Transcript 503.02_Harrison

The SuperCLASS Weak Lensing
Deep Field Survey
Ian Harrison on behalf of the SuperCLASS collaboration
AASTCS 2: Exascale Radio Astronomy
4 April 2014
SuperCLuster Assisted Shear Survey
Overview/Contents
Pathfinder for weak lensing cosmology
with the SKA
using UK e-Merlin
1. Introduction to Weak Lensing
2. Radio Weak Lensing
i.
ii.
Promises and challenges
Shape measurement with radio data
3. SuperCLASS Survey
i.
Description and status
Weak Lensing as a Cosmological Probe
• Coherent distortion of
background sources
– …by baryonic and dark
matter
• Measure integrated mass
on line of sight between
us and source
• Traces evolution of dark
matter structures
Weak Lensing as a Cosmological Probe
• Track Dark Energy
equation of state and how
it evolves with time
• Learn about DE physical
nature
– Cosmological constant?
– Scalar field?
– Modifications to GR?
• Weak Lensing can be the
best probe of Dark
Energy
Dark Energy
Task Force
FoM
WL
Weak Lensing as a Cosmological Probe
Requirements
• Large numbers of resolved background galaxies
– Beat down random shape noise
• ‘Exquisitely’ precise/accurate measurement of ellipticities
~1% level for detection
~0.01% level for 1% constraint on DE equation of state
Systematics are key!
Weak Lensing as a Cosmological Probe
Optical Systematics
• Point-Spread-Function errors
– Uncertainty in telescope, seeing
– …even in space
• Intrinsic alignments
– Galaxy ellipticities/orientations not random due to
sharing of LSS environment
• Redshift uncertainties
– Photo-zs can put sources in wrong tomographic bin
Weak Lensing as a Cosmological Probe
Systematics – How bad? Bad…
The Promise of Radio Weak Lensing
Control of Systematics
• PSF Errors
– Radio interferometer beams are (in principle)
• Precisely known
• Highly deterministic
• Intrinsic alignments (Brown & Battye 2011)
– Radio polarisation information tells about intrinsic alignment
• Polarisation angle unchanged by gravitational lensing
• Redshift uncertainties
– Large 21cm line surveys give spec-z for sources
• Cross Correlations
– Euclid comparable, similar timescale to SKA
The Promise of Radio Weak Lensing
Current Status
Chang, Refregier, Helfand
(2004)
•VLA FIRST data
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5 arcsec resolution
1 mJy depth
104 deg2
~20 sources deg-2
~20,000 source
•3σ detection of cosmic
shear
•Measure shapes in UV
plane
Patel et al (2010)
•Merlin+VLA data
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0.4 arcsec resolution
50 μJy depth
Only 70 arcmin2
~1-4 sources arcmin-2
~50-300 sources
•No detection of cosmic
shear
•Measure shapes in images
The Promise of Radio Weak Lensing
Measuring Ellipticities
• One method:
shapelets
• Model image using
truncated basis
– …or visibilities
– FT is just a phase factor
• Gives linear problem
– Easy to solve χ2 for bestfitting coefficients
• Can estimate shear from
combination of
coefficients
The Promise of Radio Weak Lensing
Current Status
Chang, Refregier, Helfand
(2004)
•Take source positions from
images
•Use Fourier-plane
shapelets to model
visibilities directly
•Model systematics with
simulations of delta-function
sources
•3σ detection
The Promise of Radio Weak Lensing
Current Status
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Patel et al (2010)
Use real-space shapelet
basis functions
Model sources in
reconstructed images
No shear signal
recovered
Also cross-correlate with
optical data (HDF-North)
– Find no correlation
The Promise of Radio Weak Lensing
Current Status
Patel et al (2013)
•Simulate e-Merlin and
LOFAR observations
•Known input ellipticities
– Noise free…
•Measure shear using
image plane shapelets
•Quantify accuracy of fit
εobs – εtrue = mεtrue + c
Amara & Refregier (2008) gives:
m < 0.05
c < 0.0075
For simulated survey to be
dominated by statistics, not
systematics
m < 0.001
c < 0.0002
for SKA
The Promise of Radio Weak Lensing
Challenges of Radio Shape Measurement
• Understanding of shape measurement algorithms for
radio data currently ‘not good’
• Only 1.5 methods have been tried
– On different datasets
• Are N potential shape measurement methods
– Which galaxy model?
• Physically motivated (e.g. Sersic)
• Image decomposition (e.g. Shapelets)
– Which data?
• UV
• Image
– Method space needs exploring
The Promise of Radio Weak Lensing
Challenges of Radio Shape Measurement
Image Plane
Only fit one object at a time
Optical algorithms can be easily
leveraged
×Correlated noise
×Need to create image with no
spurious shear from
deconvolution!
• Is a big challenge in
itself…
UV Plane
Does not require deconvolution
×Need to fit sources
simultaneously!
•
•
•
~5 parameters per source
~100 sources per FoV
~10n data points
×(Probably) still need to image to
source find
×Probably won’t have visibilities
any more
A Radio GREAT Challenge
(Gravitational lEnsing Accuracy Test)
• Understanding of shape measurement algorithms for
radio data currently ‘not good’
• Optical weak lensing community has gained much from
shape measurement challenges
– STEP, STEP2, GREAT08, GREAT10, GREAT3
– Simulate weak lensing data set
– Different algorithms compete to measure (blinded) shear in the
data with greatest fidelity
– Winners have come from non-astronomy backgrounds
=> A GREAT Challenge for radio data
A Radio GREAT Challenge
Plans
(Very simple) overview:
•Create sky model
•Simulate observation with a single pointing of a known antenna
configuration
•Provide entrants with
• Visibilities
• Fiducial image with quantified systematics due to deconvolution
Help and ideas welcome…
Sign up for updates!
jb.man.ac.uk/~harrison/
SuperCLASS
e-Merlin legacy survey
Pathfinder for radio weak lensing with the SKA
SuperCLASS
Goals
• Develop techniques for radio shear measurement
• Prove effectiveness of polarisation for mitigation of
intrinsic alignments
• Learn about source populations at μJy radio fluxes which
will be probed by SKA surveys
• Number densities
• Polarisation fraction and position angle scatter
• ~few % and rms 10-20 deg for local spirals (Stil et al 2009)
SuperCLASS
The Survey
• Specifications/performance
goals:
• 1.75 deg2
• 4μJy/beam flux rms
• L-band (1.4 GHz), 512MHz
bandwidth
• 0.2 arcsecond resolution
• 1-2 arcmin-2 source density
• Dense supercluster target
field
• Observing strategy:
• ~800 hours total
• 430 mosaic pointings
• ~20TB visibilities on disk
SuperCLASS Collaboration
Richard Battye (PI)
Michael Brown
Neal Jackson
Ian Browne
Simon Garrington
Paddy Leahy
Peter Wilkinson
Anita Richards
Scott Kay
Rob Beswick
Tom Muxlowe
Sarah Bridle
Lee Whittaker
Constantinos Demetroullas
Ian Harrison
Rafal Szepietowski
David Bacon
Bob Nichol
Steve Myers
Chris Hales
Anna Scaife
Chris Riseley
Ian Smail
Caitlin Casey
Mark Birkinshaw
Meghan Gray
Filipe Abdalla
Torsten Ensslin
Mike Bell
Hung Chao-Ling
30 People
11 Institutions
3 Countries
SuperCLASS
e-Merlin Pipeline
• Currently uses standard e-Merlin data reduction pipeline
(Argo et al, in prep)
• Requires ParselTongue, AIPS, Obit
• What it does:
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Loading & sorting
Averaging
Concatenating
Flagging
Diagnostic plotting
Calibration (with caveats)
• What it doesn’t (yet) do:
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Perfect calibration
Spectral line mode
Multiple source/phcal pairs
Wide-field imaging
Publication-quality images
(from Megan Argo)
SuperCLASS
e-Merlin Pipeline
Merlin data
manual reduction
e-Merlin data
one button reduction
(from Megan Argo)
SuperCLASS
RFI Mitigation
SERPent automated flagging of
RFI (Peck & Fenech 2013)
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Fully parallelised
Flags ~7GbCPU-1day-1
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Uses SumThreshold algorithm
(Offringa et al 2010)
Subset of visibilites thresholded
If above, flag to threshold level
SuperCLASS
Current Status
• Characterisation of
polarisation leakage
across field of view
– Appears to be stable in
time, position
– Calibratable
• Have observed initial 7
point mosaic
– ~12 hours total
– mJy sources visible in total
intensity
(from Neal Jackson)
SuperCLASS
Projected Performance
(Brown & Battye 2011)
• Expect up to 10σ detection of shear from each cluster
• Lower limit should be ~6.6σ
– Expected across a whole randomly chosen field
SuperCLASS
Additional Data and Science
Data
• LOFAR
– 120 – 180 MHz
• GMRT
– 325MHz
• JVLA (proposed)
– Short baselines
• Optical data from Subaru
SuprimeCam
– Photometric redshifts
Science
• Source populations at
μJy fluxes
• Magnetic fields in superclusters
• Dynamic state of ICM
• Strong lenses
SuperCLASS
Summary
• Radio weak lensing can do good cosmology
– Mitigates many systematics from optical surveys
• Deterministic beam
• Polarisation for intrinsic alignments (Brown & Battye 2011)
• Cross-correlations (Euclid comparable, on same timescale to SKA)
• …but will be difficult
– What are properties of sources?
– How will we do the shape measurement?
• radioGREAT challenge for shape measurement from
simulations jb.man.ac.uk/~harrison
• SuperCLASS providing real data to form a test bed