Related papers: Smokescreen: A Python package for data vector blin…
We present cosmo_learn, an open-source python-based software package designed to simulate cosmological data and perform data-driven inference using a range of modern statistical and machine learning techniques. Motivated by the growing…
Cosmic-ray observatories necessarily rely on Monte Carlo simulations for their design, calibration and analysis of their data. Detailed simulations are very demanding computationally. We present a python-based package called ShowerModel to…
The absorption and emission of light by exoplanet atmospheres encode details of atmospheric composition, temperature, and dynamics. Fundamentally, simulating these processes requires detailed knowledge of the opacity of gases within an…
The concept of blind analysis, a key procedure to remove the human-based systematic error called confirmation bias, has long been an integral part of data analysis in many research areas. In cosmology, blind analysis is recently making its…
The goal of blinding is to hide an experiment's critical results -- here the inferred cosmological parameters -- until all decisions affecting its analysis have been finalised. This is especially important in the current era of precision…
Automated searches for strong gravitational lensing in optical imaging survey datasets often employ machine learning and deep learning approaches. These techniques require more example systems to train the algorithms than have presently…
We present BROOM, a new python package for the application of blind, minimum-variance component-separation techniques to microwave observations. The package enables the reconstruction of signals with known spectral energy distributions,…
We introduce cosmocnc, a Python package for computing the number count likelihood of galaxy cluster catalogues in a fast, flexible and accurate way. cosmocnc offers three types of likelihoods: an unbinned, a binned, and an extreme value…
Early-stage fire scenes (0-15 minutes after ignition) represent a crucial temporal window for emergency interventions. During this stage, the smoke produced by combustion significantly reduces the visibility of surveillance systems,…
We introduce pymovements: a Python package for analyzing eye-tracking data that follows best practices in software development, including rigorous testing and adherence to coding standards. The package provides functionality for key…
Seglearn is an open-source python package for machine learning time series or sequences using a sliding window segmentation approach. The implementation provides a flexible pipeline for tackling classification, regression, and forecasting…
First-principles computational spectroscopy is a critical tool for interpreting experiment, performing structure refinement, and developing new physical understanding. Systematically setting up input files for different simulation codes and…
pyscreener is a Python library that seeks to alleviate the challenges of large-scale structure-based design using computational docking. It provides a simple and uniform interface that is agnostic to the backend docking engine with which to…
We introduce a software suite developed for galaxy cluster cosmological analysis with the Dark Energy Survey Data. Cosmological analyses based on galaxy cluster number counts and weak-lensing measurements need efficient software…
lightcurver is a photometric pipeline for time series astronomical imaging data, designed for the semi-automatic extraction of precise light curves from small, blended targets. Such targets include, but are not limited to, lensed quasars,…
cloelike is a Python package providing modular, composable Gaussian likelihood classes for the main cosmological large-scale structure observables targeted by the ESA Euclid space mission. It is a core component of the CLOE (Cosmology…
We describe a new open source package for calculating properties of galaxy clusters, including NFW halo profiles with and without the effects of cluster miscentering. This pure-Python package, cluster-lensing, provides well-documented and…
HSTCosmicrays is a python-based pipeline designed to find and characterize cosmic rays found in dark frames (exposures taken with the shutter closed). Dark exposures are obtained routinely by all the Hubble Space Telescope (HST) instruments…
We present starkiller, an open-source Python package for forward-modeling flux retrieval from integral field unit spectrograph (IFU) datacubes. Starkiller simultaneously provides stellar spectral classification, relative velocity, and…
We present the methodology for the weak lensing and galaxy clustering analyses of the Dark Energy Survey (DES) Year 6 data set. In this work, we design and validate the analysis pipeline for the cosmic shear, galaxy clustering plus…