deep wide field vlbi imaging - “the need for speed”
DESCRIPTION
Deep wide field VLBI imaging - “The need for speed”. Harro Verkouter Joint Institute for VLBI in Europe. Information content. VLBI datasets contain much more information than is extracted. Information content. Usually a field of 50x50 synthesized beams is imaged - PowerPoint PPT PresentationTRANSCRIPT
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Deep wide field VLBI imaging
-“The need for speed”
Harro Verkouter
Joint Institute for VLBI in Europe
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Information contentVLBI datasets contain much more information than is extracted
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Information contentUsually a field of 50x50 synthesized beams is imagedStill only 0.1% of information!
Typically corresponds with a field-of-view of 1” x 1”Primary beam of Effelsbergis 6’ (@18cm)
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Field of view limitations
1. Pre-correlationa) Sensitivity
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Field of view limitations
1. Pre-correlationa) Sensitivity
2. Post-correlationb) Time smearingc) Spectral resolution
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Field of view limitations(2)
VLBI datasets >> connected element array datasetsAlmost obsessive need for averaging to make datasets manageable
Time smearing/spectral smearing scale with baseline length!
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What can we do about it?1. Pre-correlation:
a) EVN: actively support development for more sensitivy, e.g. PCEVN, MarkV.
b) EVN: 12hrs @512Mbit 10Jy/beam
Need enhanced output data rate!
2. Post-correlation: a lot more!a) Decrease correlator integration timeb) Increase spectral resolution
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And there’s more…
‘re-correlate’ by mathematics; produce multiple phasecentresExperiment with the data: apply algorithms at willHelps with near real time space VLBIApply filters before exporting to user
Once the data is correlated, is that it?
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And there’s more (2)Applicability of the algorithms is limited by the aforementioned time- and bandwidth smearing
Need enhanced output datarate!
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Requirements
Field-of-view of 1’x1’ needsIntegration time 0.25s62kHz channelwidth 2k channels for 64MHz bandwidth
Integration time ~ 1/ Channelwidth of 62kHz remains
Want to map out considerable fraction of Ef primary beam (6’ @18cm):
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EVN MkIV Correlator limitsIntegration time
Cycle time of 0.015s (actually, 1/64th of a second)
Spectral resolution131072 complex lags per readout = 65536 spectral points per readoutDivided over 32 products leads to 2048 spectral channels per product
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DatarateEach lag occupies 5 bytes of data (4 data+1 overhead)Hence, ¼ million lags at 64 readouts/second equals 16Mlags/secondWhich works out to be 160MByte/s
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The EVN MkIV Correlator
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The PCInt projectShort for Post Correlator IntegratorWe want to capture the full output of the EVN MkIV correlator to diskNeed to replace output datapath Steve Parsley
Marcel LooseHarro Verkouter
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The PCInt project (2)High speed readout of the correlator was already prepared
Via DSP powered serial portNeed hardware and software to enable this
Receiving end of serial portGbit ethernet for transfer from correlator rack to datacollection hostFast disk subsystem in order to support 160MByte/s (parallel RAID arrays in a Storage Area Network)
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Current situationCCC
EEE (xk)
DDD (xn)
Switch
FC Switch
Correlator Board (x8)
RaidArray (xm)
RT System
Ethernet Card
C40 COMM
VME High Speed Serial
SBC (x2)
Correlator rack (x4)
PCI
100TX1000FX(x8)
Fibre Channel
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Phase 0
CCC
EEE (xk)
DDD (xn)
Switch
FC Switch
Correlator Board (x8)
RaidArray (xm)
RT System
VME High Speed Serial
Correlator rack (x4)
100TX1000FX(x8)
Fibre Channel
Ethernet Card
C40 COMM
SBC (x2)
PCI
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Phase 1
CCC
EEE (xk)
DDD (xn)
Switch
FC Switch
Correlator Board (x8)
RaidArray (xm)
RT System
VME High Speed Serial
Correlator rack (x4)
100TX1000FX(x8)
Fibre Channel
Ethernet Card
C40 COMM
SBC (x2)
PCI
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Phase 2
CCC
EEE (xk)
DDD (xn)
Switch
FC Switch
Correlator Board (x8)
RaidArray (xm)
RT System
VME High Speed Serial
Correlator rack (x4)
100TX1000FX(x8)
Fibre Channel
Ethernet Card
C40 COMM
SBC (x2)
PCI
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Post-processing issues
Data volume = huge1hour @160MByte/s equals560GBytes of dataUse a cluster of nodes
Need automated processingUse a processing pipeline
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Processing pipelineCorrelated data is saved to diskApply automaticallyNormalization correctionFlagging
Produce dataset with requested phasecentre(s) for userCan also apply filtering
Export to FITS
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Processing pipeline (2)
JIVE data quality assessment is already done using AIPS++AIPS++ supports parallel processingExport of data to user is also already done using AIPS++
Use AIPS++