Large Scale 3D Image Reconstruction in Optical Interferometry

Astronomical optical interferometers (OI) sample the Fourier transform of the intensity distribution of a source at the observation wavelength. Because of rapid atmospheric perturbations, the phases of the complex Fourier samples (visibilities) cannot be directly exploited , and instead linear relationships between the phases are used (phase closures and differential phases). Consequently, specific image reconstruction methods have been devised in the last few decades. Modern polychromatic OI instruments are now paving the way to multiwavelength imaging. This paper presents the derivation of a spatio-spectral ("3D") image reconstruction algorithm called PAINTER (Polychromatic opticAl INTErferometric Reconstruction software). The algorithm is able to solve large scale problems. It relies on an iterative process, which alternates estimation of polychromatic images and of complex visibilities. The complex visibilities are not only estimated from squared moduli and closure phases, but also from differential phases, which help to better constrain the polychromatic reconstruction. Simulations on synthetic data illustrate the efficiency of the algorithm.Comment: EUSIPCO, Aug 2015, NICE, Franc

Torque Ripple Minimization of PM-assisted Synchronous Reluctance Machines via Asymmetric Rotor Poles

Torque ripple minimization is one of the design challenges of PM-assisted Synchronous Reluctance (PM-SyR) machines. Very often, time-consuming FEA based optimization is the preferred design strategy. Also very often, the ultimate remedy to torque ripple is to skew or step-skew the rotor of the machine, at the cost of average torque reduction. Asymmetric-pole rotors demonstrated good torque oscillation smoothing capability for Synchronous Reluctance machines; previous work showed that the Flux Barriers Shift (FBS) technique can be applied off-line to a regular design, same as skewing, with no average torque reduction. This paper extends the validity of the FBS technique to PM-SyR machines. The PM-SyR machine design flowchart is reviewed and augmented with FBS. Torque waveforms obtained with FBS and skewing are compared using FEA. Finally, the FBS design is validated against a regular design with dedicated experimental tests

Fast and robust detection of a known pattern in an image

International audienceMany image processing applications require to detect a known pattern buried under noise. While maximum correlation can be implemented efficiently using fast Fourier transforms, detection criteria that are robust to the presence of outliers are typically slower by several orders of magnitude. We derive the general expression of a robust detection criterion based on the theory of locally optimal detectors. The expression of the criterion is attractive because it offers a fast implementation based on correlations. Application of this criterion to Cauchy likelihood gives good detection performance in the presence of outliers, as shown in our numerical experiments. Special attention is given to proper normalization of the criterion in order to account for truncation at the image borders and noise with a non-stationary dispersion

Channel Characterization of Diffusion-based Molecular Communication with Multiple Fully-absorbing Receivers

In this paper an analytical model is introduced to describe the impulse response of the diffusive channel between a pointwise transmitter and a given fully-absorbing (FA) receiver in a molecular communication (MC) system. The presence of neighbouring FA nanomachines in the environment is taken into account by describing them as sources of negative molecules. The channel impulse responses of all the receivers are linked in a system of integral equations. The solution of the system with two receivers is obtained analytically. For a higher number of receivers the system of integral equations is solved numerically. It is also shown that the channel impulse response shape is distorted by the presence of the neighbouring FA interferers. For instance, there is a time shift of the peak in the number of absorbed molecules compared to the case without interference, as predicted by the proposed model. The analytical derivations are validated by means of particle based simulations

Channel Characterization of Diffusion-based Molecular Communication with Multiple Fully-absorbing Receivers

In this paper an analytical model is introduced to describe the impulse response of the diffusive channel between a pointwise transmitter and a given fully-absorbing (FA) receiver in a molecular communication (MC) system. The presence of neighbouring FA nanomachines in the environment is taken into account by describing them as sources of negative molecules. The channel impulse responses of all the receivers are linked in a system of integral equations. The solution of the system with two receivers is obtained analytically. For a higher number of receivers the system of integral equations is solved numerically. It is also shown that the channel impulse response shape is distorted by the presence of the neighbouring FA interferers. For instance, there is a time shift of the peak in the number of absorbed molecules compared to the case without interference, as predicted by the proposed model. The analytical derivations are validated by means of particle based simulations

MORESANE: MOdel REconstruction by Synthesis-ANalysis Estimators. A sparse deconvolution algorithm for radio interferometric imaging

(arXiv abridged abstract) The current years are seeing huge developments of radio telescopes and a tremendous increase of their capabilities. Such systems make mandatory the design of more sophisticated techniques not only for transporting, storing and processing this new generation of radio interferometric data, but also for restoring the astrophysical information contained in such data. In this paper we present a new radio deconvolution algorithm named MORESANE and its application to fully realistic simulated data of MeerKAT, one of the SKA precursors. This method has been designed for the difficult case of restoring diffuse astronomical sources which are faint in brightness, complex in morphology and possibly buried in the dirty beam's side lobes of bright radio sources in the field. MORESANE is a greedy algorithm which combines complementary types of sparse recovery methods in order to reconstruct the most appropriate sky model from observed radio visibilities. A synthesis approach is used for the reconstruction of images, in which the synthesis atoms representing the unknown sources are learned using analysis priors. We apply this new deconvolution method to fully realistic simulations of radio observations of a galaxy cluster and of an HII region in M31. We show that MORESANE is able to efficiently reconstruct images composed from a wide variety of sources from radio interferometric data. Comparisons with other available algorithms, which include multi-scale CLEAN and the recently proposed methods by Li et al. (2011) and Carrillo et al. (2012), indicate that MORESANE provides competitive results in terms of both total flux/surface brightness conservation and fidelity of the reconstructed model. MORESANE seems particularly well suited for the recovery of diffuse and extended sources, as well as bright and compact radio sources known to be hosted in galaxy clusters.Comment: 17 pages, 11 figures, accepted for publication on A&

Living in mixed species groups promotes predator learning in degraded habitats

Living in mix-species aggregations provides animals with substantive anti-predator, foraging and locomotory advantages while simultaneously exposing them to costs, including increased competition and pathogen exposure. Given each species possess unique morphology, competitive ability, parasite vulnerability and predator defences, we can surmise that each species in mixed groups will experience a unique set of trade-offs. In addition to this unique balance, each species must also contend with anthropogenic changes, a relatively new, and rapidly increasing phenomenon, that adds further complexity to any system. This complex balance of biotic and abiotic factors is on full display in the exceptionally diverse, yet anthropogenically degraded, Great Barrier Reef of Australia. One such example within this intricate ecosystem is the inability of some damselfish to utilize their own chemical alarm cues within degraded habitats, leaving them exposed to increased predation risk. These cues, which are released when the skin is damaged, warn nearby individuals of increased predation risk and act as a crucial associative learning tool. Normally, a single exposure of alarm cues paired with an unknown predator odour facilitates learning of that new odour as dangerous. Here, we show that Ambon damselfish, Pomacentrus amboinensis, a species with impaired alarm responses in degraded habitats, failed to learn a novel predator odour as risky when associated with chemical alarm cues. However, in the same degraded habitats, the same species learned to recognize a novel predator as risky when the predator odour was paired with alarm cues of the closely related, and co-occurring, whitetail damselfish, Pomacentrus chrysurus. The importance of this learning opportunity was underscored in a survival experiment which demonstrated that fish in degraded habitats trained with heterospecific alarm cues, had higher survival than those we tried to train with conspecific alarm cues. From these data, we conclude that redundancy in learning mechanisms among prey guild members may lead to increased stability in rapidly changing environments