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voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)
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Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

Mar 27, 2015

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Page 1: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

voeventnet.caltech.edu

VOEventNet

By Matthew J. Graham (Caltech)

Page 2: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

What is VOEventNet? Real-time astronomy with a rapid-response

telescope grid A peer-to-peer cyberinfrastructure to enable

rapid and federated observations of the dynamic night sky

A network of telescopes and computers working synergistically, under the watchful eye of humans, to find and study interesting astronomical events

A transportation of events to interested subscribers, automatically in seconds or minutes after discovery

Page 3: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

What is VOEventNet? $600k 3 year NSF-funded project

under the DDDAS (Dynamic Data-Driven Applications Systems) initiative involving Caltech, UC Berkeley and LANL

Personnel:

^

really

Roy Williams (PI)Joshua BloomGeorge DjorgovskiShri KulkarniThomas Vestrand

Matthew GrahamAshish MahabalAndrew DrakeDerek FoxPrzemek Wozniak

Page 4: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Event Synthesis Engine

Pairitel

Raptor

PQ next-daypipelines

catalog

Palomar-Quest

knownvariables

knownasteroids

SDSS2MASS

PQ Event Factory

remote archives

baselinesky

eStar

VOEventNet

GRBsatellites

VOEventdatabase

Palomar 60”

Architecture

Page 5: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Palomar-Quest Survey

Synoptic sky survey using the 48” Palomar Samuel Oschin Schmidt telescope and the 112-CCD, 161-Megapixel Quest II camera

Collaboration between Caltech, Yale/Indiana U., NCSA, and JPL; et al. VO compliance/standards built in from the start Two modes: drift scan with UBRI/rizz or multiple repeated snapshots in

one filter ~70GB of data/night 15000 deg2 observed a minimum of 8 times with baselines minutes to

years

Page 6: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

A 152 ft 20 ft mural produced for Griffith Observatory from PQ survey BRI images

A swath of 15.2 2.0 swath through the center of the Virgo cluster, sampled at 0.4 arcsec/pixel, giving a 136,800 18,000 pixel image

Computed at CACR using HyperAtlas and a custom data cleaning pipeline

Reproduced on 114 steel-backed porcellain plates, expected to last many decades

Will be seen by millions of visitors Associated website will include NVO outreach

Real PQ data: The Big Picture

Page 7: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

The Big Picture: detailThe Big Picture: detail

Page 8: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

The Big Picture:Tile C12 (M87)Zoom-in

The Big Picture: more detail

Page 9: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Transients in the Big Picture

Tile b07

740 Cantabia

Page 10: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Event Synthesis Engine

Pairitel

Raptor

PQ next-daypipelines

catalog

Palomar-Quest

knownvariables

knownasteroids

SDSS2MASS

PQ Event Factory

remote archives

baselinesky

eStar

VOEventNet

GRBsatellites

VOEventdatabase

Palomar 60”

Architecture

Page 11: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Palomar-Quest Event Factory Real-time pipeline to process raw data

streaming from telescope: Remove detector signatures including glitches

masquerading as transient events: meteors, airplanes, glints from satellites and junk, etc.

Apply basic photometric and astrometric calibration

Extract detected sources and measure attributes Compare with baseline data (catalogs/images) to

identify new, transient or highly variable sources Compare with dbs of known variables, asteroids,

etc.

Page 12: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Event Synthesis Engine

Pairitel

Raptor

PQ next-daypipelines

catalog

Palomar-Quest

knownvariables

knownasteroids

SDSS2MASS

PQ Event Factory

remote archives

baselinesky

eStar

VOEventNet

GRBsatellites

VOEventdatabase

Palomar 60”

Architecture

Page 13: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Event Synthesis Engine New input arrives from PQ/elsewhere:

Establish event “portfolio” to archive and federate all subsequent data and analysis

Send initial event notification to subscribers Launch query against external dbs via NVO

Classify and prioritize: Evaluate likelihood probabilities of event being

associated with possible astrophysical sources using machine learning techniques (‘Thinking Telescope’)

Evaluate urgency of desired follow-up Send out VOEvent

Page 14: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Event Synthesis Engine

Pairitel

Raptor

PQ next-daypipelines

catalog

Palomar-Quest

knownvariables

knownasteroids

SDSS2MASS

PQ Event Factory

remote archives

baselinesky

eStar

VOEventNet

GRBsatellites

VOEventdatabase

Palomar 60”

Architecture

Page 15: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

VOEventNet Communication Fabric Author Publisher (aggregator):

Stores packet and assigns identifier Distributes to subscribers based on pre-defined

criteria using one-way web services Two dbs - Caltech for PQ and Los Alamos for

Raptor - harvest each other Subscriber:

Gets event from publisher, evaluates it and causes scheduling in telescope observing queue or an archive search

Page 16: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Event Cycling An event can be injected back into the

same decision/classification engine that published it but supplemented with data from elsewhere

Events dynamically cycle through follow-up observation and computation (no humans in loop) with subscribers make judgments and adding value until convergence

Page 17: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Robotic Telescopes RAPTOR

Stereoscopic sky monitoring with follow-up ‘fovea’ telescope

PAIRITEL Meter-class IR follow-up

P60 Principal follow-up facility for PQ Events

eSTAR

Page 18: Voeventnet.caltech.edu VOEventNet By Matthew J. Graham (Caltech)

VOEvent II6 December 2005

Timeline Year one - proof-of-concept system

consisting of: Source of VOEvents A VOEvent store Basic event discriminator Robotic telescopic capable of responding

to VOEvent: P60 and Pairitel Year two - prototype system Year three - production system