6 papers
Pointing Model Meets Deep Learning: A Retrospective Study on a MeerKAT+ Telescope Applying Deep Learning Methods for Blind Pointing Corrections
Stefan Thoms, Matthias Reichert
This study aims to compare the effectiveness of deep learning methods, specifically Feedforward Neural Networks (FNNs), with traditional Pointing Models (PMs) for compensating Blin…
Optimizing Wavefront-Deformation Sensor Placement for Active Radio-Telescope Surfaces
Stefan Thoms, Martin Timpe, Matthias Reichert
Next-generation high-frequency radio telescopes require primary-surface accuracies that passive structures alone cannot reliably achieve. The Atacama Large Aperture Submillimeter T…
The Atacama Large Aperture Submillimeter Telescope (AtLAST): enabling large-scale sub-mm science beyond 2030
Claudia Cicone, Tony Mroczkowski, Evanthia Hatziminaoglou +38
AtLAST is designed to be the largest (sub-)mm single-dish astronomical observatory and the first climate-neutral modern research infrastructure. It offers a unique combination of l…
Simulation-based dynamic pointing analysis of AtLAST under wind loading and fast-scan conditions
Aleksej Kiselev, Martin Timpe, Matthias Reichert +2
The Atacama Large Aperture Submillimeter Telescope (AtLAST) is a next-generation 50-m class single-dish facility concept designed for high-throughput, wide-field mapping at millime…
Instrument design and performance of the first seven stations of RNO-G
S. Agarwal, J. A. Aguilar, N. Alden +78
The Radio Neutrino Observatory in Greenland (RNO-G) is the first in-ice radio array in the northern hemisphere for the detection of ultra-high energy neutrinos via the coherent rad…
The conceptual design of the 50-meter Atacama Large Aperture Submillimeter Telescope (AtLAST)
Tony Mroczkowski, Patricio A. Gallardo, Martin Timpe +23
The (sub)millimeter sky contains a vast wealth of information that is both complementary and inaccessible to other wavelengths. Over half the light we receive is observable at (sub…