High Resolution Linear Polarimetric Imaging for the Event Horizon Telescope

Images of the linear polarization of synchrotron radiation around Active Galactic Nuclei (AGN) identify their projected magnetic field lines and provide key data for understanding the physics of accretion and outflow from supermassive black holes. The highest resolution polarimetric images of AGN are produced with Very Long Baseline Interferometry (VLBI). Because VLBI incompletely samples the Fourier transform of the source image, any image reconstruction that fills in unmeasured spatial frequencies will not be unique and reconstruction algorithms are required. In this paper, we explore extensions of the Maximum Entropy Method (MEM) to linear polarimetric VLBI imaging. In contrast to previous work, our polarimetric MEM algorithm combines a Stokes I imager that uses only bispectrum measurements that are immune to atmospheric phase corruption with a joint Stokes Q and U imager that operates on robust polarimetric ratios. We demonstrate the effectiveness of our technique on 7- and 3-mm wavelength quasar observations from the VLBA and simulated 1.3-mm Event Horizon Telescope observations of Sgr A* and M87. Consistent with past studies, we find that polarimetric MEM can produce superior resolution compared to the standard CLEAN algorithm when imaging smooth and compact source distributions. As an imaging framework, MEM is highly adaptable, allowing a range of constraints on polarization structure. Polarimetric MEM is thus an attractive choice for image reconstruction with the EHT.Comment: 19 pages, 9 figures. Accepted for publication in ApJ. Imaging code available at https://github.com/achael/eht-imaging

Different Observational Methods and the Detection of Seasonal and Atlantic Influence Upon Phytoplankton Communities in the Western Barents Sea

Phytoplankton community composition, and its dependency on environmental variation, are key to understanding marine primary production, processes of trophic transfer and the role of marine phytoplankton in global biogeochemical cycles. Understanding changes in phytoplankton community composition on Arctic shelves is important, because these productive environments are experiencing rapid change. Many different methods have been employed by researchers to quantify phytoplankton community composition. Previous studies have demonstrated that the way in which community composition is quantified can influence the interpretation of environmental dependencies. Researchers must consider both the suitability of the data they collect for monitoring marine ecosystems, as well as the research effort required to collect representative datasets. We therefore seek to understand how the representation of phytoplankton community structure in the western Barents Sea, a rapidly changing Arctic shelf sea, influences the interpretation of environmental dependencies. We compare datasets of cell counts, phytoplankton pigments and bio-optics (absorption spectra), relating them to a suite of environmental conditions with multivariate exploratory analyses. We show that, while cell counts reveal the greatest insight into environmental dependencies, pigment and absorption spectral datasets still provide useful information about seasonal succession and the influence of Atlantic water masses– two key subjects of great research interest in this region. As pigments and optical properties influence remotely-sensed ocean-colour, these findings hold implications for remote detection of phytoplankton community composition

Observing---and Imaging---Active Galactic Nuclei with the Event Horizon Telescope

Originally developed to image the shadow region of the central black hole in Sagittarius A* and in the nearby galaxy M87, the Event Horizon Telescope (EHT) provides deep, very high angular resolution data on other AGN sources too. The challenges of working with EHT data have spurred the development of new image reconstruction algorithms. This work briefly reviews the status of the EHT and its utility for observing AGN sources, with emphasis on novel imaging techniques that offer the promise of better reconstructions at 1.3 mm and other wavelengths.Comment: 10 pages, proceedings contribution for Blazars through Sharp Multi-Wavelength Eyes, submitted to Galaxie

Multiscale Discriminant Saliency for Visual Attention

The bottom-up saliency, an early stage of humans' visual attention, can be considered as a binary classification problem between center and surround classes. Discriminant power of features for the classification is measured as mutual information between features and two classes distribution. The estimated discrepancy of two feature classes very much depends on considered scale levels; then, multi-scale structure and discriminant power are integrated by employing discrete wavelet features and Hidden markov tree (HMT). With wavelet coefficients and Hidden Markov Tree parameters, quad-tree like label structures are constructed and utilized in maximum a posterior probability (MAP) of hidden class variables at corresponding dyadic sub-squares. Then, saliency value for each dyadic square at each scale level is computed with discriminant power principle and the MAP. Finally, across multiple scales is integrated the final saliency map by an information maximization rule. Both standard quantitative tools such as NSS, LCC, AUC and qualitative assessments are used for evaluating the proposed multiscale discriminant saliency method (MDIS) against the well-know information-based saliency method AIM on its Bruce Database wity eye-tracking data. Simulation results are presented and analyzed to verify the validity of MDIS as well as point out its disadvantages for further research direction.Comment: 16 pages, ICCSA 2013 - BIOCA sessio