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The design space of networked embedded systems is very large, posing challenges to the optimisation of such platforms when it comes to support applications with real-time guarantees. Recent research has shown that a number of inter-related…

Performance · Computer Science 2020-07-21 Leandro Soares Indrusiak , Robert I. Davis , Piotr Dziurzanski

In this paper, we develop an adaptive multiresolution discontinuous Galerkin (DG) scheme for time-dependent transport equations in multi-dimensions. The method is constructed using multiwavlelets on tensorized nested grids. Adaptivity is…

Numerical Analysis · Mathematics 2016-07-08 Wei Guo , Yingda Cheng

The density-matrix renormalization-group (DMRG) algorithm is extended to treat time-dependent problems. The method provides a systematic and robust tool to explore out-of-equilibrium phenomena in quantum many-body systems. We illustrate the…

Mesoscale and Nanoscale Physics · Physics 2009-11-07 M. A. Cazalilla , J. B. Marston

We develop deep Poisson-gamma dynamical systems (DPGDS) to model sequentially observed multivariate count data, improving previously proposed models by not only mining deep hierarchical latent structure from the data, but also capturing…

Machine Learning · Statistics 2019-01-03 Dandan Guo , Bo Chen , Hao Zhang , Mingyuan Zhou

The paper studies the problem of detecting and locating change points in multivariate time-evolving data. The problem has a long history in statistics and signal processing and various algorithms have been developed primarily for simple…

Machine Learning · Statistics 2025-03-13 Jialiang Geng , George Michailidis

We propose and develop a general method of numerical calculation of the wave function time evolution in a quantum system which is described by Hamiltonian of an arbitrary dimensionality and with arbitrary interactions. For this, we obtain a…

Atomic Physics · Physics 2014-04-25 Ivan Gonoskov , Mattias Marklund

Understanding the intricate properties of one-dimensional quantum systems coupled to multiple reservoirs poses a challenge to both analytical approaches and simulation techniques. Fortunately, density matrix renormalization group-based…

Quantum Physics · Physics 2021-07-15 Heitor P. Casagrande , Dario Poletti , Gabriel T. Landi

An analytical method for investigation of the evolution of dynamical systems {\it with independent on time accuracy} is developed for perturbed Hamiltonian systems. The error-free estimation using of computer algebra enables the application…

Instrumentation and Methods for Astrophysics · Physics 2016-12-13 A. V. Gurzadyan , A. A. Kocharyan

Multi-adaptive Galerkin methods are extensions of the standard continuous and discontinuous Galerkin methods for the numerical solution of initial value problems for ordinary or partial differential equations. In particular, the…

Numerical Analysis · Mathematics 2012-05-15 Johan Jansson , Anders Logg

Moir\'e systems provide a rich platform for studies of strong correlation physics. Recent experiments on hetero-bilayer transition metal dichalcogenide (TMD) Moir\'e systems are exciting in that they manifest a relatively simple model…

Strongly Correlated Electrons · Physics 2023-04-04 Yiqing Zhou , D. N. Sheng , Eun-Ah Kim

This paper presents an improved version of the previously proposed self-consistent drift-diffusion-reaction model correcting for non-physical behavior at longer time scales. To this end a novel boundary condition is employed that takes into…

Materials Science · Physics 2020-06-19 Behrouz Raftari , Neil Budko , Kees Vuik

In the numerical analysis of strongly correlated quantum lattice models one of the leading algorithms developed to balance the size of the effective Hilbert space and the accuracy of the simulation is the density matrix renormalization…

Strongly Correlated Electrons · Physics 2015-06-17 Csaba Nemes , Gergely Barcza , Zoltán Nagy , Örs Legeza , Péter Szolgay

A momentum-space approach of the density-matrix renormalization-group (DMRG) method is developed. Ground state energies of the Hubbard model are evaluated using this method and compared with exact diagonalization as well as quantum…

Condensed Matter · Physics 2009-10-28 T. Xiang

Dynamic Mode Decomposition (DMD) is a data-driven technique to identify a low dimensional linear time invariant dynamics underlying high-dimensional data. For systems in which such underlying low-dimensional dynamics is time-varying, a…

Signal Processing · Electrical Eng. & Systems 2020-04-09 Mustaffa Alfatlawi , Vaibhav Srivastava

We examine the performance of various time propagation schemes using a one-dimensional model of the hydrogen atom. In this model the exact Coulomb potential is replaced by a soft-core interaction. The model has been shown to be a reasonable…

Computational Physics · Physics 2019-02-12 Heman Gharibnejad , Barry I. Schneider , Mark Leadingham , Henry J. Schmale

We examine the performance of the density matrix embedding theory (DMET) recently proposed in [G. Knizia and G. K.-L. Chan, Phys. Rev. Lett. 109, 186404 (2012)]. The core of this method is to find a proper one-body potential that generates…

Strongly Correlated Electrons · Physics 2020-12-07 Masataka Kawano , Chisa Hotta

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

The time evolution of a closed quantum system is connected to its Hamiltonian through Schroedinger's equation. The ability to estimate the Hamiltonian is critical to our understanding of quantum systems, and allows optimization of control.…

We propose a computational method to obtain series expansions in powers of time for general dynamical systems described by a set of hierarchical rate equations. The method is generally applicable to problems in both equilibrium and…

Condensed Matter · Physics 2009-10-28 Chee Kwan Gan , Jian-Sheng Wang

Time-dependent density functional theory (TDDFT) is a widely used method to investigate electron dynamics under external time-dependent perturbations such as laser fields. In this work, we present a machine learning approach to accelerate…

Materials Science · Physics 2025-12-02 Karan Shah , Attila Cangi
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