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Register a new userhankl: A lightweight Python implementation of the FFTLog algorithm for Cosmology
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We introduce hankl, a lightweight Python implementation of the FFTLog algorithm for Cosmology. The FFTLog algorithm is an extension of the Fast Fourier Transform (FFT) for logarithmically spaced periodic sequences. It can be used to efficiently compute Hankel transformations, which are paramount for many modern cosmological analyses that are based on the power spectrum or the 2-point correlation function multipoles. The code is well-tested, open source, and publicly available.
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We introduce zeus, a well-tested Python implementation of the Ensemble Slice Sampling (ESS) method for Bayesian parameter inference. ESS is a novel Markov chain Monte Carlo (MCMC) algorithm specifically designed to tackle the computational challenges posed by modern astronomical and cosmological analyses. In particular, the method requires no hand-tuning of any hyper-parameters, its performance is insensitive to linear correlations and it can scale up to 1000s of CPUs without any extra effort. Furthermore, its locally adaptive nature allows to sample efficiently even when strong non-linear correlations are present. Lastly, the method achieves a high performance even in strongly multimodal distributions in high dimensions. Compared to emcee, a popular MCMC sampler, zeus performs 9 and 29 times better in a cosmological and an exoplanet application respectively.
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 easy-to-use classes and functions for calculating cluster scaling relations, including mass-richness and mass-concentration relations from the literature, as well as the surface mass density $Sigma(R)$ and differential surface mass density $DeltaSigma(R)$ profiles, probed by weak lensing magnification and shear. Galaxy cluster miscentering is especially a concern for stacked weak lensing shear studies of galaxy clusters, where offsets between the assumed and the true underlying matter distribution can lead to a significant bias in the mass estimates if not accounted for. This software has been developed and released in a public GitHub repository, and is licensed under the permissive MIT license. The cluster-lensing package is archived on Zenodo (Ford 2016). Full documentation, source code, and installation instructions are available at http://jesford.github.io/cluster-lensing/.
Computational physics problems often have a common set of aspects to them that any particular numerical code will have to address. Because these aspects are common to many problems, having a framework already designed and ready to use will not only speed the development of new codes, but also enhance compatibility between codes. Some of the most common aspects of computational physics problems are: a grid, a clock which tracks the flow of the simulation, and a set of models describing the dynamics of various quantities on the grid. Having a framework that could deal with these basic aspects of the simulation in a common way could provide great value to computational scientists by solving various numerical and class design issues that routinely arise. This paper describes the newly developed computational framework that we have built for rapidly prototyping new physics codes. This framework, called turboPy, is a lightweight physics modeling framework based on the design of the particle-in-cell code turboWAVE. It implements a class (called Simulation) which drives the simulation and manages communication between physics modules, a class (called PhysicsModule) which handles the details of the dynamics of the various parts of the problem, and some additional classes such as a Grid class and a Diagnostic class to handle various ancillary issues that commonly arise.
The Python Sky Model (PySM) is a Python package used by Cosmic Microwave Background (CMB) experiments to simulate maps, in HEALPix pixelization, of the various diffuse astrophysical components of Galactic emission relevant at CMB frequencies (i.e. dust, synchrotron, free-free and Anomalous Microwave Emission), as well as the CMB itself. These maps may be integrated over a given instrument bandpass and smoothed with a given instrument beam. PySM 2, released in 2016, has become the de-facto standard for simulating Galactic emission, for example it is used by CMB-S4, Simons Observatory, LiteBird, PICO, CLASS, POLARBEAR and other CMB experiments, as shown by the 80+ citations of the PySM 2 publication. As the resolution of upcoming experiments increases, the PySM 2 software has started to show some limitations, the solution to these issues was to reimplement PySM from scratch focusing on these features: reimplement all the models with the numba Just-In-Time compiler for Python to reduce memory overhead and optimize performance; use MPI through mpi4py to coordinate execution of PySM 3 across multiple nodes and rely on libsharp, for distributed spherical harmonic transforms; employ the data utilities infrastructure provided by astropy to download the input templates and cache them when requested. At this stage we strive to maintain full compatibility with PySM 2, therefore we implement the exact same astrophysical emission models with the same naming scheme. In the extensive test suite we compare the output of each PySM 3 model with the results obtained by PySM 2.
Clusters of galaxies are used to map the large-scale structures in the universe and as probe of universe evolution. They can be observed through the Sunyaev-Zeldovich (SZ) effect. At this respect the spectro-imaging at low resolution frequency is an important tool, today, for the study of cluster of galaxies. We have developed KISS (KIDs-Interferometer-Spectrum-Survey), a spectrometric imager dedicated to the secondary anisotropies of the Cosmic Microwave Background (CMB). The multi-frequency approach permits to improve the component separation with respect to predecessor experiments. In this paper, firstly, we provide a description of the scientific context and the state of the art of SZ observations. Secondly, we describe the KISS instrument. Finally, we show preliminary results of the ongoing commissioning campaign.
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