Relativistic single-particle scattering cross sections for strong electromagnetic waves in strongly magnetized plasma are computed for arbitrary polarization and angle, showing strong suppression and sub-unity optical depth for quasi-parallel propagation.
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5 Pith papers cite this work, alongside 112 external citations. Polarity classification is still indexing.
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Pith papers citing it
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representative citing papers
Model-independent constraints expose kinetic-luminosity and induced-Compton optical-depth bottlenecks that rule out or severely limit external-shock and light-cylinder reconnection FRB models while favoring magnetospheric scenarios with in-situ acceleration.
A 4200-hour campaign on FRB 20240114A finds that the highest-energy bursts account for most of the observed radio energy release, with a break in the energy distribution at ~2×10^40 erg and a linear DM rise of +0.96 pc cm^{-3} over 318 days.
PATH is extended with three fitted P(m_r|z) prior models combined with P(z|DM), raising host-association confidence for ASKAP FRBs while showing fainter-than-expected host magnitude distribution.
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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Scattering of Strong Radio Waves by Particles in Strongly Magnetized Plasmas and Implications for Fast Radio Bursts
Relativistic single-particle scattering cross sections for strong electromagnetic waves in strongly magnetized plasma are computed for arbitrary polarization and angle, showing strong suppression and sub-unity optical depth for quasi-parallel propagation.
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The kinetic-energy bottleneck in Fast Radio Burst models
Model-independent constraints expose kinetic-luminosity and induced-Compton optical-depth bottlenecks that rule out or severely limit external-shock and light-cylinder reconnection FRB models while favoring magnetospheric scenarios with in-situ acceleration.
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A 4200-hour HyperFlash and \'ECLAT campaign on the hyperactive FRB 20240114A: constraining energetics with the most brilliant bursts
A 4200-hour campaign on FRB 20240114A finds that the highest-energy bursts account for most of the observed radio energy release, with a break in the energy distribution at ~2×10^40 erg and a linear DM rise of +0.96 pc cm^{-3} over 318 days.
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Updating the PATH framework with FRB host galaxy models
PATH is extended with three fitted P(m_r|z) prior models combined with P(z|DM), raising host-association confidence for ASKAP FRBs while showing fainter-than-expected host magnitude distribution.
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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.