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Exploration of the Time Domain. S. G. Djorgovski VOEvent Workshop, CACR, Caltech, April 2005. Overview. Scientific motivation and opportunity A poorly explored portion of the observable parameter space A range of exciting astrophysical phenomena Possibility of fundamental new discoveries - PowerPoint PPT Presentation
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Exploration of the Time Domain
S. G. Djorgovski
VOEvent Workshop,CACR, Caltech, April 2005
Overview• Scientific motivation and opportunity
– A poorly explored portion of the observable parameter space
– A range of exciting astrophysical phenomena– Possibility of fundamental new discoveries– Technological advances and synoptic surveys
• Pilot project using DPOSS plate overlaps– A rich phenomenology of the time-variable sky
• Palomar-Quest: status and plans• Some challenges ahead
Exploration of the Time DomainThings that go bang! in the night… New and old.
Megaflares on normal stars Optical transients
Synoptic sky surveys will require a real-time mining of massive data streams and multi-PB archives
Exploration of the Time DomainThings that move…
Sedna
QuauarM. Brown et al.
NEAT
Tunguska
A Systematic Search for Transients and Highly Variable Objects Using DPOSS Plate Overlaps
~ 1.5 O overlaps between adjacent plates ~ 40% of the total survey area
Effective Area Coverage in a “Snapshot” Survey:
If texp < tburst and baseline ∆t >> tburst , then
Effective Area = Useful Area Npasses Nfilters
For DPOSS: ~ 15,000 deg2 0.4 2 3 ~ 0.9 Sky
B. Granett, A. Mahabal, S.G. Djorgovski,and the DPOSS Team
Baselines from days to ~ 10 yrs, typical ~ 2-4 yrsTypical limiting mags r ~ 20, using 3 bandpasses (JFN gri)
Plate Flaw Transient
Variable Source
Types ofDetections
Preliminary Spectroscopic Follow-Up (34 sources)
SpectroscopicSource Identifications:
35% QSOs (1/2 radio loud)18% CVs18% M dwarfs 6% Earlier type stars23% Unidentified (likely BL Lacs?)
Examples of DPOSS Transients
Examples of DPOSS Transients
flaw
asteroid
DPOSS Pilot Project Conclusions:• Faint, variable sky has a very rich phenomenology
– Spectroscopic follow-up will be a key bottleneck for any synoptic sky surveys
• Most high-amplitude variable sources down to ~ 20 mag are QSOs (Blazars, OVVs…), CVs, and flaring late-type dwarfs, with some early-type stars
• Asteroids may be a significant contaminant in a search for transients
• We find many more transients (~ 103/Sky) than expected from current models for orphan afterglows.– Most of them are probably QSOs, CVs, flaring stars, and
distant SNe; some may well be afterglows; and some may be new types of phenomena
• The Palomar-Quest survey should provide a major new venue for the exploration of the time domain
The Palomar-Quest Digital Sky Survey• The Palomar-Quest Consortium: Caltech - Yale - JPL• 50% point&shoot (NEAT, M.Brown), 50% drift scan (PQ survey)• PQ survey: a fully digital successor to the historic Palomar sky
surveys; a Caltech-JPL-Yale-NCSA-… collaboration• Data rate ~ 1 TB/month; ~100 TB total; many scientific uses• VO connections and standards built in from the start; a testbed for
many new IT/ VO applications
The PQ Survey: A new, digital, synoptic sky survey using the Quest-2 112-CCD camera
at the Palomar 48” Samuel Oschin telescope• A collaboration between Caltech, Yale/Indiana U., and
NCSA/UIUC; plus collaborations with other groups (INAOE, LBL, JPL…); started in summer of 2003
• About 50% of the telescope time, driftscan mode• Now next-day (or month… processing real-time• NVO connections and standards built in from start• Repeated observations, time baselines minutes to years• A science and technology precursor/testbed for
the LSST and other major synoptic sky surveys in the future
PQ Survey Sky Coverage• Range -25°< < +30°, excluding the Galactic plane• Ultimately cover ~ 14,000 - 15,000 deg2
• Rate ~ 500 deg2/night in 4 bands• As of Jan’05, covered ~ 13,000 deg2 in UBRI, of which
~ 11,000 deg2 at least twice, and ~ 4,700 deg2 at least 4 times; and ~ 14,100 deg2 in rizz, of which ~ 11,600 deg2
at least twice, and ~ 4,200 deg2 at least 4 times
The PQ Survey Science• Large QSO and gravitational lens survey
– Tests of the concordance cosmology– Dark mattter distribution– AGN physics and evolution
• High-redshift (z ~ 4 - 6.5) QSO survey– Probes of reionization and early structure formation
• Exploring the time domain– Supernovae, GRBs, AGN, var. stars, optical transients– Surprizes and new phenomena?– Time baselines ranging from minutes (inter-CCD) to days,
months, years (repeat scans) to decades (cross-match to DPOSS, SDSS, etc.)
• Galactic structure and stellar astrophysics• Etc. etc. - think what it can do for you
Palomar-Quest Data FlowImage
ArchiveCatalogs Archive
Master ArchivePipeline Data
Proc.Target
Selection
CIT
Yale
NCSA
JPL
LBL SNF
SDSC
P48
CITData
BrokerP200
Follow-up
PQ Survey: Recent and Upcoming Developments
• Completely redoing the DRP at Caltech– Much (much!) better data cleaning– Image remapping to a standard pixel grid, to enable
image coaddition and subtraction• Using the HyperAtlas technology for this• Using some TeraGrid resources
– Yet to come: better object detection, classification• Next: A real-time DRP for discovery of transents
and moving objects (collaborate w. JPL, M. Brown)
Improved Cleaning
of PQ Data
Improved Depth in PQ Image Coadds
PQ SDSS
A Search for Low-z Supernovae
• Calibration of the SN Ia Hubble diagram• New standard candles from SN II• Endpoints of massive star evolution
C. Baltay, R. Ellis, A. Gal-Yam, S.R. Kulkarni, and the LBL SNF
(Using the image subtraction technique)
Optical Transients and Asteroids
(Exploratory work; A. Mahabal, with P. Kollipara, a Caltech undergrad)
CITData
Broker
JPLNEAT
Archive
VariablesArchive
MasterArchive
ImageArchive
Yale
AlertDecisionEngine
SourceClassification
Engine
KnownVariablesChecker
AsteroidSeparatorEngine
CITFast
Pipeline
CIT Next-Day Pipeline
NCSA
Other?LBL SNF
Website
P48
BroadcastAlert
Off-site Archives
NVO / Multi-Off-site Archives
Palomar-Quest Real-Time TransientsDiscovery System Data Flow
ComparisonEngine:
Vars./Trans.Detector
Some Challenges Ahead• Automated, reliable, adaptive data cleaning
• High volume data generators lots of glitches• Cutting-edge systems poor stability
• High completeness / Low contamination• Must work with “solar system people” - moving
objects are the major contaminant for extra-solar-system variables and transients (and vice versa?)
• Automated, reliable event classification and alert decisions (need Machine Learning methods)– Sparse data from the event originator; folding in
heterogeneous external data; VO connections; etc.