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Full-Text Articles in Physical Sciences and Mathematics
The Hawk-I Uds And Goods Survey (Hugs): Survey Design And Deep K-Band Number Counts, A. Fontana, J.S. Dunlop, D. Paris, T.A. Targett, K. Boutsia, M. Castellano, A. Galametz, A. Grazian, R. Mclure, E. Merlin, L. Pentericci, S. Wuyts, O. Almaini, K. Caputi, R.R. Chary, M. Cirasuolo, C.J. Conselice, A. Cooray, E. Daddi, M. Dickinson, S.M. Faber, G. Fazio, H.C. Ferguson, E. Giallongo, Mauro Giavalisco, N.A. Grogin, N. Hathi, A.M. Koekemoer, D.C. Koo, R.A. Lucas, M. Nonino, H.W. Rix, A. Renzini, D. Rosario, P. Santini, C. Scarlata, V. Sommariva, D.P. Stark, A. Van Der Wel, E. Vanzella, V. Wild, H. Yan, S Zibetti
The Hawk-I Uds And Goods Survey (Hugs): Survey Design And Deep K-Band Number Counts, A. Fontana, J.S. Dunlop, D. Paris, T.A. Targett, K. Boutsia, M. Castellano, A. Galametz, A. Grazian, R. Mclure, E. Merlin, L. Pentericci, S. Wuyts, O. Almaini, K. Caputi, R.R. Chary, M. Cirasuolo, C.J. Conselice, A. Cooray, E. Daddi, M. Dickinson, S.M. Faber, G. Fazio, H.C. Ferguson, E. Giallongo, Mauro Giavalisco, N.A. Grogin, N. Hathi, A.M. Koekemoer, D.C. Koo, R.A. Lucas, M. Nonino, H.W. Rix, A. Renzini, D. Rosario, P. Santini, C. Scarlata, V. Sommariva, D.P. Stark, A. Van Der Wel, E. Vanzella, V. Wild, H. Yan, S Zibetti
Mauro Giavalisco
We present the results of a new, ultra-deep, near-infrared imaging survey executed with the Hawk-I imager at the ESO VLT, of which we make all the data (images and catalog) public. This survey, named HUGS (Hawk-I UDS and GOODS Survey), provides deep, high-quality imaging in the K and Y bands over the portions of the UKIDSS UDS and GOODS-South fields covered by the CANDELS HST WFC3/IR survey. In this paper we describe the survey strategy, the observational campaign, the data reduction process, and the data quality. We show that, thanks to exquisite image quality and extremely long exposure times, HUGS …
Stellar Masses From The Candels Survey: The Goods-South And Uds Field, P. Satini, H.C. Ferguson, A Fontana, B. Mobasher, G. Barro, M. Castellano, S.L. Finkelstein, A. Grazian, L.T. Hsu, B. Lee, S.K. Lee, J. Pforr, M. Salvato, T. Wiklind, S. Wuyts, O. Almaini, M.C. Cooper, A. Galametz, B. Weiner, R. Amorin, K. Boutsia, C.J. Conselice, T. Dahlen, M.C. Cooper, Mauro Giavalisco, N.A. Grogin, Y. Guo, N.P. Hathi, D. Kocevski, A.M. Koekemoer, P. Kurczynski, E. Merlin, A. Mortlock, J.A. Newman, D. Paris, L. Pentericci, R. Simons, S.P. Willner
Stellar Masses From The Candels Survey: The Goods-South And Uds Field, P. Satini, H.C. Ferguson, A Fontana, B. Mobasher, G. Barro, M. Castellano, S.L. Finkelstein, A. Grazian, L.T. Hsu, B. Lee, S.K. Lee, J. Pforr, M. Salvato, T. Wiklind, S. Wuyts, O. Almaini, M.C. Cooper, A. Galametz, B. Weiner, R. Amorin, K. Boutsia, C.J. Conselice, T. Dahlen, M.C. Cooper, Mauro Giavalisco, N.A. Grogin, Y. Guo, N.P. Hathi, D. Kocevski, A.M. Koekemoer, P. Kurczynski, E. Merlin, A. Mortlock, J.A. Newman, D. Paris, L. Pentericci, R. Simons, S.P. Willner
Mauro Giavalisco
We present the public release of the stellar mass catalogs for the GOODS-S and UDS fields obtained using some of the deepest near-IR images available, achieved as part of the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) project. We combine the effort from ten different teams, who computed the stellar masses using the same photometry and the same redshifts. Each team adopted their preferred fitting code, assumptions, priors, and parameter grid. The com- bination of results using the same underlying stellar isochrones reduces the systematics associated with the fitting code and other choices. Thanks to the availability of different …
Lights, Camera...Citizen Science: Assessing The Effectiveness Of Smartphone-Based Video Training In Invasive Plant Indentification, Jared Starr, Charles M. Schweik, Nathan Bush, Lena Fletcher, Jack Finn, Jennifer Fish, Charles T. Bergeron
Lights, Camera...Citizen Science: Assessing The Effectiveness Of Smartphone-Based Video Training In Invasive Plant Indentification, Jared Starr, Charles M. Schweik, Nathan Bush, Lena Fletcher, Jack Finn, Jennifer Fish, Charles T. Bergeron
Environmental Conservation Faculty Publication Series
The rapid growth and increasing popularity of smartphone technology is putting sophisticated data-collection tools in the hands of more and more citizens. This has exciting implications for the expanding field of citizen science. With smartphonebased applications (apps), it is now increasingly practical to remotely acquire high quality citizen-submitted data at a fraction of the cost of a traditional study. Yet, one impediment to citizen science projects is the question of how to train participants. The traditional ‘‘in-person’’ training model, while effective, can be cost prohibitive as the spatial scale of a project increases. To explore possible solutions, we analyze three …