Sapphire++ is an open-source code designed to numerically solve the Vlasov–Fokker–Planck equation for astrophysical applications. Sapphire++ employs a numerical algorithm based on a spherical harmonic expansion of the distribution function, expressing the Vlasov–Fokker–Planck equation as a system of partial differential equations governing the evolution of the expansion coefficients. The code utilises the discontinuous Galerkin method in conjunction with implicit and explicit time stepping methods to compute these coefficients, providing significant flexibility in its choice of spatial and temporal accuracy.

infrared_comparison compares the downwelling infrared radiation, or sky spectral brightness, of arctic/antarctic astronomical observing sites with the best mid-latitude mountain sites. The code site provides a tarfile of Fourier-transform spectra from 3.3 microns 20 microns, obtained near Eureka, on Ellesmere Island Canada, along with meteorological data. The code can compare these via an atmospheric thermal-inversion model to reported values for South Pole and other mid-latitude sites, such as Maunakea.

arctic_mass_dimm reduces data from the Multi-Aperture Seeing Sensor (MASS) and Differential Image Motion Monitor (MASS) obtained from the Polar Environment Atmospheric Research Laboratory (PEARL), reporting seeing conditions, and comparing to other observatories. The code site provides a tarfile of all MASS and DIMM data obtained near Eureka, on Ellesmere Island Canada in 2011/12 along with associated meteorological data. The code employs a simple two-component atmospheric model to allow comparison of PEARL to mid-latitude sites such as Maunakea.

allsky performs photometry of Polaris with the Polar Environment Atmospheric Research Laboratory (PEARL) All-Sky Camera (PASI) to report transparency measurements, with comparison to conditions at other observatories worldwide. The code site provides a tarfile of PASI data obtained near Eureka, on Ellesmere Island Canada in darktime of 2008/09 and 2009/10 along with associated meteorological data. The code employs a simple atmospheric thermal inversion model, with a power-law fit to ice-crystal attenuation, allowing direct comparison of PEARL dark-time photometric-sky statistics to mid-latitude sites such as Maunakea.

arctic_weather reports analysis of meteorological data recorded from High Arctic weatherstations (called Inuksuit) deployed on coastal mountains north of 80 degrees on Ellesmere Island Canada from 2006 through 2009, along with clear-sky fractions from horizon-viewing sky-monitoring cameras. The code calculates solar and lunar elevations, and so allows correlation of polar nighttime to the development of prevailing thermal inversion conditions in winter, and statistical comparison to other optical/infrared observatory sites.

We introduce COBRA (Cosmology with Optimally factorized Bases for Rapid Approximation), a novel framework for rapid computation of large-scale structure observables. COBRA separates scale dependence from cosmological parameters in the linear matter power spectrum while also minimising the number of necessary basis terms, thus enabling direct and efficient computation of derived and nonlinear observables. Moreover, the dependence on cosmological parameters is efficiently approximated using radial basis function interpolation. We apply our framework to decompose the linear matter power spectrum in the standard LCDM scenario, as well as by adding curvature, dynamical dark energy and massive neutrinos, covering all redshifts relevant for Stage IV surveys. With only a dozen basis terms, COBRA reproduces exact Boltzmann solver calculations to 0.1% precision, which improves further to 0.02% in the pure LCDM scenario. Using our decomposition, we recast the one-loop redshift space galaxy power spectrum in a separable minimal-basis form, enabling $\sim 4000$ model evaluations per second at 0.02% precision on a single thread. This constitutes a considerable improvement over previously existing methods (e.g., FFTLog) opening a new window for efficient computations of higher loop and higher order correlators involving multiple powers of the linear matter power spectra. The resulting factorisation can also be utilised in clustering, weak lensing and CMB analyses. Our implementation is publicly available at https://github.com/ThomasBakx/cobra.

astromorph performs an automatic classification of astronomical objects based on their morphology using machine learning in a self-supervised manner. Written in Python, the pipeline is an implementation for astronomical images in FITS-format files of the Boot-strap Your Own Latents (BYOL; Grill et al. 2020) method, which does not require labelling of the training data.

show_cube displays the results of reducing, aligning and combining near-infrared integral field spectroscopy with the Gemini Observatory NIFS (Near-infrared Integral Field Spectrometer) instrument. Image slices are extracted from the raw data frames to make the input datacube. The code site also provides a tarfile containing all the raw NIFS FITS-format files for the observations of high-redshift radio galaxies 3C230, 3C294, and 4C+41.17, the last of which are reported, together with line-strengths using the MAPPINGS III (ascl:1306.008) shock models.

SHELLFISH (SHELL Finding In Spheroidal Halos) finds the splashback shells of individual halos within cosmological simulations. It uses a command line toolchain to produce human-readable catalogs. It requires a configuration file that describes the layout of the particle snapshots and halo catalog and which halos to measure the splashback shell for; once that is provided, Shellfish takes care of the rest. It supports numerous particle catalog types, including gotetra, Gadget-2, and Bolshoi, all text column-based halo catalogs, and consistent-trees merger trees.

JOFILUREN analyzes and de-noises scientific data and is useful for studying and reducing the physical effects of particle noise in particle-mesh computer simulations. It uses wavelets, which can efficiently remove noise from cosmological, galaxy and plasma N-body simulations. Written in Fortran, the code is portable and can be included in grid-based N-body codes. JOFILUREN can also be applied for removing noise from standard data, such as signals and images.