LSST Alert Management VOEvent Meeting Tucson, AZ December 5-6, 2005 Robyn Allsman,LSSTC/NOAO Maria Nieto-Santisteban, JHU Ray Plante, NCSA Tim Axelrod,

LSST Alert Management

VOEvent MeetingTucson, AZ

December 5-6, 2005

Robyn Allsman,LSSTC/NOAOMaria Nieto-Santisteban, JHU

Ray Plante, NCSATim Axelrod, LSSTC/Steward Observatory

VOEvent Meeting

December 5-6, 2005 Tucson, AZ

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LSST Alert Management

• Data Pipeline• Detectable Transients• Alert and Notification Categories• Nomenclature• Triggers and Notification• LSST VOEvent Contents• LSST Alerts and the VOEvent Specification

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Applications Layer - Scope

Data Acquisition

Infrastructure

2.5.1.1.1 Image

ProcessingPipeline

2.5.1.1.2 Detection

Pipeline

2.5.1.1.3Association

Pipeline

2.5.1.1.7Image

Archive

2.5.1.1.9SourceCatalog

2.5.1.1.10ObjectCatalog

2.5.1.1.11Alert

Archive

2.5.1.2.3Deep Detect

Pipeline

2.5.1.2.4DeepObjectCatalog

VO Compliant Interface Middleware

2.5.1.2.2Classification

Pipeline

2.5.1.1.4Moving Object

Pipeline

2.5.1.2.1Calibration

Pipeline

2.5.1.2.5End User

Tools

2.5.1.1.5Alert

Processing

2.5.1.1.8Eng/Fac Data

Archive

2.5.1.1.x “Nightly” at Base Facility and Archive Center

2.5.1.2.x “Archive” Periodically at Archive Center Only

2.5.1.1.6Common Pipeline

Components

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Data Pipeline Functions

• Image Processing Pipeline is responsible for producing– Calibrated science images

• Astrometric calibration (WCS)• Photometric calibration

– Subtracted images– Stacked images

• Detection Pipeline is responsible for producing– The Source Catalog, which contains parameters of all sources

found in an image: location, brightness, shape

• Association Pipeline is responsible for associating sources found at different times and (sometimes) locations, producing– The Object Catalog, which contains parameters of all astronomical

objects: lightcurves, colors, proper motions, …

• Object Classifier, design TBD, is responsible for periodically (re)classifying all objects in the Object Catalog

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Detectable Astrophysical Transients

• We are limited mostly by– Time sampling– Photometric accuracy (goal is 1%)

• We will not see (for example)– Low amplitude pulsating WD's (photometry)– Exoplanet transits (photometry and time sampling)– Microlensing caustic crossing events (time sampling)

• We will see– Many classes of periodic variables with amplitude > 1%– Many microlensing events– Novae– SNe, QSO's, …– As well as “middle of nowhere” transients (eg transients

found by DLS)

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Classification of Events

• The LSST data pipeline will attempt to classify variable objects based on– Position in CMD– Lightcurve shape– Motion, and orbital elements, if applicable

• The classifier pipeline will play a key role in identifying “events”– If the object is already in the catalog, an event occurs relative

to the object's previous behavior (an event is not simply a change in flux)

– Not so useful for new objects, but still possible to locate in CMD

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Transient Rates

• Astrophysical rates - stars– Roughly 5% of stars are variable at the 1% level or more– A typical LSST image contains roughly 2.5e5 stars– Rate from typical images are 1e7 per night– An exceptional LSST image (LMC, bulge) contains up to 4e6

stars

• Astrophysical rates – extragalactic supernovae– SN rate about 1 / 200 yr / galaxy– Changing flux from each visible for at least 30 d– A typical LSST (unstacked) image contains roughly 4e5

galaxies– Rate is about 1e5 per night

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Dealing With High Event Rates

• LSST will detect transients at rate of O(1e5 – 1e6 / night)– No group of humans can look at these individually– No followup facility can look at more than a negligible

fraction– We need to filter these by a large factor to make them useful

• Excluding known variable objects results in the biggest reduction – but still leaves large noise rate

• Noise rates can be reduced by simply increasing the detection threshold – but at the cost of missing real information

• We need to carefully consider use cases, and make use of simulations, to find a way forward

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How can a customer specify an interesting class of event?

• An “Event” is more than a change in flux– “Notify me of all Cepheids that change period by more than

5%”– “Notify me of all transients > 5σ with no corresponding

catalogued object”– “Notify me of any newly discovered solar system object with

a > 15AU and confidence > 0.9”

• We need a flexible semantics for event filters– SQL query on the object catalog is not quite enough(?)– Need to include temporal logic so that past behavior can be

referenced(?)

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Alert and Notification Categories

• Micro-change alerts– Triggered by small changes in flux

– Could swamp pipeline and network if used indiscriminately

• Restricted to, and for, approved science missions

• Restricted to tightly bounded regions

– Example: trying to capture pre-SN conditions

• Baseline change alerts– Triggered by an exceptional change

• Thresholds set to minimize false positive alerts

– Example: change in flux; change in position

• Data product change alerts– Triggered by addition or, possibly, refinement in data product

– Example: new image in area of interest, new/re- classification

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Nomenclature

• Author (aka Pipelines) generates alerts and provides them to Event Repository

• Event Repository Service (aka Producer) provides alerts to Distribution Service

• Distribution Service – Queries Event Repository Service for alerts satisfying a

Notification Request and forwards them to requestorOR receives alerts from Events Repository Service, determines

matching Requests for Notification and then forwards….– Queries Data Products Repository for DPChanges corresponding

to a Notification Request and forwards them to requestor

• Subscription Service receives and validates User Requests for Notification

• Request for Notification defines the user’s constraints on when to be notified of a trigger-able event, and delivery mechanism.

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Alert and Notification Scenario

Subscription Service

Author(Pipelines)

Distribution Service

Event Repository Service

Data Products Repository

Service

EventRepository

DataProducts

Repository

Insider’s Backdoor to Thresholds

NotificationConstraints

TriggerThresholds

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Triggers

• Micro-change and Baseline Trigger-able events– are determined solely by the Project

• Baseline trigger thresholds – are determined by the Project

• Micro-change trigger thresholds – are determined by privileged Subscribers

• Data Product Change notification – is harvested from the Data Products Repository– is expected to be periodic, not real-time

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Triggers and Notification

• Author (Pipeline) defines suite of allowable constraints– when registering the alert service at the VORegistry

• Subscription service uses that info – when validating a new subscription request

• Distribution service uses that info – when determining who should receive an alert

• Distribution Service queries – Event Repository for micro-change & baseline alerts– DP Archive for data product alerts

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LSST VO Event contents

• Who, Where/When• Trigger Type• Additional data depending on Trigger Type

– e.g. flux, flux change; trajectory, anticipated trajectory

• LSST Object Id• Previous Object Classification, if one exists• Reference Links to

– LSST VO Event web page– LSST Object web page – for on-the-fly generation of:

• Image cut-out• Lightcurve• Cone search centered on object• Attributes

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LSST Alerts and the VO Event Spec

We want to leverage on VO Event Development• What we will support

– Alert generation and archiving– Threading of VOEvents on an Object– Authenticated subscription for backdoor threshold criteria

• What we don’t currently see as necessary– Retractions –if we make a major error, would probably use

an IAU Circular or equivalent

• What we hope to be provided by VO Open Software Consortium by 2010– Subscription Service– Distribution Service

Documents

LSST Alert Management VOEvent Meeting Tucson, AZ December 5-6, 2005 Robyn Allsman,LSSTC/NOAO Maria Nieto-Santisteban, JHU Ray Plante, NCSA Tim Axelrod,