5 papers · 1 filter
LeoNet: A Machine Learning Method for Binary Pulsar Classification
Zhaocheng Gong, Jack White, Zeyu Yang +3
Binary pulsars provide valuable laboratories for testing theories of gravity, but orbital Doppler shifts complicate their detection. Fourier-domain acceleration and jerk searches a…
Distribution of the Högbom CLEAN Algorithm Using Tiled Images with Feedback
Daniel Wright, Karel Adámek, Wesley Armour
Data sizes for next generation radio telescopes, such as the Square Kilometre Array (SKA), are far above that of their predecessors. The CLEAN algorithm was originally developed by…
Lowering In-Memory Footprint of Antenna Beams via Polynomial Approximation
Ali Taqi, Karel Adámek, Quentin Gueuning +3
With the emergence of new radio telescopes promising larger fields of view at lower observation frequencies (e.g., SKA), addressing direction-dependent effects (DDE) (e.g., directi…
Pulscan: Binary pulsar detection using unmatched filters on NVIDIA GPUs
Jack White, Karel Adámek, Jayanta Roy +2
The Fourier Domain Acceleration Search (FDAS) and Fourier Domain Jerk Search (FDJS) are proven matched filtering techniques for detecting binary pulsar signatures in time-domain ra…
CLEAN algorithm implementation comparisons between popular software packages
Daniel Wright, Karel Adámek, Wesley Armour
The CLEAN algorithm, first published by Högbom and its later variants such as Multiscale CLEAN (msCLEAN) by Cornwell, has been the most popular tool for deconvolution in radio astr…