Quantum machine learning is a rapidly growing field at the intersection of quantum
technology and artificial intelligence. This review provides a two-fold overview of several key …

Recently, increased computational power and data availability, as well as algorithmic
advances, have led machine learning (ML) techniques to impressive results in regression …

Quantum walks, the quantum mechanical counterpart of classical random walks, is an
advanced tool for building quantum algorithms that has been recently shown to constitute a …

Random walks have been employed in virtually every science related discipline to model
everyday phenomena such as biochemical reaction pathways and DNA synapsis …

The development of quantum walks in the context of quantum computation, as
generalisations of random walk techniques, has led rapidly to several new quantum …

We present quantum algorithms for solving two problems regarding stochastic processes.
The first algorithm prepares the thermal Gibbs state of a quantum system and runs in time …

Quantum walks can be considered as a generalized version of the classical random walk.
There are two classes of quantum walks, that is, the discrete-time (or coined) and the …

Quantum computation, one of the latest joint ventures between physics and the theory of
computation, is a scientific field whose main goals include the development of hardware and …

We provide a general framework to compute the probability distribution $ F_ r (t) $ of the first
detection time of a'state of interest'in a closed quantum system subjected to random …

We analyze the recurrence probability (Pólya number) for d-dimensional unbiased quantum
walks. A sufficient condition for a quantum walk to be recurrent is derived. As a by-product …