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Searching For Low Frequency Fast Radio Bursts With Vlite, Suryarao Bethapudi
Searching For Low Frequency Fast Radio Bursts With Vlite, Suryarao Bethapudi
Theses and Dissertations
The VLITE (VLA Low Band Ionosphere and Transient Experiment; http://vlite.nrao.edu) program performs commensal observations using 16 antennas of the Very Large Array radio telescope from 320-384 MHz. The VLITE-Fast program searches for short time-scale (<100ms) transients, such as Fast Radio Bursts (FRBs), in real time and triggers recording of baseband voltages for offline imaging. Searches are made possible by a 12 node cluster, each housing GPUs for digital signal processing. A real-time Message Passing Interface (MPI)-based co-adder incoherently sums the data streams from all the antennas to boost the signal-to-noise. To undo the dispersion effects of signal propagation through the ionized interstellar medium, the co-added stream is de-dispersed and matched-filtered to search for transients. This operation is completely performed on GPUs by the software package Heimdall . A selection logic is applied to the candidates and interesting candidates with their corresponding data are processed and packaged in a binary file along with a diagnostic plot. Furthermore, a Machine Learning classification is applied on the reduced data product and, based on its decision, baseband voltages are recorded. Reduced data products collected over 126 days of on-sky operation form the VLITE-Fast Pathfinder Survey (VFPS). This pipeline has triggered on single pulses from 7 known radio pulsars. Lastly, the pipeline capabilities are tested against pure random noise and simulated injected signals.
Astroalign: A Python Module For Astronomical Image Registration, Martin Beroiz, Juan B. Cabral, Bruno Sanchez
Astroalign: A Python Module For Astronomical Image Registration, Martin Beroiz, Juan B. Cabral, Bruno Sanchez
Physics and Astronomy Faculty Publications and Presentations
We present an algorithm implemented in the Astroalign Python module for image registration in astronomy. Our module does not rely on WCS information and instead matches three-point asterisms (triangles) on the images to find the most accurate linear transformation between them. It is especially useful in the context of aligning images prior to stacking or performing difference image analysis. Astroalign can match images of different point-spread functions, seeing, and atmospheric conditions.