Ramesh Bhat Centre for Astrophysics & Supercomputing Swinburne University of Technology

1. Ramesh BhatCentre for Astrophysics & Supercomputing Swinburne University of Technology Searching for Fast Transients with Interferometric Arrays Time Domain Astronomy Meeting, Marsfield, 24 October 2011

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)

3. In This Talk: Searching for fast transients - important considerations GMRT as a test bed instrument Transient detection pipeline Event analysis methodology

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

6. De-dispersion Dispersion smearing can be quite severe at low obs frequencies DM = Dispersion Measure (in units of pc cm-3) • 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

7. Searching for “events” in the time - DM parameter space Matched filtering Detections of single pulses from J0628+0909 Matched filtering Time domain clustering Standard search strategy: Dedispersion + matched filtering Each “event” is characterised by its amplitude, width, time of arrival and dispersion measure (DM)

8. Observational Parameter Space S (x, t, , ) x : Location of the station  : Direction on sky t : Time domain  : Radio frequency • Celestial transients vs. RFI: • May have similar -t signature (e.g. swept-frequency radar and pulsars) • Will have very different occupancy of x- space: RFI is site-specific & direction dependent: function of x and  Effective use of “coincidence” or “anti-coincidence” filters

9. Detecting fast transients: search algorithms and strategies PSR J1129-53 - an RRAT discovered by Burke-Spolaor & Bailes (2010)

10. Transient Exploration with GMRT GMRT makes an excellent test-bed for developing the techniques and strategies applicable for next-generation (array type) instruments • 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

11. Considerations for sub-arraying: False alarm probabilities N independent elements Incoherent combination Multiple sub-arrays, p = N/n

12. 1 km x 1 km 14 km Considerations for sub-arraying: RFI environment Local RFI sources: • TV boosters • Cell phone towers • Power lines 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)

13. Locations of RFI sources are marked in blue Antenna locations are marked in red courtesy: Ue-Li Pen

14. GMRT software backend (GSB) GMRT + configurability +

15. Transient Detection Pipeline for GMRT GMRT array Trigger Generator GSB cluster Transient Detector 512 MB/sec @ 2 GB/sec (Ndm/Nchan) x 64 MB/sec Real-time processing and Trigger generation + Local recording of Raw Data

16. Salient features of GMRT transient project • The GMRT + GSB combination offers some unique featuresfor 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

17. Pilot transient surveys with the GMRT • Primary goals: • Technical development • Efficacies at low frequencies • Survey region: • -10o < l < 50o , | b | < 1o @ 610 • -10o < l < 50o, 1o < | b | 3o @ 325 • Data recording • Software backend’s “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

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

19. Examples from the pipeline: a real astrophysical signal

20. Examples from the pipeline: spurious signals (local RFI)

21. Spectral Kurtosis Filter for RFI excision: Implementation on CASPSR Andrew Jameson (Swinburne)

22. Need for high resolutions in time, frequency and DM space An example from the GMRT transient detection pipeline (mode: 7 sub-arrays) • Signals can be as short as tens of micro seconds at GMRT frequencies • Maximum achievable time resolution ~ 30 us with the current pipeline A Giant Pulse from Crab Pulsar at GMRT 610 MHz, Time duration ~ 50 us

23. Processing Requirements De-dispersion (searching in DM parameter space) is the most computationally intensive part of the pipeline • 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 • 30 us, 512-channels • 16 bit data samples • DM range: 0 - 500 • tolerance level: T1.25 GPU dedispersion code by Ben Barsdell (Swinburne)

24. Considerations for the real-time system: false positives and RFI signals

25. Considerations for the real-time system: (false positives + RFI) + real signal

26. Event Analysis (offline) Pipeline Localisation of the event on sky + phasing up + further checks

27. FLAGCAL: A flagging and calibration package Description of the FLAGCAL pipeline in Prasad & Chengalur (2011)

28. Snapshot imaging for event localisation Single pulse from J1752-2806 “dirty” image “Dirty” image After cleaning and self-cal Signal peak ~ 0.27 Jy rms ~ 6 mJy; beam ~ 59” x 10” Currently FLAGCAL + AIPS; will soon be integrated into the main event analysis pipeline

29. Example from Event Analysis Pipeline Detection On phasing up Phase up the array

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