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We present a new chemodynamical code based on the adaptive mesh refinement code RAMSES. The new code uses Eulerian hydrodynamics and N-body dynamics in a cosmological framework to trace the production and advection of several chemical…

Astrophysics of Galaxies · Physics 2012-02-13 C. Gareth Few , Stephanie Courty , Brad K. Gibson

We present the advantages of a multiscale modelling strategy for the understanding of systems with charged interfaces. On the one hand, one can simulate a complex system at different levels, depending on the relevant length and time scales…

Chemical Physics · Physics 2018-11-26 Benjamin Rotenberg

We present a comparison between independent computer codes, modeling the physics and chemistry of interstellar photon dominated regions (PDRs). Our goal was to understand the mutual differences in the PDR codes and their effects on the…

An end-to-end platform for chemical science research has been developed that integrates data from computational and experimental approaches through a modern web-based interface. The platform offers a highly interactive visualization and…

Software Engineering · Computer Science 2017-07-17 Marcus D. Hanwell , Wibe A. de Jong , Christopher J. Harris

Molecular dynamics simulations play an increasingly important role in the rational design of (nano)-materials and in the study of biomacromolecules. However, generating input files and realistic starting coordinates for these simulations is…

With the launch of the James Webb Space Telescope, we are firmly in the era of exoplanet atmosphere characterization. Understanding exoplanet spectra requires atmospheric chemical and climate models that span the diversity of planetary…

This review discusses recent results on the astrochemistry of (mostly high-mass) star-forming regions. After an introduction on the use of chemistry in astrophysics and some basic concepts of astrochemistry, specific results are presented.…

Astrophysics · Physics 2007-11-26 Floris van der Tak

In chemical reaction network theory, ordinary differential equations are used to model the temporal change of chemical species concentration. As the functional form of these ordinary differential equations systems is derived from an…

Molecular Networks · Quantitative Biology 2025-02-27 Anna C. M. Thöni , William E. Robinson , Yoram Bachrach , Wilhelm T. S. Huck , Tal Kachman

This paper presents a new language called APSL for formally describing protocols to facilitate automated testing. Many real world communication protocols exchange messages whose structures are not trivial, e.g. they may consist of multiple…

Software Engineering · Computer Science 2018-04-12 Tom Tervoort , I. S. W. B. Prasetya

Molecules are ubiquitous in space. They are necessary component in the creation of habitable planetary systems and can provide the basic building blocks of life. Solid-state processes are pivotal in the formation of molecules in space and…

I review the basic concepts for the spectrophotometric and chemical evolution of galaxies, contrast various approaches and discuss their respective advantages and shortcomings, both for the interpretation of nearby and high redshift…

Astrophysics · Physics 2007-05-23 U. Fritze-v. Alvensleben

In the last few years, we have seen the transformative impact of deep learning in many applications, particularly in speech recognition and computer vision. Inspired by Google's Inception-ResNet deep convolutional neural network (CNN) for…

Machine Learning · Statistics 2018-08-15 Garrett B. Goh , Charles Siegel , Abhinav Vishnu , Nathan O. Hodas , Nathan Baker

A major limitation and a continuing source of confusion in the interpretation of molecular line observations has been the large degree of chemical complexity that is observed in star-forming molecular cores. The past decade has seen…

Astrophysics · Physics 2017-01-18 Edwin A. Bergin

Visual data is used in numerous different scientific workflows ranging from remote sensing to ecology. As the amount of observation data increases, the challenge is not just to make accurate predictions but also to understand the underlying…

Computer Vision and Pattern Recognition · Computer Science 2025-02-17 Utkarsh Mall , Cheng Perng Phoo , Mia Chiquier , Bharath Hariharan , Kavita Bala , Carl Vondrick

Chemical reactivity models are developed to predict chemical reaction outcomes in the form of classification (success/failure) or regression (product yield) tasks. The vast majority of the reported models are trained solely on chemical…

Machine Learning · Computer Science 2024-01-31 Aline Hartgers , Ramil Nugmanov , Kostiantyn Chernichenko , Joerg Kurt Wegner

We have undertaken numerical simulations of galaxy interactions and mergers, coupling the dynamics with the star formation history and the chemical evolution. The self-gravity of stars and gas is taken into account through a tree-code…

Astrophysics · Physics 2009-11-07 F. Combes , A. L. Melchior

Large Language Models (LLMs) are widely used across various scenarios due to their exceptional reasoning capabilities and natural language understanding. While LLMs demonstrate strong performance in tasks involving mathematics and coding,…

Artificial Intelligence · Computer Science 2025-06-03 Xinyi Liu , Lipeng Ma , Yixuan Li , Weidong Yang , Qingyuan Zhou , Jiayi Song , Shuhao Li , Ben Fei

Chemistry has a key role in the evolution of the interstellar medium (ISM), so it is highly desirable to follow its evolution in numerical simulations. However, it may easily dominate the computational cost when applied to large systems. In…

Instrumentation and Methods for Astrophysics · Physics 2015-06-12 T. Grassi , S. Bovino , D. Schleicher , F. A. Gianturco

In this era of exoplanet characterisation with JWST, the need for a fast implementation of classical forward models to understand the chemical and physical processes in exoplanet atmospheres is more important than ever. Notably, the…

Earth and Planetary Astrophysics · Physics 2023-06-28 Julius L. A. M. Hendrix , Amy J. Louca , Yamila Miguel

In this review, we highlight recent developments in the application of machine learning for molecular modeling and simulation. After giving a brief overview of the foundations, components, and workflow of a typical supervised learning…

Data Analysis, Statistics and Probability · Physics 2019-02-21 Mojtaba Haghighatlari , Johannes Hachmann
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