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Python code that solves the eigensystem associated with Hermitan matrices. Demonstrated by finding the the first few eigenvalues and the corresponding eigenvectors of the aharmonic oscillator Hamiltonian.
This program is implemented as a project for EE 242 course, and it implements Normalized Power Iteration with Deflation algorithmm to calculate most dominant eigenvalue, its eigenvector and the second most dominant eigenvalue.
An in-depth exploration of foot traffic patterns at Namsan Library using a page-rank-like mathematical model. This project represents the culmination of a linear algebra course, showcasing practical applications of matrix operations and eigenvalue analysis in real-world scenarios.