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Non-adiabatic molecular dynamics (NAMD) simulations have become an indispensable tool for investigating excited-state dynamics in solids. In this work, we propose a general framework, N$^2$AMD which employs an E(3)-equivariant deep neural…

In order to describe excitable reaction-diffusion systems, we derive a two-dimensional model with a Hopf and a semilocal saddle-node homoclinic bifurcation. This model gives the theoretical framework for the analysis of the saddle-node…

Mathematical Physics · Physics 2007-05-23 Rui Dilao , Andras Volford

We point out that superconducting quantum computers are prospective for the simulation of the dynamics of spin models far from equilibrium, including nonadiabatic phenomena and quenches. The important advantage of these machines is that…

Quantum Physics · Physics 2018-07-27 A. A. Zhukov , S. V. Remizov , W. V. Pogosov , Yu. E. Lozovik

In this paper a formalism for studying the dynamics of quantum systems coupled to classical spin environments is reviewed. The theory is based on generalized antisymmetric brackets and naturally predicts open-path off-diagonal geometric…

Quantum Physics · Physics 2016-10-21 Alessandro Sergi

We study nonparametric clustering of smooth random curves on the basis of the L2 gradient flow associated to a pseudo-density functional and we show that the clustering is well-defined both at the population and at the sample level. We…

Statistics Theory · Mathematics 2020-10-22 Mattia Ciollaro , Christopher R. Genovese , Daren Wang

The thermodynamic properties of vector (O(2) and Complex Spherical) models with four-body interactions are analyzed. When defined in dense topologies, these are effective models for the nonlinear interaction of scalar fields in the presence…

Statistical Mechanics · Physics 2015-07-15 Fabrizio Antenucci , Miguel Ibáñez Berganza , Luca Leuzzi

In this paper, we present a parallel computing method for the coupled-cluster singles and doubles (CCSD) in periodic systems. The CCSD in periodic systems solves simultaneous equations for single-excitation and double-excitation amplitudes.…

Strongly Correlated Electrons · Physics 2019-11-04 Takumi Yamashita , Taichi Kosugi , Yu-ichiro Matsushita , Tetsuya Sakurai

Numerous numerical studies have shown that geminal-based methods are a promising direction to model strongly correlated systems with low computational costs. Several strategies have been introduced to capture the missing dynamical…

Chemical Physics · Physics 2023-03-22 Artur Nowak , Katharina Boguslawski

The simulation of molecular electronic structure is an important application of quantum devices. Recently, it has been shown that quantum devices can be effectively combined with classical supercomputing centers in the context of the…

Quantum Physics · Physics 2025-02-28 Stefano Barison , Javier Robledo Moreno , Mario Motta

For settling the problem with rotating turbulence modelling, a quasi-dynamic one-equation subgrid-scale (SGS) model is proposed in this paper. Considering the key role of the joint cascade of kinetic energy and helicity in rotating…

Fluid Dynamics · Physics 2024-01-05 Depei Song , Changping Yu , Zheng Yan , Xinliang Li

We present a non-perturbative framework for deriving effective Hamiltonians that describe low-energy excitations in quantum many-body systems. The method combines block diagonalization based on the Cederbaum--Schirmer--Meyer transformation…

Strongly Correlated Electrons · Physics 2025-05-19 Tsutomu Momoi , Owen Benton

We evaluate the dependence of the cluster correlation length r_c on the mean intercluster separation D_c, for three models with critical matter density, vanishing vacuum energy (Lambda = 0) and COBE normalized: a tilted CDM (tCDM) model…

Astrophysics · Physics 2009-10-31 A. Gardini , S. A. Bonometto , G. Murante , G. Yepes

The structure of oxide-supported metal nanoclusters plays an essential role in their sharply enhanced catalytic activity over bulk metals. Simulations provide the atomic-scale resolution needed to understand these systems. However, the…

Materials Science · Physics 2024-05-22 Benjamin X. Shi , David J. Wales , Angelos Michaelides , Chang Woo Myung

Although useful to extract excitation energies of states of double-excitation character in time-dependent density functional theory that are missing in the adiabatic approximation, the frequency-dependent kernel derived earlier [J. Chem.…

Chemical Physics · Physics 2023-09-19 Davood B. Dar , Neepa T. Maitra

The goal of this paper is to propose a new mathematical model for the combined effect of different treatments and lifestyles on the glucose-insulin dynamics of Type 2 diabetes (T2D) patients. The model gives the possibility to take into…

Systems and Control · Electrical Eng. & Systems 2023-01-11 Mohamad Al Ahdab , John Leth , Torben Knudsen , Peter Vestergaard , Henrik Clausen

We extend the DeePMD neural network architecture to predict electronic structure properties necessary to perform non-adiabatic dynamics simulations. While learning the excited state energies and forces follows a straightforward extension of…

Chemical Physics · Physics 2024-10-17 Lucien Dupuy , Neepa T. Maitra

Solid-solid collapse transition in open framework structures is ubiquitous in nature. The real difficulty in understanding detailed microscopic aspects of such transitions in molecular systems arises from the interplay between different…

Soft Condensed Matter · Physics 2015-06-15 Rakesh S. Singh , Biman Bagchi

A relativistic version of the coupled-cluster single-double (CCSD) method is developed for atoms with a single valence electron. In earlier work, a linearized version of the CCSD method (with extensions to include a dominant class of triple…

Atomic Physics · Physics 2009-11-13 Rupsi Pal , M. S. Safronova , W. R. Johnson , Andrei Derevianko , Sergey G. Porsev

The excited states of polyatomic systems are rather complex, and often exhibit meta-stable dynamical behaviors. Static analysis of reaction pathway often fails to sufficiently characterize excited state motions due to their highly…

Chemical Physics · Physics 2017-08-22 Fang Liu , Likai Du , Dongju Zhang , Jun Gao

Deep subspace clustering based on auto-encoder has received wide attention. However, most subspace clustering based on auto-encoder does not utilize the structural information in the self-expressive coefficient matrix, which limits the…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Ling Zhao , Yunpeng Ma , Shanxiong Chen , Jun Zhou
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