Quantum polar decomposition algorithm
Quantum Physics
2020-06-02 v1
Abstract
The polar decomposition for a matrix is , where is a positive Hermitian matrix and is unitary (or, if is not square, an isometry). This paper shows that the ability to apply a Hamiltonian \pmatrix{ 0 & A^\dagger \cr A & 0 \cr} translates into the ability to perform the transformations and in a deterministic fashion. We show how to use the quantum polar decomposition algorithm to solve the quantum Procrustes problem, to perform pretty good measurements, to find the positive Hamiltonian closest to any Hamiltonian, and to perform a Hamiltonian version of the quantum singular value transformation.
Cite
@article{arxiv.2006.00841,
title = {Quantum polar decomposition algorithm},
author = {Seth Lloyd and Samuel Bosch and Giacomo De Palma and Bobak Kiani and Zi-Wen Liu and Milad Marvian and Patrick Rebentrost and David M. Arvidsson-Shukur},
journal= {arXiv preprint arXiv:2006.00841},
year = {2020}
}
Comments
10 pages