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The Large Synoptic Survey Telescope Project
Bob Mann
LSST:UK Project Leader
Wide-Field Astronomy Unit, Edinburgh

LSST basics

UK involvement in LSST

Operations Plans
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Computing Issues
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Large optical survey telescope to be located in Chile
 Ten year sky survey from 2022
 US-led: NSF + DoE (camera) plus foreign partners
 6.5m effective primary; 9.6 sq. deg FOV
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Étendue = mirror area x
camera field of view
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If étendue is large enough, can go
wide, deep and fast at same time
 Different kinds of analysis from the same dataset
 LSST will have a great impact across almost all of astronomy
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The LSST Science Book
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Contents:
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Introduction
LSST System Design
System Performance
Education and Public Outreach
The Solar System
Stellar Populations
Milky Way and Local Volume
Structure
The Transient and Variable Universe
Galaxies
Active Galactic Nuclei
Supernovae
Strong Lenses
Large-Scale Structure
Weak Lensing
Cosmological Physics
arXiv:0912.0201
LSST@Europe Meeting, Cambridge, UK September 9-12, 2013
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
LSST basics

UK involvement in LSST

Operations Plans

Computing Issues
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35/36 UK Astronomy Groups
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LSST:UK
Consortium
Defines the
programme
of work for…
Works on
behalf of…
LSST:UK Science Centre (LUSC)
Phase B:
Commissioning
Phase C:
Early Ops.
Phase D:
Standard Operations
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
UK
Phase A:
Development
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1 August 2014: start of construction project
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October 2019: telescope First Light
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October 2022: start of main survey
operations
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LUSC-DAC: UK Data Access Centre
LUSC-DEV: Software development towards (Level 3)
data analysis software
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Phase A proposal
 Baseline programme for 2015-2033: ~£32M [not DAC h/w]
 Initial funding (£17.7M):
▪ £15M contribution to LSST operations (“subscription”)
▪ 6 staff-years of LUSC-DAC staff effort + modest testbed h/w
▪ 16 staff-years of LUSC-DEV staff effort
 Phase A Project started on 1 July 2015
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
LSST basics

UK involvement in LSST

Operations Plans

Computing Issues
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Archive Site
Difference Imaging
Alerts within < 60 sec
Solar System orbits < 24h
106 alerts per night:
need “event broker”
at NCSA to filter these
Base Site
Summit Site
French Site
Archive Site
Processing Center
Data Release Production
All extant data included:
• per-visit images
• per-visit catalogues
• co-add images
• co-add catalogues
• Per-visit forced photom.
Data Access Center
Data Access and User Services
Base Site
Data Access Center
Data Access and User Services
Processing Center
Data Release Production
UK Site (?)
Data Access Center
Data Access and User Services
Summit Site
French Site
Archive Site
Processing Center
Data Release Production
Beyond requirements
Data Access Center
Data Access and User Services
of LSST project delivery:
• needed for much science
• mainly coordinated through
Science Collaborations
• some resources provided
• may be incorporated into L2
Base Site
Data Access Center
Data Access and User Services
Processing Center
Data Release Production
UK Site (?)
Data Access Center
Data Access and User Services
Summit Site

LSST basics

UK involvement in LSST

Operations Plans

Computing Issues
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Archive Site

Archive Sites
 Nightly difference
 NCSA
imaging: alerts
 Annual direct image
pipeline: data releases
 CCIN2p3 (Lyon)?
Data Access Centre
▪ Offering to take 50% load
▪ Valued at ~$900k/year
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Data Access Centres
 Ingest data releases
 NCSA
 Run Level 3 data
 Chile
analysis code
 UK?
 Others?
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Image files
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Databases
 ~38 billion distinct objects (24B gals, 14B stars)
observed ~1000 times ~38 trillion sources
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Nodes
connected
by xrootd
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Compute
LSST assume DAC will
need ~10% for Level3:
i.e. ~20-140 Tflops
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Two timescales for data ingest
 Every night – for event streams
 Once a year – for data releases
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Different types in different science areas
Examples
1. Classification of transients – time critical
2. Galactic archaeology – large, catalogue-based
3. Weak lensing – large, image-based
Different DACs may specialise in different types
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Different computing infrastructures
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UK computing issues centre on Level 3
 Currently no interest in IN2P3-like offer on pipeline
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Scale of Level 3 not well constrained
 Nor relationship between different DACs
 But clear requirements exceed current expertise
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DAC needs flexibility to support range of users
 Suggest virtualised or containerised environment
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LUSC-DEV: Algorithm development
 Using simulations and data from other surveys
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LUSC-DAC: Prototyping DAC operations
 Data ingest and query workload
 Supporting large-scale analyses of images & DBs(?)
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Quantitative requirements will become clear over
the next year or so
 Lessons from DES (Joe Zuntz) & Euclid (Keith Noddle)
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1 August 2014
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US agencies – NSF and DoE
 Construction: ~$640M
 Operations: ~$270M out of ~$370M
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International partners must contribute ~$100M
 Default model: ~$200k per P.I. inc. students/postdocs
 Plus extra ~10% for additional load on DAC system
or operate own DAC
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£15M set aside for operations contribution
£2.7M for Phase A programme (4 years)
 LUSC-DAC: six staff-years
▪ DAC testbed, Data Challenges, supporting LUSC-DEV
 LUSC-DEV: sixteen staff-years
▪ Weak lensing: simulations, PSF, deblending, Euclid synergy
▪ Milky Way: star/galaxy separation, tidal stream detection
▪ Transients: alert handling, classification, cadence optimis.
▪ Solar System: postage stamps, lightcurves
▪ Sensor characterisation: image analysis systematics
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Stream of ~106 events per night
 Most boring; need to find the interesting ones
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Cross-match with other source catalogues
Machine learning to attempt classification
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Time critical:
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 Schedule follow-up observations of interesting ones
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Need to run all night, every night
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Catalogue filtering
to reveal structures in
(colour,position) space
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Statistical manipulation of multi-PB databases
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Likely to be repeated with annual data releases
 Low signal/noise features…iterative?...visualisation?
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Measuring galaxy shapes very accurately
Systematics-limited: simulations to quantify
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May need to go back to image data
 If Level 2 pipeline image analysis not good enough
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Embarrassingly parallel, but large amounts of data
and even larger amounts of simulated data
 More details from Joe Zuntz
 Commonalities with Euclid weak lensing
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