The highly optimized Kotekan framework processes streaming data. Written in a combination of C/C++, it is primarily designed for use on radio telescopes and was originally developed for the CHIME project. It is similar to radio projects such as GNUradio (ascl:2504.029) or Bifrost (ascl:1711.021), though has a greater focus on efficiency and throughput. Kotekan is conceptually straightforward: data is carried through the system in a series of ring buffer objects, which are connected by processing blocks which manipulate the data, and optional metadata structures can be passed alongside the streaming data.

ASpec is a spectrum and line analysis package developed at STScI. ASpec is designed as an add-on package for IRAF and incorporates a variety of analysis techniques for astronomical spectra. ASpec operates on spectra from a wide variety of ground-based and space-based instruments and allows simultaneous handling of spectra from different wavelength regimes. The package accommodates non-linear dispersion relations and provides a variety of functions, individually or in combination, with which to fit spectral features and the continuum. It also permits the masking of known bad data. ASpec provides a powerful, intuitive graphical user interface implemented using the IRAF Object Manager and customized to handle: data input/output (I/O); on-line help; selection of relevant features for analysis; plotting and graphical interaction; and data base management.

Driftscan simulates and analyzes transit radio interferometers, with a particular focus on 21cm cosmology. Given a design of a telescope, it generates a set of products used to analyze data from it and simulate timestreams. Driftscan also constructs a filter to extract cosmological 21 cm emission from astrophysical foregrounds, such as our galaxy and radio point sources, and estimates the 21cm power spectrum using an optimal quadratic estimator.

Caput (Cluster Astronomical Python Utilities) contains utilities for handling large datasets on computer clusters. Written with radio astronomy in mind, the package provides an infrastructure for building, managing and configuring pipelines for data processing. It includes modules for dynamically importing and utilizing mpi4py, in-memory mock-ups of h5py objects, and infrastructure for running data analysis pipelines on computer clusters. Caput features a generic container for holding self-documenting datasets in memory with straightforward syncing to h5py files, and offers specialization for holding time stream data. Caput also includes tools for MPI-parallel analysis and routines for converting between different time representations, dealing with leap seconds, and calculating celestial times.

cambmag is a modification to CAMB (ascl:1102.026) that calculates the compensated magnetic mode in the scalar, vector and tensor case. Previously CAMB included code only for the vectors. It also corrects for tight-coupling issues and adds in the ability to include massive neutrinos when calculating vector modes.

DecouplingModes calculates the amplitude of the passive modes, which requires solving the Einstein equations on superhorizon scales sourced by the anisotropic stress from the magnetic fields (prior to neutrino decoupling), and the magnetic and neutrino stress (after decoupling). The code is available as a Mathematica notebook.

InitialConditions finds the initial series solutions for perturbations in our Universe. This includes all scalar (1 adiabatic, 4 isocurvature and 2 magnetic modes), vector (1 vorticity mode, 1 magnetic mode), and tensor (1 gravitational wave mode and 1 magnetic mode) perturbations including terms up to second order in the neutrino mass. It can handle the standard species (cdm, baryons, photons), and two neutrino mass eigenstates (1 light, 1 heavy).

draco analyzes transit radio data with the m-mode formalism. It is telescope agnostic, and is used as part of the analysis and simulation pipeline for the CHIME (Canadian Hydrogen Intensity Mapping Experiment) telescope. It can simulate time stream data from maps of the sky (using the m-mode formalism) and add gain fluctuations and correctly correlated instrumental noise (i.e. Wishart distributed). Further, it can perform various cuts on the data and make maps of the sky from data using the m-mode formalism.