most citedDeep Learning Assisted Data Inspection for Radio Astronomy

25 citations · 25 across the 1 of their papers we have counts for

collaborators

5 papers

astro-ph.IM202025 cited

Deep Learning Assisted Data Inspection for Radio Astronomy

Michael Mesarcik, Albert-Jan Boonstra, Christiaan Meijer +3

Modern radio telescopes combine thousands of receivers, long-distance networks, large-scale compute hardware, and intricate software. Due to this complexity, failures occur relativ…

astro-ph.IM2019

A Roadmap towards a Space-based Radio Telescope for Ultra-Low Frequency Radio Astronomy

M. J. Bentum, M. K. Verma, R. T. Rajan +10

The past two decades saw a renewed interest in low frequency radio astronomy, with a particular focus on frequencies above 30 MHz. However, at frequencies below 30 MHz, Earth-based…

astro-ph.IM2019

Peering into the Dark (Ages) with Low-Frequency Space Interferometers

Leon Koopmans, Rennan Barkana, Mark Bentum +28

Neutral hydrogen pervades the infant Universe, and its redshifted 21-cm signal allows one to chart the Universe. This signal allows one to probe astrophysical processes such as the…

cs.AR2019

Near-Memory Computing: Past, Present, and Future

Gagandeep Singh, Lorenzo Chelini, Stefano Corda +5

The conventional approach of moving data to the CPU for computation has become a significant performance bottleneck for emerging scale-out data-intensive applications due to their…

astro-ph.IM2019

Discovering the Sky at the Longest Wavelengths with Small Satellite Constellations

Xuelei Chen, Jack Burns, Leon Koopmans +29

Due to ionosphere absorption and the interference by natural and artificial radio emissions, ground observation of the sky at the decameter or longer is very difficult. This unexpl…