The new availability of wide-field images from Schmidt telescopes in the 1940's meant that astronomers no longer had to make educated guesses about where to look to find new and interesting phenomena but were now spoilt for choice. The advent of synoptic surveys presents more extreme opportunities; as an illustration, consider the SDSS which over the course of 5 years represents a factor of a million increase in information over previous surveys; however, the LSST (Large Sky Synoptic Telescope, Tyson (2002)) will amass a SDSS every 3 nights.
Although overviews of synoptic surveys are riddled with cliches concerning undiscovered countries and uncharted waters, the exploration of the temporal domain results in data sets that are not just more voluminous than before, but far richer and more complex (Paczynski 2001; Djorgovski et al. 2000). This presents challenges to all aspects of astronomy: data gathering, distribution, reduction, analysis, storage, archiving, dissemination and mining. VO technologies are being designed precisely to meet these types of challenges, but to use them requires changes in survey design philosophies.
The Palomar-QUEST survey is a major new survey being undertaken by Caltech, Yale, JPL and Indiana University employing the world's largest astronomical camera and the recently refurbished Oschin Schmidt telescope at Palomar to observe a third of the sky ( sq. deg. between ) a minimum of 8 times in 7 passbands to nominally twice the depth of SDSS.
The QUEST camera consists of 112 CCDs arranged in four filter strips. Each CCD has 2400 600 13m 13m pixels, giving a total of 161 10 pixels. At the prime focus of the Oschin Schmidt, QUEST covers a sky area of 4.6 3.6 (the effective area is sq. deg) and in a night can survey sq. deg. Two filter sets are used: Johnson and Gunn , with a doubling of Gunn to afford extra depth.
The data rate is 2.45MB/s and with a monthly average of 10 nights' observing, QUEST produces TB of data/month.
Some of the immediate science goals are searching for high redshift quasars, strong gravitational lensing, supernovae and GRBs, and near-Earth asteroids and trans-Neptunian objects. Obviously once there is a sufficient body of repeat observations, searching for new types of variable object and phenomena will play a dominant part; in particular, a rapid response mechanism to transients (see section 4) is planned.
As this survey is one of the first of the new breed of synoptic surveys, it is being used as a testbed for the VO technologies which will enable astronomers to exploit such surveys to the full. There are currently four areas of attention:
Different groups want to process the raw data in different ways to optimize the detection of specific types of object. Access requirements to the data are also either near real-time or delayed. Data distribution must be secure, fault tolerant (error checking, multiply redundant) and accountable (transaction logging).
The nature of the data is extremely well suited to parallelization, either on a multi-processor machine or in a more general distributed computing environment, e.g. an advanced highly CPU-intensive pipeline would be a suitable Grid-level application.
The identification of variable objects poses many problems:
Other federated data sets will be employed in the data analysis to assist identification, e.g. SDSS, DPOSS, 2MASS.
The deployment of QUEST as a federated data set needs to support both interactive and batch mode access. Access to data products also needs to be transparent to the access rights of different users: QUEST survey team, collaborators and the general astronomy community.
To illustrate how QUEST will make use of VO technologies in an integrated fashion, consider one of the pipeline systems under construction (see Fig. 1 for a cartoon depiction): this will produce real time (within four minutes of the data being taken) alerts of transient events (e.g. supernovae). The specific processes which need to mesh are:
Djorgovski, S. G. et al. 2001, in Virtual Observatories of the Future, ed. R. J. Brunner, S. G. Djorgovski & A. S. Szalay (ASP Conf. Ser. 225), 52
Paczynski, B. 2000, PASP, 112, 1281
Tyson, J. A. 2002, SPIE, 4836, 10