Parameter estimation with mixed quantum states

Quantum parameter estimation using general single-mode Gaussian states

Parameter Estimation in Spatial Generalized Linear Mixed Models with Skew Gaussian Random Effects using Laplace Approximation

 Spatial generalized linear mixed models are used commonly for modelling non-Gaussian discrete spatial responses. We present an algorithm for parameter estimation of the models using Laplace approximation of likelihood function. In these models, the spatial correlation structure of data is carried out by random effects or latent variables. In most spatial analysis, it is assumed that rando...

Quantum computational logic with mixed states

Using an algebraic framework we solve a problem posed in [5] and [7] about the axiomatizability of a type quantum computational logic related to fuzzy logic. A Hilbert-style calculus is developed obtaining an algebraic strong completeness theorem.

Quantum metrology with mixed states: when recovering

(2015) Quantum metrology with mixed states: when recovering lost information is better than never losing it. This document is made available in accordance with publisher policies and may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the URL above for details on accessing the published...

Quantum programming with mixed states ( extended abstract )

In this paper we offer a programming approach to quantum computation using mixed states. Mixed-state quantum systems generalise standard (pure) quantum systems by allowing the state of the system to be a probabilistic distribution of pure states. We build on previous work by Aharonov et al. and generalise their results from quantum circuits to probabilistic (and quantum) programs.