Quantum Gaussian process state: A kernel-inspired state with quantum support data

Gaussian Kernel in Quantum Paradigm

Gaussian kernel is a very popular kernel function used in many machine learning algorithms, especially in support vector machines (SVM). For nonlinear training instances in machine learning, it often outperforms polynomial kernels in model accuracy. The Gaussian kernel is heavily used in formulating nonlinear classical SVM. A very elegant quantum version of least square support vector machine w...

Quantum State Discrimination with Bosonic Channels and Gaussian States

Discriminating between quantum states is an indispensable part of quantum information theory. This thesis investigates state discrimination of continuous quantum variables, focusing on bosonic communication channels and Gaussian states. The specific state discrimination problems studied are (a) quantum illumination and (b) optimal measurements for decoding bosonic channels. Quantum illumination...

On the Dual Concepts of 'Quantum State' and 'Quantum Process'

Maximum-likelihood coherent-state quantum process tomography

Coherent-state quantum process tomography (csQPT) is a method for completely characterizing a quantum-optical ‘black box’ by probing it with coherent states and carrying out homodyne measurements on the output (Lobino et al 2008 Science 322 563). We present a technique for csQPT that is fully based on statistical inference, in particular, quantum expectation-maximization. The method relies on t...

Measure of the non-Gaussian character of a quantum state

We address the issue of quantifying the non-Gaussian character of a bosonic quantum state and introduce a non-Gaussianity measure based on the Hilbert-Schmidt distance between the state under examination and a reference Gaussian state. We analyze in detail the properties of the proposed measure and exploit it to evaluate the non-Gaussianity of some relevant single-mode and multimode quantum sta...