Observing pulsars and fast transients with LOFAR

Low frequency radio waves, while challenging to observe,are a rich source of information about pulsars. The LOw Frequency ARray (LOFAR) is a new radio interferometer operating in the lowest 4 octaves of the ionospheric “radio window”: 10–240 MHz, that will greatly facilitate observing pulsars at low radio frequencies. Through the huge collecting area, long baselines, and flexible digital hardware, it is expected that LOFAR will revolutionize radio astronomy at the lowest frequencies visible from Earth.LOFAR is a next-generation radio telescope and a pathfinder to the Square Kilometre Array (SKA), in that it incorporates advanced multi-beaming techniques between thousands of individual elements. We discuss the motivation for low-frequency pulsar observations in general and the potential of LOFAR in addressing these science goals.We present LOFAR as it is designed to perform high-time-resolution observations of pulsars and other fast transients, and outline the various relevant observing modes and data reduction pipelines that are already or will soon be implemented to facilitate these observations. A number of results obtained from commissioning observations are presented to demonstrate the exciting potential of the telescope. This paper outlines the case for low frequency pulsar observations and is also intended to serve as a reference for upcoming pulsar/fast transient science papers with LOFAR

Adaptive Real Time Imaging Synthesis Telescopes

The digital revolution is transforming astronomy from a data-starved to a data-submerged science. Instruments such as the Atacama Large Millimeter Array (ALMA), the Large Synoptic Survey Telescope (LSST), and the Square Kilometer Array (SKA) will measure their accumulated data in petabytes. The capacity to produce enormous volumes of data must be matched with the computing power to process that data and produce meaningful results. In addition to handling huge data rates, we need adaptive calibration and beamforming to handle atmospheric fluctuations and radio frequency interference, and to provide a user environment which makes the full power of large telescope arrays accessible to both expert and non-expert users. Delayed calibration and analysis limit the science which can be done. To make the best use of both telescope and human resources we must reduce the burden of data reduction. Our instrumentation comprises of a flexible correlator, beam former and imager with digital signal processing closely coupled with a computing cluster. This instrumentation will be highly accessible to scientists, engineers, and students for research and development of real-time processing algorithms, and will tap into the pool of talented and innovative students and visiting scientists from engineering, computing, and astronomy backgrounds. Adaptive real-time imaging will transform radio astronomy by providing real-time feedback to observers. Calibration of the data is made in close to real time using a model of the sky brightness distribution. The derived calibration parameters are fed back into the imagers and beam formers. The regions imaged are used to update and improve the a-priori model, which becomes the final calibrated image by the time the observations are complete

Hydrogen Epoch of Reionization Array (HERA)

The Hydrogen Epoch of Reionization Array (HERA) is a staged experiment to measure 21 cm emission from the primordial intergalactic medium (IGM) throughout cosmic reionization ($z=6-12$), and to explore earlier epochs of our Cosmic Dawn ($z\sim30$). During these epochs, early stars and black holes heated and ionized the IGM, introducing fluctuations in 21 cm emission. HERA is designed to characterize the evolution of the 21 cm power spectrum to constrain the timing and morphology of reionization, the properties of the first galaxies, the evolution of large-scale structure, and the early sources of heating. The full HERA instrument will be a 350-element interferometer in South Africa consisting of 14-m parabolic dishes observing from 50 to 250 MHz. Currently, 19 dishes have been deployed on site and the next 18 are under construction. HERA has been designated as an SKA Precursor instrument. In this paper, we summarize HERA's scientific context and provide forecasts for its key science results. After reviewing the current state of the art in foreground mitigation, we use the delay-spectrum technique to motivate high-level performance requirements for the HERA instrument. Next, we present the HERA instrument design, along with the subsystem specifications that ensure that HERA meets its performance requirements. Finally, we summarize the schedule and status of the project. We conclude by suggesting that, given the realities of foreground contamination, current-generation 21 cm instruments are approaching their sensitivity limits. HERA is designed to bring both the sensitivity and the precision to deliver its primary science on the basis of proven foreground filtering techniques, while developing new subtraction techniques to unlock new capabilities. The result will be a major step toward realizing the widely recognized scientific potential of 21 cm cosmology.Comment: 26 pages, 24 figures, 2 table

Applying Deep Learning to Fast Radio Burst Classification

Upcoming Fast Radio Burst (FRB) surveys will search $\sim$10\,$^3$ beams on sky with very high duty cycle, generating large numbers of single-pulse candidates. The abundance of false positives presents an intractable problem if candidates are to be inspected by eye, making it a good application for artificial intelligence (AI). We apply deep learning to single pulse classification and develop a hierarchical framework for ranking events by their probability of being true astrophysical transients. We construct a tree-like deep neural network (DNN) that takes multiple or individual data products as input (e.g. dynamic spectra and multi-beam detection information) and trains on them simultaneously. We have built training and test sets using false-positive triggers from real telescopes, along with simulated FRBs, and single pulses from pulsars. Training of the DNN was independently done for two radio telescopes: the CHIME Pathfinder, and Apertif on Westerbork. High accuracy and recall can be achieved with a labelled training set of a few thousand events. Even with high triggering rates, classification can be done very quickly on Graphical Processing Units (GPUs). That speed is essential for selective voltage dumps or issuing real-time VOEvents. Next, we investigate whether dedispersion back-ends could be completely replaced by a real-time DNN classifier. It is shown that a single forward propagation through a moderate convolutional network could be faster than brute-force dedispersion; but the low signal-to-noise per pixel makes such a classifier sub-optimal for this problem. Real-time automated classification may prove useful for bright, unexpected signals, both now and in the era of radio astronomy when data volumes and the searchable parameter spaces further outgrow our ability to manually inspect the data, such as for SKA and ngVLA

Pathway to the Square Kilometre Array - The German White Paper -

The Square Kilometre Array (SKA) is the most ambitious radio telescope ever planned. With a collecting area of about a square kilometre, the SKA will be far superior in sensitivity and observing speed to all current radio facilities. The scientific capability promised by the SKA and its technological challenges provide an ideal base for interdisciplinary research, technology transfer, and collaboration between universities, research centres and industry. The SKA in the radio regime and the European Extreme Large Telescope (E-ELT) in the optical band are on the roadmap of the European Strategy Forum for Research Infrastructures (ESFRI) and have been recognised as the essential facilities for European research in astronomy. This "White Paper" outlines the German science and R&D interests in the SKA project and will provide the basis for future funding applications to secure German involvement in the Square Kilometre Array.Comment: Editors: H. R. Kl\"ockner, M. Kramer, H. Falcke, D.J. Schwarz, A. Eckart, G. Kauffmann, A. Zensus; 150 pages (low resolution- and colour-scale images), published in July 2012, language English (including a foreword and an executive summary in German), the original file is available via the MPIfR homepag

Radio-Astronomical Imaging on Accelerators

Imaging is considered the most compute-intensive and therefore most challenging part of a radio-astronomical data-processing pipeline. To reach the high dynamic ranges imposed by the high sensitivity and large field of view of the new generation of radio telescopes such as the Square Kilometre Array (SKA), we need to be able to correct for direction-independent effects (DIEs) such as the curvature of the earth as well as for direction-dependent time-varying effects (DDEs) such as those caused by the ionosphere during imaging. The novel Image-Domain gridding (IDG) algorithm was designed to avoid the performance bottlenecks of traditional imaging algorithms. We implement, optimize, and analyze the performance and energy efficiency of IDG on a variety of hardware platforms to find which platform is the best for IDG. We analyze traditional CPUs, as well as several accelerators architectures. IDG alleviates the limitations of traditional imaging algorithms while it enables the advantages of GPU acceleration: better performance at lower power consumption. The hardware-software co-design has resulted in a highly efficient imager. This makes IDG on GPUs an ideal candidate for meeting the computational and energy efficiency constraints of the SKA. IDG has been integrated with a widely-used astronomical imager (WSClean) and is now being used in production by a variety of different radio observatories such as LOFAR and the MWA. It is not only faster and more energy-efficient than its competitors, but it also produces better quality images