Related papers: GGCHEMPY: A pure Python-based gas-grain chemical c…
Computer simulation has become one of the most important tools in scientific research in many disciplines. Benefiting from the dynamical trajectories regulated by versatile interatomic interactions, various material properties can be…
Common analysis techniques in multi-messenger astronomy involve hypothesis tests with unbinned log-likelihood (LLH) functions using data recorded in celestial coordinates to identify sources of high-energy cosmic particles in the Universe.…
The exponential growth of complex data demands fully automatic clustering. Gaussian mixture models (GMMs) provide uncertainty-aware grouping but often require expertise to specify hyperparameters, e.g., component count and covariance…
FluidDyn is a project to foster open-science and open-source in the fluid dynamics community. It is thought of as a research project to channel open-source dynamics, methods and tools to do science. We propose a set of Python packages…
SparseChem provides fast and accurate machine learning models for biochemical applications. Especially, the package supports very high-dimensional sparse inputs, e.g., millions of features and millions of compounds. It is possible to train…
We have successfully ported under GNU Linux ATLAS 9, the widely used stellar atmosphere modeling code, as well as both the SYNTHE suite of programs, its ``companion'' for spectral synthesis, and WIDTH, used to derive chemical abundances…
Qudi is a general, modular, multi-operating system suite written in Python 3 for controlling laboratory experiments. It provides a structured environment by separating functionality into hardware abstraction, experiment logic and user…
Chemical tagging of stars based on their similar compositions can offer new insights about the star formation and dynamical history of the Milky Way. We investigate the feasibility of identifying groups of stars in chemical space by…
Particle tracking simulations with space charge effects are very important for high-intensity proton rings. Since they include not only Hamilton mechanics of a single particle but constructing charge densities and solving Poisson equations…
We present the easy-to-use, publicly available, Python package petitRADTRANS, built for the spectral characterization of exoplanet atmospheres. The code is fast, accurate, and versatile; it can calculate both transmission and emission…
GANDALF is a new hydrodynamics and N-body dynamics code designed for investigating planet formation, star formation and star cluster problems. GANDALF is written in C++, parallelised with both OpenMP and MPI and contains a python library…
The scientific computing ecosystem in Python is largely confined to single-node parallelism, creating a gap between high-level prototyping in NumPy and high-performance execution on modern supercomputers. The increasing prevalence of…
We present the library {\tt ggxy}, written in {\tt C++}, which can be used to compute partonic and hadronic cross sections for gluon-induced processes with at least one closed heavy quark loop. It is based on analytic ingredients which…
The Python Sky Model (PySM) is a Python package used by Cosmic Microwave Background (CMB) experiments to simulate maps, in HEALPix pixelization, of the various diffuse astrophysical components of Galactic emission relevant at CMB…
In this study we demonstrate for the first time that the unified Monte Carlo approach can be applied to model gas-grain chemistry in large reaction networks. Specifically, we build a time-dependent gas-grain chemical model of the…
Understanding whether prebiotic molecules can endure and reform through the energetic stages of star formation is essential for tracing the continuity of interstellar chemistry toward life. Glycolamide, an isomer of glycine, was recently…
Molecules in space are synthesized via a large variety of gas-phase reactions, and reactions on dust-grain surfaces, where the surface acts as a catalyst. Especially, saturated, hydrogen-rich molecules are formed through surface chemistry.…
We describe a novel, interdisciplinary, computational methods course that uses Python and associated numerical and visualization libraries to enable students to implement simulations for a number of different course modules. Problems in…
In this paper we present a framework for solving two phase flow problems in porous media. The discretization is based on a Discontinuous Galerkin method and includes local grid adaptivity and local choice of polynomial degree. The method is…
DisCoPy (Distributional Compositional Python) is an open source toolbox for computing with string diagrams and functors. In particular, the diagram data structure allows to encode various kinds of quantum processes, with functors for…