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Register a new userRFI Flagging Implications for Short-Duration Transients
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With their wide fields of view and often relatively long coverage of any position in the sky in imaging survey mode, modern radio telescopes provide a data stream that is naturally suited to searching for rare transients. However, Radio Frequency Interference (RFI) can show up in the data stream in similar ways to such transients, and thus the normal pre-treatment of filtering RFI (flagging) may also remove astrophysical transients from the data stream before imaging. In this paper we investigate how standard flagging affects the detectability of such transients by examining the case of transient detection in an observing mode used for Low Frequency Array (LOFAR; citep{LOFAR}) surveys. We quantify the fluence range of transients that would be detected, and the reduction of their SNR due to partial flagging. We find that transients with a duration close to the integration sampling time, as well as bright transients with durations on the order of tens of seconds, are completely flagged. For longer transients on the order of several tens of seconds to minutes, the flagging effects are not as severe, although part of the signal is lost. For these transients, we present a modified flagging strategy which mitigates the effect of flagging on transient signals. We also present a script which uses the differences between the two strategies, and known differences between transient RFI and astrophysical transients, to notify the observer when a potential transient is in the data stream.
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Aims: We have analyzed low frequency radio data of tidal disruption event (TDE) Swift J1644+57 to search for a counterpart. We consider how brief transient signals (on the order of seconds or minutes) originating from this location would appear in our data. We also consider how automatic radio frequency interference (RFI) flagging at radio telescope observatories might affect these and other transient observations in the future, particularly with brief transients of a few seconds duration. Methods: We observed the field in the low-frequency regime at 149 MHz with data obtained over several months with the Low Frequency Array (LOFAR). We also present simulations where a brief transient is injected into the data in order to see how it would appear in our measurement sets, and how it would be affected by RFI flagging. Finally, both based on simulation work and the weighted average of the observed background over the course of the individual observations, we present the possibility of brief radio transients in the data. Results: Our observations of Swift J1644+57 yielded no detection of the source and a peak flux density at this position of 24.7 $pm$ 8.9 mJy. Our upper limit on the transient rate of the snapshot surface density in this field at sensitivities < 0.5 Jy is $rho < 2.2 times10^{-2}$ deg$^{-2}$. We also conclude that we did not observe any brief transient signals originating specifically from the Swift J1644+57 source itself, and searches for such transients are severely limited by automatic RFI flagging algorithms which flag transients of less than 2 minutes duration. As such, careful consideration of RFI flagging techniques must occur when searching for transient signals.
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We present an algorithm for the identification of transient noise artifacts (glitches) in cross-correlation searches for long O(10s) gravitational-wave transients. The algorithm utilizes the auto-power in each detector as a discriminator between well-behaved Gaussian noise (possibly including a gravitational-wave signal) and glitches. We test the algorithm with both Monte Carlo noise and time-shifted data from the LIGO S5 science run and find that it is effective at removing a significant fraction of glitches while keeping the vast majority (99.6%) of the data. Using an accretion disk instability signal model, we estimate that the algorithm is accidentally triggered at a rate of less than 10^-5% by realistic signals, and less than 3% even for exceptionally loud signals. We conclude that the algorithm is a safe and effective method for cleaning the cross-correlation data used in searches for long gravitational-wave transients.
We investigate the performance of the generalized Spectral Kurtosis (SK) estimator in detecting and discriminating natural and artificial very short duration transients in the 2-bit sampling time domain Very-Long-Baseline Interferometry (VLBI) data. We demonstrate that, while both types of transients may be efficiently detected, their natural or artificial nature cannot be distinguished if only a time domain SK analysis is performed. However, these two types of transients become distinguishable from each other in the spectral domain, after a 32-bit FFT operation is performed on the 2-bit time domain voltages. We discuss the implication of these findings on the ability of the Spectral Kurtosis estimator to automatically detect bright astronomical transient signals of interests -- such as pulsar or fast radio bursts (FRB) -- in VLBI data streams that have been severely contaminated by unwanted radio frequency interference.
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