Thijs van der Hulst Kapteyn Institute
Challenges for calibration and analysis pipelines Thijs van der Hulst Kapteyn Institute Thijs van der Hulst PHISCC2015 Rutgers University 16 - 18 March Challenges for calibration and analysis pipelines can clever algorithms replace a life time experience? Thijs van der Hulst Kapteyn Institute Thijs van der Hulst PHISCC2015 Rutgers University 16 - 18 March Challenges for calibration and analysis pipelines can clever algorithms replace a life time experience? • • • • Thijs van der Hulst From visibilities to science ready data Forthcoming HI surveys Source finding and characterisation Visualisation challenges Thijs van der Hulst Kapteyn Institute PHISCC2015 Rutgers University 16 - 18 March Steps from visibilities to science ready data • flagging for RFI, system problems, etc. baseline length => ! ! ! ! ! ! ! • applying amplitude and phase (self) calibration • continuum subtraction ! ! courtesy Tom Oosterloo frequency => • frequency => frequency => imaging including deconvolution Thijs van der Hulst PHISCC2015 Rutgers University 16 - 18 March Number of detections in planned HI surveys rendering by Davide Punzo APERTIF APERTIF DINGO Survey: Wallaby shallow survey medium deep >10 beams 800 300 30 3 3-10 beams 35000 10000 2000 200 <3 beams 500000 125000 25000 5000 estimates from Duffy et al. MNRAS 426, 3385, 2012 Thijs van der Hulst PHISCC2015 Rutgers University 16 - 18 March Required tools • • • • • Data flagging (good experience with LOFAR) Continuum subtraction (requires knowledge of the HI emission) Source finding (demo by Paolo Serra) Source characterisation (talk by Nadine Giese) Interactive and quantitative visualisation (talk by Davide Punzo) and • • • Thijs van der Hulst Algorithms must be able to handle ~ 4 Tb/day Integrate source finding and HI imaging pipeline Visualisation/modelling capabilities required at desk top level PHISCC2015 Rutgers University 16 - 18 March Source finding with SoFiA (Serra et al. MNRAS 448, 1929, 2015) Thijs van der Hulst 24 pointing mosaic with the WSRT PHISCC2015 Rutgers University 16 - 18 March An example data cube of ~ 8 square degrees Rendering by Davide Punzo • • Thijs van der Hulst Perseus-Pisces filament Ramatsoku et al. 2015 one APERTIF pointing will deliver ~100 detections occupying ~ 109 voxels one pointing has ~1011 voxels (~1 TB): so 99% is noise PHISCC2015 Rutgers University 16 - 18 March Characterizing 3D structures automatically galaxies in the Ursa Major cluster (courtesy Busekool and Verheijen) Thijs van der Hulst rendering by Davide Punzo PHISCC2015 Rutgers University 16 - 18 March 3D Visualisation and smoothing original cube UGC12808 WHISP rendering by Davide Punzo SDSS Thijs van der Hulst PHISCC2015 Rutgers University 16 - 18 March 3D Visualisation and smoothing smoothed cube UGC12808 SDSS WHISP rendering by Davide Punzo Thijs van der Hulst PHISCC2015 Rutgers University 16 - 18 March Summary HI surveys require clever pipelines dealing with: ! • • • • RFI rejection selfcalibration, in some cases direction dependent continuum subtraction avoiding line emission high fidelity, fast deconvolution ! and ! ! • 3D source finding and source characterisation • error analysis and reliability assessment of results • quantitative and interactive 3D/2D visualisation tools Thijs van der Hulst subject of PhD of Nadine Giese and Davide Punzo PHISCC2015 Rutgers University 16 - 18 March
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