Cosmological data analysis using the MCMC technique—LambdaCDM model fitting using Python code.

✍️ About : Dive deep into the realm of cosmology with this comprehensive guide to analyzing cosmological data using the Markov Chain Monte Carlo (MCMC) technique. In this video tutorial, we explore the LambdaCDM model fitting process step-by-step, employing Python code for practical implementation. From understanding the theoretical background to hands-on application, this tutorial equips viewers with the knowledge and tools needed to navigate the complexities of cosmological data analysis. Git-Hub repo link -- https://github.com/sleonardokap/cosmological_data ___________________ 📚 Research Articles : My Research Papers and Other Important Research Articles: [1] Dynamical stability of K-essence field interacting non-minimally with a perfect fluid -- https://arxiv.org/abs/2105.00361 [2] Dynamics of dark energy -- https://arxiv.org/abs/hep-th/0603057 [3] Dynamics of purely kinetic k-essence in presence of a perfect fluid -- https://arxiv.org/abs/2203.10607 [5] Dynamical Systems and Cosmology -- https://bit.ly/42KHcta [6] Dynamical Systems in Cosmology -- https://bit.ly/3TOM9wV [7] TASI Lectures on Inflation -- https://arxiv.org/abs/0907.5424 [8] Dynamical systems analysis of tachyon-dark-energy models from a new perspective -- https://doi.org/10.1103/PhysRevD.107.063515 _____________________ 👽 Tags : #cosmo_data #cosmological_data #data_analysis #mcmc #mcmc_cosmology #sstatistical_cosmology #LambdaCDM #inflation #SlowRollinflaion #SlowRollParameter #ultraslowrollinflation #InflationaryCosmology #dark_energy #dark_matter #Physics_research #Quintessence #kessence #dynamical_stability #CosmicInflation #GravitationalWaves #CosmicMicrowaveBackground #TachyonDynamics #vscode ____________________ 🤯 Keywords: Cosmological data analysis MCMC technique LambdaCDM model fitting Python code Cosmology Markov Chain Monte Carlo Data science Astrophysics VS code Bayesian statistics Scientific computing _______________________ 🎞️ Time interval: 0:00 -- Start 01:15 -- Physics of Model 13:30 -- Theoretical understanding of data analysis 27:23 -- Python Coding 49:00 -- Running your code on VS Code (Jupyter Notebook) 1:06:00 -- Windows Linux Subsystem