Fast Radio Bursts (FRBs), are millisecond radio signals that exhibit dispersion larger than what the Galactic electron density can account for. We have conducted a 1446 hour survey for Fast Radio Bursts (FRBs) at 145 MHz, covering a total of 4193 sq. deg on the sky. We used the UK station of the LOFAR radio telescope -the Rawlings Array -, accompanied for a majority of the time by the LOFAR station at Nançay, observing the same fields at the same frequency. Our real-time search backend, ARTEMIS, utilizes graphics processing units to search for pulses with dispersion measures up to 320 cm −3 pc. Previous derived FRB rates from surveys around 1.4 GHz, and favoured FRB interpretations, motivated this survey, despite all previous detections occurring at higher dispersion measures. We detected no new FRBs above a signal-to-noise threshold of 10, leading to the most stringent upper limit yet on the FRB event rate at these frequencies: 29 sky −1 day −1 for 5 ms-duration pulses above 62 Jy. The non-detection could be due to scatter-broadening, limitations on the volume and time searched, or the shape of FRB flux density spectra. Assuming the latter and that FRBs are standard candles, the non-detection is compatible with the published FRB sky rate, if their spectra follow a power law with frequency (∝ ν α ), with α +0.1, demonstrating a marked difference from pulsar spectra. Our results suggest that surveys at higher frequencies, including the low frequency component of the Square Kilometre Array, will have better chances to detect, estimate rates and understand the origin and properties of FRBs.
Context. Modern radio astronomical arrays have (or will have) more than one order of magnitude more receivers than classical synthesis arrays, such as the VLA and the WSRT. This makes gain calibration a computationally demanding task. Several alternating direction implicit (ADI) approaches have therefore been proposed that reduce numerical complexity for this task from O(P 3 ) to O(P 2 ), where P is the number of receive paths to be calibrated Aims. We present an ADI method, show that it converges to the optimal solution, and assess its numerical, computational and statistical performance. We also discuss its suitability for application in self-calibration and report on its successful application in LOFAR standard pipelines. Methods. Convergence is proved by rigorous mathematical analysis using a contraction mapping. Its numerical, algorithmic, and statistical performance, as well as its suitability for application in self-calibration, are assessed using simulations. Results. Our simulations confirm the O(P 2 ) complexity and excellent numerical and computational properties of the algorithm. They also confirm that the algorithm performs at or close to the Cramer-Rao bound (CRB, lower bound on the variance of estimated parameters). We find that the algorithm is suitable for application in self-calibration and discuss how it can be included. We demonstrate an order-of-magnitude speed improvement in calibration over traditional methods on actual LOFAR data. Conclusions. In this paper, we demonstrate that ADI methods are a valid and computationally more efficient alternative to traditional gain calibration methods and we report on its successful application in a number of actual data reduction pipelines.
The identification, and subsequent discovery, of fast radio transients through blind-search surveys requires a large amount of processing power, in worst cases scaling as $\mathcal{O}(N^3)$. For this reason, survey data are generally processed offline, using high-performance computing architectures or hardware-based designs. In recent years, graphics processing units have been extensively used for numerical analysis and scientific simulations, especially after the introduction of new high-level application programming interfaces. Here we show how GPUs can be used for fast transient discovery in real-time. We present a solution to the problem of de-dispersion, providing performance comparisons with a typical computing machine and traditional pulsar processing software. We describe the architecture of a real-time, GPU-based transient search machine. In terms of performance, our GPU solution provides a speed-up factor of between 50 and 200, depending on the parameters of the search.Comment: Accepted for publication (2011 July 12): Monthly Notices of the Royal Astronomical Society, 10 pages, 9 figures and 6 table
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