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

2. Cast of Characters Shep Doeleman Colin Lonsdale Roger Cappallo Ramesh Bhat Joanne Attridge Divya Oberoi With contributions from Gary Bust (ARL/U. Texas) Tanja Bode (REU, Cornell) Laurel Ruhlen (REU, MIT)

3. 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)

4. Functional Flow Diagram array skies obs_spec proc_spec config generator Lists images Script driven Simulator Module sites (u,v) FITS MIRIAD PSF Stats Imaging Fidelity Calibration “ground truth” data ionosphere

5. Architecture Kernel of visibility generation: Transform arbitrary sky to perfect “reference” uv grid For each baseline For each time For each frequency channel Copy relevant piece of uv grid Convolve with station beam and atmosphere/ionosphere functions Precision numerical integration over correlation cell Add noise, simple RFI … Write output uv data file

6. 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)

7. 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

8. Image Import and Simulation Before After

9. Effect of Variable Station Beams

10. Effects of Ionosphere (Virgo A at 74 MHz) R. Perley (2003 )

11. 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) Electron Density

12. 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

13. Ionospheric Movie: Refraction,Defocusing Demonstrate that PS can reproduce characteristics of real ionosphere: Virgo A. Gain experience with Ionospheric generation code and verify simulator code. Original data images: 2048as Movie images: 600x600as. Elapsed time 1000 seconds 1 TID with wavelength large compared to VLA A array. Code verified with ‘perfect wedge’.

14. Ionospheric Effects on Point Source Motion of brightest component Flux of brightest component

15. Baseline Phases on VLA arms North Arm SE Arm

16. Ionosphere above the VLA N_e as a function of Altitude above the VLA.

17. Sky Noise Contribution 408 MHz All Sky Map Use spectral index (2.55) to scale in frequency Convolved with receptor beam pattern.

18. LOFAR skies: deep field at 330MHz

19. Simulated Sky at 74MHz Extrapolation to 74MHz from VLA P-band image. 2000x2000 arcsec 1Jy to 0.1mJy 24 Hour integration

20. 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

21. 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

22. 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.

23. Searching in Parameter Space

24. Configuration Optimization Figures of Merit: PSF RMS vs Radius PSF Beam Size Cable Length

25. Configuration Optimization Figures of Merit weighted And Combined into Optmization function

26. Effects of Integration Time and BW x = instantaneous o = ½ hour x = 0.25% o = 10%  = 20%

27. 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

28. 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.

29. Configuration Editor

30. Site Constraint Impact Used idealized configurations and measured PSF metrics before and after editing to accommodate site constraints. PSF Metrics: Beam Size Beam Ellipticity RMS at various radii Extrema near center Skewness vs. radius Snapshot, 30min, 2 hour integrations.

31. Configuration Editor

32. Effects of Configuration Constraints Real-world constraints (mountains, cities, existing fibers …) Optimization of configuration is complicated problem

33. 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)