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The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

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Page 1: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

The Haystack SKA/LOFAR Performance Simulator

Feb 13, 2004

Ramesh Bhat

MIT/Haystack

Page 2: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Cast of Characters

Shep DoelemanColin LonsdaleRoger CappalloRamesh Bhat

Joanne AttridgeDivya Oberoi

With contributions from

Gary Bust (ARL/U. Texas)Tanja Bode (REU, Cornell)Laurel Ruhlen (REU, MIT)

Page 3: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Goals of Haystack Simulator• Create datasets with SKA/LOFAR properties

– Large scope (baseline range, station numbers, …)– Generality of array and observation specification – Time-variable station beams– Atmospheric/ionospheric structure across FoV– Densely populated sky– Sources in station sidelobes

• Search design parameter space efficiently– Sophisticated, script-driven automation– Figures of merit for performance assessment

• Testing Calibration and Post-processing• Science Applications (e.g. EOR)

Page 4: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Functional Flow Diagram

array skies obs_specproc_spec

configgenerator

Listsimages

Script driven Simulator Module

sites

(u,v) FITS

MIRIADPSF StatsImagingFidelity

Calibration“ground truth”data

ionosphere

Page 5: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Architecture

Kernel of visibility generation:

Transform arbitrary sky to perfect “reference” uv grid

For each baseline

For each time

For each frequency channelCopy relevant piece of uv gridConvolve with station beam and atmosphere/ionosphere functionsPrecision numerical integration over correlation cellAdd noise, simple RFI …

Write output uv data file

Page 6: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Simulator Status• Includes

– FITS Image import– Variable station beams– Thermal Noise (Rx)– Arbitrary array configuration.– Arbitrary station config.– Gaussian sources– Arbitrary time/freq obs.– True parallelization in time.– Functional parallelization

otherwise– Exportable to FITS– Script driven to support

automated parameter searches

– 4-D Ionosphere with line integration.

– Site mask incorporation

– Sky noise due to Galactic Background.

• Will Include– Polarization

– Realistic skies

– Source Spectral Index

– Out-of-beam source contributions (CasA in sidelobes, etc…)

– Extension to 3-D FFTs for wide field imaging.

– RFI (limited)

Page 7: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

• 20 nodes

– 2.4 GHz P4, $900 each

– 1 Gbyte of RAM

– 60 Gbyte of disk

• Gigabit ethernet switch

– 24-port

– $2000

• UPS and misc

• Excellent price/performance

– 50-80 Gflops

– 3 Tbytes of disk

– <$25,000

Simulator Beowulf

Page 8: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Image Import and Simulation

Before After

Page 9: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Effect of Variable Station Beams

Page 10: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Effects of Ionosphere (Virgo A at 74 MHz)

R. Perley (2003)

Page 11: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Ionospheric Effects • Line integration through realistic 4-D ionospheric model (from G. Bust)

• Vertical profile, TIDs, Kolmogorov Spectrum of inhomogeneities.

• Gaussian depletions/enhancements (transient, drifting, stationary…)

• IDL-based visualization software for 2-D or 3-D (animation) data.

Altitude (10km)

Latitude (26km)

ElectronDensity

Page 12: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Ionospheric effects

• 4-dimensional ionosphere generation

• 2-D phase screen by line integration

for each station/time

• (u,v) plane convolution

independently for each data

point/channel

Page 13: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Ionospheric Movie: Refraction,Defocusing

Demonstrate that PS can reproduce characteristics ofreal ionosphere: Virgo A.

Gain experience with Ionospheric generation codeand verify simulator code.

Original data images: 2048as

Movie images: 600x600as.

Elapsed time 1000 seconds

1 TID with wavelength largecompared to VLA A array.

Code verified with‘perfect wedge’.

Page 14: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Ionospheric Effects on Point Source

Motion of brightest component Flux of brightest component

Page 15: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Baseline Phases on VLA armsNorth Arm SE Arm

Page 16: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Ionosphere above the VLA

N_e as a functionof Altitude above the VLA.

Page 17: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Sky Noise Contribution

408 MHz All Sky MapUse spectral index (2.55) to scale in frequencyConvolved with receptor beam pattern.

Page 18: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

LOFAR skies: deep field at 330MHz

Page 19: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Simulated Sky at 74MHzExtrapolation to 74MHzfrom VLA P-band image.

2000x2000 arcsec1Jy to 0.1mJy

24 Hour integration

Page 20: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Configuration Studies

• Different types of configurations: log spirals, symmetric/asymmetric, 1, 3

and 5 arms, random perturbations of station

• Scripts and codes that generate families of a given type, for a given parameter range

• Hard constraints from design, and other considerations, cable length, cable routing, etc

Page 21: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Configuration Studies - in progress

• Parameter space is vast:• Configurations (log spirals, random,…)

• Number of stations (variable sensitivity …)

• No of elements/station, Staion layout

• Bandwidth and integration time

• Sky properties and observing geometry

• Frequency, polarization, spectrum, …

• Weighting schemes, tapering

• Ranges of corrupting influences.

• Strategy: parameterize configurations and explore limited ranges, identify trends

• Input from ALMA, ATA, SMA studies.

Proposed USSKA Configuration

Inner ~100 km array

Page 22: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Figures of Merit:

• PSF statistics: RMS, size, min, max, deviation. Computed for declination, integration, bw.

• Cable Length (Prim’s Algorithm).• Sensitivity Loss due to: weighting, fixed taper.• PSF statistics for Inner compact array/core.• Image fidelity for a few benchmark images.• Robustness: impact of random station loss.• Calibratability: requires calibration software.

Page 23: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Searching in Parameter Space

Page 24: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Configuration Optimization

Figures of Merit:PSF RMS vs RadiusPSF Beam SizeCable Length

Page 25: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Configuration Optimization

Figures of Merit weighted And Combined into Optmization function

Page 26: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Effects of Integration Time and BW

x = instantaneouso = ½ hour

x = 0.25%o = 10% = 20%

Page 27: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Compact Core Configurations

• Outer configuration won’t continue to Core.

• Scale free distribution breaks down in Core• Lower limit of receptors/station relaxed.

• Calibration and cabling issues.• ASM and EOR require excellent Core PSF

Page 28: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Genetic Algorithm Optimization

-Optimizes using (u,v) coverage and cable length figures of merit.-Uses ‘mutations’ to avoid local minima-Excellent beam size and RMS characteristics-Scale free constraints to be included.

Page 29: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Configuration Editor

Page 30: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Site Constraint ImpactUsed idealized configurations andmeasured PSF metricsbefore and after editingto accommodate siteconstraints.

PSF Metrics:Beam SizeBeam EllipticityRMS at various radiiExtrema near centerSkewness vs. radius

Snapshot, 30min,2 hour integrations.

Page 31: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Configuration Editor

Page 32: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Effects of Configuration Constraints

• Real-world constraints (mountains, cities, existing fibers …)• Optimization of configuration is complicated problem

Page 33: The Haystack SKA/LOFAR Performance Simulator Feb 13, 2004 Ramesh Bhat MIT/Haystack

Summary

• Robust simulation package exists– Very general, supports full range of SKA designs

– Supports wide range of model sky properties

– Precision visibility generation, wrapped in support utilities

– Includes key sources of error for SKA/LOFAR

– Suitable for comprehensive analyses of array performance

• Does not simulate all observing modes– Imaging mode only at this stage

• Work in progress– Continued code development (3DFFT, out-of-beam, etc)

– Support for outside use (simulations/science)