Linear Control Theory with an ℋ∞ Optimality Criterion

This expository paper sets out the principal results in ℋ∞ control theory in the context of continuous-time linear systems. The focus is on the mathematical theory rather than computational methods

Efficient high-dimensional entanglement imaging with a compressive sensing, double-pixel camera

We implement a double-pixel, compressive sensing camera to efficiently characterize, at high resolution, the spatially entangled fields produced by spontaneous parametric downconversion. This technique leverages sparsity in spatial correlations between entangled photons to improve acquisition times over raster-scanning by a scaling factor up to n^2/log(n) for n-dimensional images. We image at resolutions up to 1024 dimensions per detector and demonstrate a channel capacity of 8.4 bits per photon. By comparing the classical mutual information in conjugate bases, we violate an entropic Einstein-Podolsky-Rosen separability criterion for all measured resolutions. More broadly, our result indicates compressive sensing can be especially effective for higher-order measurements on correlated systems.Comment: 10 pages, 7 figure

Measuring the Effects of Artificial Viscosity in SPH Simulations of Rotating Fluid Flows

A commonly cited drawback of SPH is the introduction of spurious shear viscosity by the artificial viscosity term in situations involving rotation. Existing approaches for quantifying its effect include approximate analytic formulae and disc-averaged be- haviour in specific ring-spreading simulations, based on the kinematic effects produced by the artificial viscosity. These methods have disadvantages, in that they typically are applicable to a very small range of physical scenarios, have a large number of simplifying assumptions, and often are tied to specific SPH formulations which do not include corrective (e.g., Balsara) or time-dependent viscosity terms. In this study we have developed a simple, generally applicable and practical technique for evaluating the local effect of artificial viscosity directly from the creation of specific entropy for each SPH particle. This local approach is simple and quick to implement, and it al- lows a detailed characterization of viscous effects as a function of position. Several advantages of this method are discussed, including its ease in evaluation, its greater accuracy and its broad applicability. In order to compare this new method with ex- isting ones, simple disc flow examples are used. Even in these basic cases, the very roughly approximate nature of the previous methods is shown. Our local method pro- vides a detailed description of the effects of the artificial viscosity throughout the disc, even for extended examples which implement Balsara corrections. As a further use of this approach, explicit dependencies of the effective viscosity in terms of SPH and flow parameters are estimated from the example cases. In an appendix, a method for the initial placement of SPH particles is discussed which is very effective in reducing numerical fluctuations.Comment: 15 pages, 9 figures, resubmitted to MNRA

Quantifying the Morphologies and Dynamical Evolution of Galaxy Clusters. I. The Method

We describe and test a method to quantitatively classify clusters of galaxies according to their projected morphologies. This method will be subsequently used to place constraints on cosmological parameters ($\Omega$ and the power spectrum of primordial fluctuations on scales at or slightly smaller than that of clusters) and to test theories of cluster formation. We specifically address structure that is easily discernible in projection and dynamically important to the cluster. The method is derived from the two-dimensional multipole expansion of the projected gravitational potential and yields dimensionless {\it power ratios} as morphological statistics. If the projected mass profile is used to characterize the cluster morphology, the power ratios are directly related to the cluster potential. However, since detailed mass profiles currently exist for only a few clusters, we use the X-ray--emitting gas as an alternative tracer of cluster morphology. In this case, the relation of the power ratios to the potential is qualitatively preserved. We demonstrate the feasibility of the method by analyzing simulated observations of simple models of X-ray clusters using the instrument parameters of the ROSAT PSPC. For illustrative purposes, we apply the method to ROSAT PSPC images of A85, A514, A1750, and A2029. These clusters, which differ substantially in their X-ray morphologies, are easily distinguished by their respective power ratios. We discuss the suitability of this method to address the connection between cluster morphology and cosmology and to assess whether an individual cluster is sufficiently relaxed for analysis of its intrinsic shape using hydrostatic methods. Approximately 50 X-ray observations of Abell clusters with the PSPC will be amenable to morphological analysis using the method of this paper.Comment: To appear in ApJ October 20, 1995. 29 pages (7 figures missing), PostScrip

Tamper Proof RFID Security Tag

In this publication we present a tamper proof long range platform tolerant uhf smart RFID tag to identify valuable or security sensitive products. The smart tag functions as platform tolerant tag but once detached from the host object, it will permanently stop to function buy rendering the RFID chip unusable. The tag substrate design for additive manufacturing, platform tolerant antenna design as well as electromagnetic performance and read range are provided

An Optical Altitude Indicator for Night Landing

One of the most ingenious of the devices intended for use in night landing, especially emergency landing, is a very simple optical instrument known as the Jenkins night altitude indicator. The design and operation of this instrument, which allows a pilot to determine the altitude of the aircraft, is discussed. The author discusses various modifications and improvements that might be made to the instrument

Control of Complex Dynamic Systems by Neural Networks

This paper considers the use of neural networks (NN's) in controlling a nonlinear, stochastic system with unknown process equations. The NN is used to model the resulting unknown control law. The approach here is based on using the output error of the system to train the NN controller without the need to construct a separate model (NN or other type) for the unknown process dynamics. To implement such a direct adaptive control approach, it is required that connection weights in the NN be estimated while the system is being controlled. As a result of the feedback of the unknown process dynamics, however, it is not possible to determine the gradient of the loss function for use in standard (back-propagation-type) weight estimation algorithms. Therefore, this paper considers the use of a new stochastic approximation algorithm for this weight estimation, which is based on a 'simultaneous perturbation' gradient approximation that only requires the system output error. It is shown that this algorithm can greatly enhance the efficiency over more standard stochastic approximation algorithms based on finite-difference gradient approximations

Are Wild Bee Pollinator Populations Declining?

How climate change may affect insect pollinator populations in the Midwest.Environmental Change Institute UIUCAgroecology and Sustainable Agriculture Program UIUCunpublishednot peer reviewe

Passive UHF RFID Tilt Sensor

In this paper we introduce a bio-axis passive wireless UHF RFID tilt sensor for applications such as to increase safety in warehouse environment and damage detection in consumer goods and where long term monitoring of the product is essential without the need to supply power to the sensors. Simulation and prototype testing indicate it is possible to detect and isolate tilting in 3 axes