes involving baryon number non-conservation at high temperature using real time evolution of classical equations, and summing over initial conditions with a…

High Energy Physics - Theory · Physics 2008-11-26 Dietrich Bödeker , Larry McLerran , Andrei Smilga

The nuclear time-dependent density functional theory (TDDFT) is a tool of choice for describing various dynamical phenomena in atomic nuclei. In a recent study, we reported an extension of the framework - the multiconfigurational TDDFT…

Nuclear Theory · Physics 2024-01-24 Petar Marević , David Regnier , Denis Lacroix

In wireless communications, estimation of channels in OFDM systems spans frequency and time, which relies on sparse collections of pilot data, posing an ill-posed inverse problem. Moreover, deep learning estimators require large amounts of…

Machine Learning · Computer Science 2025-04-14 Mohammed Mallik , Guillaume Villemaud