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Paul Alexander Dynamic RangeAAVP 2010 Overview of Calibration and Dynamic Range Challenges Paul Alexander.

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Presentation on theme: "Paul Alexander Dynamic RangeAAVP 2010 Overview of Calibration and Dynamic Range Challenges Paul Alexander."— Presentation transcript:

1 Paul Alexander Dynamic RangeAAVP 2010 Overview of Calibration and Dynamic Range Challenges Paul Alexander

2 Dynamic RangeAAVP 2010 Required Dynamic Range Suggests 10 7 : 1 Sensitivity: 2000 m 2 /K at 150 MHz; 300 MHz BW; station beam ~ 1 degree In 24 hrs integration  = 0.2  Jy ~ 1 500 mJy source per sq degree at 150 MHz  2.5 × 10 6 EoR signal ~ 10 mK in presence of ~1000K foreground. Image at > 10   1 × 10 6  Take this estimate with a “pinch of salt” – limited by foreground subtraction

3 Paul Alexander Dynamic RangeAAVP 2010 Required Dynamic Range Note do need to think about source confusion In 24 hrs integration  = 0.2  Jy Source density ~ 1.5 x 10 5 sources per sq degree  Required baseline ~ 100km at 450 MHz

4 Paul Alexander Dynamic RangeAAVP 2010 Achieving high dynamic range now What do we know we have to include in an analysis: IncludeDiscussionMaturity Antenna-based complex gains Standard calibration and self calibration – iterative Removing sources in global sky model Removing bright sources from UV data even with local phase solution is relatively robust RFI and “bad data” excision Can be critically important: still largely done by hand for GMRT, eVLA and LOFAR Expert algorithms not well developed Bandpass calibrationWell defined, but often more problematic than it should be – software limitation ?

5 Paul Alexander Dynamic RangeAAVP 2010 Achieving high dynamic range now IncludeDiscussionMaturity Debugging the systemWe learn a great deal about our instruments over time and correct often 2 nd order errors Position-dependent effectsHugely Important relatively recent advance Time dependent pointing errors – antenna models may be limit Position-dependent phase screen – critically important for the ionosphere – modelling? Many algorithms (peeling. A- projection...) Full stokes imagingA position-dependent effect – polarization response changes across FoV

6 Paul Alexander Dynamic RangeAAVP 2010 Achieving high dynamic range now Other known issues Algorithm approximations mean analysis has known problems and errors which are not necessarily well dealt with  Wide-field imaging approximations (faceting, w-projection)  Deconvolution errors and artefacts – still an art using human judgement to drive non-linear algorithms  Time-averaging and bandwidth smearing poorly dealt with (but also useful in very wide fields).

7 Paul Alexander Dynamic RangeAAVP 2010 AA is operating at low frequencyIonosphere! Physical stability (wind etc.)Good, study details Unblocked apertureInherent Smaller beams are better>60m collectors Narrow band is importantAA is Wide Band but many channels Calibration capabilityExcellent, by channel Trade DR for sensitivityAA v. flexible AA Pros and Cons

8 Paul Alexander Dynamic RangeAAVP 2010 Designing for dynamic range Stable, known antenna patterns are key AA advantages AA’s mechanically stable Unblocked aperture Direct measurement of field But Need to calibrate 10 5 elements per station What accuracy of element calibration is needed Model dependent calibration – how many parameters can we solve for? Station beam is time dependent – transit experiment for individual elements Multiple independent elements for AA-low

9 Paul Alexander Dynamic RangeAAVP 2010 Designing for dynamic range Element-level calibration options and issues Importance of phase versus amplitude – how accurate? How often? Where are the main errors introduced in the RF chain - If copper is used for signal transport – active measurement of cable lengths? Deployment issues – position, orientation, misalignment If digitisation at the element – accuracy of clock distribution Temperature variations – large ambient fluctuations – fibre better than copper? Expert health monitoring system at element level – flag failed or failing elements Noise injection?

10 Paul Alexander Dynamic RangeAAVP 2010 Pathfinders The design decision must be informed by the pathfinders and precursors SKA community mu go beyond – “waiting to see what we will learn”  SKA team must pose the questions that we want to be answered Get answers either from experience of the pathfinders or doing explicit experiments and measurements  Obvious area of immediate cooperation between all the experiments and the AAVP team

11 Paul Alexander Dynamic RangeAAVP 2010 Other design issues Sufficiently good ionospheric model Station size and UV coverage – competing issues Larger stations – smaller station beam easier ionospheric model? Lower cost & less processing Smaller station size better – more stations better UV coverage, better imaging capability Hierarchical beam former Hierarchical beamformer in which data decimated reduced accuracy of station beam

12 Paul Alexander Dynamic RangeAAVP 2010 Algorithm issues (AA emphasis) Maturity of approaches is not there yet Much use of human intervention still required Transitioning to totally automated pipelines will be a major challenge Expert system for RFI excision? Are wide-field imaging approaches sufficiently accurate? Is our underpinning understanding of interferometry based too much on “experience” rather than a formal understanding of the underpinning formalism? Relying very much on a tiny group of real experts who have both the “experience” and the formal analysis

13 Paul Alexander Dynamic RangeAAVP 2010 Magnitude of the task Imaging processor Visibility processors Science product archive Local science reduction Science proposal Data product distribution Data routing Collectors Grid science reduction and visualisation Cloud store Correlator Data excision Monitor and Control system M&C database Global and local sky model Calibration loop Observation definition

14 Paul Alexander Dynamic RangeAAVP 2010 SKA 1 Data Rates and Configuration AA Line experiment 50 AA-low stations 100 sq degrees, 10000 channels over 380 MHz bandwidth  3.3 GS/s Issues What data rate can we process? Trade UV coverage ( N s ) for FoV and hence survey speed (  ) Line vs continuum requirements What is the longest baseline Single or multi-pass algorithms  increase data rate and buffering

15 Paul Alexander Dynamic RangeAAVP 2010 Reducing the data rate Relax criteria for dump rates and frequency resolution –My criteria based on uniqueness in UV plane –Can the criteria be relaxed and still achieve high dynamic range? Dump times and frequency resolution baseline dependent Design correlator for worse case  upgrade path

16 Paul Alexander Dynamic RangeAAVP 2010


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