Motivated by estimation of quantum noise models, we study the problem learning a Pauli channel, or more generally error rates an arbitrary channel. By employing novel reduction to "Population Recovery" problem, give extremely simple algorithm that learns $n$-qubit channel precision $\epsilon$ in $\ell_\infty$ using just $O(1/\epsilon^2) \log(n/\epsilon)$ applications This is optimal up logarith...

This paper deals with state estimation of micro tunable capacitor subjected to nonlinear electrostatic force. For this end a nonlinear observer has been designed for state estimation of the structure.  Necessary and sufficient conditions for construction of the observer are presented. Stability of the observer is checked using Lyapunov theorem. Observer design is based on converting of differen...

A loss function is a mapping l : Y×Y "→ R (sometimes R×R "→ R). For example, in binary classification the 0/1 loss function l(y, p) = I(y ≠ p) is often used and in regression the squared error loss function l(y, p) = (y − p) is often used. Other loss functions include the following: absolute loss, Huber loss, εinsensitive loss, hinge loss, logistic loss, exponential loss, modified least squares...

Background: The aim of the present study is to compare time perception among drug addicts and controls. Methods: 30 drug addicts were selected, and 30 non-addict individuals were selected as the control group. The two groups performed three tests of time reproduction, time estimation, and time discrimination. Findings: There was a significant difference between the addicts group and the control...

the problem of estimating the parameter ?, when it is restricted to an interval of the form , in a class of discrete distributions, including binomial negative binomial discrete weibull and etc., is considered. we give necessary and sufficient conditions for which the bayes estimator of with respect to a two points boundary supported prior is minimax under squared log error loss function. for s...