Aspects of the feeding biology of certain sea-birds

Not availabl

<i>AKARI</i>/IRC source catalogues and source counts for the IRAC Dark Field, ELAIS North and the <i>AKARI</i> Deep Field South

We present the first detailed analysis of three extragalactic fields (IRAC Dark Field, ELAIS-N1, ADF-S) observed by the infrared satellite, AKARI, using an optimized data analysis toolkit specifically for the processing of extragalactic point sources. The InfaRed Camera (IRC) on AKARI complements the SpitzerSpace Telescope via its comprehensive coverage between 8–24 μm filling the gap between the Spitzer/IRAC and MIPS instruments. Source counts in the AKARI bands at 3.2, 4.1, 7, 11, 15 and 18 μm are presented. At near-infrared wavelengths, our source counts are consistent with counts made in other AKARI fields and in general with SpitzerIRAC (except at 3.2 μm where our counts lie above). In the mid-infrared (11 – 18 μm), we find our counts are consistent with both previous surveys by AKARI and the Spitzer peak-up imaging survey with the InfraRed Spectrograph (IRS). Using our counts to constrain contemporary evolutionary models, we find that although the models and counts are in agreement at mid-infrared wavelengths there are inconsistencies at wavelengths shortward of 7 μm, suggesting either a problem with stellar subtraction or indicating the need for refinement of the stellar population models. We have also investigated the AKARI/IRC filters, and find an active galactic nucleus selection criteria out to z AKARI 4.1, 11, 15 and 18 μm colours

Chandra survey in the AKARI North Ecliptic Pole Deep Field. I. X-ray data, point-like source catalog, sensitivity maps, and number counts

We present data products from the 300 ks Chandra survey in the AKARI North Ecliptic Pole (NEP) deep field. This field has a unique set of 9-band infrared photometry covering 2-24 micron from the AKARI Infrared Camera, including mid-infrared (MIR) bands not covered by Spitzer. The survey is one of the deepest ever achieved at ~15 micron, and is by far the widest among those with similar depths in the MIR. This makes this field unique for the MIR-selection of AGN at z~1. We design a source detection procedure, which performs joint Maximum Likelihood PSF fits on all of our 15 mosaicked Chandra pointings covering an area of 0.34 square degree. The procedure has been highly optimized and tested by simulations. We provide a point source catalog with photometry and Bayesian-based 90 per cent confidence upper limits in the 0.5-7, 0.5-2, 2-7, 2-4, and 4-7 keV bands. The catalog contains 457 X-ray sources and the spurious fraction is estimated to be ~1.7 per cent. Sensitivity and 90 per cent confidence upper flux limits maps in all bands are provided as well. We search for optical MIR counterparts in the central 0.25 square degree, where deep Subaru Suprime-Cam multiband images exist. Among the 377 X-ray sources detected there, ~80 per cent have optical counterparts and ~60 per cent also have AKARI mid-IR counterparts. We cross-match our X-ray sources with MIR-selected AGN from Hanami et al. (2012). Around 30 per cent of all AGN that have MID-IR SEDs purely explainable by AGN activity are strong Compton-thick AGN candidates.Comment: 23 pages, 20 figures; catalogs, sensitivity maps, and upper limit flux maps are available from the VizieR Servic

Environmental dependence of 8 μm luminosity functions of galaxies at z ~ 0.8: Comparison between RXJ1716.4+6708 and the AKARI NEP-deep field

Aims. We aim to reveal environmental dependence of infrared luminosity functions (IR LFs) of galaxies at z ~ 0.8 using the AKARI satellite. AKARI’s wide field of view and unique mid-IR filters help us to construct restframe 8 μm LFs directly without relying on SED models. Methods. We construct restframe 8 μm IR LFs in the cluster region RXJ1716.4+6708 at z = 0.81, and compare them with a blank field using the AKARI north ecliptic pole deep field data at the same redshift. AKARI’s wide field of view (10' × 10') is suitable to investigate wide range of galaxy environments. AKARI’s 15 μm filter is advantageous here since it directly probes restframe 8 μm at z ~ 0.8, without relying on a large extrapolation based on a SED fit, which was the largest uncertainty in previous work. Results. We have found that cluster IR LFs at restframe 8 μm have a factor of 2.4 smaller L^∗ and a steeper faint-end slope than that of the field. Confirming this trend, we also found that faint-end slopes of the cluster LFs becomes flatter and flatter with decreasing local galaxy density. These changes in LFs cannot be explained by a simple infall of field galaxy population into a cluster. Physics that can preferentially suppress IR luminous galaxies in high density regions is required to explain the observed results

Extracting quantum dynamics from genetic learning algorithms through principal control analysis

Genetic learning algorithms are widely used to control ultrafast optical pulse shapes for photo-induced quantum control of atoms and molecules. An unresolved issue is how to use the solutions found by these algorithms to learn about the system's quantum dynamics. We propose a simple method based on covariance analysis of the control space, which can reveal the degrees of freedom in the effective control Hamiltonian. We have applied this technique to stimulated Raman scattering in liquid methanol. A simple model of two-mode stimulated Raman scattering is consistent with the results.Comment: 4 pages, 5 figures. Presented at coherent control Ringberg conference 200

Principal Component Analysis with Noisy and/or Missing Data

We present a method for performing Principal Component Analysis (PCA) on noisy datasets with missing values. Estimates of the measurement error are used to weight the input data such that compared to classic PCA, the resulting eigenvectors are more sensitive to the true underlying signal variations rather than being pulled by heteroskedastic measurement noise. Missing data is simply the limiting case of weight=0. The underlying algorithm is a noise weighted Expectation Maximization (EM) PCA, which has additional benefits of implementation speed and flexibility for smoothing eigenvectors to reduce the noise contribution. We present applications of this method on simulated data and QSO spectra from the Sloan Digital Sky Survey.Comment: Accepted for publication in PASP; v2 with minor updates, mostly to bibliograph