Related papers: binary_c-python: A Python-based stellar population…
We compute and present the distribution in mass of single and binary neutron stars, strange stars, and black holes. The calculations were performed using a stellar population synthesis code. We follow evolution of massive single stars as…
The planetary population synthesis method aims at comprehensively testing planet formation theories against observational evidence and providing theoretical sets of planets to help interpret observations and inform instrument development.…
Probabilistic programming (PP) allows flexible specification of Bayesian statistical models in code. PyMC3 is a new, open-source PP framework with an intutive and readable, yet powerful, syntax that is close to the natural syntax…
The lack of freely available (real-life or synthetic) high or ultra-high dimensional, multi-class datasets may hamper the rapidly growing research on feature screening, especially in the field of biometrics, where the usage of such datasets…
Computer algebra systems play an important role in science as they facilitate the development of new theoretical models. The resulting symbolic equations are often implemented in a compiled programming language in order to provide fast and…
The purpose of this paper is to show how existing scientific software can be parallelized using a separate thin layer of Python code where all parallel communication is implemented. We provide specific examples on such layers of code, and…
For high-assurance software, source-level reasoning is insufficient: we need binary-level guarantees. Despite constrained Horn clause (CHC) solving being one of the most popular forms of automated verification, prior work has not evaluated…
We introduce cellanneal, a python-based software for deconvolving bulk RNA sequencing data. cellanneal relies on the optimization of Spearman's rank correlation coefficient between experimental and computational mixture gene expression…
We describe a web-based cgi calculator for constructing synthetic color-magnitude diagrams for a simple stellar population (SSP) using the Yonsei-Yale (YY) isochrone data base. This calculator is designed to be used interactively. It…
The evolution of binary stellar systems involves a wide range of physical processes, many of which are not yet well understood. We aim to build a general-purpose algorithm based on inverse population synthesis techniques, able to…
For synthesising star clusters and whole galaxies, stellar populations need to be modelled by a set of four functions that define their initial distribution of stellar masses and of the orbital properties of their binary-star populations.…
{\mu}Manager, an open-source microscopy acquisition software, has been an essential tool for many microscopy experiments over the past 15 years, but is not easy to use for experiments in which image acquisition and analysis are closely…
Understanding astrophysical and cosmological processes can be challenging due to their complexity and lack of intuitive analogies. To address this, we present \texttt{AstronomyCalc}, a Python package specifically designed to aid…
Binary stars are common in star clusters and galaxies, but the detailed effects of binary evolution are not taken into account in some colour-magnitude diagram (CMD) studies. This paper studies the CMDs of twelve globular clusters via…
Context: Field stars are not always single stars, but can often be found in bound double systems. Since binary frequencies in the birth places of stars, young embedded clusters, are sometimes even higher than on average the question arises…
One promising way to extract information about stellar astrophysics from gravitational wave catalogs is to compare the catalog to the outputs of stellar population synthesis modeling with varying physical assumptions. The parameter space of…
We present the Python package CELL, which provides a modular approach to the cluster expansion (CE) method. CELL can treat a wide variety of substitutional systems, including one-, two-, and three-dimensional alloys, in a general…
ABCpy is a highly modular scientific library for Approximate Bayesian Computation (ABC) written in Python. The main contribution of this paper is to document a software engineering effort that enables domain scientists to easily apply ABC…
Numerical stability is a crucial requirement of reliable scientific computing. However, despite the pervasiveness of Python in data science, analyzing large Python programs remains challenging due to the lack of scalable numerical analysis…
Context. Understanding the formation and evolution of star clusters in the Milky Way requires precise identification of clusters that form binary or multiple systems. Such systems offer valuable insight into the dynamical processes and…