Surveys | RAVE: The Radial Velocity Experiment

May 5, 2011

Editor’s note: The following was kindly submitted by Dr. Arnaud Siebert of the Centre de Donnés de Strasbourg (CDS) and the Observatoire Astronomique de Stasbourg. RAVE has just made public its third data release, as described in greater detail in a paper available on the arXiv, to appear in the Astrophysical Journal.

Heliocentric radial velocity of stars measured by RAVE projected on to the night sky. The smooth change in color (radial velocity) is due to the motion of the Sun around our galaxy.

The RAVE (RAdial Velocity Experiment) project is a multi-fiber spectroscopic survey of stars in the Milky Way using the 1.2-m UK Schmidt Telescope of the Anglo-Australian Observatory (AAO). The RAVE collaboration consists of researchers from over 20 institutions around the world and is coordinated by the Astrophysical Institute Potsdam.

As a southern hemisphere survey covering 20,000 square degrees of the sky, RAVE’s primary aim is to derive the radial velocity of stars from the observed spectra. Additional information is also derived such as effective temperature, surface gravity, metallicity, photometric parallax and elemental abundance data for the stars. The survey represents a giant leap forward in our understanding of our own Milky Way galaxy; with RAVE’s vast stellar kinematic database the structure, formation and evolution of our Galaxy can be studied.

Beginning in 2003, RAVE had obtained 465,000 observations of stars to the end of 2010. It is expected to run to the end of 2012. In April 2011 RAVE released its third catalog containing more than 80,000 radial velocity measurements and atmospheric parameters for nearly 40,000 stars. A full description of the project can be found on the RAVE project website.

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Posted by John Rachlin

Papers | Synthetic Milky Way Galaxies

January 24, 2011
Artist's conception of the Milky Way galaxy.

Image via Wikipedia

Future surveys such as the LSST and GAIA will create object catalogs of staggering size. But beyond such qualitative statements, how do astronomers anticipate the scientific return on these projects? To some extent, you can extrapolate on past surveys taking into account anticpated advances in instrumentation. “Survey X imaged to magnitude M over P percent of the sky. Survey X’ will image to magnitude M’ over P’ percent of the sky, therefore….” But there are really a great number of variables to consider. In order to anticipate the productivity and capabilities of future surveys, one approach is to generate synthetic astrometric catalogs based upon models for the density and distribution of stars throughout the galaxy. As explained in a recent paper by Bland-Hawthorn, Johnston, and Binney (“Galaxia: A Code to Generate a Synthetic Survey of the Milky Way“), such synthetic catalogs are useful for:

a. Interpreting observational data
b. Testing theories on which the models are based, and
c. Testing the capabilities of different instruments and for defining strategies to reduce measurement errors (BJB, 2011).

Using a program that the authors developed, known as Galaxia, the authors implemented a complex model of the “stellar content” of the Galaxy as a function of position, velocity, age, metallicity, and mass. Different components of the Milky Way (thin/thick disc, stellar halo, galactic bulge) are modeled separately.

A fragment of the complex model encoded within Galaxia

In order to consider how future surveys might perform, you also have to take into account factors such as extinction due to interstellar dust, which itself requires a 3D model for the distribution of dust in the galaxy. The figure below shows an impressive correlation with observations obtained between Hipparcos observations and those that would be anticipated based upon the models encoded within Galaxia.

1 Comment | astrometry, papers, surveys & catalogs, visualization | Permalink
Posted by John Rachlin

Surveys | GAIA: The micro-arcsecond era

September 6, 2010

I’ve been reading a number of papers lately about GAIA, a future spaced-based mission planned for launch in 2012.   The aim of GAIA is to make astrometric measurements of nearly one percent of the Milky Way’s stellar population, amounting to some 1 billion stars down to a visual magnitude of m=20.   Following up on the success of Hipparcos, the GAIA mission will achieve an extraordinary degree of precision, with stellar positions  measured to an accuracy of about 10-20 µ arc seconds in conjunction with radial velocity and parallax measurements.    Consider, the moon with a diameter of about 1700 km subtends an apparent angle of 30 arc minutes, so 10 μ asec is like pinpointing the position of a marble-sized object (1-2 cm) on the surface of the moon!    In comparison to Hipparcos, GAIA will be about 50 times more accurate and survey some 10,000 times more objects.

Artist Rendition of GAIA. Source:ESA

Astrometry has gotten short shrift over the years.   After all, it’s not going to produce the kinds of mind-blowing images that Hubble pumps out, and that have made the HST a cultural icon.    And efforts to catalog huge swaths of the Milky Way to such precision would seem to be an exercise in obsessive compulsion.   But by precisely measuring the position, motion, and distance of billions of stars, the GAIA mission will enable fundamentally new discoveries including:

  • New insights into the structure, dynamics, and evolution of the Milky Way.
  • A veritable factory for the discovery of tens of thousands of new exoplanets (at least!) and a half-million quasars.
  • An improved understanding of the nature and distribution of dark matter in our galaxy
  • Cataloging pulsating variables as  the result of repeated measurements over it’s five year mission, enabling new statistical studies of variable stars.

The opportunities for data mining and in silico discovery abound.   In a status update from a couple of years back, S. Jordan of the Astronomisches Rechen-Institut, Zentrum für Astronomie, Heidelberg, German (see references below) writes of the computational challenges:

The total raw data volume is estimated to be of the order of 100TB, the total amount of processed and archived data is of the order of 1 PB.  Current estimated [sic] for the computational volume is 1.5.1021 floating-point operations, but this may actually be a lower limit and will probably increase due to the correction tasks for the radiation-induced CCD damages. If the processing of one star (with typically 1000 measurement per star) would need 1 second, 30 years of the data analysis would be needed. However, with massively distributed computation and the faster computers of the time of Gaia’s data analysis, this task will be feasible.

And it is the end-product of this data analysis that promises to be stunning – producing in effect a kind of movie of the Milky Way.    So while GAIA may not immediately return the kinds of images that HST has become famous for, it’s data will be no less beautiful, and its value to astronomical research no less important.

References:

GAIA Homepage

P.T. de Zeeuw (2002). Into the future with GAIA.

S. Jordan (2008).  The Gaia Project – technique, performance, and status.

A. Brown (2008). Getting ready for the micro-arcsecond era.

M. A. Strauss et al. (2009).  Wide-Field Astronomical Surveys in the Next Decade: A White Paper for Astro2010.

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Posted by John Rachlin

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