Related papers: CosmoMC Installation and Running Guidelines
HOOMD-blue is a particle simulation engine designed for nano- and colloidal-scale molecular dynamics and hard particle Monte Carlo simulations. It has been actively developed since March 2007 and available open source since August 2008.…
Markov Chain Monte Carlo (MCMC) methods for sampling probability density functions (combined with abundant computational resources) have transformed the sciences, especially in performing probabilistic inferences, or fitting models to data.…
We present validation tests of emulator-based halo model method for cosmological parameter inference, assuming hypothetical measurements of the projected correlation function of galaxies, $w_{\rm p}(R)$, and the galaxy-galaxy weak lensing,…
We introduce interacting particle Markov chain Monte Carlo (iPMCMC), a PMCMC method based on an interacting pool of standard and conditional sequential Monte Carlo samplers. Like related methods, iPMCMC is a Markov chain Monte Carlo sampler…
Dark energy is a fundamental constituent of our universe, its status in the cosmological field equation should be equivalent to that of gravity. Here we construct a dark energy and matter gravity coupling (DEMC) model of cosmology in a way…
Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be…
We apply Markov Chain Monte Carlo (MCMC) to the problem of parametric galaxy modeling, estimating posterior distributions of galaxy properties such as ellipticity and brightness for more than 100,000 images of galaxies taken from DC2, a…
We present a Monte-Carlo package for simulation of high-redshift supernova data, SNOC. Optical and near-infrared photons from supernovae are ray-traced over cosmological distances from the simulated host galaxy to the observer at Earth. The…
We introduce and present results from the COCOA (Cluster simulatiOn Comparison with ObservAtions) code that has been developed to create idealized mock photometric observations using results from numerical simulations of star cluster…
Markov Chain Monte Carlo (MCMC) methods have become a cornerstone of many modern scientific analyses by providing a straightforward approach to numerically estimate uncertainties in the parameters of a model using a sequence of random…
The observation of cosmic microwave background (CMB) anisotropies is one of the key probes of physical cosmology. The weak nature of this signal has driven the construction of increasingly complex and sensitive experiments observing the sky…
A simple transit model is described along with tests of this model against published results for 4 exoplanet systems (Kepler-1, 2, 8, and 77). Data from the Kepler mission are used. The Markov Chain Monte Carlo (MCMC) method is applied to…
mVMC (many-variable Variational Monte Carlo) is an open-source software based on the variational Monte Carlo method applicable for a wide range of Hamiltonians for interacting fermion systems. In mVMC, we introduce more than ten thousands…
Cosmological Boltzmann codes are often used by researchers for calculating the CMB angular power spectra from different theoretical models, for cosmological parameter estimation, etc. Therefore, the accuracy of a Boltzmann code is of utmost…
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…
We present a method that extends the capabilities of the PINpointing Orbit-Crossing Collapsed HIerarchical Objects (PINOCCHIO) code, allowing it to generate accurate dark matter halo mock catalogues in cosmological models where the linear…
We present a self-contained description of everything needed to write a program that calculates the CMB power spectrum for the standard model of cosmology (LCDM). This includes the equations used, assumptions and approximations imposed on…
The power spectrum of density fluctuations is a foundational source of cosmological information. Precision cosmological probes targeted primarily at investigations of dark energy require accurate theoretical determinations of the power…
Markov chain Monte Carlo (MCMC) is a sampling-based method for estimating features of probability distributions. MCMC methods produce a serially correlated, yet representative, sample from the desired distribution. As such it can be…
Recent observational progress has led to the establishment of the standard $\Lambda$CDM model for cosmology. This development is based on different cosmological probes that are usually combined through their likelihoods at the latest stage…