Ramesh Bhat Centre for Astrophysics & Supercomputing
Swinburne University of Technology Time Domain Astronomy Meeting,
Marsfield, 24 October 2011 Searching for Fast Transients with
Interferometric Arrays Slide 2 An Australia-India collaborative
project Developing new scientific capabilities for the GMRT
Transient detection pipeline High time resolution pulsar science
VLBI between GMRT and Australian LBA Collaborating institutions:
Swinburne, Curtin/ICRAR, CASS (Australia) National Centre for Radio
Astrophysics (India) Project team: Matthew Bailes (Swinburne)Ben
Barsdell (Swinburne) Ramesh Bhat (Swinburne) Sarah Burke-Spolaor
(JPL) Jayaram Chengalur (NCRA)Peter Cox (Swinburne) Yashwant Gupta
(NCRA)Chris Phillips (CASS) Jayanti Prasad (IUCAA) Jayanta Roy
(NCRA) Steven Tingay (Curtin)Tasso Tzioumis (CASS) W van Straten
(Swinburne)Randall Wayth (Curtin) Slide 3 In This Talk: Searching
for fast transients - important considerations GMRT as a test bed
instrument Transient detection pipeline Event analysis methodology
Slide 4 Slide 5 Searching for fast radio transients: Important
considerations Detection sensitivity, survey speed, and search
volume -- Figure of Merit (FoM) Propagation effects: e.g.
dispersion, scattering, and scintillation due to the intervening
media Parameter space to search for: DM, time scale; computational
requirements Radio frequency interference (RFI) -- a major
impediment in the detection of fast transients! Detection
algorithms; candidate identification and verification strategies
Slide 6 De-dispersion DM = Dispersion Measure (in units of pc cm -3
) Dispersion smearing can be quite severe at low obs frequencies
Processing will involve searching over a large range of dispersion
measure (DM) Low frequencies will require very fine steps in DM
(e.g. ~1000 trial DMs @325 MHz) Incoherent dedispersion: channelise
data, shift and align the channels, then sum Slide 7 Searching for
events in the time - DM parameter space Detections of single pulses
from J0628+0909 Standard search strategy: Dedispersion + matched
filtering Each event is characterised by its amplitude, width, time
of arrival and dispersion measure (DM) Matched filtering Time
domain clustering Matched filtering Slide 8 Observational Parameter
Space S (x, t,, ) x : Location of the station : Direction on sky t
: Time domain : Radio frequency RFI is site-specific &
direction dependent: function of x and Effective use of coincidence
or anti-coincidence filters Celestial transients vs. RFI: May have
similar -t signature (e.g. swept-frequency radar and pulsars) Will
have very different occupancy of x- space: Slide 9 Detecting fast
transients: search algorithms and strategies PSR J1129-53 - an RRAT
discovered by Burke-Spolaor & Bailes (2010) Slide 10 Transient
Exploration with GMRT 30 x 45m dishes, collecting area ~ 3% SKA
Modest number of elements, long baselines Advent of GMRT software
backend (GSB) Demonstration of multibeaming across FoV Superb event
localisation capabilities (~5) Computational requirements are
significant, however affordable GMRT makes an excellent test-bed
for developing the techniques and strategies applicable for next-
generation (array type) instruments Slide 11 Considerations for
sub-arraying: False alarm probabilities N independent
elementsMultiple sub-arrays, p = N/nIncoherent combination Slide 12
14 km 1 km x 1 km RFI environment is known to vary significantly
across the array; e.g. between the arms; between the central square
and the arms (east, west, south) Considerations for sub-arraying:
RFI environment Local RFI sources: TV boosters Cell phone towers
Power lines Slide 13 Antenna locations are marked in red Locations
of RFI sources are marked in blue courtesy: Ue-Li Pen Slide 14 +
GMRT software backend (GSB) GMRT + configurability Slide 15
Transient Detection Pipeline for GMRT Real-time processing and
Trigger generation + Local recording of Raw Data GMRT array GSB
clusterTransient Detector Trigger Generator @ 2 GB/sec 512 MB/sec
(Ndm/Nchan) x 64 MB/sec Slide 16 Salient features of GMRT transient
project The GMRT + GSB combination offers some unique features for
efficient transient surveys at low radio frequencies Long
baselines: powerful discrimination between signals of RFI origin vs
celestial origin (via effective coincidence filtering) High
resolution imaging: event localization (~ 5-10) possible through
imaging the field of view and/or full beam synthesis Software
phasing (offline): sensitive phased array beams toward candidate
directions (~5 x sensitivity); base-band data benefits (e.g.
coherent de-dispersion) Search strategy: commensal mode with other
observing programs; real-time processing and local recording Slide
17 Pilot transient surveys with the GMRT Primary goals: Technical
development Efficacies at low frequencies Survey region: -10 o <
l < 50 o, | b | < 1 o @ 610 -10 o < l < 50 o, 1 o <
| b | 3 o @ 325 Data recording Software backends raw dump DR = 2 x
30 x (32 MHz) -1 x 4 bps Data from the surveys are used to develop
the transient processing and the event analysis pipelines Slide 18
Transient Detection Pipeline RFI + quality checks Form N Sub-arrays
De-dispersion Transient detection Event identification Coincidence
filter Trigger generation Data extraction Event analysis Slide 19
Examples from the pipeline: a real astrophysical signal Slide 20
Examples from the pipeline: spurious signals (local RFI) Slide 21
Spectral Kurtosis Filter for RFI excision: Implementation on CASPSR
Andrew Jameson (Swinburne) Slide 22 Need for high resolutions in
time, frequency and DM space Signals can be as short as tens of
micro seconds at GMRT frequencies Maximum achievable time
resolution ~ 30 us with the current pipeline An example from the
GMRT transient detection pipeline (mode: 7 sub-arrays) A Giant
Pulse from Crab Pulsar at GMRT 610 MHz, Time duration ~ 50 us Slide
23 Processing Requirements Benchmark with current software: data at
full resolution (30 us, 512 channel FB) 15 x real-time on a dual
quad-core Dell PE1950 equivalent to 133 Gflops (theoretical) Net
processing requirement: 15 x 133 Gflops = 2 Tflops (per beam!)
Possible (practical) solutions: Data down sampling (degrading
resolution in f-t) by a factor 4 4 machines per beam OR 16 machines
for 4 subarray beams Alternatively, 4 x GPUs, each of 0.5 Tflops
De-dispersion (searching in DM parameter space) is the most
computationally intensive part of the pipeline 30 us, 512-channels
16 bit data samples DM range: 0 - 500 tolerance level: T1.25 GPU
dedispersion code by Ben Barsdell (Swinburne) Slide 24
Considerations for the real-time system: false positives and RFI
signals Slide 25 Considerations for the real-time system: (false
positives + RFI) + real signal Slide 26 Event Analysis (offline)
Pipeline Localisation of the event on sky + phasing up + further
checks Slide 27 FLAGCAL: A flagging and calibration package
Description of the FLAGCAL pipeline in Prasad & Chengalur
(2011) Slide 28 Snapshot imaging for event localisation Currently
FLAGCAL + AIPS; will soon be integrated into the main event
analysis pipeline Dirty imageSingle pulse from J1752-2806 dirty
image After cleaning and self-cal Signal peak ~ 0.27 Jy rms ~ 6
mJy; beam ~ 59 x 10 Slide 29 Example from Event Analysis Pipeline
On phasing up Detection Phase up the array Slide 30 Summary and
Concluding Remarks Searching for fast transients with multi-element
instruments involve several considerations and challenges;
propagation effects, RFI, signal processing, etc. The GMRT makes a
powerful test bed for developing and demonstrating novel transient
detection techniques and methodologies applicable for
next-generation (LNSD type) instruments such as ASKAP Transient
detection pipeline for GMRT - development nearly complete; the
commensal surveys to start by early 2012; the system will be
extended to larger bandwidths The VLBA and GMRT based efforts will
help demonstrate the advantages of multiple stations and long
baselines for transient exploration; valuable lessons for the
SKA-era
