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[ascl:1808.010]
hi_class: Horndeski in the Cosmic Linear Anisotropy Solving System

hi_class implements Horndeski's theory of gravity in the modern Cosmic Linear Anisotropy Solving System (ascl:1106.020). It can be used to compute any cosmological observable at the level of background or linear perturbations, such as cosmological distances, cosmic microwave background, matter power and number count spectra (including relativistic effects). hi_class can be readily interfaced with Monte Python (ascl:1307.002) to test Gravity and Dark Energy models.

[ascl:2103.013]
schNell: Fast calculation of N_ell for GW anisotropies

schNell computes basic map-level noise properties for generic networks of gravitational wave interferometers, primarily the noise power spectrum "N_ell", but this lightweight python module that can also be used for, for example, antenna patterns, overlap functions, and inverse variance maps, among other tasks. The code has three main classes; detectors contain information about each individual detector of the network, such as their positions, noise properties, and orientation. NoiseCorrelations describes the noise-level correlation between pairs of detectors, and the MapCalculators class combines a list of Detectors into a network (potentially together with a NoiseCorrelation object) and computes the corresponding map-level noise properties arising from their correlations.

[ascl:2103.017]
CRIME: Cosmological Realizations for Intensity Mapping Experiments

CRIME (Cosmological Realizations for Intensity Mapping Experiments) generates mock realizations of intensity mapping observations of the neutral hydrogen distribution. It contains three separate tools, GetHI, ForGet, and JoinT. GetHI generates realizations of the temperature fluctuations due to the 21cm emission of neutral hydrogen. Optionally it can also generate a realization of the point-source continuum emission (for a given population) by sampling the same density distribution, though using this feature greatly affects performance. ForGet generates realizations of the different galactic and extra-galactic foregrounds relevant for intensity mapping experiments using some external datasets (e.g. the Haslam 408 MHz map) stored in the "data"folder. JoinT is provided for convenience; it joins the temperature maps generated by GetHI and ForGet and includes several instrument-dependent effects (in an overly simplistic way).

[ascl:2104.022]
RadioFisher: Fisher forecasting for 21cm intensity mapping and spectroscopic galaxy surveys

RadioFisher is a Fisher forecasting code for cosmology with intensity maps of the redshifted 21cm emission line of neutral hydrogen. It uses CAMB (ascl:1102.026) to produce a high-resolution P(k) for the fiducial cosmology when the code is first run and caches the results, making subsequent runs faster and more efficient. It includes specifications for a large number of experiments, as well as survey parameters and the fiducial cosmological parameters, and can run a forecast for a galaxy redshift survey rather than an IM survey. RadioFisher also contains a number of options for plotting results.

[ascl:2105.019]
RandomQuintessence: Integrate the Klein-Gordon and Friedmann equations with random initial conditions

RandomQuintessence integrates the Klein-Gordon and Friedmann equations for quintessence models with random initial conditions and functional forms for the potential. Quintessence models generically impose non-trivial structure on observables like the equation of state of dark energy. There are three main modules; montecarlo_nompi.py sets initial conditions, loops over a bunch of randomly-initialised models, integrates the equations, and then analyses and saves the resulting solutions for each model. Models are defined in potentials.py; each model corresponds to an object that defines the functional form of the potential, various model parameters, and functions to randomly draw those parameters. All of the equation-solving code and methods to analyze the solution are kept in solve.py under the base class DEModel(). Other files available analyze and plot the data in a variety of ways.

[ascl:2306.039]
GRChombo: Numerical relativity simulator

Andrade, Tomas; Salo, Llibert; Aurrekoetxea, Josu; Bamber, Jamie; Clough, Katy; Croft, Robin; de Jong, Eloy; Drew, Amelia; Duran, Alejandro; Ferreira, Pedro; Figueras, Pau; Finkel, Hal; França, Tiago; Ge, Bo-Xuan; Gu, Chenxia; Helfer, Thomas; Jäykkä, Juha; Joana, Cristian; Kunesch, Markus; Kornet, Kacper; Lim, Eugene; Muia, Francesco; Nazari, Zainab; Radia, Miren; Ripley, Justin; Shellard, Paul; Sperhake, Ulrich; Traykova, Dina; Tunyasuvunakool, Saran; Wang, Zipeng; Widdicombe, James; Wong, Kaze

GRChombo performs numerical relativity simulations. It uses Chombo (ascl:1202.008) for adaptive mesh refinement and can evolve standard spacetimes such as binary black hole mergers and scalar collapses into black holes. The code supports non-trivial *many-boxes-in-many-boxes* mesh hierarchies and massive parallelism and evolves the Einstein equation using the standard BSSN formalism. GRChombo is written in C++14 and uses hybrid MPI/OpenMP parallelism and vector intrinsics to achieve good performance.

[ascl:2312.014]
GRFolres: Extension to GRChombo for modified gravity simulations

Aresté Saló, Llibert; Brady, Sam E.; Clough, Katy; Doneva, Daniela; Evstafyeva, Tamara; Figueras, Pau; França, Tiago; Rossi, Lorenzo; Yao, Shunhui; Andrade, Tomas; Aurrekoetxea, Josu; Bamber, Jamie; Croft, Robin; de Jong, Eloy; Drew, Amelia; Duran, Alejandro; Ferreira, Pedro; Finkel, Hal; Ge, Bo-Xuan; Gu, Chenxia; Helfer, Thomas; Jäykkä, Juha; Joana, Cristian; Kunesch, Markus; Kornet, Kacper; Lim, Eugene; Muia, Francesco; Nazari, Zainab; Radia, Miren; Ripley, Justin; Shellard, Paul; Sperhake, Ulrich; Traykova, Dina; Tunyasuvunakool, Saran; Wang, Zipeng; Widdicombe, James; Wong, Kaze

GRFolres performs simulations in modified theories of gravity. It is based on GRChombo (ascl:2306.039) and inherits all of the capabilities of the main GRChombo code, which makes use of the Chombo library (ascl:1202.008) for adaptive mesh refinement. The code implements the 4∂ST theory of modified gravity and the cubic Horndeski theory in (3+1)-dimensional numerical relativity. GRFolres can be used for stable gauge evolution, solving the modified energy and momentum constraints for initial conditions, and monitoring the constraint violation and calculating the energy densities associated with the different scalar terms in the action. It can also extract data for the tensor and scalar gravitational waveforms.