Search

Your search keyword '"Jonathan Sick"' showing total 15 results
Start Over Author "Jonathan Sick"
15 results on '"Jonathan Sick"'

1. The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package*

Author

Adrian M. Price-Whelan, Pey Lian Lim, Nicholas Earl, Nathaniel Starkman, Larry Bradley, David L. Shupe, Aarya A. Patil, Lia Corrales, C. E. Brasseur, Maximilian Nöthe, Axel Donath, Erik Tollerud, Brett M. Morris, Adam Ginsburg, Eero Vaher, Benjamin A. Weaver, James Tocknell, William Jamieson, Marten H. van Kerkwijk, Thomas P. Robitaille, Bruce Merry, Matteo Bachetti, H. Moritz Günther, Thomas L. Aldcroft, Jaime A. Alvarado-Montes, Anne M. Archibald, Attila Bódi, Shreyas Bapat, Geert Barentsen, Juanjo Bazán, Manish Biswas, Médéric Boquien, D. J. Burke, Daria Cara, Mihai Cara, Kyle E Conroy, Simon Conseil, Matthew W. Craig, Robert M. Cross, Kelle L. Cruz, Francesco D’Eugenio, Nadia Dencheva, Hadrien A. R. Devillepoix, Jörg P. Dietrich, Arthur Davis Eigenbrot, Thomas Erben, Leonardo Ferreira, Daniel Foreman-Mackey, Ryan Fox, Nabil Freij, Suyog Garg, Robel Geda, Lauren Glattly, Yash Gondhalekar, Karl D. Gordon, David Grant, Perry Greenfield, Austen M. Groener, Steve Guest, Sebastian Gurovich, Rasmus Handberg, Akeem Hart, Zac Hatfield-Dodds, Derek Homeier, Griffin Hosseinzadeh, Tim Jenness, Craig K. Jones, Prajwel Joseph, J. Bryce Kalmbach, Emir Karamehmetoglu, Mikołaj Kałuszyński, Michael S. P. Kelley, Nicholas Kern, Wolfgang E. Kerzendorf, Eric W. Koch, Shankar Kulumani, Antony Lee, Chun Ly, Zhiyuan Ma, Conor MacBride, Jakob M. Maljaars, Demitri Muna, N. A. Murphy, Henrik Norman, Richard O’Steen, Kyle A. Oman, Camilla Pacifici, Sergio Pascual, J. Pascual-Granado, Rohit R. Patil, Gabriel I Perren, Timothy E. Pickering, Tanuj Rastogi, Benjamin R. Roulston, Daniel F Ryan, Eli S. Rykoff, Jose Sabater, Parikshit Sakurikar, Jesús Salgado, Aniket Sanghi, Nicholas Saunders, Volodymyr Savchenko, Ludwig Schwardt, Michael Seifert-Eckert, Albert Y. Shih, Anany Shrey Jain, Gyanendra Shukla, Jonathan Sick, Chris Simpson, Sudheesh Singanamalla, Leo P. Singer, Jaladh Singhal, Manodeep Sinha, Brigitta M. Sipőcz, Lee R. Spitler, David Stansby, Ole Streicher, Jani Šumak, John D. Swinbank, Dan S. Taranu, Nikita Tewary, Grant R. Tremblay, Miguel de Val-Borro, Samuel J. Van Kooten, Zlatan Vasović, Shresth Verma, José Vinícius de Miranda Cardoso, Peter K. G. Williams, Tom J. Wilson, Benjamin Winkel, W. M. Wood-Vasey, Rui Xue, Peter Yoachim, Chen Zhang, and Andrea Zonca

Published
2022
Full Text
View/download PDF

3. Documentation automation for the verification and validation of Rubin Observatory software

Author

Austin Roberts, Leanne P. Guy, Brian Van Klaveren, Jonathan Sick, William O'Mullane, Keith Bechtol, Jeffrey L. Carlin, and Gabriele Comoretto

Subjects
Test management, Traceability, Computer science, business.industry, Data management, Python (programming language), Automation, System requirements, Documentation, Software, Software engineering, business, computer, computer.programming_language
Abstract

The Data Management (DM) subsystem of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) is responsible for creating the software, services, and systems that will be used to produce science ready data products. The software, currently under development, is heterogeneous, comprising both C++ and Python components, and is designed to facilitate both the processing of the observatory images and to enable value-added contributions from the broader scientific community. Verification and validation of these software products, services, and systems is an essential yet time-consuming task. In this paper, we present the tooling and procedures developed to ensure a systematic approach to the production of documentation for verification and validation. By adopting a systematic approach, we guarantee full traceability to system requirements, integration with the project’s Systems Engineering model, and substantially reduce the time required for the whole process.

Published
2020
Full Text
View/download PDF

4. LSST: from Science Drivers to Reference Design and Anticipated Data Products

Author

Željko Ivezić, Steven M. Kahn, J. Anthony Tyson, Bob Abel, Emily Acosta, Robyn Allsman, David Alonso, Yusra AlSayyad, Scott F. Anderson, John Andrew, James Roger P. Angel, George Z. Angeli, Reza Ansari, Pierre Antilogus, Constanza Araujo, Robert Armstrong, Kirk T. Arndt, Pierre Astier, Éric Aubourg, Nicole Auza, Tim S. Axelrod, Deborah J. Bard, Jeff D. Barr, Aurelian Barrau, James G. Bartlett, Amanda E. Bauer, Brian J. Bauman, Sylvain Baumont, Ellen Bechtol, Keith Bechtol, Andrew C. Becker, Jacek Becla, Cristina Beldica, Steve Bellavia, Federica B. Bianco, Rahul Biswas, Guillaume Blanc, Jonathan Blazek, Roger D. Blandford, Josh S. Bloom, Joanne Bogart, Tim W. Bond, Michael T. Booth, Anders W. Borgland, Kirk Borne, James F. Bosch, Dominique Boutigny, Craig A. Brackett, Andrew Bradshaw, William Nielsen Brandt, Michael E. Brown, James S. Bullock, Patricia Burchat, David L. Burke, Gianpietro Cagnoli, Daniel Calabrese, Shawn Callahan, Alice L. Callen, Jeffrey L. Carlin, Erin L. Carlson, Srinivasan Chandrasekharan, Glenaver Charles-Emerson, Steve Chesley, Elliott C. Cheu, Hsin-Fang Chiang, James Chiang, Carol Chirino, Derek Chow, David R. Ciardi, Charles F. Claver, Johann Cohen-Tanugi, Joseph J. Cockrum, Rebecca Coles, Andrew J. Connolly, Kem H. Cook, Asantha Cooray, Kevin R. Covey, Chris Cribbs, Wei Cui, Roc Cutri, Philip N. Daly, Scott F. Daniel, Felipe Daruich, Guillaume Daubard, Greg Daues, William Dawson, Francisco Delgado, Alfred Dellapenna, Robert de Peyster, Miguel de Val-Borro, Seth W. Digel, Peter Doherty, Richard Dubois, Gregory P. Dubois-Felsmann, Josef Durech, Frossie Economou, Tim Eifler, Michael Eracleous, Benjamin L. Emmons, Angelo Fausti Neto, Henry Ferguson, Enrique Figueroa, Merlin Fisher-Levine, Warren Focke, Michael D. Foss, James Frank, Michael D. Freemon, Emmanuel Gangler, Eric Gawiser, John C. Geary, Perry Gee, Marla Geha, Charles J. B. Gessner, Robert R. Gibson, D. Kirk Gilmore, Thomas Glanzman, William Glick, Tatiana Goldina, Daniel A. Goldstein, Iain Goodenow, Melissa L. Graham, William J. Gressler, Philippe Gris, Leanne P. Guy, Augustin Guyonnet, Gunther Haller, Ron Harris, Patrick A. Hascall, Justine Haupt, Fabio Hernandez, Sven Herrmann, Edward Hileman, Joshua Hoblitt, John A. Hodgson, Craig Hogan, James D. Howard, Dajun Huang, Michael E. Huffer, Patrick Ingraham, Walter R. Innes, Suzanne H. Jacoby, Bhuvnesh Jain, Fabrice Jammes, James Jee, Tim Jenness, Garrett Jernigan, Darko Jevremović, Kenneth Johns, Anthony S. Johnson, Margaret W. G. Johnson, R. Lynne Jones, Claire Juramy-Gilles, Mario Jurić, Jason S. Kalirai, Nitya J. Kallivayalil, Bryce Kalmbach, Jeffrey P. Kantor, Pierre Karst, Mansi M. Kasliwal, Heather Kelly, Richard Kessler, Veronica Kinnison, David Kirkby, Lloyd Knox, Ivan V. Kotov, Victor L. Krabbendam, K. Simon Krughoff, Petr Kubánek, John Kuczewski, Shri Kulkarni, John Ku, Nadine R. Kurita, Craig S. Lage, Ron Lambert, Travis Lange, J. Brian Langton, Laurent Le Guillou, Deborah Levine, Ming Liang, Kian-Tat Lim, Chris J. Lintott, Kevin E. Long, Margaux Lopez, Paul J. Lotz, Robert H. Lupton, Nate B. Lust, Lauren A. MacArthur, Ashish Mahabal, Rachel Mandelbaum, Thomas W. Markiewicz, Darren S. Marsh, Philip J. Marshall, Stuart Marshall, Morgan May, Robert McKercher, Michelle McQueen, Joshua Meyers, Myriam Migliore, Michelle Miller, David J. Mills, Connor Miraval, Joachim Moeyens, Fred E. Moolekamp, David G. Monet, Marc Moniez, Serge Monkewitz, Christopher Montgomery, Christopher B. Morrison, Fritz Mueller, Gary P. Muller, Freddy Muñoz Arancibia, Douglas R. Neill, Scott P. Newbry, Jean-Yves Nief, Andrei Nomerotski, Martin Nordby, Paul O’Connor, John Oliver, Scot S. Olivier, Knut Olsen, William O’Mullane, Sandra Ortiz, Shawn Osier, Russell E. Owen, Reynald Pain, Paul E. Palecek, John K. Parejko, James B. Parsons, Nathan M. Pease, J. Matt Peterson, John R. Peterson, Donald L. Petravick, M. E. Libby Petrick, Cathy E. Petry, Francesco Pierfederici, Stephen Pietrowicz, Rob Pike, Philip A. Pinto, Raymond Plante, Stephen Plate, Joel P. Plutchak, Paul A. Price, Michael Prouza, Veljko Radeka, Jayadev Rajagopal, Andrew P. Rasmussen, Nicolas Regnault, Kevin A. Reil, David J. Reiss, Michael A. Reuter, Stephen T. Ridgway, Vincent J. Riot, Steve Ritz, Sean Robinson, William Roby, Aaron Roodman, Wayne Rosing, Cecille Roucelle, Matthew R. Rumore, Stefano Russo, Abhijit Saha, Benoit Sassolas, Terry L. Schalk, Pim Schellart, Rafe H. Schindler, Samuel Schmidt, Donald P. Schneider, Michael D. Schneider, William Schoening, German Schumacher, Megan E. Schwamb, Jacques Sebag, Brian Selvy, Glenn H. Sembroski, Lynn G. Seppala, Andrew Serio, Eduardo Serrano, Richard A. Shaw, Ian Shipsey, Jonathan Sick, Nicole Silvestri, Colin T. Slater, J. Allyn Smith, R. Chris Smith, Shahram Sobhani, Christine Soldahl, Lisa Storrie-Lombardi, Edward Stover, Michael A. Strauss, Rachel A. Street, Christopher W. Stubbs, Ian S. Sullivan, Donald Sweeney, John D. Swinbank, Alexander Szalay, Peter Takacs, Stephen A. Tether, Jon J. Thaler, John Gregg Thayer, Sandrine Thomas, Adam J. Thornton, Vaikunth Thukral, Jeffrey Tice, David E. Trilling, Max Turri, Richard Van Berg, Daniel Vanden Berk, Kurt Vetter, Francoise Virieux, Tomislav Vucina, William Wahl, Lucianne Walkowicz, Brian Walsh, Christopher W. Walter, Daniel L. Wang, Shin-Yawn Wang, Michael Warner, Oliver Wiecha, Beth Willman, Scott E. Winters, David Wittman, Sidney C. Wolff, W. Michael Wood-Vasey, Xiuqin Wu, Bo Xin, Peter Yoachim, Hu Zhan, Laboratoire de l'Accélérateur Linéaire (LAL), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE (UMR_7585)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), AstroParticule et Cosmologie (APC (UMR_7164)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Laboratoire de Physique Subatomique et de Cosmologie (LPSC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Université Paris Diderot - Paris 7 (UPD7), Laboratoire d'Annecy de Physique des Particules (LAPP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire des matériaux avancés (LMA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Univers et Particules de Montpellier (LUPM), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Physique de Clermont (LPC), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Centre National de la Recherche Scientifique (CNRS), Centre de Calcul de l'IN2P3 (CC-IN2P3), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Centre de Physique des Particules de Marseille (CPPM), Aix Marseille Université (AMU)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Instituto de RadioAstronomía Milimétrica (IRAM), Centre National de la Recherche Scientifique (CNRS), LSST, Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris Diderot - Paris 7 (UPD7)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Institut Polytechnique de Grenoble - Grenoble Institute of Technology-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Laboratoire d'Annecy de Physique des Particules (LAPP/Laboratoire d'Annecy-le-Vieux de Physique des Particules), Centre National de la Recherche Scientifique (CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Montpellier (UM)-Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Clermont Auvergne (UCA)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Aix Marseille Université (AMU), Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Université Montpellier 2 - Sciences et Techniques (UM2)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Clermont Auvergne (UCA), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), and Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Montpellier 2 - Sciences et Techniques (UM2)

Subjects
010504 meteorology & atmospheric sciences, Astronomy, observational [methods], Field of view, Astrophysics, 7. Clean energy, 01 natural sciences, law.invention, law, size distribution, sagittarius dwarf galaxy, 010303 astronomy & astrophysics, stars: general, media_common, Physics, Reference design, general [stars], gamma-ray bursts, Astrophysics (astro-ph), observations [cosmology], proper motion stars, ia supernovae, astrometry, methods: observational, Astronomical and Space Sciences, Physical Chemistry (incl. Structural), Milky Way, media_common.quotation_subject, Dark matter, FOS: Physical sciences, Large Synoptic Survey Telescope, Astronomy & Astrophysics, milky-way tomography, Primary mirror, Telescope, surveys, astro-ph, 0103 physical sciences, Galaxy: general, general [Galaxy], 0105 earth and related environmental sciences, dark-energy constraints, Organic Chemistry, Astronomy and Astrophysics, Space and Planetary Science, Sky, tidal disruption events, cosmology: observations, digital sky survey, lensing power spectrum, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]
Abstract

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta, Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overview

Published
2019
Full Text
View/download PDF

5. LSST data management software development practices and tools

Author

Brian Van Klaveren, William O'Mullane, Frossie Economou, K. Simon Krughoff, Pim Schellart, K. T. Lim, Fritz Mueller, John D. Swinbank, James Bosch, Jonathan Sick, John K. Parejko, Josh Hoblitt, Paul A. Price, Tim Jenness, Adam J. Thornton, Robert H. Lupton, K. Findeisen, Russell Owen, Fabio Hernandez, Jeffrey Kantor, and Stephen R. Pietrowicz

Subjects
010308 nuclear & particles physics, business.industry, Computer science, Data management, Software development, Petabyte, Large Synoptic Survey Telescope, 01 natural sciences, Software, Software deployment, 0103 physical sciences, Distributed development, business, Software engineering, 010303 astronomy & astrophysics, Agile software development
Abstract

The Large Synoptic Survey Telescope (LSST) is an 8.4m optical survey telescope being constructed on Cerro Pach´on in Chile. The data management system being developed must be able to process the nightly alert data, 20,000 expected transient alerts per minute, in near real time, and construct annual data releases at the petabyte scale. The development team consists of more than 90 people working in six different sites across the US developing an integrated set of software to realize the LSST science goals. In this paper we discuss our agile software development methodology and our API and developer decision making process. We also discuss the software tools that we use for continuous integration and deployment.

Published
2018
Full Text
View/download PDF

6. Getting Started with LSST

Author

Jonathan Sick

Subjects
lsst
Abstract

There are many ways participate in the LSST project. This talk provides some links to websites that can help you follow LSST news and join LSST's Science Collaborations. To enable discussions across the LSST Project and the astronomy community, we also provide the https://community.lsst.org forum and the https://lsstc.slack.com chat platform.

Published
2016
Full Text
View/download PDF

7. Investigating interoperability of the LSST Data Management software stack with Astropy

Author

James Bosch, Russell Owen, Tim Jenness, Erik Tollerud, K. Simon Krughoff, John K. Parejko, Pim Schellart, Miguel de Val-Borro, Robert H. Lupton, Jonathan Sick, G. P. Dubois-Felsmann, K. T. Lim, John D. Swinbank, Chiozzi, Gianluca, and Guzman, Juan C.

Subjects
Source lines of code, Computer science, business.industry, Data management, media_common.quotation_subject, Interoperability, Large Synoptic Survey Telescope, Python (programming language), computer.software_genre, 01 natural sciences, Pipeline (software), law.invention, 010309 optics, Telescope, Software, law, Sky, 0103 physical sciences, Operating system, Software engineering, business, 010303 astronomy & astrophysics, computer, computer.programming_language, media_common
Abstract

The Large Synoptic Survey Telescope (LSST) will be an 8.4m optical survey telescope sited in Chile and capable of imaging the entire sky twice a week. The data rate of approximately 15TB per night and the requirements to both issue alerts on transient sources within 60 seconds of observing and create annual data releases means that automated data management systems and data processing pipelines are a key deliverable of the LSST construction project. The LSST data management software has been in development since 2004 and is based on a C++ core with a Python control layer. The software consists of nearly a quarter of a million lines of code covering the system from fundamental WCS and table libraries to pipeline environments and distributed process execution. The Astropy project began in 2011 as an attempt to bring together disparate open source Python projects and build a core standard infrastructure that can be used and built upon by the astronomy community. This project has been phenomenally successful in the years since it has begun and has grown to be the de facto standard for Python software in astronomy. Astropy brings with it considerable expectations from the community on how astronomy Python software should be developed and it is clear that by the time LSST is fully operational in the 2020s many of the prospective users of the LSST software stack will expect it to be fully interoperable with Astropy. In this paper we describe the overlap between the LSST science pipeline software and Astropy software and investigate areas where the LSST software provides new functionality. We also discuss the possibilities of re-engineering the LSST science pipeline software to build upon Astropy, including the option of contributing affliated packages.

Published
2016

8. smtn-005 v1.0 Cloud Statistics via All-Sky Camera

Author

Peter Yoachim and Jonathan Sick

Subjects
lsst, lsst-smtn
Abstract

Summary of ~1 year of data taken at the LSST site with an optical all-sky camera. We look at the number of detected stars and how often the sky is clear, partly cloudy, and totally cloudy.

Published
2016
Full Text
View/download PDF

9. SQR-000 v1.0 The LSST DM Technical Note Publishing Platform

Author

Jonathan Sick

Subjects
lsst, lsst-sqr
Abstract

Technical notes (technotes) are a new documentation medium for LSST Data Management (DM)staff to publish stand-alone documents that are native to the web.Technotes are written in reStructuredText, version controlled on GitHub, built with the same stack as DM's software documentation, and made universally citeable with digital object identifiers (DOIs)provided through Zenodo. DM team members can create a new technote today by following the instructions at https://github.com/lsst-sqre/lsst-technote-bootstrap.

Published
2015
Full Text
View/download PDF

10. SQR-001 v1.0

Author

Frossie Economou, JMatt Peterson, Joshua Hoblitt, and Jonathan Sick

Subjects
lsst, lsst-sqr
Abstract

SQR-001: Git LFS Architecture Noteversion 1.0 release

Published
2015
Full Text
View/download PDF

11. The Stellar Mass of M31 as inferred by the Andromeda Optical & Infrared Disk Survey

Author

Jonathan Sick, Dana Simard, R. Brent Tully, Julianne J. Dalcanton, Michael McDonald, Stéphane Courteau, Jean-Charles Cuillandre, and Roelof S. de Jong

Subjects
Physics, Spiral galaxy, Stellar mass, Stellar population, media_common.quotation_subject, Metallicity, Astrophysics::High Energy Astrophysical Phenomena, FOS: Physical sciences, Astronomy and Astrophysics, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Andromeda, Space and Planetary Science, Sky, Bulge, Astrophysics of Galaxies (astro-ph.GA), Spectral energy distribution, Astrophysics::Solar and Stellar Astrophysics, Astrophysics::Earth and Planetary Astrophysics, Astrophysics::Galaxy Astrophysics, media_common
Abstract

Our proximity and external vantage point make M31 an ideal testbed for understanding the structure of spiral galaxies. The Andromeda Optical and Infrared Disk Survey (ANDROIDS) has mapped M31's bulge and disk out to R=40 kpc in $ugriJK_s$ bands with CFHT using a careful sky calibration. We use Bayesian modelling of the optical-infrared spectral energy distribution (SED) to estimate profiles of M31's stellar populations and mass along the major axis. This analysis provides evidence for inside-out disk formation and a declining metallicity gradient. M31's $i$-band mass-to-light ratio ($M/L_i^*$) decreases from 0.5 dex in the bulge to $\sim 0.2$ dex at 40 kpc. The best-constrained stellar population models use the full $ugriJK_s$ SED but are also consistent with optical-only fits. Therefore, while NIR data can be successfully modelled with modern stellar population synthesis, NIR data do not provide additional constraints in this application. Fits to the $gi$-SED alone yield $M/L_i^*$ that are systematically lower than the full SED fit by 0.1 dex. This is still smaller than the 0.3 dex scatter amongst different relations for $M/L_i$ via $g-i$ colour found in the literature. We advocate a stellar mass of $M_*(30\mathrm{kpc})=10.3^{+2.3}_{-1.7}\times 10^{10}\mathrm{M}_\odot$ for the M31 bulge and disk., Sick et al. 2014, in IAU Symp. 311, Galaxy Masses as Constraints of Formation Models, ed. M. Cappellari & S. Courteau, (Cambridge: Cambridge Univ. Press), in press. Version 2 corrects a typo in the abstract

Published
2014

12. Stellar populations across the NGC4244 truncated galactic disk

Author

Benne W. Holwerda, Paul Goudfrooij, James S. Bullock, Chris W. Purcell, Jonathan Sick, Roelof S. de Jong, Julianne J. Dalcanton, Thomas M. Brown, S. Holfeltz, Daniel B. Zucker, Eric F. Bell, H. C. Ferguson, Anil C. Seth, D. J. Radburn-Smith, and Stephane Courteau

Subjects
Physics, Radial position, Angular momentum, Dark matter, Astrophysics (astro-ph), FOS: Physical sciences, Astronomy and Astrophysics, Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Galaxy, Photometry (optics), Stars, Space and Planetary Science, Astrophysics::Solar and Stellar Astrophysics, Astrophysics::Earth and Planetary Astrophysics, Disc, Stellar density, Astrophysics::Galaxy Astrophysics
Abstract

We use HST/ACS to study the resolved stellar populations of the nearby, nearly edge-on galaxy NGC4244 across its outer disk surface density break. The stellar photometry allows us to study the distribution of different stellar populations and reach very low equivalent surface brightnesses. We find that the break occurs at the same radius for young, intermediate age, and old stars. The stellar density beyond the break drops sharply by a factor of at least 600 in 5 kpc. The break occurs at the same radius independent of height above the disk, but is sharpest in the midplane and nearly disappears at large heights. These results make it unlikely that truncations are caused by a star formation threshold alone: the threshold would have to keep the same radial position from less than 100 Myr to 10 Gyr ago, in spite of potential disturbances such as infall and redistribution of gas by internal processes. A dynamical interpretation of truncation formation is more likely such as due to angular momentum redistribution by bars or density waves, or heating and stripping of stars caused by the bombardment of dark matter sub-halos. The latter explanation is also in quantitative agreement with the small diffuse component we see around the galaxy., Comment: ApJ Letters, in press. Five pages, 2 figures

Published
2007
Full Text
View/download PDF

13. 3D ionization structure and kinematics of NGC 2392

Author

Jonathan Sick, Richard C. Henry, Joaquin Bohigas, Reginald J. Dufour, Patrick Hartigan, and Karen B. Kwitter

Subjects
Physics, Nebula, Astrophysics::High Energy Astrophysical Phenomena, Astronomy, Astronomy and Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Kinematics, Astrophysics, Spectral line, law.invention, Hubble sequence, Telescope, symbols.namesake, Space and Planetary Science, law, Ionization, symbols, Astrophysics::Solar and Stellar Astrophysics, Astrophysics::Earth and Planetary Astrophysics, Emission spectrum, Spectroscopy, Astrophysics::Galaxy Astrophysics
Abstract

We discuss the 3D morphology, ionization structure, and kinematics of NGC 2392, the “Eskimo,” based on new and archival HST imagery and new long-slit echelle spectroscopy. High spatial resolution ionization maps of the nebula were made from HST WFPC2 imagery and compared with their velocity structure in various emission lines from echelle spectra taken with the 4m telescope at Kitt Peak. The imagery and spectra were then compared to map the kinematics of the nebula in several emission lines and decode the 3-dimensional morphology and ionization structure of the nebula, including that of C+2 from C III] 1909 Å for the first time.

Published
2011
Full Text
View/download PDF

14. ANDROMEDA (M31) OPTICAL AND INFRARED DISK SURVEY. I. INSIGHTS IN WIDE-FIELD NEAR-IR SURFACE PHOTOMETRY

Author

Roelof S. de Jong, R. Brent Tully, Jean-Charles Cuillandre, Michael McDonald, Jonathan Sick, and Stéphane Courteau

Subjects
Physics, Background subtraction, Brightness, Andromeda Galaxy, Skyglow, media_common.quotation_subject, Night sky, Astrophysics::Instrumentation and Methods for Astrophysics, Astronomy and Astrophysics, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics, Photometry (optics), Space and Planetary Science, Sky, Astrophysics::Earth and Planetary Astrophysics, Surface brightness, Astrophysics::Galaxy Astrophysics, media_common
Abstract

We present wide-field near-infrared J and K{sub s} images of the Andromeda Galaxy (M31) taken with WIRCam at the Canada-France-Hawaii Telescope as part of the Andromeda Optical and Infrared Disk Survey. This data set allows simultaneous observations of resolved stars and near-infrared (NIR) surface brightness across M31's entire bulge and disk (within R = 22 kpc), permitting a direct test of the stellar composition of near-infrared light in a nearby galaxy. Here we develop NIR observation and reduction methods to recover a uniform surface brightness map across the 3° × 1° disk of M31 with 27 WIRCam fields. Two sky-target nodding strategies are tested, and we find that strictly minimizing sky sampling latency cannot improve background subtraction accuracy to better than 2% of the background level due to spatio-temporal variations in the NIR skyglow. We fully describe our WIRCam reduction pipeline and advocate using flats built from night-sky images over a single night, rather than dome flats that do not capture the WIRCam illumination field. Contamination from scattered light and thermal background in sky flats has a negligible effect on the surface brightness shape compared to the stochastic differences in background shape between sky and galaxy disk fields, which aremore » ∼0.3% of the background level. The most dramatic calibration step is the introduction of scalar sky offsets to each image that optimizes surface brightness continuity. Sky offsets reduce the mean surface brightness difference between observation blocks from 1% to

Published
2014
Full Text
View/download PDF

15. THE GHOSTS SURVEY. I. HUBBLE SPACE TELESCOPE ADVANCED CAMERA FOR SURVEYS DATA

Author

Jonathan Sick, James S. Bullock, Benne W. Holwerda, Julianne J. Dalcanton, Chris W. Purcell, Thomas M. Brown, Daniel B. Zucker, Jeremy Bailin, Paul Goudfrooij, Stéphane Courteau, David J. Radburn-Smith, M. Vlajic, Anil C. Seth, Eric F. Bell, S. Holfeltz, R. S. de Jong, D. Streich, and Henry C. Ferguson

Subjects
Physics, Extinction (astronomy), Astronomy, Astronomy and Astrophysics, Extragalactic astronomy, Astrophysics::Cosmology and Extragalactic Astrophysics, Astrophysics, Advanced Camera for Surveys, Galaxy, Photometry (optics), Red-giant branch, Stars, Space and Planetary Science, Astrophysics::Solar and Stellar Astrophysics, Astrophysics::Earth and Planetary Astrophysics, Surface brightness, Astrophysics::Galaxy Astrophysics
Abstract

We present an overview of the GHOSTS survey, the largest study to date of the resolved stellar populations in the outskirts of disk galaxies. The sample consists of 14 disk galaxies within 17 Mpc, whose outer disks and halos are imaged with the Hubble Space Telescope Advanced Camera for Surveys (ACS). In the first paper of this series, we describe the sample, explore the benefits of using resolved stellar populations, and discuss our ACS F606W and F814W photometry. We use artificial star tests to assess completeness and use overlapping regions to estimate photometric uncertainties. The median depth of the survey at 50% completeness is 2.7?mag below the tip of the red giant branch (TRGB). We comprehensively explore and parameterize contamination from unresolved background galaxies and foreground stars using archival fields of high-redshift ACS observations. Left uncorrected, these would account for 100.65 ? F814W ? 19.0 detections per mag per arcsec2. We therefore identify several selection criteria that typically remove 95% of the contaminants. Even with these culls, background galaxies are a significant limitation to the surface brightness detection limit which, for this survey, is typically V ~ 30?mag?arcsec?2. The resulting photometric catalogs are publicly available and contain some 3.1 million stars across 76 ACS fields, predominantly of low extinction. The uniform magnitudes of TRGB stars in these fields enable galaxy distance estimates with 2%-7% accuracy.

Published
2011
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results