CHIME/FRB has now cataloged 80 repeating FRB sources whose burst rates and upper limits are consistent with a power-law distribution implying 50-100% of all FRBs repeat.
Title resolution pending
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
representative citing papers
The BURSTT back-end system achieves real-time multi-stage beamforming and de-dispersion search to detect FRBs and trigger VLBI localization using RFSoC and optimized server processing.
Frabjous applies deep learning to classify FRB morphologies into five classes at 55% accuracy by augmenting limited real data with simulations.
citing papers explorer
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Discovery of 30 Repeating Fast Radio Burst Sources and Uniform Population Statistics of 80 Repeating Sources from CHIME/FRB
CHIME/FRB has now cataloged 80 repeating FRB sources whose burst rates and upper limits are consistent with a power-law distribution implying 50-100% of all FRBs repeat.
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Back-End System of BURSTT
The BURSTT back-end system achieves real-time multi-stage beamforming and de-dispersion search to detect FRBs and trigger VLBI localization using RFSoC and optimized server processing.
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Frabjous: Deep Learning Fast Radio Burst Morphologies
Frabjous applies deep learning to classify FRB morphologies into five classes at 55% accuracy by augmenting limited real data with simulations.