SDSS Data Management and Photometric Quality Assessment

Size: px
Start display at page:

Download "SDSS Data Management and Photometric Quality Assessment"

Transcription

1 SDSS Data Management and Photometric Quality Assessment Željko Ivezić Princeton University / University of Washington (and SDSS Collaboration) Thinkshop Robotic Astronomy, Potsdam, July 12-15,

2 Outline 1. Overview of SDSS 2. SDSS Data Flow 3. Automated Data Quality Assessment 2

3 Overview of SDSS Imaging Survey 10,000 deg 2 (1/4 of the full sky), V < ,000,000 stars and 100,000,000 galaxies 5 bands (ugriz: UV-IR), 0.02 mag photometric accuracy < 0.1 arcsec astrometric accuracy 3

4 SDSS Telescope (2.5m) 4

5 5

6 Overview of SDSS Imaging Survey 10,000 deg 2 (1/4 of the full sky), V < 22.5 over 100,000,000 stars and 100,000,000 galaxies 5 bands (ugriz: UV-IR), 0.02 mag photometric accuracy < 0.1 arcsec astrometric accuracy Spectroscopic Survey 1,000,000 galaxies 100,000 quasars 100,000 stars 6

7 Overview of SDSS Imaging Survey and Spectroscopic Survey (about 2/3 finished) Sophisticated data acquisition, processing and distribution systems ( 1 million lines of code): Science Factory: over 1,000 papers based on SDSS data, or referring to SDSS, already published (in 5 years since the first light) SDSS-II: more emphasis on Galactic structure and time domain You can join, too! (for a small fee) 7

8 SDSS Data Flow 1. Data Acquisition at Apache Point Observatory Peak data rate: 20 GB/hr 2. DLTs mailed to Fermilab 3. Pipelines run in successive order: Serial Stamp Collecting (SSC) Pipeline (bookkeeping) Postage Stamp Pipeline (PSP) (flatfields, PSF, etc) astrom (astrometric calibration) Frames (with PSP, aka Photo) most complex nfcalib (photometric calibration) 8

9 4. Stuffing operational database, resolving. 5. Spectroscopic target pipelines 6. Plate drilling at the University of Washington 7. Spectroscopic Data Acquisition at APO 8. DLTs mailed to Fermilab 9. Spectroscopic processing (spectro2d and spectro1d) 10. Stuffing database 11. All data eventually loaded into Catalog Archive Server

10 Web Interfaces to SDSS DR2 ( Catalog Archive Server (CAS): search tools for querying the imaging and spectro catalogs from SDSS. Spectro Query Server: search spectra by position, or by spectral or photometric parameters. Retrieve survey files. Imaging Query Server: search photometry catalog by position, or by photometric parameters. Retrieve survey files. SpecList: upload plate,mjd,fiber list as part of a SQL query Imaging cross-id: find SDSS neighbors for a list of positions Navigate, Finding charts, : Point and click on images, finding charts, etc. 9

11 Automated Data Quality Assessment The quality of data is of paramount importance for their scientific impact; e.g. should you trust SDSS photometry (both measurements and errors)? The quantitative data quality assessment is a difficult problem, and automated quantitative assessment is even harder SDSS automated quantitative data quality assessment: the matchqa and runqa pipelines 10

12 SDSS Automated Data Quality Assessment 1. matchqa pipeline: compares two observations of the same objects magnitudes (aperture, psf, model, fiber, Petrosian) positions shapes star/galaxy separation 11

13 12

14 SDSS Automated Data Quality Assessment 1. matchqa pipeline: compares two observations of the same objects 2. runqa pipeline: estimate data quality from single observations the quality of PSF photometry the photometric zeropoint errors 13

15 Point Spread Function Magnitudes The PSF flux is computed using the PSF as a weighting function: the PSF must be known exquisitely well for required photometric accuracy ( 0.01 mag) 14

16 SDSS Imaging Point Spread Function 15

17 Point Spread Function Modeling The PSF is determined heuristically using Karhunen-Loeve transform there is no assumption on the PSF functional form (e.g. Gaussians): a set of N stellar images is expressed as a linear combination of N eigenimages, and the first 3 terms are retained Typical variation in the effective width across a frame is 10%. Modeled by expanding eigencoefficients in terms of x a y b with a + b <= 2. Greatly improves photometric accuracy (rms from 0.05 mag to 0.02 mag, with better outlier behavior) Use the difference between the aperture and PSF magnitudes (for bright stars) to recognize bad PSF models 16

18 17

19 Photometric Calibration Imaging data are photometrically calibrated using a network of calibration stars obtained in 2 degree large patches by the Photometric Telescope Patches are separated by of order an hour of scanning time any changes in atmospheric transparency, or other conditions affecting the photometric sensitivity, may not be recognized on shorter timescales. Problem: a dense network of calibration stars across the sky, accurate to 0.01 mag, in five SDSS bands, which could be used for an independent verification of SDSS photometric calibration, does not yet exist. The position of the stellar locus in color-color diagrams is stable can be used to estimate errors in photometric zeropoints 18

20 19

21 P2 P

22 21

23 u z g 22

24 Photometric Calibration The position of the stellar locus in color-color diagrams can be used to estimate errors in photometric zeropoints to <0.01 mag in patches as small 0.03 deg 2 The width of the stellar locus can be used to automatically recognize substandard photometry Typical errors for SDSS photometric zeropoints are 0.01 mag in g, r, and i, 0.02 mag in z, and 0.03 mag in u (upper limits!) 23

25 Conclusions SDSS a science factory sophisticated data acquisition, processing and distribution systems The tracking of the position and the width of the stellar locus in color-color diagrams offers a robust automated method, accurate to 0.01 mag, for estimating the photometric accuracy of optical surveys (at least for b > 10 ) SDSS provides encouragement that even more ambitious surveys, such as LSST (20 TB/night!), may also be successful endeavors. 24

26 Update on Large Synoptic Survey Telescope LSST: a deeper SDSS (V < 24 per epoch, V < 26 coadded), every 3 days, for 10 years! Celestial Cinematography We are incorporated! (Founding partners: NOAO, Research Corporation, University of Arizona, University of Washington) New institutions are joining: the DoE group (2 Gigapixel camera), NCSC, UC Davis, Harvard, Google,... Mirror (8.4m) contract signed with the University of Arizona Mirror Lab The first light in December of

The SDSS Data. Processing the Data

The SDSS Data. Processing the Data The SDSS Data Processing the Data On a clear, dark night, light that has traveled through space for a billion years touches a mountaintop in southern New Mexico and enters the sophisticated instrumentation

More information

Large Synoptic Survey Telescope

Large Synoptic Survey Telescope Large Synoptic Survey Telescope Željko Ivezić University of Washington Santa Barbara, March 14, 2006 1 Outline 1. LSST baseline design Monolithic 8.4 m aperture, 10 deg 2 FOV, 3.2 Gpix camera 2. LSST science

More information

Introduction to the Sloan Survey

Introduction to the Sloan Survey Introduction to the Sloan Survey Title Rita Sinha IUCAA SDSS The SDSS uses a dedicated, 2.5-meter telescope on Apache Point, NM, equipped with two powerful special-purpose instruments. The 120-megapixel

More information

Introduction to SDSS -instruments, survey strategy, etc

Introduction to SDSS -instruments, survey strategy, etc Introduction to SDSS -instruments, survey strategy, etc (materials from http://www.sdss.org/) Shan Huang 17 February 2010 Survey type Status Imaging and Spectroscopy Basic Facts SDSS-II completed, SDSS-III

More information

Searching for Needles in the Sloan Digital Haystack

Searching for Needles in the Sloan Digital Haystack Searching for Needles in the Sloan Digital Haystack Robert Lupton Željko Ivezić Jim Gunn Jill Knapp Michael Strauss University of Chicago, Fermilab, Institute for Advanced Study, Japanese Participation

More information

Science Results Enabled by SDSS Astrometric Observations

Science Results Enabled by SDSS Astrometric Observations Science Results Enabled by SDSS Astrometric Observations Željko Ivezić 1, Mario Jurić 2, Nick Bond 2, Jeff Munn 3, Robert Lupton 2, et al. 1 University of Washington 2 Princeton University 3 USNO Flagstaff

More information

The Sloan Digital Sky Survey

The Sloan Digital Sky Survey The Sloan Digital Sky Survey Robert Lupton Xiaohui Fan Jim Gunn Željko Ivezić Jill Knapp Michael Strauss University of Chicago, Fermilab, Institute for Advanced Study, Japanese Participation Group, Johns

More information

JINA Observations, Now and in the Near Future

JINA Observations, Now and in the Near Future JINA Observations, Now and in the Near Future Timothy C. Beers Department of Physics & Astronomy Michigan State University & JINA: Joint Institute for Nuclear Astrophysics Examples SDSS-I, II, and III

More information

The Dark Energy Survey Public Data Release 1

The Dark Energy Survey Public Data Release 1 The Dark Energy Survey Public Data Release 1 Matias Carrasco Kind (NCSA/UIUC) and the DR1 Release Team https://des.ncsa.illinois.edu/ Near-Field Cosmology with DES DR1 and Beyond Workshop, June 27-29th,

More information

The Large Synoptic Survey Telescope

The Large Synoptic Survey Telescope The Large Synoptic Survey Telescope Philip A. Pinto Steward Observatory University of Arizona for the LSST Collaboration 17 May, 2006 NRAO, Socorro Large Synoptic Survey Telescope The need for a facility

More information

Lecture 11: SDSS Sources at Other Wavelengths: From X rays to radio. Astr 598: Astronomy with SDSS

Lecture 11: SDSS Sources at Other Wavelengths: From X rays to radio. Astr 598: Astronomy with SDSS Astr 598: Astronomy with SDSS Spring Quarter 4, University of Washington, Željko Ivezić Lecture : SDSS Sources at Other Wavelengths: From X rays to radio Large Surveys at Many Wavelengths SDSS: UV-IR five-band

More information

Doing astronomy with SDSS from your armchair

Doing astronomy with SDSS from your armchair Doing astronomy with SDSS from your armchair Željko Ivezić, University of Washington & University of Zagreb Partners in Learning webinar, Zagreb, 15. XII 2010 Supported by: Microsoft Croatia and the Croatian

More information

Studying galaxies with the Sloan Digital Sky Survey

Studying galaxies with the Sloan Digital Sky Survey Studying galaxies with the Sloan Digital Sky Survey Laboratory exercise, Physics of Galaxies, Spring 2017 (Uppsala Universitet) by Beatriz Villarroel *** The Sloan Digital Sky Survey (SDSS) is the largest

More information

VISTA HEMISPHERE SURVEY DATA RELEASE 1

VISTA HEMISPHERE SURVEY DATA RELEASE 1 Release date (will be set by ESO) VISTA HEMISPHERE SURVEY DATA RELEASE 1 PROPOSAL ESO No.: 179.A-2010 PRINCIPAL INVESTIGATOR: Richard McMahon Authors: R. McMahon, M. Banerji, N. Lodieu for the VHS Collaboration

More information

Data Processing in DES

Data Processing in DES Data Processing in DES Brian Yanny Oct 28, 2016 http://data.darkenergysurvey.org/fnalmisc/talk/detrend.p Basic Signal-to-Noise calculation in astronomy: Assuming a perfect atmosphere (fixed PSF of p arcsec

More information

The SDSS is Two Surveys

The SDSS is Two Surveys The SDSS is Two Surveys The Fuzzy Blob Survey The Squiggly Line Survey The Site The telescope 2.5 m mirror Digital Cameras 1.3 MegaPixels $150 4.3 Megapixels $850 100 GigaPixels $10,000,000 CCDs CCDs:

More information

arxiv:astro-ph/ v1 7 Mar 2007

arxiv:astro-ph/ v1 7 Mar 2007 SDSS Standard Star Catalog for Stripe 82: the Dawn of Industrial 1% Optical Photometry arxiv:astro-ph/73157v1 7 Mar 27 Željko Ivezić 18, J. Allyn Smith 18, Gajus Miknaitis 18, Huan Lin 18, Douglas Tucker

More information

ROSAT Roentgen Satellite. Chandra X-ray Observatory

ROSAT Roentgen Satellite. Chandra X-ray Observatory ROSAT Roentgen Satellite Joint facility: US, Germany, UK Operated 1990 1999 All-sky survey + pointed observations Chandra X-ray Observatory US Mission Operating 1999 present Pointed observations How do

More information

(Present and) Future Surveys for Metal-Poor Stars

(Present and) Future Surveys for Metal-Poor Stars (Present and) Future Surveys for Metal-Poor Stars Timothy C. Beers Department of Physics & Astronomy Michigan State University & JINA: Joint Institute for Nuclear Astrophysics SDSS 1 Why the Fascination

More information

Astr 323: Extragalactic Astronomy and Cosmology. Spring Quarter 2014, University of Washington, Željko Ivezić. Lecture 1:

Astr 323: Extragalactic Astronomy and Cosmology. Spring Quarter 2014, University of Washington, Željko Ivezić. Lecture 1: Astr 323: Extragalactic Astronomy and Cosmology Spring Quarter 2014, University of Washington, Željko Ivezić Lecture 1: Review of Stellar Astrophysics 1 Understanding Galaxy Properties and Cosmology The

More information

Astronomical image reduction using the Tractor

Astronomical image reduction using the Tractor the Tractor DECaLS Fin Astronomical image reduction using the Tractor Dustin Lang McWilliams Postdoc Fellow Carnegie Mellon University visiting University of Waterloo UW / 2015-03-31 1 Astronomical image

More information

Data Release 5. Sky coverage of imaging data in the DR5

Data Release 5. Sky coverage of imaging data in the DR5 Data Release 5 The Sloan Digital Sky Survey has released its fifth Data Release (DR5). The spatial coverage of DR5 is about 20% larger than that of DR4. The photometric data in DR5 are based on five band

More information

An end-to-end simulation framework for the Large Synoptic Survey Telescope Andrew Connolly University of Washington

An end-to-end simulation framework for the Large Synoptic Survey Telescope Andrew Connolly University of Washington An end-to-end simulation framework for the Large Synoptic Survey Telescope Andrew Connolly University of Washington LSST in a nutshell The LSST will be a large, wide-field, ground-based optical/near-ir

More information

A Random Walk Through Astrometry

A Random Walk Through Astrometry A Random Walk Through Astrometry Astrometry: The Second Oldest Profession George H. Kaplan Astronomical Applications Department Astrometry Department U.S. Naval Observatory Random Topics to be Covered

More information

LSST Science. Željko Ivezić, LSST Project Scientist University of Washington

LSST Science. Željko Ivezić, LSST Project Scientist University of Washington LSST Science Željko Ivezić, LSST Project Scientist University of Washington LSST@Europe, Cambridge, UK, Sep 9-12, 2013 OUTLINE Brief overview of LSST science drivers LSST science-driven design Examples

More information

SLOAN DIGITAL SKY SURVEY STANDARD STAR CATALOG FOR STRIPE 82: THE DAWN OF INDUSTRIAL 1% OPTICAL PHOTOMETRY

SLOAN DIGITAL SKY SURVEY STANDARD STAR CATALOG FOR STRIPE 82: THE DAWN OF INDUSTRIAL 1% OPTICAL PHOTOMETRY The Astronomical Journal, 134:973Y998, 2007 September # 2007. The American Astronomical Society. All rights reserved. Printed in U.S.A. A SLOAN DIGITAL SKY SURVEY STANDARD STAR CATALOG FOR STRIPE 82: THE

More information

Flagging Bad Data in Imaging

Flagging Bad Data in Imaging Flagging Bad Data Flagging Bad Data in Imaging Observations are never perfect, due to observing conditions e.g., bad seeing, moonlight, the solar wind, clouds, airplanes, cosmic rays, telescope malfunctions

More information

Astr 511: Galactic Astronomy. Winter Quarter 2015, University of Washington, Željko Ivezić. Lecture 1:

Astr 511: Galactic Astronomy. Winter Quarter 2015, University of Washington, Željko Ivezić. Lecture 1: Astr 511: Galactic Astronomy Winter Quarter 2015, University of Washington, Željko Ivezić Lecture 1: Review of Stellar Astrophysics (and other useful stuff) 1 Understanding Galaxy Properties and the Milky

More information

Design and implementation of the spectra reduction and analysis software for LAMOST telescope

Design and implementation of the spectra reduction and analysis software for LAMOST telescope Design and implementation of the spectra reduction and analysis software for LAMOST telescope A-Li Luo *a, Yan-Xia Zhang a and Yong-Heng Zhao a *a National Astronomical Observatories, Chinese Academy of

More information

Department of Astrophysical Sciences Peyton Hall Princeton, New Jersey Telephone: (609)

Department of Astrophysical Sciences Peyton Hall Princeton, New Jersey Telephone: (609) Princeton University Department of Astrophysical Sciences Peyton Hall Princeton, New Jersey 08544-1001 Telephone: (609) 258-3808 Email: strauss@astro.princeton.edu January 18, 2007 Dr. George Helou, IPAC

More information

Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS

Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS SLAC-PUB-14716 Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS Ž. Ivezić, T. Axelrod, A.C. Becker, J. Becla, K. Borne, D.L. Burke, C.F. Claver, K.H. Cook, A. Connolly,

More information

Data Management Plan Extended Baryon Oscillation Spectroscopic Survey

Data Management Plan Extended Baryon Oscillation Spectroscopic Survey Data Management Plan Extended Baryon Oscillation Spectroscopic Survey Experiment description: eboss is the cosmological component of the fourth generation of the Sloan Digital Sky Survey (SDSS-IV) located

More information

arxiv:astro-ph/ v1 17 Jan 2007

arxiv:astro-ph/ v1 17 Jan 2007 THE FUTURE OF PHOTOMETRIC, SPECTROPHOTOMETRIC AND POLARIMETRIC STANDARDIZATION ASP Conference Series, Vol. 999, 27 C. Sterken A Comparison of SDSS Standard Star Catalog for Stripe 82 with Stetson s Photometric

More information

arxiv: v1 [astro-ph.im] 9 May 2013

arxiv: v1 [astro-ph.im] 9 May 2013 Astron. Nachr. / AN Volume, No. Issue, 1 4 (212) / DOI DOI Photo-Met: a non-parametric method for estimating stellar metallicity from photometric observations Gyöngyi Kerekes 1, István Csabai 1, László

More information

A Comparison of SDSS Standard Star Catalog for Stripe 82 with Stetson s Photometric Standards

A Comparison of SDSS Standard Star Catalog for Stripe 82 with Stetson s Photometric Standards THE FUTURE OF PHOTOMETRIC, SPECTROPHOTOMETRIC AND POLARIMETRIC STANDARDIZATION ASP Conference Series, Vol. 364, 2007 C. Sterken A Comparison of SDSS Standard Star Catalog for Stripe 82 with Stetson s Photometric

More information

Local Volume, Milky Way, Stars, Planets, Solar System: L3 Requirements

Local Volume, Milky Way, Stars, Planets, Solar System: L3 Requirements Local Volume, Milky Way, Stars, Planets, Solar System: L3 Requirements Anthony Brown Sterrewacht Leiden brown@strw.leidenuniv.nl Sterrewacht Leiden LSST@Europe2 2016.06.21-1/8 LSST data product levels

More information

SDSS spectroscopic survey of stars

SDSS spectroscopic survey of stars Mem. S.A.It. Vol. 77, 1057 c SAIt 2006 Memorie della SDSS spectroscopic survey of stars Ž. Ivezić 1, D. Schlegel 2, A. Uomoto 3, N. Bond 4, T. Beers 5, C. Allende Prieto 6, R. Wilhelm 7, Y. Sun Lee 5,

More information

Surprise Detection in Multivariate Astronomical Data Kirk Borne George Mason University

Surprise Detection in Multivariate Astronomical Data Kirk Borne George Mason University Surprise Detection in Multivariate Astronomical Data Kirk Borne George Mason University kborne@gmu.edu, http://classweb.gmu.edu/kborne/ Outline What is Surprise Detection? Example Application: The LSST

More information

GOODS/FORS2 Final Data Release: Version 3.0

GOODS/FORS2 Final Data Release: Version 3.0 ESO Phase 3 Data Release Description Data Collection GOODS_FORS2 Release Number 1 Data Provider C. Cesarsky Date 30.10.2007 update 11.07.2014 GOODS/FORS2 Final Data Release: Version 3.0 As part of the

More information

Modern Image Processing Techniques in Astronomical Sky Surveys

Modern Image Processing Techniques in Astronomical Sky Surveys Modern Image Processing Techniques in Astronomical Sky Surveys Items of the PhD thesis József Varga Astronomy MSc Eötvös Loránd University, Faculty of Science PhD School of Physics, Programme of Particle

More information

A SPEctra Clustering Tool for the exploration of large spectroscopic surveys. Philipp Schalldach (HU Berlin & TLS Tautenburg, Germany)

A SPEctra Clustering Tool for the exploration of large spectroscopic surveys. Philipp Schalldach (HU Berlin & TLS Tautenburg, Germany) A SPEctra Clustering Tool for the exploration of large spectroscopic surveys Philipp Schalldach (HU Berlin & TLS Tautenburg, Germany) Working Group Helmut Meusinger (Tautenburg, Germany) Philipp Schalldach

More information

Real Astronomy from Virtual Observatories

Real Astronomy from Virtual Observatories THE US NATIONAL VIRTUAL OBSERVATORY Real Astronomy from Virtual Observatories Robert Hanisch Space Telescope Science Institute US National Virtual Observatory About this presentation What is a Virtual

More information

Image Processing in Astronomy: Current Practice & Challenges Going Forward

Image Processing in Astronomy: Current Practice & Challenges Going Forward Image Processing in Astronomy: Current Practice & Challenges Going Forward Mario Juric University of Washington With thanks to Andy Connolly, Robert Lupton, Ian Sullivan, David Reiss, and the LSST DM Team

More information

MULTIPLE EXPOSURES IN LARGE SURVEYS

MULTIPLE EXPOSURES IN LARGE SURVEYS MULTIPLE EXPOSURES IN LARGE SURVEYS / Johns Hopkins University Big Data? Noisy Skewed Artifacts Big Data? Noisy Skewed Artifacts Serious Issues Significant fraction of catalogs is junk GALEX 50% PS1 3PI

More information

Gaia Photometric Data Analysis Overview

Gaia Photometric Data Analysis Overview Gaia Photometric Data Analysis Overview Gaia photometric system Paola Marrese Sterrewacht Leiden marrese@strw.leidenuniv.nl Role of photometry in overall Gaia data analysis Photometric data analysis goals

More information

The Two Micron All-Sky Survey: Removing the Infrared Foreground

The Two Micron All-Sky Survey: Removing the Infrared Foreground University of Massachusetts Amherst ScholarWorks@UMass Amherst Astronomy Department Faculty Publication Series Astronomy 2000 The Two Micron All-Sky Survey: Removing the Infrared Foreground John E. Gizis

More information

Lab 7: The H-R Diagram of an Open Cluster

Lab 7: The H-R Diagram of an Open Cluster Lab 7: The H-R Diagram of an Open Cluster Due Date: 2007 Nov 27 (after thanksgiving) 1 Introduction: The HR Diagram In this two week project you will do absolute (not differential) photometry with a CCD

More information

Reverberation Mapping in the Era of MOS and Time-Domain Surveys: from SDSS to MSE

Reverberation Mapping in the Era of MOS and Time-Domain Surveys: from SDSS to MSE Reverberation Mapping in the Era of MOS and Time-Domain Surveys: from SDSS to MSE Yue Shen Carnegie Obs -> University of Illinois at Urbana-Champaign MSE Science Team Meeting, July 29-31 2015, Big Island

More information

Surprise Detection in Science Data Streams Kirk Borne Dept of Computational & Data Sciences George Mason University

Surprise Detection in Science Data Streams Kirk Borne Dept of Computational & Data Sciences George Mason University Surprise Detection in Science Data Streams Kirk Borne Dept of Computational & Data Sciences George Mason University kborne@gmu.edu, http://classweb.gmu.edu/kborne/ Outline Astroinformatics Example Application:

More information

Chapter 6: Transforming your data

Chapter 6: Transforming your data Why is transformation necessary? Chapter 6: Transforming your data The AAVSO International Database is composed of data collected from many different observers, at different times, from around the globe.

More information

Automated analysis: SDSS, BOSS, GIRAFFE

Automated analysis: SDSS, BOSS, GIRAFFE Automated analysis: SDSS, BOSS, GIRAFFE Tests with MILES spectra (R~2000) from the INT (Sanchez Blazquez et al. 2006) The same code (FERRE) Fitting data calibrated in flux and continuumnormalized Software

More information

The SKYGRID Project A Calibration Star Catalog for New Sensors. Stephen A. Gregory Boeing LTS. Tamara E. Payne Boeing LTS. John L. Africano Boeing LTS

The SKYGRID Project A Calibration Star Catalog for New Sensors. Stephen A. Gregory Boeing LTS. Tamara E. Payne Boeing LTS. John L. Africano Boeing LTS The SKYGRID Project A Calibration Star Catalog for New Sensors Stephen A. Gregory Boeing LTS Tamara E. Payne Boeing LTS John L. Africano Boeing LTS Paul Kervin Air Force Research Laboratory POSTER SESSION

More information

SkyMapper and the Southern Sky Survey

SkyMapper and the Southern Sky Survey and the Southern Sky Survey, Brian Schmidt and Mike Bessell Slide 1 What is? 1.35m telescope with a 5.7 sq. degree field of view To reside at Siding Spring Observatory, NSW To conduct the Southern Sky

More information

DRM Update Joe Liske

DRM Update Joe Liske DRM Update Joe Liske ETC Update Bug fix in spectroscopic mode: ETC used to calculate S/N per spectral pixel, not per resolution element. Correction and clarification of ETC document. In progress: update

More information

the open-source sky survey David W. Hogg (NYU)

the open-source sky survey David W. Hogg (NYU) the open-source sky survey David W. Hogg (NYU) http://astrometry.net/ non-text searching need to search things that aren t text, with queries that aren t text even image search in Google requires accurate

More information

arxiv:astro-ph/ v2 24 May 2001

arxiv:astro-ph/ v2 24 May 2001 The SDSS Imaging Pipelines arxiv:astro-ph/0101420v2 24 May 2001 Robert Lupton, James E. Gunn, Željko Ivezić, Gillian R. Knapp Princeton University Observatory Princeton University, Princeton, NJ 08544

More information

What shall we learn about the Milky Way using Gaia and LSST?

What shall we learn about the Milky Way using Gaia and LSST? What shall we learn about the Milky Way using Gaia and LSST? Astr 511: Galactic Astronomy! Winter Quarter 2015! University of Washington, Željko Ivezić!! The era of surveys... Standard: What data do I

More information

Separating Stars and Galaxies Based on Color

Separating Stars and Galaxies Based on Color Separating Stars and Galaxies Based on Color Victoria Strait Furman University, 3300 Poinsett Hwy, Greenville, SC 29613 and University of California, Davis, 1 Shields Ave., Davis, CA, 95616 Using photometric

More information

Large Imaging Surveys for Cosmology:

Large Imaging Surveys for Cosmology: Large Imaging Surveys for Cosmology: cosmic magnification AND photometric calibration Alexandre Boucaud Thesis work realized at APC under the supervision of James G. BARTLETT and Michel CRÉZÉ Outline Introduction

More information

Quasar Candidate Selection by Clustering using Fibonacci Series for Astronomical Surveys

Quasar Candidate Selection by Clustering using Fibonacci Series for Astronomical Surveys Quasar Candidate Selection by Clustering using Fibonacci Series for Astronomical Surveys Abstract It is becoming apparent that the next generation astronomical analysis requires good domain knowledge to

More information

arxiv:astro-ph/ v1 30 Aug 2001

arxiv:astro-ph/ v1 30 Aug 2001 TRACING LUMINOUS AND DARK MATTER WITH THE SLOAN DIGITAL SKY SURVEY J. LOVEDAY 1, for the SDSS collaboration 1 Astronomy Centre, University of Sussex, Falmer, Brighton, BN1 9QJ, England arxiv:astro-ph/18488v1

More information

WHEN THE. Pi on the Sky. The Sloan Digital Sky Survey. by HEIDI JO NEWBERG

WHEN THE. Pi on the Sky. The Sloan Digital Sky Survey. by HEIDI JO NEWBERG by HEIDI JO NEWBERG The Sloan Digital Sky Survey Pi on the Sky WHEN THE originators of the Sloan Digital Sky Survey (SDSS) met at O Hare International airport in the fall of 1988, their intent was to form

More information

Resolved Star Formation Surface Density and Stellar Mass Density of Galaxies in the Local Universe. Abstract

Resolved Star Formation Surface Density and Stellar Mass Density of Galaxies in the Local Universe. Abstract Resolved Star Formation Surface Density and Stellar Mass Density of Galaxies in the Local Universe Abdurrouf Astronomical Institute of Tohoku University Abstract In order to understand how the stellar

More information

RLW paper titles:

RLW paper titles: RLW paper titles: http://www.wordle.net Astronomical Surveys and Data Archives Richard L. White Space Telescope Science Institute HiPACC Summer School, July 2012 Overview Surveys & catalogs: Fundamental

More information

AN IMPROVED PROPER-MOTION CATALOG COMBINING USNO-B AND THE SLOAN DIGITAL SKY SURVEY

AN IMPROVED PROPER-MOTION CATALOG COMBINING USNO-B AND THE SLOAN DIGITAL SKY SURVEY The Astronomical Journal, 127:3034 3042, 2004 May # 2004. The American Astronomical Society. All rights reserved. Printed in U.S.A. AN IMPROVED PROPER-MOTION CATALOG COMBINING USNO-B AND THE SLOAN DIGITAL

More information

LSST Pipelines and Data Products. Jim Bosch / LSST PST / January 30, 2018

LSST Pipelines and Data Products. Jim Bosch / LSST PST / January 30, 2018 LSST Pipelines and Data Products Jim Bosch / LSST PST / January 30, 2018 1 Context This is the first of six talks on LSST's data products: 1. Pipelines and Data Products Overview (January 30, Jim Bosch)

More information

LCO Global Telescope Network: Operations and policies for a time-domain facility. Todd Boroson

LCO Global Telescope Network: Operations and policies for a time-domain facility. Todd Boroson LCO Global Telescope Network: Operations and policies for a time-domain facility Todd Boroson Network Concept Eighteen robotic telescopes ultimately ~27 2-meter, 1-meter, 40-cm Eight high-quality sites

More information

Promote AGASC 1.6 for use with OFLS 10.3 and SAUSAGE. Tom Aldcroft Brett Unks

Promote AGASC 1.6 for use with OFLS 10.3 and SAUSAGE. Tom Aldcroft Brett Unks Promote AGASC 1.6 for use with OFLS 10.3 and SAUSAGE Tom Aldcroft Brett Unks Summary Seek approval to promote AGASC 1.6 for operational use with OFLS 10.3 and SAUSAGE AGASC 1.6 corrects a calibration error

More information

Present and Future Large Optical Transient Surveys. Supernovae Rates and Expectations

Present and Future Large Optical Transient Surveys. Supernovae Rates and Expectations Present and Future Large Optical Transient Surveys Supernovae Rates and Expectations Phil Marshall, Lars Bildsten, Mansi Kasliwal Transients Seminar Weds 12th December 2007 Many surveys designed to find

More information

Quasar Selection from Combined Radio and Optical Surveys using Neural Networks

Quasar Selection from Combined Radio and Optical Surveys using Neural Networks Quasar Selection from Combined Radio and Optical Surveys using Neural Networks Ruth Carballo and Antonio Santiago Cofiño Dpto. de Matemática Aplicada y C. Computación. Universidad de Cantabria, Avda de

More information

Reduced data products in the ESO Phase 3 archive (Status: 02 August 2017)

Reduced data products in the ESO Phase 3 archive (Status: 02 August 2017) Reduced data products in the ESO Phase 3 archive (Status: 02 August 2017) The ESO Phase 3 archive provides access to reduced and calibrated data products. All these data are stored in standard formats

More information

Target Selection for future spectroscopic surveys (DESpec) Stephanie Jouvel, Filipe Abdalla, With DESpec target selection team.

Target Selection for future spectroscopic surveys (DESpec) Stephanie Jouvel, Filipe Abdalla, With DESpec target selection team. Target Selection for future spectroscopic surveys (DESpec) Stephanie Jouvel, Filipe Abdalla, With DESpec target selection team. 1 1 Outline: Scientific motivation (has an impact on how to select targets...)

More information

(Slides for Tue start here.)

(Slides for Tue start here.) (Slides for Tue start here.) Science with Large Samples 3:30-5:00, Tue Feb 20 Chairs: Knut Olsen & Melissa Graham Please sit roughly by science interest. Form small groups of 6-8. Assign a scribe. Multiple/blended

More information

First results from the Stockholm VIMOS Supernova Survey

First results from the Stockholm VIMOS Supernova Survey First results from the Stockholm VIMOS Supernova Survey - Detection efficiencies and photometric accuracy in supernova surveys Outline The Stockholm VIMOS Supernova Survey, SVISS. First results from the

More information

COLOR SEPARATION OF GALAXY TYPES IN THE SLOAN DIGITAL SKY SURVEY IMAGING DATA

COLOR SEPARATION OF GALAXY TYPES IN THE SLOAN DIGITAL SKY SURVEY IMAGING DATA COLOR SEPARATION OF GALAXY TYPES IN THE SLOAN DIGITAL SKY SURVEY IMAGING DATA Strateva et al. 2001, AJ, 122, 1861 Presenter: Ken Mawatari Date: 2011 October 31 2011/10/31 1 Outline Abstruct : roughly Introduction

More information

Real-time Variability Studies with the NOAO Mosaic Imagers

Real-time Variability Studies with the NOAO Mosaic Imagers Mem. S.A.It. Vol. 74, 989 c SAIt 2003 Memorie della Real-time Variability Studies with the NOAO Mosaic Imagers R. Chris Smith 1 and Armin Rest 1,2 1 NOAO/Cerro Tololo Inter-American Observatory, Colina

More information

AstroBITS: Open Cluster Project

AstroBITS: Open Cluster Project AstroBITS: Open Cluster Project I. Introduction The observational data that astronomers have gathered over many years indicate that all stars form in clusters. In a cloud of hydrogen gas, laced with helium

More information

APLUS: A Data Reduction Pipeline for HST/ACS and WFC3 Images

APLUS: A Data Reduction Pipeline for HST/ACS and WFC3 Images APLUS: A Data Reduction Pipeline for HST/ACS and WFC3 Images Wei Zheng 1,AmitSaraff 2,3,LarryBradley 4,DanCoe 4,AlexViana 4 and Sara Ogaz 4 1 Department of Physics and Astronomy, Johns Hopkins University,

More information

PHYS/ASTR 2060 Popular Observational Astronomy(3) Syllabus

PHYS/ASTR 2060 Popular Observational Astronomy(3) Syllabus PHYS/ASTR 2060 Popular Observational Astronomy(3) Syllabus Instructor: Prof. Wayne Springer (wayne.springer@utah.edu) Office: 226 INSCC (Office Hours: T 3PM-5PM or by appt.) Phone: 801-585-1390 TA: Jinqi

More information

arxiv: v1 [astro-ph] 31 Jul 2008

arxiv: v1 [astro-ph] 31 Jul 2008 ACCEPTED FOR PUBLICATION IN APJS Preprint typeset using LATEX style emulateapj v. 10/09/06 GALACTIC GLOBULAR AND OPEN CLUSTERS IN THE SLOAN DIGITAL SKY SURVEY. I. CROWDED FIELD PHOTOMETRY AND CLUSTER FIDUCIAL

More information

HETDEX Overview. Hobby Eberly Telescope Dark Energy Experiment. HETDEX is: HETDEX enables a lot of ancillary science. HETDEX Science Workshop Feb 09

HETDEX Overview. Hobby Eberly Telescope Dark Energy Experiment. HETDEX is: HETDEX enables a lot of ancillary science. HETDEX Science Workshop Feb 09 Introduction to WFU, VIRUS, & DEX Gary J. Hill, McDonald Observatory Scope What HETDEX is WFU VIRUS DEX survey parameters 1 HETDEX is: Upgrade of HET to have a new 22 arcmin wide field of view Deployment

More information

2-D Images in Astronomy

2-D Images in Astronomy 2-D Images in Astronomy ZTF camera FOV is 50 square degrees. Largest camera on >1m telescope by area in the world. Or, to make a little clearer, here s Orion. The white box is the ZTF imaging area. The

More information

The SDSS, Databases and SQL Just another day in database land

The SDSS, Databases and SQL Just another day in database land The SDSS, Databases and SQL Just another day in database land Overview of the day A more in-depth discussion of how data bases are put together. Searching data - why databases are useful. The Structured

More information

arxiv:astro-ph/ v1 3 Aug 2004

arxiv:astro-ph/ v1 3 Aug 2004 Exploring the Time Domain with the Palomar-QUEST Sky Survey arxiv:astro-ph/0408035 v1 3 Aug 2004 A. Mahabal a, S. G. Djorgovski a, M. Graham a, R. Williams a, B. Granett a, M. Bogosavljevic a, C. Baltay

More information

Fourteen-color Photometry of M13 and Ruprecht 8 using the Dichroic-Mirror Camera (DMC)

Fourteen-color Photometry of M13 and Ruprecht 8 using the Dichroic-Mirror Camera (DMC) Fourteen-color Photometry of M13 and Ruprecht 8 using the Dichroic-Mirror Camera (DMC) MASTER S THESIS A manuscript written as one requirement to obtain Master s degree from Institut Teknologi Bandung

More information

Basics of Photometry

Basics of Photometry Basics of Photometry Photometry: Basic Questions How do you identify objects in your image? How do you measure the flux from an object? What are the potential challenges? Does it matter what type of object

More information

A Calibration Method for Wide Field Multicolor. Photometric System 1

A Calibration Method for Wide Field Multicolor. Photometric System 1 A Calibration Method for Wide Field Multicolor Photometric System 1 Xu Zhou,Jiansheng Chen, Wen Xu, Mei Zhang... Beijing Astronomical Observatory,Chinese Academy of Sciences, Beijing 100080, China Beijing

More information

Detection of Polarization Effects in Gaia Data

Detection of Polarization Effects in Gaia Data Detection of Polarization Effects in Gaia Data Frederic Raison ADA7 14-18/05/2012 Introduction Gaia is an astrometry mission using 2 telescopes. The idea is to use Gaia as a polarimeter (low precision

More information

New Opportunities in Petascale Astronomy. Robert J. Brunner University of Illinois

New Opportunities in Petascale Astronomy. Robert J. Brunner University of Illinois New Opportunities in Petascale Astronomy University of Illinois Overview The Challenge New Opportunity: Probabilistic Cosmology New Opportunity: Model-Based Mining New Opportunity: Accelerating Analyses

More information

Halo Tidal Star Streams with DECAM. Brian Yanny Fermilab. DECam Community Workshop NOAO Tucson Aug

Halo Tidal Star Streams with DECAM. Brian Yanny Fermilab. DECam Community Workshop NOAO Tucson Aug Halo Tidal Star Streams with DECAM Brian Yanny Fermilab DECam Community Workshop NOAO Tucson Aug 19 2011 M31 (Andromeda) Our Local Group neighbors: Spiral galaxies similar to The Milky Way 150 kpc M33

More information

Apache Point Observatory

Apache Point Observatory Capabilities Relevant to Time-Domain Astronomy Nancy Chanover (NMSU), Director Ben Williams (UW), Deputy Director 1 From Friday Night! Boyajian s Star 5/20/17 10:34 UTC Brett Morris (UW grad student) triggered

More information

Theoretical quantities: blackbody radiation

Theoretical quantities: blackbody radiation Theoretical quantities: blackbody radiation Magnitudes are observed quantities; that is, in practice, optical astronomers typically 1. take pictures of stars 2. measure the apparent brightness of each

More information

Improving the Absolute Astrometry of HST Data with GSC-II

Improving the Absolute Astrometry of HST Data with GSC-II The 2005 HST Calibration Workshop Space Telescope Science Institute, 2005 A. M. Koekemoer, P. Goudfrooij, and L. L. Dressel, eds. Improving the Absolute Astrometry of HST Data with GSC-II A. M. Koekemoer,

More information

Larger Optics and Improved Calibration Techniques for Small Satellite Observations with the ERAU OSCOM System

Larger Optics and Improved Calibration Techniques for Small Satellite Observations with the ERAU OSCOM System Larger Optics and Improved Calibration Techniques for Small Satellite Observations with the ERAU OSCOM System Sergei Bilardi 1, Aroh Barjatya 1, Forrest Gasdia 2 1 Space and Atmospheric Instrumentation

More information

The Plato Input Catalog (PIC)

The Plato Input Catalog (PIC) The Plato Input Catalog (PIC) Giampaolo Piotto and the WP130000 group Dipartimento di Fisica e Astronomia Universita di Padova Because of the huge size of PLATO field (~2124 sq deg) and the consequent

More information

Astronomy of the Next Decade: From Photons to Petabytes. R. Chris Smith AURA Observatory in Chile CTIO/Gemini/SOAR/LSST

Astronomy of the Next Decade: From Photons to Petabytes. R. Chris Smith AURA Observatory in Chile CTIO/Gemini/SOAR/LSST Astronomy of the Next Decade: From Photons to Petabytes R. Chris Smith AURA Observatory in Chile CTIO/Gemini/SOAR/LSST Classical Astronomy still dominates new facilities Even new large facilities (VLT,

More information

Lecture 8. October 25, 2017 Lab 5

Lecture 8. October 25, 2017 Lab 5 Lecture 8 October 25, 2017 Lab 5 News Lab 2 & 3 Handed back next week (I hope). Lab 4 Due today Lab 5 (Transiting Exoplanets) Handed out and observing will start Friday. Due November 8 (or later) Stellar

More information

Intro to SQL. Two components. Data Definition Language (DDL): create table, etc. Data Manipulation Language (DML):

Intro to SQL. Two components. Data Definition Language (DDL): create table, etc. Data Manipulation Language (DML): Intro to SQL Two components Data Definition Language (DDL): create table, etc. Data Manipulation Language (DML): select, insert, delete, update, etc. The basic SELECT statement: Select From Where A1, A2,...AN

More information

The J-PAS Survey. Silvia Bonoli

The J-PAS Survey. Silvia Bonoli The J-PAS Survey The Javalambre-PAU Astrophysical Survey A Spanish-Brazilian collaboration, the J-PAS survey will scan ~8500 deg2 of the northern sky with 54 narrow-band filters covering the whole optical

More information

Classifying Galaxy Morphology using Machine Learning

Classifying Galaxy Morphology using Machine Learning Julian Kates-Harbeck, Introduction: Classifying Galaxy Morphology using Machine Learning The goal of this project is to classify galaxy morphologies. Generally, galaxy morphologies fall into one of two

More information