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Project funded by DFG. A jupyter-book that explores mearly a chunk of the field of nonlinear dynamics, specifically diffusion and random search in heterogeneous media. The book has various simulations for the stochastic process known as Brownian motion. The motion dynamics are simulated by solving the Langevin equation numerically for the different initial parameters. After an ensemble finishes, the trajectories of Brownian particles together with the probability density function and the mean square displacement are plotted. The book has chapters on Brownian search, Backbone problems, and Stochastic resetting.

Home Page: https://zelenkastiot.github.io/brownian/index

License: MIT License

Jupyter Notebook 81.62% HTML 17.90% CSS 0.07% JavaScript 0.11% Python 0.29%
brownian-motion dfg jupyter-book langevin-equations physics-simulation python

brownian's Introduction

ย 

  • DevOps Engineer at @LokaHQ
  • AWS cloud engineering, IaC, statistics/machine learning, GenAI, epidemiology, stochastic process
  • Finishing MSc in Statistics for Data Analytics at FCSE, Skopje supervised by mentor Lasko Basnarkov, Ph.D.
  • Former Research Associate at the Macedonian Academy of Sciences and Arts (MASA)
  • ๐ŸŽ“ Google scholar
  • ๐Ÿ™ GitLab profile
  • โ˜๏ธ Credly profile: 11 x AWS certifications

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