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Related papers: UKRmol+: a suite for modelling of electronic proce…

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The new version of the Ultra-relativistic Quantum Molecular Dynamics model (UrQMD-2.3) is presented. The Ultra-relativistic Quantum Molecular Dynamics model (UrQMD) is a microscopic many body approach to pp, pA and AA interactions at…

High Energy Physics - Phenomenology · Physics 2008-05-06 Hannah Petersen , Marcus Bleicher , Steffen A. Bass , Horst Stöcker

The advent of a next linear $e^\pm e^-$ collider and back-scatterd laser beams will allow the study of a vast array of high energy processes of the Standard Model through the fusion of real and virtual photons and other gauge bosons. As…

High Energy Physics - Phenomenology · Physics 2009-09-11 S. J. Brodsky

We have developed the polyatomic extension of a recently established (M. Gustafsson, J. Chem. Phys, 138, 074308 (2013)) classical theory of radiative association in the absence of electronic transitions. The cross section of the process is…

Chemical Physics · Physics 2021-10-22 Péter Szabó , Magnus Gustafsson

We propose the idea of using Kuramoto models (including their higher-dimensional generalizations) for machine learning over non-Euclidean data sets. These models are systems of matrix ODE's describing collective motions (swarming dynamics)…

Machine Learning · Computer Science 2024-05-16 Vladimir Jacimovic

Machine learning has emerged as a powerful tool in materials discovery, enabling the rapid design of novel materials with tailored properties for countless applications, including in the context of energy and sustainability. To ensure the…

Within the framework of intermittency analysis, a search for critical fluctuations is ongoing to locate the possible critical point in the quantum chromodynamics phase diagram. In this study, self-similar critical fluctuations from a…

Nuclear Theory · Physics 2022-12-09 Jin Wu , Zhiming Li , Xiaofeng Luo , Mingmei Xu , Yuanfang Wu

We address the degree to which machine learning can be used to accurately and transferably predict post-Hartree-Fock correlation energies. Refined strategies for feature design and selection are presented, and the molecular-orbital-based…

Chemical Physics · Physics 2019-04-17 Lixue Cheng , Matthew Welborn , Anders S. Christensen , Thomas F. Miller

This paper proposes a machine learning (ML) method to predict stable molecular geometries from their chemical composition. The method is useful for generating molecular conformations which may serve as initial geometries for saving time…

Our ultimate goal is the construction of a model for interactions of two nuclei in the energy range between several tens of GeV up to several TeV per nucleon in the centre-of-mass system. Such nuclear collisions are very complex, being…

High Energy Physics - Phenomenology · Physics 2007-05-23 H. J. Drescher , M. Hladik , S. Ostapchenko , K. Werner

To analyse ultrarelativistic nuclear interactions, usually either dynamical models like the string model are employed, or a thermal treatment based on hadrons or quarks is applied. String models encounter problems due to high string…

Nuclear Theory · Physics 2016-09-08 Klaus WERNER , Joerg AICHELIN

An accurate description of nonadiabatic dynamics of molecular species on metallic surfaces poses a serious computational challenge associated with a multitude of closely-spaced electronic states. We propose a mixed quantum-classical scheme…

Chemical Physics · Physics 2017-01-10 Ilya G. Ryabinkin , Artur F. Izmaylov

Machine learning (ML) plays an important role in quantum chemistry, providing fast-to-evaluate predictive models for various properties of molecules. However, most existing ML models for molecular electronic properties use density…

Chemical Physics · Physics 2024-06-26 Hao Tang , Brian Xiao , Wenhao He , Pero Subasic , Avetik R. Harutyunyan , Yao Wang , Fang Liu , Haowei Xu , Ju Li

The three-body scattering problem in Coulombic systems is widespread, however yet unresolved problem by the mathematically rigorous methods. In this work this long term challenge has been undertaken by combining distorted waves and…

Quantum Physics · Physics 2017-03-08 R. Lazauskas

An overview of quantum-mechanical methods to generate cross-section data for electron collisions with atoms and molecules is presented. Particular emphasis is placed on the time-independent close-coupling approach, since it is particularly…

Plasma Physics · Physics 2016-10-21 Klaus Bartschat , Jonathan Tennyson , Oleg Zatsarinny

An algorithm for the calculation of hyperfine structure and spectra of diatomic molecules based on the variational nuclear motion is presented. Hyperfine coupling terms considered are Fermi-contact, nuclear spin-electron spin dipole-dipole,…

Chemical Physics · Physics 2022-02-15 Qianwei Qu , Sergei N. Yurchenko , Jonathan Tennyson

Quantum computation and quantum information processing are emerging technologies that have potential to overcome the physical limitation of traditional computation systems. Present quantum systems based on photons, atoms and molecules,…

Quantum Physics · Physics 2021-07-15 Mingfeng Wang , Yipeng Zhang , Wei Zhang

We present a novel scattering emulator utilizing the complex scaling method to enhance nuclear reaction analysis. This approach leverages a single set of reduced bases, allowing for efficient and simultaneous emulation across multiple…

Nuclear Theory · Physics 2024-10-24 Junzhe Liu , Jin Lei , Zhongzhou Ren

We present a non-perturbative expression for the scattering matrix of $N$ particles interacting inside a quantum dot. Characterizing the dot by its resonances, we find a compact form for the scattering matrix in a real-time representation.…

Mesoscale and Nanoscale Physics · Physics 2008-06-10 A. V. Lebedev , G. B. Lesovik , G. Blatter

Neutrinos are likely the most poorly understood basic constituents of the Standard Model. In order to investigate precisely their interactions one should be able to create high intensity and well-collimated neutrino beams with known flavor…

High Energy Physics - Phenomenology · Physics 2020-02-13 I. Alikhanov

In the search for novel nanostructured materials for UV plasmonics a limited number of choices can be done. Materials such as aluminum, rhodium, gallium and few others can be used. One of the most interesting application for UV plasmonics…