Science Results Enabled by SDSS Astrometric Observations

Similar documents
Astr 598: Astronomy with SDSS. Spring Quarter 2004, University of Washington, Željko Ivezić. Lecture 4: Moving Objects Detected by SDSS

Solar System Science with the SDSS

The Sloan Digital Sky Survey

Searching for Needles in the Sloan Digital Haystack

Mario Juric Institute for Advanced Study, Princeton

Large Synoptic Survey Telescope

JINA Observations, Now and in the Near Future

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

SDSS Data Management and Photometric Quality Assessment

Introduction to SDSS -instruments, survey strategy, etc

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

SkyMapper and the Southern Sky Survey

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

arxiv:astro-ph/ v1 5 Aug 2002

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

(Present and) Future Surveys for Metal-Poor Stars

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

The halo is specially interesting because gravitational potential becomes dominated by the dark matter halo

1. INTRODUCTION 2. SDSS OBSERVATIONS OF ASTEROIDS. The Astronomical Journal, 124: , 2002 November

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

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

Astr As ome tr tr ome y I M. Shao

SkyMapper and the Southern Sky Survey

Astr 598: Astronomy with SDSS. Spring Quarter 2004, University of Washington, Željko Ivezić. Lecture 6: Milky Way Structure I: Thin and Thick Disks

Milky Way star clusters

The Yale/ODI Survey(s)

The Gaia Mission. Coryn Bailer-Jones Max Planck Institute for Astronomy Heidelberg, Germany. ISYA 2016, Tehran

The Pan-STARRS1 view of the Hyades cluster

Finding habitable earths around white dwarfs with a robotic telescope transit survey

Thoughts on future space astrometry missions

Observed Properties of Stars ASTR 2120 Sarazin

Astrometry in Gaia DR1

The Porcupine Survey: Spitzer Warm Mission Followup of WISE Brown Dwarf Candidates

Tristan Cantat-Gaudin

Pre-observations and models

How to Understand Stars Chapter 17 How do stars differ? Is the Sun typical? Location in space. Gaia. How parallax relates to distance

The Large Synoptic Survey Telescope

SDSS spectroscopic survey of stars

Doing astronomy with SDSS from your armchair

Lecture 16 The Measuring the Stars 3/26/2018

The Three Dimensional Universe, Meudon - October, 2004

Surface Brightness of Spiral Galaxies

Synergies between E-ELT and space instrumentation for extrasolar planet science

The Brown Dwarfs of our Milky Way

VISTA HEMISPHERE SURVEY DATA RELEASE 1

MASS FUNCTION OF STELLAR REMNANTS IN THE MILKY WAY

Exploring the Structure of the Milky Way with WFIRST

Gaia-LSST Synergy. A. Vallenari. INAF, Padova

Milky Way S&G Ch 2. Milky Way in near 1 IR H-W Rixhttp://online.kitp.ucsb.edu/online/galarcheo-c15/rix/

Gaia & Ultra-Cool Dwarfs: a high-denition picture of the Milky Way

ASTR 200 : Lecture 22 Structure of our Galaxy

Celestial Coordinate Systems

Extrasolar Planet Science with High-Precision Astrometry Johannes Sahlmann

Optical variability of quasars: damped random walk Željko Ivezić, University of Washington with Chelsea MacLeod, U.S.

Deep fields around bright stars ( Galaxies around Stars )

FAINT HIGH-LATITUDE CARBON STARS DISCOVERED BY THE SLOAN DIGITAL SKY SURVEY: AN INITIAL CATALOG

Light and Stars ASTR 2110 Sarazin

Catalog Information and Recommendations

VARIABLE FAINT OPTICAL SOURCES DISCOVERED BY COMPARING THE POSS AND SDSS CATALOGS

GDR1 photometry. CU5/DPCI team

Measuring the evolution of the star formation rate efficiency of neutral atomic hydrogen gas from z ~1 4

arxiv:astro-ph/ v1 3 Aug 2004

Accurate Mass Determination of the Old White Dwarf G through Astrometric Microlensing

The Cosmological Distance Ladder. It's not perfect, but it works!

HD Transits HST/STIS First Transiting Exo-Planet. Exoplanet Discovery Methods. Paper Due Tue, Feb 23. (4) Transits. Transits.

Universe. Tenth Edition. The Nature of the Stars. Parallax. CHAPTER 17 The Nature of Stars

arxiv: v1 [astro-ph.ep] 10 Feb 2012

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

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

Time-series Photometry of Earth Flyby Asteroid 2012 DA14

arxiv:astro-ph/ v1 11 May 1999

TMT and Space-Based Survey Missions

GAIA: SOLAR SYSTEM ASTROMETRY IN DR2

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

The Pan-STARRS1 view of the Hyades cluster

Galaxies: The Nature of Galaxies

MULTIPLE EXPOSURES IN LARGE SURVEYS

Real Astronomy from Virtual Observatories

Searching for Other Worlds

Techniques for measuring astronomical distances generally come in two variates, absolute and relative.

The Milky Way, Hubble Law, the expansion of the Universe and Dark Matter Chapter 14 and 15 The Milky Way Galaxy and the two Magellanic Clouds.

PHY2083 ASTRONOMY. Dr. Rubina Kotak Office F016. Dr. Chris Watson Office S036

New halo white dwarf candidates in the Sloan Digital Sky Survey

The Astrometry Satellite Gaia

Galaxy formation and evolution. Astro 850

A wide brown dwarf binary around a planet-host star

Jonckheere Double Star Photometry Part V: Cancer

The Stellar Low-Mass IMF: SDSS Observations of 15 Million M Dwarfs

Characterization of the exoplanet host stars. Exoplanets Properties of the host stars. Characterization of the exoplanet host stars

LSST: Comprehensive NEO detection, characterization, and orbits

Page # Astronomical Distances. Lecture 2. Astronomical Distances. Cosmic Distance Ladder. Distance Methods. Size of Earth

Stellar distances and velocities. ASTR320 Wednesday January 24, 2018

A Random Walk Through Astrometry

Exoplanetary transits as seen by Gaia

Galaxies. The majority of known galaxies fall into one of three major classes: spirals (78 %), ellipticals (18 %) and irregulars (4 %).

Image Processing in Astronomy: Current Practice & Challenges Going Forward

Outline. c.f. Zhao et al. 2006, ChJA&A, 6, 265. Stellar Abundance and Galactic Chemical Evolution through LAMOST Spectroscopic Survey

ROSAT Roentgen Satellite. Chandra X-ray Observatory

Lecture 12. November 20, 2018 Lab 6

MESSIER Unveiling galaxy formation

Transcription:

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 Astrometry in the Age of the Next Generation of Large Telescopes Flagstaff, Oct 17-20, 2004 1

SDSS Astrometric Data Quality 1. Pipeline astrom developed by USNO (Pier et al. 2003) 2. Dynamic range: 14 < V < 22.5, exposure 54 sec, 5 bands (ugriz) over 5 minutes 3. Absolute accuracy: < 50 mas 4. Relative band-to-band accuracy: 30 mas for sources not limited by photon statistics, and 100 mas at the survey limit 5. SDSS DR3: 141 million unique objects 2

3

4

Science Results Based on SDSS Astrometric Data 1. Solar System Objects: move during 5 minutes 2. Stellar Proper Motions: SDSS-POSS: 50 yrs baseline, g < 20, proper motion errors 3 mas/yr SDSS-SDSS: 5 yrs baseline, g < 22, proper motion errors 6 mas/yr 3. Stellar Parallaxes: 100 deg 2, out to 10 pc, advantage of faint flux limit 4. Optical identifications for sources detected at other wavelengths (FIRST, Chandra, 2MASS) 5

SDSS Asteroid Observations Moving objects in Solar System can be efficiently detected out to 20 AU even in a single scan: 5 minutes between the exposures in the r and g bands 6

Asteroids move during 5 minutes and thus appear to have peculiar colors. The images map the i-r-g filters to RGB. The data is taken in the order riuzg, i.e. GR B 7

SDSS Asteroid Observations Moving objects must be efficiently found to prevent the contamination of quasar candidates (and other objects with nonstellar colors) Detected as moving objects with a baseline of only 5 minutes The sample completeness is 90%, with a contamination of 3%, to a magnitudes fainter completeness limit than available before The velocity errors 2-10%, sufficient for recovery within a few weeks Accurate ( 0.02 mag) 5-band photometry SDSS Moving Object Catalog is public at www.sdss.org Detected 204,305 moving objects, 67,637 are identified with known objects in Bowell s catalog, 43,329 are unique 8

Asteroid Counts 9

Main SDSS Asteroid Results The size distribution for main-belt asteroids: measured to a significantly smaller size limit (< 1 km) than possible before, discovery of a change of slope at D 5 km, a smaller number of asteroids compared to previous work by a factor of 2 (N(D>1km) 0.75 million) Strong correlation between colors and position/dynamics: Confirmation of color gradient: rocky S-type in the inner belt vs. carbonaceous C type asteroids in the outer belt; dynamical families have distinctive colors; Colors are correlated with the family age: space weathering 10

COMPARISON OF ASTEROID SIZE DISTR IBUTION: OBSERVATIONS AND MODELS 10 12 Farinella et al. 92 (1) CUMULATIVE NUMBER > D 10 11 10 10 10 9 10 8 10 7 10 6 10 5 10 4 10 3 10 2 10 1 <---- Farinella et al. 92 (2) Farinella et al. 92 (3) Farinella et al. 92 (4) Galileo team Davis et al. 94 Durda et al 98. Model SAM99 Model SDSS 2001 SMALL SIZE BUMP <----- LARGE SIZE BUMP 10 0 10-2 10-1 10 0 10 1 10 2 10 3 D (km) The asteroid size distribution (Davis 2002, in Asteroids III). SDSS results: 1) Extended the observed range to 300m 2) Detected the second break at 5 km 11

The semi-major axis v. (proper) inclination for known asteroids from Bowell s catalog that were observed by SDSS 12

The semi-major axis v. (proper) inclination for known asteroids color-coded using measured SDSS colors 13

The osculating inclination vs. semi-major axis diagram. 14

What is the meaning of different color shades? Chemistry, of course, for the gross differences (red vs. blue), but what about different shades of red? 15

0.65 Eunomia 0.6 0.55 Rafita Maria 0.5 Brangane Gefion Massalia Koronis Colour 0.45 0.4 0.35 Karin Agnia Merxia Eos Solar System 0.3 Iannini 0.25 7 10 8 10 9 10 10 10 Age (Years) 16

What is the meaning of different color shades? Chemistry, of course, for the gross differences (red vs. blue) Within a given chemical class, colors also depend on age: SDSS colors can be used to date asteroids 17

18

Prospects for Proper Motion Studies SDSS-POSS proper motions limited by the POSS astrometric accuracy (0.15 arcsec) resulting in proper motion accuracy of 3 mas/yr; usable to g 20 (recalibrated POSS astrometry by Munn et al.) SDSS-SDSS proper motions with 5 years baseline accurate to 6 mas/yr (using only 2 epochs); usable to g 22 SDSS-LSST proper motions will be limited by the SDSS astrometric accuracy ( 30 mas): with 15 years baseline accurate to 2 mas/yr This is >100 times more sensitive than Luyten s catalog (a standard resource for proper motion studies)! SDSS (and especially LSST) may revolutionize proper motion based studies of the Galactic structure (2 mas/yr corresponds to 10 km/s at 1 kpc)! 19

14 15 2 16 17 1 18 19 20 0 21 0 1 2 3 0 1 2 3 14 15 2 16 17 1 18 19 20 0 21 0 1 2 3 0 1 2 3 20

Tangential Velocity Distributions for M dwarfs (D<1 kpc) Top row: l=0, b 45, v l and v b for D=300 pc Middle row: l=90, b 45, v l for D=300 pc and D=800 pc Bottom row: l=180, D=300 pc, v l for b 45 and b -45 Note strong non-gaussianity: asymmetric drift The main advantage of SDSS- POSS sample: probes larger distances than possible before, accurate distance estimates, large number of sources: enormous amount of detailed information! 21

Thick Disk vs. Halo Velocity Distributions Top: v b, bottom: v l Turn-off stars selected in r vs. g r color diagram: black Further separated by u g color (metallicity proxy) into halo (blue) and thick disk (red) stars Note the strong lag Note strong non-gaussianity: asymmetric drift The main advantage of SDSS- POSS sample: probes larger distances than possible before, accurate distance estimates, large number of sources: enormous amount of detailed information! 22

Conclusions It s good to have accurate astrometry for a lot of faint sources across a large chunk of the sky. 23

Conclusions It s good to have accurate astrometry for a lot of faint sources across a large chunk of the sky. Especially when accurate multi-band photometry is also available. 24

Conclusions It s good to have accurate astrometry for a lot of faint sources across a large chunk of the sky. Especially when accurate multi-band photometry is also available. And radial velocities, and variability information, and... 25