Darshan Beniwal, Ph.D.'s repositories
Astrophy_Py_STACUP_BDU_CUTN_IUCAA_2023
This repository hosts materials and code from the 'School on Statistical Techniques in Astrophysics & Cosmology Using Python (STACUP)' (Oct 16-20, 2023) at CUTN- BDU, Tiruchirapalli. Â These resources are designed to support the attendees in exploring statistical techniques & their applications in astrophysics & cosmology using Python programming.
Data_to_Discovery_ASTROCOSMOCON_SGT_2023
This repository hosts materials and code for the ASTROCOSMOCON workshop taking place at The Thanu Padmanabhan Center for Cosmology and Science Popularization, SGT University, Gurgaon (October 26-28, 2023). These resources are provided to support workshop attendees in their exploration of statistical techniques in Astrophysics & Cosmology.
Parameter_Estimation_by_Minimising_Chi_Square
This code cover most basic way to estimate best fit parameters for a given dataset and model by chi-square minimisation. This analysis based on Hubble dataset with Flat LCDM model with two parameters.
AICTE_ATAL_FDP_program_GHRCE_NAGPUR_2023
This repository contains resources and materials for the AICTE ATAL Faculty Development Program (FDP) on LaTeX and Mathematica conducted in 2023. The FDP aims to provide participants with a comprehensive theoretical and hands-on practical experience in using LaTeX and Mathematica for research and academic purposes.
Astro_data_analysis_w_Python_GHRCE_IUCAA_2023
This repository contains files related to the Python programming workshop conducted for astrophysics and cosmology work at Nagpur. The repository includes sample codes, datasets, and presentations used during the workshop. These materials can be useful for beginners who want to learn Python programming for astrophysics and cosmology work.
Exploring_Astro_Data_w_Py_GLA_IUCAA_2023
This repository contains files related to the Python programming workshop conducted for astrophysics and cosmology work at GLA-Mathura. The repository includes sample codes, datasets, and presentations used during the workshop. These materials can be useful for beginners who want to learn Python programming for astrophysics and cosmology work.
Hubble_Expansion_Using_SNIa_dataset
This repository gives an idea to estimate Hubble constant for a given dataset of distance and redshift. The Python implementation in this repository uses the standard cosmological model to estimate the Hubble constant from a given dataset of distance and redshift using the maximum likelihood method.
Statistical_Cosmology_using_Python_ICARD_2021
This course provides an introduction to the Python language and its application in cosmology. It may be more comprehensive than other beginner Python-based statistical cosmology courses since it explores deeper into several key programming concepts in cosmology.
Metropolis_Hasting_MCMC_in_R
This repository is a collection of R scripts that implement Markov Chain Monte Carlo (MCMC) and Metropolis Hastings algorithms for various statistical applications. The scripts in this repository can be used as a starting point for understanding and implementing these algorithms in R.