Quantum algorithm for the gradient of a logarithm-determinant
This quantum algorithm computes derivatives of a logarithm-determinant efficiently using multivariable quantum techniques. It relates these derivatives to eigenvalues and their variations, achieving poly-logarithmic scaling with respect to matrix size. This method is vital for tasks like finding matrix inverses in statistical physics and machine learning.