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 a sensor scheduling considering estimation error variance and communication energy in sensor networked feedback system. We propose an decentralized estimation algorithm with unknown inputs in each sensor node. Most existing works deal with the sensor network systems as sensing systems and it is difficult to apply them to the real physical feedback control systems Then some...

In this paper, we present variable-stepsize explicit parallel peer methods grounded in the interpolation idea. Approximation, stability, and convergence are studied in detail. In particular, we prove that some interpolating peer methods are stable on any variable mesh in practice. Double quasi consistency is utilized to introduce an efficient global error estimation formula in the numerical met...

This work introduces a scalable filtering algorithm for multi-agent traffic estimation. Large-scale networks are spatially partitioned into overlapping road sections. The traffic dynamics of each section is given by the switching mode model (SMM) using a conservation principle, and the traffic state in each section is estimated by a local agent. In the proposed filter, a consensus term is appli...

Localization is essential part of network control in many ad-hoc and sensor network applications. Many localization scenarios handle just simple, uniform and isotropic network structures and often some localization aware nodes called anchors or beacons are needed. Here we present a geometry-aware localization algorithm, what can operate in unisotropic networks that have complex topology. To all...

Error estimation and control are critical ingredients for improving the reliability of computational simulations. Adjoint-based techniques can be used to both estimate the error in chosen solution outputs and to provide local indicators for adaptive refinement. This article reviews recent work on these techniques for computational fluid dynamics applications in aerospace engineering. The defini...

This paper addresses the problem of distributed state estimation in formations of vehicles with timevarying measurement topology. One or more vehicles have access to measurements of their own state, while the rest must rely on measurements relative to other vehicles in the vicinity and limited communication to estimate their own state, and it is assumed that the vehicles may gain or lose access...

A new approach to a posteriori error estimation and adaptive mesh design based on techniques from optimal control is presented for primal-mixed finite element models in elasto-plasticity. This method uses global duality arguments for deriving weighted a posteriori error bounds for arbitrary functionals of the error representing physical quantities of interest. In these estimates local residuals...