Actionable Intelligence from Multisourced Events Roy Williams Caltech with S.G.Djorgovski, C. Donalek, A. Drake, M. Graham, A. Mahabal, R. Seaman (NOAO).

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Presentation transcript:

Actionable Intelligence from Multisourced Events Roy Williams Caltech with S.G.Djorgovski, C. Donalek, A. Drake, M. Graham, A. Mahabal, R. Seaman (NOAO).

VOEvent VORapid Skyalert Infrastructure Decision = Human + Archive + Machine please pray for VAO

What is VOEvent XML document according to VO-standard Who, Wherewhen, Why, Params Each event belongs to a Stream –key-value-semantic records Author, Subscriber, Broker functions Information not Imperative Follow-ups are other VOEvents Connected in citation graph to form Portfolio

Microlensing event (OGLE)

Global Event Authors and Followup Caltech eStar Exeter NOAO Tucson Pairitel Berkeley Palomar P60 Caltech Catalina RTS UAriz Liverpool Telescope La Palma UKIRT Hawaii Stream Author Publisher Repository Relay Followup Subscriber Faulkes Hawaii/Australia OGLE III Poland NASA/GSFC SWIFT Fermi Integral AGILE CTIO/KPNO LCOGT MOA AAVSO PannSTARRS

VORapid Virtual Observatory Rapid Transients Facility Content –VOEvent –Consume Browse, Query, Subscribe, Decision –Author Streams, Alerts, Automation –Portfolio Annotation, Mining –Brokering Transport –Tier 1 –Broker, Forward –Tier 2 –Applications please pray for VAO

Tier1 and Tier2 Event Nodes Tier1: Immediate forwarding, standard & capable protocols Tier2: Subscription service, Repository, Query, Archive, Machine Learning, etc etc Broker (Tier1) Author (Tier2) Repository (Tier2) Jabber/XMPP or custom TCP? please pray for VAO

Microlensing Optical transients Radio transients X-ray transients Gamma transients Grav. waves Neutrinos Followup Scheduler Telescope Astronomers Amateurs Students Telescope Event AuthorsEvent Subscribers International GCN Broker Annotation from archives Events and annotation disseminated to subscribers in real time with intelligence skyalert.org

Stream as Event Template Taming Multisourced Data streamevent made by person in daytime made by robot system at night skyalert.org

Future.... ASKAP, IceCube LIGO/Virgo, MWA, SkyMapper, Veritas TeV secondary streams skyalert.org

Portfolio of One First Discovery VOEvent skyalert.org

Ground based telescop e Hubble WFPC2 DSS 1967 Astronomer’ s Telegram Lightcurve Spectru m Discovery Image Rich portfolio: Supernova 2007sr in Antennae skyalert.org

SDSS archive uMag gMag uCutoutURL gCutoutURL Catalina Sky Survey mag1 mag2 mag3 asteroidness stellarity cutoutURL Berkeley lightcurves lightcurveURL probSN probCV Palomar 60” follow-up gmag rmag ipmag zpmag datapackageURL % 97% % 12% Streams (event template) Events (template instance) Annotation (linked data) Original detection Archive follow-up Telescope follow-up joint rule Triggers (for action) subscribers Event-Action-Event Cycle

Google Sky has VOEvents skyalert.org Thanks to Ryan Scranton

WWT Realtime Event Display skyalert.org Thanks to Jonathan Fay

Bayesian Learning Feature Vectors Best Recommendation Combine with Human judgment Error bars, upper limits, and missing values All are part of the prior Summing opinions of multiple experts Some not experts! Relevance Vector Machine Best of training set (most learning) Tutorial Escalation to real expert

Building Feature Vector Mahabal et al arXiv: [astro-ph]

Recommendation for Follow-Up Sparse data  Ambiguous classification  best follow-up strategy to reduce confusion Example: optical light curve with a particular time cadence would discriminate between a Supernova and a quasar, Example: particular color measurement would discriminate between a cataclysmic variable eruption and a gravitational microlensing event, Mahabal et al arXiv: [astro-ph]

Human Volunteers Science Layer –Describe what you see in image –Each person has level of expertise –How to use data most effectively Game Layer –Makes people come back –Top 10 ranking etc –Anonymous partner a la gwap.com

Human Computing Ask humans to *describe* –not *interpret*

Automated Decision through Tripod of Data Archive nearby radio source escalates p(blazar) nearby galaxy escalates p(supernova) Human Crowded field? Artifact present? Can make follow-up observation Machine Fuzzy center escalates p(host galaxy) Moving source escalates p(asteroid) Bobotic follow-up observation decision human machine learning archive

Please try skyalert.org register, then set an alert Do you have a stream of astronomical events? (and can I have them) Who knows how to make a scalable push network? (can we talk?) skyalert.org