Implementation of serial and parallel(MPI) Jacobi algorithm for estimating of eigenvalues of symmetric matrix
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Updated
Jun 5, 2018 - C++
Implementation of serial and parallel(MPI) Jacobi algorithm for estimating of eigenvalues of symmetric matrix
LearnMelt: Learning to Minimize Dissemination on Large Graphs
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.
Computational Linear Algebra course covering topics like iterative methods, matrix decompositions, and applications. It includes theoretical concepts, practical exercises, and code. Advanced methods like QR factorization, spectral theorem, and iterative solvers for linear systems.
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mpi program ofjacobi algorithm for solving eigen values of a symmetric matrix
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Section 14 of a tentative book on Markov chains with detailed analysis of eigenvalues of Markov chains of random walks.
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