Ronald Nijboer (ASTRON) with input from Athol Kembal (TDP) Tim Cornwell / Maxim Voronkov (CSIRO)

1. WP 2.6.3 Calibration and Imaging techniques: Calibration Ronald Nijboer (ASTRON)with input fromAthol Kembal (TDP)Tim Cornwell / Maxim Voronkov (CSIRO)

2. Content • Introduction • Status • Real time calibration of stations and PAFs • Removing contaminating signals • RFI • A-team and / or other strong sources • Calibrating the FoV • Sky model • Bandpass • Clocks • Primary beam • Ionosphere • Troposphere • Other • Work to be done • Challenges and risks • Conclusion

3. SKA • Phase 1 • Definition is work in progress: numbers from Calim2010 (Hall) • Dish SPF array • 250 15 m dishes • 450 MHz – 10 GHz • Baseline up to 180 km • ~50000 channels • ~0.1 s dump time • AA array (sparse) • 50 180 m diameter stations • 70 MHz – 450 MHz • Baseline up to 180 km • ~50000 channels • ~1 s dump time • ~480 Independent beams on the sky • Demonstrators for PAFs and dense AAs • Phase 2 • More …

4. Feasibility: practical community experience in high-DR imaging • Community survey of current DR limitations (EVLA, WSRT, GMRT, ATCA) (Chakraborty & Kemball 2009): • Hardware is destiny • Sky-mount vs rotating antennas • Closure errors • Direction-dependent errors: • Pointing • Beam pattern errors • RFI • Computational and software limits • Longitudinal study on 3C273, 1974-2010 (Chakraborty & Kemball, 2010). • DR is tracking thermal sensitivity evolution, but at cost of calibration complexity. Mean DR evolution over time (Chakraborty & Kemball 2010)

5. Traditional Calibration Calibration needed for • Astrometry: accurate (absolute or relative) positions • Photometry: accurate (absolute or relative) flux scale, spectral shape • Image / PSF quality and image fidelity / DR Traditional method: • determine phase / gain (freq) on stable external (point) source • Good for 1) and 2) • Self-cal needed for 3)

6. Some observations • External calibrator • AA can use separate calibration beam and transfer cal solution • Repoint beam and extrapolate cal solution • If enough sensitivity “in-beam calibration” can be used • Provided the strongest sources in the FoV are known • Self-cal • Needed to obtain accurate (calibration) source model • Iterates through calibration and imaging / deconvolution steps • Hence needs to buffer all the uv-data • Complicates streaming processing

7. For calibration, we require a GSM Threshold requires investigation, probably ~ 1mJy Required accuracy not clearly understood yet During commissioning, we first image the entire sky in continuum We expect the processing will take all the computation resources Necessary to deconvolve and self-calibrate with many cycles Perform source detection For each source detected in Stokes I, take spectral index information from MFS image Repeat observations During commissioning to converge on accurate GSM During operations to update for variable sources 6km baselines May be necessary to bootstrap from 2km baselines ASKAP: Global Sky Model CSIRO

8. The instrument is stable and kept well-calibrated Most significant PAF calibration is done up-stream Only increments need be solved Always use prediction-forward Gains are fed back to correlator/beamformer/frontend in real time We always have a fairly accurate continuum model at hand No self-calibration is needed for spectral line and transients Real-time calibration per synthetic beam is adequate 3-axis antenna mount takes care of the beam rotation issues ASKAP: Calibration during observations • Processing is I/O intensive, iteration over visibilities is costly • The number of iterations must be kept to minimum (ideally just 1) ASKAP approach to solve this problem: CP Applications / Calibration and Imaging

9. A number of concurrent pipelines One for beam-dependent gains, one for bandpasses, one for polarisation Each accumulates data for a certain time interval Then reports the solution back to the Telescope Control System Solution is then applied to all future data closing the loop Tropospheric phase absorbed into beam-dependent gains Can add an antenna-dependent phase calibrated at a finer timescale, if necessary Ionosphere is isoplanatic Frequency dependence is absorbed into bandpass Complex gains of PAF beams Calibrate e.g. every 60s (or longer) Always predict forward (no interpolation of calibration solution) ASKAP: Calibration pipelines CSIRO

10. Initial LOFAR Calibration • The following initial approach is proposed on weak source fields ( < 5 - 10 Jy peak in HBA) • Calibrate on a bright dominant source and solve for clocks • Transfer calibration per subband, or interpolate, to target field • Then inspect data quality, noise, X and Y • Flag bad stations/baselines • Make snapshot image (within ~15m from the calibrator), create a model • Solve for clock drifts which become important after >15m • Combine multiple bands (BBS-global) to improve solutions etc • Iterate • Start with core stations (<3 km baselines) and work from inside out • i.e. get a proper low resolution LSM with all the flux contained in the FOV • Process 5-15m snapshots individually and combine beam-corrected images • Then bring in remote stations which involve longer baselines

11. Content • Introduction • Status • Real time calibration of stations and PAFs • Removing contaminating signals • RFI • A-team and / or other strong sources • Calibrating the FoV • Sky model • Bandpass • Clocks • Primary beam • Ionosphere • Troposphere • Other • Work to be done • Challenges and risks • Conclusion

12. Station / PAF calibration • Calibration approach determined by availability of calibrator sources • Station of AAs • Random array of dipoles • All sky FoV; • Regular array of tiles or vivaldis • Tile FoV; repointing and / or redundancy • Station of Dishes • Dish FoV; repointing? • PAFs • Radiators on the antenna surface • Repointing

13. LOFAR LBA Calibration Wijnholds

14. Embrace calibration Wijnholds Use Afristar satelite (or Sun) to calibrate

15. PAF Calibration M. V. Ivashina, S.J. Wijnholds, R. Maaskant, K. F. Warnick, and B. Jeffs

16. Content • Introduction • Status • Real time calibration of stations and PAFs • Removing contaminating signals • RFI • A-team and / or other strong sources • Calibrating the FoV • Sky model • Bandpass • Clocks • Primary beam • Ionosphere • Troposphere • Other • Work to be done • Challenges and risks • Conclusion

17. Removing RFI Offringa, MNRS 405 (June 2010) 155-167 Example: LOFAR low level RFI Developing a “streaming flagger” remains a challenge

18. WSRT 150 MHz; 3C196 CygA Sun CasA NCP VirA TauA De Bruyn

19. LOFAR Core Station 1: NCP Yatawatta

20. LOFAR: 3C465 Jackson

21. Correlator Field-of-View Shaping Background: Use of small (~12m) antennas for SKA ⇒ large FOV ⇒ potentially excessive data volumes/rates (up to PB/s) and maps sizes ⇒ removal of dynamic range-limiting sidelobes from sources across the full FOV will become an intractable problem using current techniques One solution is to employ intelligent weighting in frequency/time to limit the FOV for high-resolution work. This can be accomplished using Correlator Field-of-View Shaping (Lonsdale et al. 2004 & recent paper in prep.)

22. Sidelobe confusion levels at the phase center due to sources beyond angular distance r from Lonsdale et al., in prep. Bottom line: suppression levels below ~10-8 Jy can be achieved by this technique.

23. Content • Introduction • Status • Real time calibration of stations and PAFs • Removing contaminating signals • RFI • A-team and / or other strong sources • Calibrating the FoV • Sky model • Bandpass • Clocks • Primary beam • Ionosphere • Troposphere • Other • Work to be done • Challenges and risks • Conclusion

24. Sky model • On long baselines sources become resolved • Accurate source models are needed for calibration Van Weeren 3C 61.1, 60 hr, 20 HBA stations (16 split core + 4 remote),1 sub-band, 9.7 by 9.4 arcsec resolution

25. Sky model: shapelets EVLA 8.5 GHz 256 2 MHz channels 34 m – 1 km baselines Peak flux 34 Jy Residual 2.5 mJy DR ~13000 Sarod Yatawatta (RuG/ASTRON), Tony Willis (DRAO) and Rick Perley (NRAO)

26. Bandpass • Digital bandpasses can be corrected for without calibration Romein

27. Bandpass • Analogue bandpasses need calibration • For high DR imaging with WSRT per channel calibration of bandpass is needed (De Bruyn / Smirnov) Smirnov, submitted

28. Clocks • In LOFAR each station has a separate clock • Clock drifts complicate calibration • Make coherent beamforming more difficult (Pulsar observations) • Mix with ionospheric phase variations • To be considered in SKA system design

29. Primary beams • Pointing errors can be treated with A Projection • But need full pol treatment • Only for known PB patterns • Reflections by e.g. struts for dishes • Projection and time dependence for AA beams • How to calibrate general PB variations? • Work by Smirnov • In field calibration beacons for calibration • Solving for deliberate mispointing

30. Simulations: DD effects • Accept WBSPF radiation patterns from antenna design programs. • Simulate direction-dependent calibration using these patterns in SKA array configurations to assess: • Impact on image quality. • Impact of errors in direction-dependent calibration models.

31. Differential gains • Differential phases for 14 telescopes in the direction of 7 sources • Interpretation is still hard • This may be the basis for a general PB calibration approach Smirnov, submitted

32. Ionosphere • Typically below ~2 GHz observing frequency • Phase • SPAM by Huib Intema • Tested on VLSS data • Being implemented in LOFAR pipeline • But: SPAM tested on few 10s km baselines only • Faraday rotation • To be developed

33. SPAM

34. Troposphere • Typically above ~2 GHz observing frequency • In general a DD antenna based effect • May need a SPAM like approach for the SKA

35. Feasibility: wide-band polarization calibration Pathfinder ATA studies (Bower et al) Typical values up to 10%. Smooth changes with frequency.  Rate of ~3%/10 MHz at 1.4 GHz. Spiral and loop patterns seen in real-imag space. Period of loops similar to that of log-periodic feed (e.g., 3/4 of a turn at 1.4 GHz). Leakages are contiguous between adjacent bands.  This suggests leakages originate in the feed. 1.4 GHz leakages for antennas (numbered) in real,imaginary space as a function of frequency. Leakages for two adjacent correlator tunings.  The leakages change smoothly between bands.

36. Feasibility: DD polarization calibration Pathfinder ATA studies (Bower et al) Leakages are measured in offset pointings from calibrator. Similar leakages throughout the primary beam. Random contribution increases off-axis and toward higher frequencies. Random component of order 3% within half the HP point at 1.4 GHz. Leakages for ant 11x at center and half power points.  Color shows frequency dependence.  Axes show leakage scale. Same leakages, but showing diff with center.

37. Polarisation: RM Synthesis • 3C66AB-NGC891-PSRJ0218 6h HBA Scaife, Heald, de Bruyn, Trassati, …

38. Polarisation: RM Synthesis Scaife, Heald, de Bruyn, Trassati, …

39. Other effects • “VLBI” • Retarded baselines (Voronkov) • Continental drift • Effect of wheather fronts, oceanic loading, etc. on station positions • BSR / beam squint

40. Content • Introduction • Status • Real time calibration of stations and PAFs • Removing contaminating signals • RFI • A-team and / or other strong sources • Calibrating the FoV • Sky model • Bandpass • Clocks • Primary beam • Ionosphere • Troposphere • Other • Work to be done • Challenges and risks • Conclusion

41. Work to be done • Requirements & system design • Feed back of initial findings to system design group • Further develop & implement algorithms / strategies • Integrate in a pipeline • Assessment of performance • Optimization of performance / finding alternative approaches

42. Challenges & Risks • Different approaches / pipelines will be needed for different receptor types / frequency regimes • Calibration approaches can only be fully validated when hardware is in the field • Total computational power needed is unclear • For current LOFAR calibration cost equals imaging cost, but is is unclear how this scales to full LOFAR, let alone SKA

43. Conclusion • Ideas on how to calibrate the SKA exist • Software for some modules exist • Integration into end-to-end pipeline is underway for the pathfinders and precursors • Performance and scalability to SKA regime remains to be evaluated

44. Some final remarks • DR is tracking thermal sensitivity evolution, but at cost of calibration complexity. • SKA processing is likely to differ at points from precursor and pathfinder processing • Need for streaming processing has implications for system design and algorithms • Some of the current algorithms might (will) not scale up to SKA size • The sheer size of the SKA makes it a whole new regime • Incremental construction will help the learning process • Pathfinders, precursors, SKA1, SKA2, …