- LensFlow: A Convolutional Neural Network in Search of Strong Gravitational Lenses (May 16, 2016)
Milad Pourrahmani, Hooshang Nayyeri, Asantha Cooray
In this work, we present our classification algorithm to identify strong gravitational lenses from wide-area surveys using machine learning convolutional neural network; LensExtractor. We train and test the algorithm using a wide variety of strong gravitational lens configurations from simulations of lensing events. Images are processed through multiple convolutional layers which extract feature maps necessary to assign a lens probability to each image. LensExtractor provides a ranking scheme for all sources which could be used to identify potential gravitational lens candidates significantly reducing the number of images that have to be visually inspected. We further apply our algorithm to the HST/ACS i-band observations of the COSMOS field and present our sample of identified lensing candidates. The developed machine learning algorithm is much more computationally efficient than classical lens identification algorithms and is ideal for discovering such events across wide areas from current and future surveys such as LSST and WFIRST.
- Stacked Average Far-Infrared Spectrum of Dusty Star-Forming Galaxies from the Herschel/SPIRE Fourier Transform Spectrometer (May 1, 2017)
Derek Wilson, Asantha Cooray, Hooshang Nayyeri, Matteo Bonato, Charles M. Bradford, David L. Clements, Gianfranco De Zotti, Tanio Díaz-Santos, Duncan Farrah, Georgios Magdis, Michał J. Michałowski, Chris Pearson, Dimitra Rigopoulou, Ivan Valtchanov, Lingyu Wang, Julie Wardlow
We present stacked average far-infrared spectra of a sample of 197 dusty, star-forming galaxies (DSFGs) at 0.005<z<4 using close to 90% of the SPIRE Fourier Transform Spectrometer (FTS) extragalactic data archive from the Herschel Space Observatory based on 3.5 years of science operations. These spectra explore an observed-frame 447GHz−1568GHz (191μm−671μm) frequency (wavelength) range allowing us to observe the main atomic and molecular lines emitted by gas in the interstellar medium. The sample is sub-divided into five redshift bins at 0.005<z<0.05, 0.05<z<0.2, 0.2<z<0.5, 0.8<z<2, and 2<z<4. To study the dependence of observed spectral lines on total infrared luminosity, the sources in a subset of the redshift bins are stacked in luminosity bins. These stacked spectra are used to determine the average properties of the interstellar medium and dense molecular gas properties of DSFGs, in particular, the fine-structure line ([CII] 158 μm and [OI] 63 μm) luminosity ratios, and the line to far-IR luminosity ratios are used to model the gas density and radiation field strength in the photodissociation regions (PDRs). For the low-redshift sample, we additionally present the average spectral line energy distributions (SLED) of CO and H2O rotational transitions and also consider PDR conditions based on a combination of [CI] 370 μm and 609 μm and CO(7−6) lines. For the high-z (0.8<z<4) sample PDR models suggest a molecular gas distribution in the presence of a radiation field that is at least a factor of 103 larger than the Milky-Way and with a neutral gas density of roughly 10^3 to 10^5 cm−3. The corresponding PDR models for the low-z sample suggest a UV radiation field and gas density comparable to those at high-z.
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