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๐Ÿ‘พ ๐—ป๐˜‚๐—บ๐—ฒ๐—ฟ๐—ถ๐—ฐ๐—ฎ๐—น ๐—บ๐—ฒ๐˜๐—ต๐—ผ๐—ฑ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ฝ๐—ต๐˜†๐˜€๐—ถ๐—ฐ๐˜€: ๐—ฑ๐—ถ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐˜๐—ถ๐—ฎ๐˜๐—ถ๐—ผ๐—ป, ๐—ผ๐—ฟ๐—ฑ๐—ถ๐—ป๐—ฎ๐—ฟ๐˜†, ๐—ฎ๐—ฑ๐˜ƒ๐—ฒ๐—ฐ๐˜๐—ถ๐—ผ๐—ป ๐—ฎ๐—ป๐—ฑ ๐—ต๐˜†๐—ฝ๐—ฒ๐—ฟ๐—ฏ๐—ผ๐—น๐—ถ๐—ฐ ๐—ฝ๐—ฎ๐—ฟ๐˜๐—ถ๐—ฎ๐—น ๐—ฑ๐—ถ๐—ณ๐—ณ๐—ฒ๐—ฟ๐—ฒ๐—ป๐˜๐—ถ๐—ฎ๐—น ๐—ฒ๐—พ๐˜€

Home Page: http://www.astro.sunysb.edu/steinkirch/

Python 74.89% TeX 9.97% Fortran 13.69% Shell 0.71% Makefile 0.60% Logos 0.06% Yacc 0.06% Pawn 0.01%
ordinary-differential-equations numerical-methods physics computational-fluid-dynamics ffts astrophysics differentiation linear-algebra python differential-equations

adv-optimization-physics-py's Introduction

๐ŸŒŒ๐Ÿ›ฉ advanced numerical methods and optimization for physics


๐Ÿ‘‰ integration and differentiation: numerical derivatives, error estimates, simpson's rule.

๐Ÿ‘‰ ordinary differential equations: eulder and euler-cromer methods, verlet method.

๐Ÿ‘‰ linear Aagebra and FFTs: time series for the damped driven pendulum, matrix inverse, conditional number.

๐Ÿ‘‰ advection and Hhperbolic partial differential equations: implicit advection, lax wendroff, non-linear hyperbolic equations.

๐Ÿ‘‰ elliptic partial differential equations.

๐Ÿ‘‰ computational fluid dynamics: rayleigh-taylor instabilities.



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