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A method to generate reactive trajectories, namely equilibrium trajectories leaving a metastable state and ending in another one is proposed. The algorithm is based on simulating in parallel many copies of the system, and selecting the…

Statistical Mechanics · Physics 2015-05-19 Frédéric Cérou , Arnaud Guyader , Tony Lelièvre , David Pommier

The density matrix renormalization group (DMRG) method allows for very precise calculations of ground state properties in low-dimensional strongly correlated systems. We investigate two methods to expand the DMRG to calculations of…

Condensed Matter · Physics 2009-10-31 Till D. Kuehner , Steven R. White

Differential equations containing memory terms that depend nonlinearly on past states model a variety of non-Markovian processes. In this study, we present a Markovian embedding procedure for such equations with distributed delay by…

Numerical Analysis · Mathematics 2025-12-05 Divya Jaganathan , Rahil N. Valani

Stable partitioned techniques for simulating unsteady fluid-structure interaction (FSI) are known to be computationally expensive when high added-mass is involved. Multiple coupling strategies have been developed to accelerate these…

Computational Engineering, Finance, and Science · Computer Science 2025-02-18 Azzeddine Tiba , Thibault Dairay , Florian de Vuyst , Iraj Mortazavi , Juan-Pedro Berro Ramirez

Infinite projected entangled-pair states (iPEPS) provide a powerful tool to study two-dimensional strongly correlated systems directly in the thermodynamic limit. In this work, we extend the iPEPS toolbox by a method to efficiently evaluate…

Strongly Correlated Electrons · Physics 2025-01-27 Juan Diego Arias Espinoza , Philippe Corboz

Simulating quantum many-body systems (QMBS) is one of the long-standing, highly non-trivial challenges in condensed matter physics and quantum information due to the exponentially growing size of the system's Hilbert space. To date, tensor…

Quantum Physics · Physics 2026-02-06 Belal Abouraya , Jirawat Saiphet , Fedor Jelezko , Ressa S. Said

The reconstruction of spectral function from correlation function in Euclidean space is a challenging task. In this paper, we employ the Machine Learning techniques in terms of the radial basis functions networks to reconstruct the spectral…

High Energy Physics - Phenomenology · Physics 2021-10-27 Meng Zhou , Fei Gao , Jingyi Chao , Yu-Xin Liu , Huichao Song

Hyper-reduction methods have gained increasing attention for their potential to accelerate reduced order models for nonlinear systems, yet their comparative accuracy and computational efficiency are not well understood. Motivated by this…

Mathematical Software · Computer Science 2026-03-02 Axel Larsson , Minji Kim , Chris Vales , Sigrid Adriaenssens , Dylan Matthew Copeland , Youngsoo Choi , Siu Wun Cheung

We present an implementation of the GW approximation for the electronic self-energy within the full-potential linearized augmented-plane-wave (FLAPW) method. The algorithm uses an all-electron mixed product basis for the representation of…

Materials Science · Physics 2010-11-15 Christoph Friedrich , Stefan Blügel , Arno Schindlmayr

In this paper, a hybrid measurement- and model-based method is proposed which can estimate the dynamic state Jacobian matrix in near real-time. The proposed method is computationally efficient and robust to the variation of network…

Systems and Control · Computer Science 2017-03-10 Xiaozhe Wang , Konstantin Turitsyn

In this paper, we disclose the statistical behavior of the max-product algorithm configured to solve a maximum a posteriori (MAP) estimation problem in a network of distributed agents. Specifically, we first build a distributed hypothesis…

Information Theory · Computer Science 2020-04-30 Younes Abdi , Tapani Ristaniemi

The interplay of nuclear and electronic dynamics characterizes the multi-dimensional electronic spectra of various molecular and solid-state systems. Theoretically, the observable effect of such interplay can be accounted for by response…

Quantum Physics · Physics 2023-02-07 Filippo Troiani

Traditional linear methods for forecasting multivariate time series are not able to satisfactorily model the non-linear dependencies that may exist in non-Gaussian series. We build on the theory of learning vector-valued functions in the…

Machine Learning · Computer Science 2017-06-28 Magda Gregorová , Alexandros Kalousis , Stéphane Marchand-Maillet

By revisiting the path-integral formulation of the Hubbard model, we propose a theoretical approach based on a semiclassical approximation employing an unconventional coherent-state representation. Within this framework, a subset of the…

Strongly Correlated Electrons · Physics 2026-04-06 Yuki Yamasaki , Hidemaro Suwa , Cristian D. Batista , Shintaro Hoshino

Nonlinear dynamical systems are ubiquitous in nature and they are hard to forecast. Not only they may be sensitive to small perturbations in their initial conditions, but they are often composed of processes acting at multiple scales.…

Chaotic Dynamics · Physics 2025-10-06 Chenyu Dong , Davide Faranda , Adriano Gualandi , Valerio Lucarini , Gianmarco Mengaldo

We describe and discuss a recently proposed quantum Monte Carlo algorithm to compute the ground-state properties of various systems of interacting fermions. In this method, the ground state is projected from an initial wave function by a…

Condensed Matter · Physics 2009-10-28 Shiwei Zhang , J. Carlson , J. E. Gubernatis

We propose and analyze an approximate message passing (AMP) algorithm for the matrix tensor product model, which is a generalization of the standard spiked matrix models that allows for multiple types of pairwise observations over a…

Machine Learning · Statistics 2023-06-28 Riccardo Rossetti , Galen Reeves

We introduce a method based on matrix product states (MPS) for computing spectral functions of (quasi) one-dimensional spin chains, working directly in momentum space in the thermodynamic limit. We simulate the time evolution after applying…

Strongly Correlated Electrons · Physics 2022-06-08 Maarten Van Damme , Laurens Vanderstraeten

Computationally expensive Radiative Transfer Models (RTMs) are widely used} to realistically reproduce the light interaction with the Earth surface and atmosphere. Because these models take long processing time, the common practice is to…

Solving quantum many-body systems is one of the most significant regimes where quantum computing applies. Currently, as a hardware-friendly computational paradigms, variational algorithms are often used for finding the ground energy of…

Quantum Physics · Physics 2026-02-10 Yong Liu , Guangyao Huang , Yizhi Wang , Junjie Wu