Abstract
Computationally efficient wave-front reconstruction techniques for astronomical adaptive-optics (AO) systems have seen great development in the past decade. Algorithms developed in the spatial-frequency (Fourier) domain have gathered much attention, especially for high-contrast imaging systems. In this paper we present the Wiener filter (resulting in the maximization of the Strehl ratio) and further develop formulae for the anti-aliasing (AA) Wiener filter that optimally takes into account high-order wave-front terms folded in-band during the sensing (i.e., discrete sampling) process. We employ a continuous spatial-frequency representation for the forward measurement operators and derive the Wiener filter when aliasing is explicitly taken into account. We further investigate and compare to classical estimates using least-squares filters the reconstructed wave-front, measurement noise, and aliasing propagation coefficients as a function of the system order. Regarding high-contrast systems, we provide achievable performance results as a function of an ensemble of forward models for the Shack-Hartmann wave-front sensor (using sparse and nonsparse representations) and compute point-spread-function raw intensities. We find that for a 32 × 32 single-conjugated AOs system the aliasing propagation coefficient is roughly 60% of the least-squares filters, whereas the noise propagation is around 80%. Contrast improvements of factors of up to 2 are achievable across the field in the H band. For current and next-generation high-contrast imagers, despite better aliasing mitigation, AA Wiener filtering cannot be used as a standalone method and must therefore be used in combination with optical spatial filters deployed before image formation actually takes place. © 2014 Optical Society of America.

Abstract
Object Oriented Mat lab Adaptive Optics (OOMAO) is a Mat lab toolbox dedicated to Adaptive Optics (AO) systems. OOMAO is based on a small set of classes representing the source, atmosphere, telescope, wavefront sensor, Deformable Mirror (DM) and an imager of an AO system. This simple set of classes allows simulating Natural Guide Star (NGS) and Laser Guide Star (LGS) Single Conjugate AO (SCAO) and tomography AO systems on telescopes up to the size of the Extremely Large Telescopes (ELT). The discrete phase screens that make the atmosphere model can be of infinite size, useful for modeling system performance on large time scales. OOMAO comes with its own parametric influence function model to emulate different types of DMs. The cone effect, altitude thickness and intensity profile of LGSs are also reproduced. Both modal and zonal modeling approach are implemented. OOMAO has also an extensive library of theoretical expressions to evaluate the statistical properties of turbulence wavefronts. The main design characteristics of the OOMAO toolbox are object oriented modularity, vectorized code and transparent parallel computing. OOMAO has been used to simulate and to design the Multi Object AO prototype Raven at the Subaru telescope and the Laser Tomography AO system of the Giant Magellan Telescope. In this paper, a Laser Tomography AO system on an ELT is simulated with OOMAO. In the first part, we set up the class parameters and we link the instantiated objects to create the source optical path. Then we build the tomographic reconstructor and write the script for the pseudo-open-loop controller.

Abstract
Raven is a Multi Object Adaptive Optics (MOAO) technical and science demonstrator which had its first light at the Subaru telescope on May 13-14, 2014. Raven was built and tested at the University of Victoria AO Lab before shipping to Hawai`i. Raven includes three open loop wavefront sensors (WFSs), a central laser guide star WFS, and two independent science channels feeding light to the Subaru IRCS spectrograph. Raven supports different kinds of AO correction: SCAO, open-loop GLAO and MOAO. The MOAO mode can use different tomographic reconstructors, such as Learn-&-Apply or a model-based reconstructor. This paper presents the latest results obtained in the lab, which are consistent with simulated performance, as well as preliminary on-sky results, including echelle spectra from IRCS. Ensquared energy obtained on sky in 140mas slit is 17%, 30% and 41% for GLAO, MOAO and SCAO respectively. This result confirms that MOAO can provide a level of correction in between GLAO and SCAO, in any direction of the field of regard, regardless of the science target brightness.

Abstract
Computationally efficient wave-front reconstruction techniques for astronomical adaptive-optics (AO) systems have seen great development in the past decade. Algorithms developed in the spatial-frequency (Fourier) domain have gathered much attention, especially for high-contrast imaging systems. In this paper we present the Wiener filter (resulting in the maximization of the Strehl ratio) and further develop formulae for the anti-aliasing (AA) Wiener filter that optimally takes into account high-order wave-front terms folded in-band during the sensing (i.e., discrete sampling) process. We employ a continuous spatial-frequency representation for the forward measurement operators and derive the Wiener filter when aliasing is explicitly taken into account. We further investigate and compare to classical estimates using least-squares filters the reconstructed wave-front, measurement noise, and aliasing propagation coefficients as a function of the system order. Regarding high-contrast systems, we provide achievable performance results as a function of an ensemble of forward models for the Shack-Hartmann wave-front sensor (using sparse and nonsparse representations) and compute raw intensities. We find that for a 32 x 32 single-conjugated AOs system the aliasing propagation coefficient is roughly 60% of the least-squares filters, whereas the noise propagation is around 80%. Contrast improvements of factors of up to 2 are achievable across the field in the H band. For current and next-generation high-contrast imagers, despite better aliasing mitigation, AA Wiener filtering cannot be used as a standalone method and must therefore be used in combination with optical spatial filters deployed before image formation actually takes place. (C) 2014 Optical Society of America

Abstract
Multi-object adaptive optics (MOAO) systems are still in their infancy: their complex optical designs for tomographic, wide-field wavefront sensing, coupled with open-loop (OL) correction, make their calibration a challenge. The correction of a discrete number of specific directions in the field allows for streamlined application of a general class of spatio-angular algorithms, initially proposed in Whiteley et al. [J. Opt. Soc. Am. A 15, 2097 (1998)], which is compatible with partial on-line calibration. The recent Learn & Apply algorithm from Vidal et al. [ J. Opt. Soc. Am. A 27, A253 (2010)] can then be reinterpreted in a broader framework of tomographic algorithms and is shown to be a special case that exploits the particulars of OL and aperture-plane phase conjugation. An extension to embed a temporal prediction step to tackle sky-coverage limitations is discussed. The trade-off between lengthening the camera integration period, therefore increasing system lag error, and the resulting improvement in SNR can be shifted to higher guide-star magnitudes by introducing temporal prediction. The derivation of the optimal predictor and a comparison to suboptimal autoregressive models is provided using temporal structure functions. It is shown using end-to-end simulations of Raven, the MOAO science, and technology demonstrator for the 8 m Subaru telescope that prediction allows by itself the use of 1-magnitude-fainter guide stars. (C) 2013 Optical Society of America

Abstract
Due to its availability and low cost, the use of wireless communication technologies increases in domains beyond the originally intended usage areas, e.g. M2M communication in industrial applications. Such industrial applications often have specific security requirements. Hence, it is important to understand the characteristics of such applications and evaluate the vulnerabilities bearing the highest risk in this context. We present a comprehensive overview of security issues and features in existing WLAN, NFC and ZigBee standards, investigating the usage characteristics of these standards in industrial environments. We apply standard risk assessment methods to identify vulnerabilities with the highest risk across multiple technologies. We present a threat catalogue, conclude in which direction new mitigation methods should progress and how security analysis methods should be extended to meet requirements in the M2M domain. © 2014 IEEE.