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Cosmic structure simulations have improved enormously over the past decade, both in terms of the resolution which can be achieved, and with the addition of hydrodynamic and other techniques to formerly purely gravitational methods. This is…

Astrophysics · Physics 2007-05-23 H. M. P. Couchman

Computational chemistry allows researchers to experiment in sillico: by running a computer simulations of a biological or chemical processes of interest. Molecular dynamics with molecular mechanics model of interactions simulates N-body…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-03-03 Jana Pazúriková

With the advent of high-performance computing techniques, the data for analysis has grown significantly. Here, graphic processing unit (GPU) based program kernels are discussed to exploit parallelism in the analysis codes specific to…

Computational Physics · Physics 2018-11-07 Gourav Shrivastav , Manish Agarwal

BondGraphTools is a Python library for scripted modelling of complex multi-physics systems. In contrast to existing modelling solutions, BondGraphTools is based upon the well established bond graph methodology, provides a programming…

Systems and Control · Electrical Eng. & Systems 2019-06-27 Peter Cudmore , Peter J. Gawthrop , Michael Pan , Edmund J. Crampin

Probabilistic graphical models (PGMs) have become a popular tool for computational analysis of biological data in a variety of domains. But, what exactly are they and how do they work? How can we use PGMs to discover patterns that are…

Quantitative Methods · Quantitative Biology 2010-02-22 Edoardo M Airoldi

The development of new superconducting circuits and the improvement of existing ones rely on the accurate modeling of spectral properties which are key to achieving the needed advances in qubit performance. Systematic circuit analysis at…

Quantum Physics · Physics 2023-02-07 Sai Pavan Chitta , Tianpu Zhao , Ziwen Huang , Ian Mondragon-Shem , Jens Koch

Graph neural networks (GNNs), which are capable of learning representations from graphical data, are naturally suitable for modeling molecular systems. This review introduces GNNs and their various applications for small organic molecules.…

Machine Learning · Computer Science 2023-10-10 Yuyang Wang , Zijie Li , Amir Barati Farimani

Development of computer technology in chemistry, bring many application of chemistry. Not only the application to visualize the structure of molecule but also to molecular dynamics simulation. One of them is Gromacs. Gromacs is an example…

Computational Engineering, Finance, and Science · Computer Science 2009-12-07 A. D. Astuti , A. B. Mutiara

Determining visibility in planar polygons and arrangements is an important subroutine for many algorithms in computational geometry. In this paper, we report on new implementations, and corresponding experimental evaluations, for two…

Computational Geometry · Computer Science 2014-03-18 Francisc Bungiu , Michael Hemmer , John Hershberger , Kan Huang , Alexander Kröller

In this paper, we introduce a new approach for drawing diagrams that have applications in software visualization. Our approach is to use a technique we call confluent drawing for visualizing non-planar diagrams in a planar way. This…

Computational Geometry · Computer Science 2007-05-23 Matthew Dickerson , David Eppstein , Michael T. Goodrich , Jeremy Meng

PACKMOL is a widely utilized molecular modeling tool within the computational chemistry community. However, its perceivable advantages have been impeded by the long-standing lack of a robust open-source graphical user interface (GUI) that…

Chemical Physics · Physics 2024-08-26 Jian Huang , Chenchen Wu , Xiner Yang , Zaixing Yang , Shengtang Liu , Gang Yu

This chapter summarizes several approaches combining theory, simulation and experiment that aim for a better understanding of phenomena in lipid bilayers and membrane protein systems, covering topics such as lipid rafts, membrane mediated…

Biological Physics · Physics 2014-12-17 Markus Deserno , Kurt Kremer , Harald Paulsen , Christine Peter , Friederike Schmid

We introduce a visual representation of qubits to assist in explaining quantum computing to a broad audience. The representation follows from physical devices that we developed to explain superposition, entanglement, measurement, phases,…

Quantum Physics · Physics 2022-11-30 Sophie Laplante , Loris Perez , Sylvie Tissot , Lou Vettier

Machine learning has proven to be a valuable tool to approximate functions in high-dimensional spaces. Unfortunately, analysis of these models to extract the relevant physics is never as easy as applying machine learning to a large dataset…

Materials Science · Physics 2020-05-06 Conrad W. Rosenbrock , Eric R. Homer , Gábor Csányi , Gus L. W. Hart

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims…

This article provides an introduction to and review of the field of computer-aided molecular design (CAMD). It is intended to be approachable for the absolute beginner as well as useful to the seasoned CAMD practitioner. We begin by…

Computational Engineering, Finance, and Science · Computer Science 2017-01-17 Nick D. Austin , Nikolaos V. Sahinidis , Daniel W. Trahan

This article is intended to an introductory lecture in material physics, in which the modern computational group theory and the electronic structure calculation are in collaboration. The effort of mathematicians in field of the group…

Materials Science · Physics 2019-08-08 Akihito Kikuchi

In order to take advantage of the enormous potential of graphene for future electronic micro-circuits and other applications it is necessary to develop reliable, rapid and widely applicable methods to visualize graphene based structures. We…

Mesoscale and Nanoscale Physics · Physics 2010-12-15 Hugo Gonçalves , Michael Belsley , Cacilda Moura , Tobias Stauber , Peter Schellenberg

The purpose of this review is to introduce the reader to graph kernels and the corresponding literature, with an emphasis on those with direct application to chemoinformatics. Graph kernels are functions that allow for the inference of…

Machine Learning · Statistics 2022-08-29 James Young

Molecular dynamics simulations use statistical mechanics at the atomistic scale to enable both the elucidation of fundamental mechanisms and the engineering of matter for desired tasks. The behavior of molecular systems at the microscale is…

Computational Physics · Physics 2020-12-25 Wujie Wang , Simon Axelrod , Rafael Gómez-Bombarelli