Singular value decomposition is central to many problems in engineering and scientific
fields. Several quantum algorithms have been proposed to determine the singular values …

The Petz recovery channel plays an important role in quantum information science as an
operation that approximately reverses the effect of a quantum channel. The pretty good …

Quantifying how far the output of a learning algorithm is from its target is an essential task in
machine learning. However, in quantum settings, the loss landscapes of commonly used …

We propose a series of quantum algorithms for computing a wide range of quantum
entropies and distances, including the von Neumann entropy, quantum Rényi entropy, trace …

The goal of quantum metrology is to improve measurements' sensitivities by harnessing
quantum resources. Metrologists often aim to maximize the quantum Fisher information …

We propose a quantum algorithm that emulates the action of an unknown unitary
transformation on a given input state, using multiple copies of some unknown sample input …

Recently, JM Arrazola [Phys. Rev. A 100, 032306 (2019)] 2469-9926 10.1103/PhysRevA.
100.032306 proposed a quantum algorithm for solving nonhomogeneous linear partial …

The polar decomposition of a matrix is a key element in the quantum linear algebra toolbox.
We show that the problem of quantum polar decomposition, recently studied in Lloyd et …

Vector representations have become a central element in semantic language modelling,
leading to mathematical overlaps with many fields including quantum theory …

The potential emergence of practical quantum computers has guided research into their
potential applications, particularly in the context of artificial intelligence. Motivated by the …