ﻻ يوجد ملخص باللغة العربية
The polar decomposition for a matrix $A$ is $A=UB$, where $B$ is a positive Hermitian matrix and $U$ is unitary (or, if $A$ 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 $e^{-iBt}$ and $U$ 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.
In the Grover-type quantum search process a search operator is iteratively applied, say, k times, on the initial database state. We present an additive decomposition scheme such that the iteration process is expressed, in the computational space, as
The quantum discord was introduced by Ollivier, Zurek, Henderson and Vedral as an indicator of the degree of quantumness of mixed states. In this paper, we give out the decomposition condition of quantum discords. Moreover, we show that under the con
Currently available quantum hardware allows for small scale implementations of quantum machine learning algorithms. Such experiments aid the search for applications of quantum computers by benchmarking the near-term feasibility of candidate algorithm
Visual tracking (VT) is the process of locating a moving object of interest in a video. It is a fundamental problem in computer vision, with various applications in human-computer interaction, security and surveillance, robot perception, traffic cont
For two unknown quantum states $rho$ and $sigma$ in an $N$-dimensional Hilbert space, computing their fidelity $F(rho,sigma)$ is a basic problem with many important applications in quantum computing and quantum information, for example verification a