If the source matrix is a covariance matrix, then using Cholesky decomposition is more efficient. The implementation of SVD-Jacobi matrix inverse presented in this article emphasizes simplicity and ...

The most famous quantum linear system solving algorithm is the Harrow-Hassidim-Lloyd (HHL) algorithm, which accelerates the solution of linear systems through quantum superposition and interference.

Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

If the source matrix is a covariance matrix, then using Cholesky decomposition is efficient. The implementation of QR-Householder matrix inverse presented in this article emphasizes simplicity and ...

VQAs solve problems by implementing parameterized quantum circuits in quantum computing and optimizing the parameters of the quantum circuit using classical optimizers. VQAs are widely applied in ...