The SuperCLASS Weak Lensing

Deep Field Survey

Ian Harrison on behalf of the SuperCLASS collaboration

AASTCS 2: Exascale Radio Astronomy

4 April 2014

1. Introduction to Weak Lensing

2. Radio Weak Lensingi. Promises and challenges

ii. Shape measurement with radio data

3. SuperCLASS Surveyi. Description and status

SuperCLuster Assisted Shear Survey

Overview/Contents

Pathfinder for weak lensing cosmologywith the SKA

using UK e-Merlin

• 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

Weak Lensing as a Cosmological Probe

WL

Dark Energy Task Force FoM

• 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

Requirements

• 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

Optical Systematics

Weak Lensing as a Cosmological Probe

Systematics – How bad? Bad…

• 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

Control of Systematics

Chang, Refregier, Helfand (2004)

•VLA FIRST data– 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– 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

Current Status

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 best-

fitting coefficients

• Can estimate shear from combination of coefficients

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

The Promise of Radio Weak Lensing

Current Status

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

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

The Promise of Radio Weak Lensing

Current Status

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

• 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

The Promise of Radio Weak Lensing

Challenges of Radio Shape MeasurementImage Plane

Only fit one object at a timeOptical algorithms can be easily leveraged×Correlated noise×Need to create image with no spurious shear from deconvolution!

• Is a big challenge in itself…

UV PlaneDoes 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

• 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 Radio GREAT Challenge

(Gravitational lEnsing Accuracy Test)

=> A GREAT Challenge for radio data

(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/

A Radio GREAT Challenge

Plans

SuperCLASS

e-Merlin legacy survey

Pathfinder for radio weak lensing with the SKA

• 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

Goals

• 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

The Survey

Richard Battye (PI)Michael BrownNeal JacksonIan BrowneSimon GarringtonPaddy LeahyPeter WilkinsonAnita RichardsScott KayRob BeswickTom MuxloweSarah BridleLee WhittakerConstantinos DemetroullasIan HarrisonRafal Szepietowski

Filipe Abdalla

David BaconBob Nichol

Anna ScaifeChris Riseley

Ian Smail

Mark Birkinshaw

Meghan Gray

Steve MyersChris Hales

Caitlin Casey

Torsten EnsslinMike Bell

Hung Chao-Ling

30 People11 Institutions3 Countries

SuperCLASS Collaboration

• What it does:– Loading & sorting– Averaging– Concatenating– Flagging– Diagnostic plotting– Calibration (with caveats)

• What it doesn’t (yet) do:– Perfect calibration– Spectral line mode– Multiple source/phcal pairs– Wide-field imaging– Publication-quality images

SuperCLASS

e-Merlin Pipeline

• Currently uses standard e-Merlin data reduction pipeline(Argo et al, in prep)

• Requires ParselTongue, AIPS, Obit

(from Megan Argo)

Merlin data

manual reduction

e-Merlin data

one button reduction

SuperCLASS

e-Merlin Pipeline

(from Megan Argo)

SuperCLASS

RFI Mitigation

• 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

SuperCLASS

Current Status

(from Neal Jackson)

SuperCLASS

Projected Performance

• Expect up to 10σ detection of shear from each cluster• Lower limit should be ~6.6σ

– Expected across a whole randomly chosen field

(Brown & Battye 2011)

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 super-clusters

• Dynamic state of ICM• Strong lenses

SuperCLASS

Additional Data and Science

• 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

SuperCLASS

Summary