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VAO: Archival follow-up and time series
Matthew J. Graham, Caltech/VAO
July 5, 2012Matthew J. Graham
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Time domain requirements
Stakeholder perspective:Many observed phenomena are short-livedScientific returns depend on:
detection timely and well-chosen follow-up
A system needs to:Fully process data as they stream from telescopesCompare with previous data from same region of skyReliably detect any changesClassify and prioritize detections for followup
July 5, 2012Matthew J. Graham
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VAO at the heart of the time domain
Identified early (2001) as prime arena for VO applications Two-track approach:
Transient events (VOEvent) (see Williams et al.) Publish, disseminate, and archive event notifications
Time series data Describe, represent and access from different archives Characterize Classify
Letter of cooperation with LSST Standards and mechanisms for distributing transient event notices Accessing LSST databases and images with VO-compliant
interfaces
July 5, 2012Matthew J. Graham
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Interoperable time series - I
Common set of data access protocols:
Common data formats: VOTable FITS CSV
Name Description
Simple Cone Search (SCS) Retrieve all objects within a region
Simple Image Access (SIA) Retrieve all images within a region
Simple Spectral Access (SSA) Retrieve all spectra within a region
Simple Line Access (SLA) Retrieve spectral line data
Simulations (SIMDAL) Retrieve simulations
Table Access (TAP) Retrieve tabular data
July 5, 2012Matthew J. Graham
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Interoperable time series - II
Common data models with pointer mechanism (Utype):VOEvent Describes observations of transient astronomical eventsWho, What, Where/When, How, Why
SpectralDescribes generalized spectrophotometric sequencesBasis for Spectrum, SED and TimeSeries DMs
TimeSeriesDescribes any observed or derived quantity that varies with time
Light curve (time series with one photometric band) Multi-band time series Time series with variable time sample bin sizes
Associated metadata such as period, target variability amplitude, and derived SNR
July 5, 2012Matthew J. Graham
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Data providers
CRTS HATNet
Kepler CoRoT
July 5, 2012Matthew J. Graham
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VAO Time Series Search Tool
July 5, 2012Matthew J. Graham
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Event and source cross-identification
VAO Cross-Comparison Tool Up to 1 million sources against common source catalogs
Constructing time histories from sets of individual observations Bayesian formalism (Budavari)
July 5, 2012Matthew J. Graham
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Synoptic surveys
Transitive set of associations for n sources from a set of m observations scales as O(nm2):
Master catalog with per night updates of associations Full revisions still needed periodically Schemes needed – spatial indexing not sufficient
Survey Sources Obs/source Associations
PQDR1 ~10 million ~15 ~4 billion
CRTS ~500 million ~250 ~20 trillion
Next gen Billions ~1000 > Quadrillions
July 5, 2012Matthew J. Graham
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Source characterization
Popular activity: Richards et al. (2011), Dubath et al. (2011), Shin et al. (2009),…
Variety of (fast) characterizing measures: Moments Flux ratios Shape ratios (e.g., fraction of curve below median) Variability indices (e.g., Stetson K, von Neumann, Abbé) Periodicity measures:
base frequencies + harmonics amplitudes and phases
Specific class indicators (e.g., quasar index) Wavelets Singular value decomposition Segmentation methods and pattern analysis Discretization (e.g., SAX, Persist)
Defines high-dimensional (representative) feature space Noisy, irregularly sampled data can lead to false features
July 5, 2012Matthew J. Graham
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Relevant features
Richards et al. 2011
July 5, 2012Matthew J. Graham
Sparsity and heterogeneity of available data make this a very challenging problem
Real-time vs. archival Decision trees:
Blazars, CVs and RR Lyrae: ~90% completeness, ~9% contamination
Probabilistic structure function 2D distribution of (Δm, Δt) for all possible epoch pairs >90% completeness
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Source classification
July 5, 2012Matthew J. Graham
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Summary
VAO is developing an interoperable framework to: connect partner providers of both data and analysis resources expose them as an integrated whole for wider community use
Community call for collaborative proposals: Access to data related to VAST (PI: T. Murphy) Access to databases of AAVSO (PI: M. Templeton)
Cooperative work with LSST Complementary efforts on real-time and archival
characterization and classification, particularly based around CRTS