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Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assis…
Symbolic Perturbation Theory (SymPT) is a Python package for symbolic perturbative transformations on quantum systems. SymPT helps compute effective Hamiltonians for both time-independent and time-dependent systems at both operator and matrix level.
Finding the finest simultaneous block diagonalization of multiple matrices by sequentially exploring invariant subspaces under matrix multiplications. Applications include the efficient analysis of arbitrary synchronization patterns in complex networks.
This gives steady state Network Flow from the given Pref-Defined Network Flow of a System. And a Python implementation of Larry Page's famous PageRank algorithm.