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Two Days Workshop on Python Programming in Astronomy, Astrophysics & Cosmology

Organized by Department of Applied Science, G H Raisoni College of Engineering, GHRCE, Nagpur

Funded by Inter-University Centre for Astronomy and Astrophysics (IUCAA)

I was among the invited speakers, along with Prof S. N. Hasan and Prof Priya Hasan, and in this repository, I have included all the files, including the data file and Python notebook, that were covered in two lecture sessions and four hands-on sessions by me.

Day-1. April 07th 2023; 🔗

  • Lecture-1

    • Introduction to Statistics
    • Maximum Likelihood Estimator (MLE)
    • Minimum Chi-square Test

  • Hands-on Session-1

    • Linear Model Fitting with Mock Data Using Basic Code: A Tutorial
    • Linear Model Fitting with Mock Data Using lmfit

  • Hands-on Session-2

    • Flat $\Lambda CDM$ Model fitting with Hubble Parameter Measurements using lmfit

  • Exercise-1

    • Estimate the value of $\pi$ using Monte Carlo simulation, by considering a sphere inscribed inside a cube.

Day-2. April 08th 2023; 🔗

  • Lecture-2

    • Bayesian Statistics
    • Monte Carlo
    • Markov Chain Monte Carlo
    • Metropolis-Hastings Algorithm

  • Hands-on Session-3

    • $\pi$ Value Estimation using Monte Carlo
    • Integration Evaluation using Monte Carlo

  • Hands-on Session-4

    • Flat $\Lambda CDM$ Model fitting with Hubble Parameter Measurements using Metropolis-Hastings Algorithm
    • Non-Flat $\Lambda CDM$ Model fitting with Hubble Parameter Measurements using Metropolis-Hastings Algorithm

  • Exercise-2

    • Fit $\omega CDM$ Model with Hubble Parameter Measurements and compare your results with arXiv:2209.05782

References for Further Reading

  • Basics of Statistics

    • Introduction To Error Analysis by J. R. Taylor 🔗
    • Data analysis: a Bayesian tutorial by Devinderjit Sivia and John Skilling 🔗
    • Data Reduction and Error Analysis for the Physical Sciences by P. R. Bevington and D. K. Robinson 🔗

  • Statistical Cosmology

    • Statistical methods in cosmology by L. Verde 🔗
    • Statistical methods for cosmological parameter selection and estimation by A. R. Liddle 🔗
    • Bayesian Methods in Cosmology by R. Trotta 🔗

Contact Email: [email protected]

Copyright

© Darshan Kumar Beniwal, University of Delhi, 2023, Presented at Department of Applied Science, G H Raisoni College of Engineering, Nagpur.