Fast Radio Transients and Next- Generation Instruments In Search of the Rare and Elusive Jean-Pierre Macquart
Scientific Motivation Fast timescale transients probe high brightness temperature emission extreme states of matter physics of strong gravitational fields win Nobel prizes Extragalactic impulsive transients would afford a new view of the huge reservoir of baryons in the ionized IGM
Detecting IGM baryons Cen & Ostriker 1999
Ioka 2003 Extragalactic Dispersion
Known Knowns, Known Unknowns and Unknown Unknowns Known Knowns Giant pulses Magnetars RRATs Known Unknowns Lorimer Bursts Annihilating Black Holes Gravitational Wave Events Unknown Unknowns?
Field of View and Sensitivity Mimimum detectable signal in 1 ms (Jy) Field of view (deg 2 )
Parameter Space Field of View Sensitivity Temporal Resolution Dispersion measure RFI rejection capabilities Event Localisation quality Followup/triggering resources Which holds the greatest reward?
Boolardy at ultrashort timescales 0.4 µs
What about the Lorimer Burst? First detection of local ionized IGM? DM suggests extragalactic, but the time-frequency sweep may not be actually be due to dispersion Position poorly localised Verification difficult with single antenna Long baselines used to veto local RFI Large FoV needed to detect even relatively common events (e.g. GRBs ~1 sky -1 day -1 )
Perytons (a) Peryton 08 in 13 beams (b) Peryton 08 Burke-Spolaor, Bailes, Ekers, Macquart & Crawford, ApJ Lett in press (c) Peryton 06 (d) Peryton 15
Perytons Subsequent discovery of more Lorimer bursts using a dedispersion code But not all objects follow the cold plasma dispersion law DM can vary across the band Emission may be patchy at different frequencies Peryton 06 Peryton 08 Peryton 15
Fast Transients Instrumentation VLBA ICRAR-Curtin/JPL/NRAO [incoherent] DiFX software correlator pipes 1ms telescope powers to a dedispersion/search engine [coherent] Candidates identified and 1s sections of baseband data on candidates dumped Telescope separation - excellent signal localisation & false rejection Proving ground for new approaches: JPL machine learning algorithms, FPGAbased dedispersion hardware GMRT NCRA/Swinburne/ICRAR-Curtin [incoherent] total powers dedispersed using GPU-based hardware [coherent] follow up of candidates using a ~10s buffer CRAFT ICRAR-Curtin/JPL/NRAO/UC Berkeley/ Swinburne/ASTRON et al. ASKAP high time and frequency resolution real-time, wide field transients detection FPGA-based de-dispersers and CPU-based post processors invoking machine learning algorithms FPGAs: combine dedispersion + detection (threshold/machinelearning) on a single board
Commensal VLBA experiment The VFAST-R experiment DiFX dumps 1ms spectrometer data of each telescope to a dedispersion/ detection box Candidate transients identified and raw baseband data dumped at end of correlation Long baselines & high time resolution enables precise localization and high S/N followup Detection box easily portable to ASKAP
VFAST-R algorithm development What if the time-frequency behaviour of a transient is not completely governed by the cold plasma dispersion law?
VFAST-R algorithms (cont)
Conclusions Serendipity - our field is technology bound. In the absence of any other information, parameter space is our goal Fundamental discoveries tend to follow within 5y of a new technical innovation (Harwit; Ekers;...) Corollary: if we don t innovate, we won t discover anything particularly new or interesting Fortune favours the brave, not the stupid: Physics already dictates several limits Nonlinear limiting effects at high brightness temperatures around dense environments Induced Compton Scattering Induced Raman Scattering Multipath propagation/temporal smearing Which innovations will bring us the greatest reward?
Slow Transients
Intra-Day Variable Quasars J1819+3845 PKS 1257-326 (Bignall et al. 2003) Flux density (Jy) 0.30 0.25 0.20 0.15 0 2 4 6 8 10 12 Time (h) 4.8 GHz 8.6 GHz
The MicroArcsecond Scintillation-Induced Variability survey Survey for intra-day variability in 525 compact, flat/invertedspectrum sources @ 4.8 GHz 4 x 3-day epochs spaced throughout a year (+ additional followup session) to eliminate annual-cycle selection effects VLA divided into 5 sub-arrays Aim: form a large sample of IDVs to 1. Understand the properties of the local ISM that causes IDV 2. Determine if the phenomenon is episodic 3. Dependence on source properties (spectral index, flux density, redshift, AGN type)
IDV maps turbulence in ionized hydrogen... Hα all-sky map (as a rough tracer of HII)
IDV maps the ISM on extraordinarily small scales Lovell et al. 2008
Does it also map the IGM? Lovell et al. 2008