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A set of analytical and computational tools based on transition path theory (TPT) is proposed to analyze flows in complex networks. Specifically, TPT is used to study the statistical properties of the reactive trajectories by which…

PyPOTS is an open-source Python library dedicated to data mining and analysis on multivariate partially-observed time series with missing values. Particularly, it provides easy access to diverse algorithms categorized into five tasks:…

This paper documents package for the particle level fast simulation. The package is designed to complete the AcerMC generator framework with the easy-to-use simulation and reconstruction algorithms. The package provides, starting from list…

RefDB is the CMS Monte Carlo Reference Database. It is used for recording and managing all details of physics simulation, reconstruction and analysis requests, for coordinating task assignments to world-wide distributed Regional Centers,…

We introduce MCCE: Monte Carlo sampling of valid and realistic Counterfactual Explanations for tabular data, a novel counterfactual explanation method that generates on-manifold, actionable and valid counterfactuals by modeling the joint…

PowNet is a free modelling tool for simulating the Unit Commitment / Economic Dispatch of large-scale power systems. PowNet is specifically conceived for applications in the water-energy nexus domain, which investigate the impact of water…

A new data format for Monte Carlo (MC) events, or any structural data, including experimental data, is discussed. The format is designed to store data in a compact binary form using variable-size integer encoding as implemented in the…

The use of virtual data for enhancing the collaboration between large groups of scientists is explored in several ways: - by defining ``virtual'' parameter spaces which can be searched and shared in an organized way by a collaboration of…

We propose a data format for Monte Carlo (MC) events, or any structural data, including experimental data, in a compact binary form using variable-size integer encoding as implemented in the Google's Protocol Buffers package. This approach…

swdatatoolkit is a Python-based scientific software library designed to support the acquisition, preprocessing, and analysis of solar and space weather data. The toolkit consolidates functionality across multiple domains, including data…

We present a new environment for computations in particle physics phenomenology employing recent developments in cloud computing. On this environment users can create and manage "virtual" machines on which the phenomenology codes/tools can…

Computational experiments have become essential for scientific discovery, allowing researchers to test hypotheses, analyze complex datasets, and validate findings. However, as computational experiments grow in scale and complexity, ensuring…

We present the pulsar_spectra software repository, an open-source pulsar flux density catalogue and automated spectral fitting software that finds the best spectral model and produces publication-quality plots. The Python-based software…

The development of a knowledge repository for climate science data is a multidisciplinary effort between the domain experts (climate scientists), data engineers whos skills include design and building a knowledge repository, and machine…

Current and future astroparticle physics experiments are operated or are being built to observe highly energetic particles, high energy electromagnetic radiation and gravitational waves originating from all kinds of cosmic sources. The data…

Recently, much attention has been focused on the replicability of scientific results, causing scientists, statisticians, and journal editors to examine closely their methodologies and publishing criteria. Experimental particle physicists…

The modeling of physical processes is an integral part of scientific and technical research. In this area, the Extendible C++ Application in Quantum Technologies (ECAQT) package provides the numerical simulations and modeling of complex…

A number of scientific competitions have been organised in the last few years with the objective of discovering innovative techniques to perform typical High Energy Physics tasks, like event reconstruction, classification and new physics…

The Python functions distributed with this article can be used for calculating the parameters of multichannel quantum defect theory models describing excited bound states of complex atoms. These parameters are obtained by fitting a model to…

DIPLODOCUS (Distribution-In-PLateaux methODOlogy for the CompUtation of transport equationS) is a framework being developed for the mesoscopic modelling of astrophysical systems via the transport of particle distribution functions through…