26/03/2003 omegacam: the 16k x 16k survey camera for the vst observing and data reduction a virtual...
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26/03/2003
OmegaCAM: The 16k x 16k Survey Camera for the VST
OmegaCAM: The 16k x 16k Survey Camera for the VST
Observing and data reduction a Virtual Survey System
Observing and data reduction a Virtual Survey System
Edwin A. ValentijnEdwin A. Valentijn
26/03/2003
Paranal Paranal
July 2004July 2004
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VLT Survey Telescope-VSTVLT Survey Telescope-VST
– Alt-AZ - Cassegrain
– aperture 2.610 m
– corrected FOV 1.47 degree
– lens corrector: U - z
– Atmospheric disp. correct.: B -z
– f/5.5
– scale 14.266 arcsec/mm
– CCD pixel size: 15 um
– 0.214 arcsec/pixel
– image quality: 80% EE
– two-lens: 1.70 pixel
– ADC: 1.77 - 2.18 pixel
– Alt-AZ - Cassegrain
– aperture 2.610 m
– corrected FOV 1.47 degree
– lens corrector: U - z
– Atmospheric disp. correct.: B -z
– f/5.5
– scale 14.266 arcsec/mm
– CCD pixel size: 15 um
– 0.214 arcsec/pixel
– image quality: 80% EE
– two-lens: 1.70 pixel
– ADC: 1.77 - 2.18 pixel
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VST factory - NapoliVST factory - Napoli
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DetectorsDetectors
• Science array 1 x 1 degree, 32 CCDs– 15 m pixels – 0.21 arcsec/pixel– Marconi (former EEV) 2k x 4k– 16k x 16k pixels
• Auxiliary CCD’s – 4 CCDs– For guiding– Image analysis
• Science array 1 x 1 degree, 32 CCDs– 15 m pixels – 0.21 arcsec/pixel– Marconi (former EEV) 2k x 4k– 16k x 16k pixels
• Auxiliary CCD’s – 4 CCDs– For guiding– Image analysis
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FiltersFilters
• Primary set: Sloan u’, g’, r’, i’, z’ high throughput interference• Johnson B, V, Stromgren-v• Segm H up to ~12000 km/s 658.8 665.5 672.2 678.9/ 10.7 nm
– 1100, 4200, 7300, 10400km/sec / 4900 km/sec
• Composite u’, g’, r’ ,i’ in four quadrants• Segm Ly alpha z=2-3 372, 400, 450, 507nm / 8 nm • Night sky leak CWL=851.8nm - 877.8nm /13nm
• Primary set: Sloan u’, g’, r’, i’, z’ high throughput interference• Johnson B, V, Stromgren-v• Segm H up to ~12000 km/s 658.8 665.5 672.2 678.9/ 10.7 nm
– 1100, 4200, 7300, 10400km/sec / 4900 km/sec
• Composite u’, g’, r’ ,i’ in four quadrants• Segm Ly alpha z=2-3 372, 400, 450, 507nm / 8 nm • Night sky leak CWL=851.8nm - 877.8nm /13nm
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Wide Field Imaging Science
Wide Field Imaging Science
• Provide targets for VLT• ~60% of time through ESO’s OPC• Individual programs
– Supernovae, Lensing, Kuiper belt objects, Gamma ray, bursts, Microlensing, Brown dwarfs, High proper motion objects, Galactic halo objects, Quasars, AGNs
• Sky Surveys• Long term archival research (10 yr mission)
• Science Cases– Finding exceptional single, rare objects– Statistics on large samples of objects
• Provide targets for VLT• ~60% of time through ESO’s OPC• Individual programs
– Supernovae, Lensing, Kuiper belt objects, Gamma ray, bursts, Microlensing, Brown dwarfs, High proper motion objects, Galactic halo objects, Quasars, AGNs
• Sky Surveys• Long term archival research (10 yr mission)
• Science Cases– Finding exceptional single, rare objects– Statistics on large samples of objects
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Large Data VolumeLarge Data Volume
• Wide-field imaging instruments, vast amounts of data– E.g.: VST = Southern sky (30 min exp, 300 nights/y) in
3 years. Large amount of data! 100 Tbyte of image data and Tbytes of source list data
• Wide-field imaging instruments, vast amounts of data– E.g.: VST = Southern sky (30 min exp, 300 nights/y) in
3 years. Large amount of data! 100 Tbyte of image data and Tbytes of source list data
• Science can only be archive-based• Science can only be archive-based
• Handling of the data is non-trivial– Pipeline data reduction– Calibration and re-calibration– Image comparisons and combinations– Working with source lists– Visualization
• Handling of the data is non-trivial– Pipeline data reduction– Calibration and re-calibration– Image comparisons and combinations– Working with source lists– Visualization
ESOcompliantESOcompliant}}
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Concepts for solutionVirtual Survey SystemConcepts for solutionVirtual Survey System
• Environment that provides systematic and controlled– Access to all raw and calibration data– Execution and modification reduction/calibration pipelines– Execution of source extraction algorithms– Archiving reduced data and source lists, or regenerates these
dynamically– Can be federated to link different data centers
• Environment that provides systematic and controlled– Access to all raw and calibration data– Execution and modification reduction/calibration pipelines– Execution of source extraction algorithms– Archiving reduced data and source lists, or regenerates these
dynamically– Can be federated to link different data centers
• Dynamical archive continuously grows, can be used for – small or large science projects– generating and checking calibration data– exchanging methods, scripts and configuration
• Dynamical archive continuously grows, can be used for – small or large science projects– generating and checking calibration data– exchanging methods, scripts and configuration
• Key functionality– Link back from source data to the original raw pixel data and
calibration files
• Key functionality– Link back from source data to the original raw pixel data and
calibration files
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How to use thisHow to use this
• Deep multi-color fields– No need to take all data in one campaign– Combine data of particular quality, assess results– Select sources, visualize interesting ones, …
• 1-in-1,000,000 events spurious or not?
• Deep multi-color fields– No need to take all data in one campaign– Combine data of particular quality, assess results– Select sources, visualize interesting ones, …
• 1-in-1,000,000 events spurious or not?
• Large homogeneous surveys– E.g. weak lensing maps, cluster searches, star counts
• Large homogeneous surveys– E.g. weak lensing maps, cluster searches, star counts
• Variability (source list - or pixel based) – Proper motions (asteroids, nearby stars)– Flux variations
• Variability (source list - or pixel based) – Proper motions (asteroids, nearby stars)– Flux variations
• Monitor instrument (calibration files)• Monitor instrument (calibration files)
• Planning observations– View quality of existing data– Build on what already exists, add more filters, more
exposure time, better seeing, …
• Planning observations– View quality of existing data– Build on what already exists, add more filters, more
exposure time, better seeing, …
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Keys -SolutionKeys -Solution
• Procedurizing– Data taking at telescope for both science and
calibration data– Full integration with data reduction– Design – Data model (classes) defined for data reduction and
calibration– View pipeline as an administrative problem
• Procedurizing– Data taking at telescope for both science and
calibration data– Full integration with data reduction– Design – Data model (classes) defined for data reduction and
calibration– View pipeline as an administrative problem
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Observing Modes Dither
Observing Modes Dither
• Dither matching max. gap between arrays ~400 pixels– N pointings (N=5 is standard) – nearly cover all gaps in focal plane and maximizes sky coverage– Very complex context map– couple the photometry among individual CCDs.
• Dither matching max. gap between arrays ~400 pixels– N pointings (N=5 is standard) – nearly cover all gaps in focal plane and maximizes sky coverage– Very complex context map– couple the photometry among individual CCDs.
–Dither with N = 5–Dither with N = 5
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Observing Modes Jitter
Observing Modes Jitter
• Jitter matching the smallest gaps in CCDs ~5 pixels– optimizes for maximum homogeneity of the context map – observations for which the wide CCD gaps are not critical– all data from single sky pixel originates from single chip
• Jitter matching the smallest gaps in CCDs ~5 pixels– optimizes for maximum homogeneity of the context map – observations for which the wide CCD gaps are not critical– all data from single sky pixel originates from single chip
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Observing ModesStare and SSO
Observing ModesStare and SSO
• Stare reobserving fixed pointing positions multiple times– main workhorse monitoring instrument and optical
transients.
• Stare reobserving fixed pointing positions multiple times– main workhorse monitoring instrument and optical
transients.
• SSO observing Solar System objects– non-siderial tracking and the auto guiding switched off.
• SSO observing Solar System objects– non-siderial tracking and the auto guiding switched off.
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Strategiesscheduling observing modes
Strategiesscheduling observing modes
• Standard– Single observations (one observing block)
• Deep– Long, multiple integrations– Selected atmospheric conditions– Several nights
• Frequent– Monitors same field– Timescales from minutes to months (overriding)
• Mosaïc– Maps areas of sky > 1o
• Standard– Single observations (one observing block)
• Deep– Long, multiple integrations– Selected atmospheric conditions– Several nights
• Frequent– Monitors same field– Timescales from minutes to months (overriding)
• Mosaïc– Maps areas of sky > 1o
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Calibration proceduresCalibration procedures
Sanity checksSanity checks
Quality controlQuality controlCalibration proceduresCalibration procedures
Image pipelineImage pipeline
Source pipelineSource pipeline
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Science ObservationsScience Observations
Photometric pipelinePhotometric pipeline
Bias pipeline
Flatfield pipeline
Image pipeline
Source pipeline
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Share the loadAstroWise Survey System
Share the loadAstroWise Survey System • Processing
– Hardware • Beowulf processors – 32 (most cases)• Multi Terabyte disks (10 – 100)
– Data reduction• Derive calibration• Run image pipeline (1 Mpx/s)
• Processing– Hardware
• Beowulf processors – 32 (most cases)• Multi Terabyte disks (10 – 100)
– Data reduction• Derive calibration• Run image pipeline (1 Mpx/s)
• Archiving– Storage
• Images (100’s Tbyte), Calibration files (10 Tbyte)• Source parameters (1-10 Tbyte)
– Federate (network speed)• 5 Mb/s (24 hours/day) full replication • 200 Mb/s no replication, on-the-fly retrieval
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Concepts of federationConcepts of federation
• Federation maintained by a single database- Oracle9i• Full history tracking
– of all input that went into result – providing on-the fly reprocessing
• Dynamical archive - Context as object attributes– Project: Calibration, Science, Survey, Personal– Owner: Pipeline, Developer, User– Strategy: Standard, Deep, Freq (monitoring), Mosaïc– Mode: Stare, Jitter, Dither, SSO
– Time: Time stamping VO interface• Software standards
– Classes/data model/procedures– 00 – inheritance/ persistency
– Python scripts/ c-libraries USER Python
• Federation maintained by a single database- Oracle9i• Full history tracking
– of all input that went into result – providing on-the fly reprocessing
• Dynamical archive - Context as object attributes– Project: Calibration, Science, Survey, Personal– Owner: Pipeline, Developer, User– Strategy: Standard, Deep, Freq (monitoring), Mosaïc– Mode: Stare, Jitter, Dither, SSO
– Time: Time stamping VO interface• Software standards
– Classes/data model/procedures– 00 – inheritance/ persistency
– Python scripts/ c-libraries USER Python
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Observing proposalsObserving proposals
• Garanteed time NOVA 10%• Call – 25 April--- see www.omegacam• Super clusters- distant clusters• Galactic structure
– Weak shear, microlensing– Bulge
• 2dF, 100 Sq Degree, 10000 Sq Deg• Deep field • Lorentz center July 2003• Fall 2004
• Garanteed time NOVA 10%• Call – 25 April--- see www.omegacam• Super clusters- distant clusters• Galactic structure
– Weak shear, microlensing– Bulge
• 2dF, 100 Sq Degree, 10000 Sq Deg• Deep field • Lorentz center July 2003• Fall 2004