March 5, 2020

eigenvalue decomposition of Pauli matrices

At the heart of linear algebra is a task called eigenvalue decomposition. This task, in the simplest words possible, allows you to analyze a given matrix to determine how it’s constructed from a combination of basis vectors, called eigenvectors, and scalars, called eigenvalues. Many statistical models, machine learning algorithms, and scientific theories use eigenvector decomposition to go from a muddle of data to a understandable theory. Here, I’ll talk about using eigenvalue decomposition to inspect the fundamental logic gates used in quantum computing. Read more

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