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arXiv · 2111.03405

Probing the High-energy $\gamma$-ray Emission Mechanism in the Vela Pulsar via Phase-resolved Spectral and Energy-dependent Light Curve Modeling

Abstract

Recent kinetic simulations sparked a debate regarding the emission mechanism responsible for pulsed GeV $\gamma$-ray emission from pulsars. Some models invoke curvature radiation, while other models assume synchrotron radiation in the current-sheet. We interpret the curved spectrum of the Vela pulsar as seen by H.E.S.S. II (up to $\sim$100 GeV) and the $Fermi$ Large Area Telescope (LAT) to be the result of curvature radiation due to primary particles in the pulsar magnetosphere and current sheet. We present phase-resolved spectra and energy-dependent light curves using an extended slot gap and current sheet model, invoking a step function for the accelerating electric field as motivated by kinetic simulations. We include a refined calculation of the curvature radius of particle trajectories in the lab frame, impacting the particle transport, predicted light curves, and spectra. Our model reproduces the decrease of the flux of the first peak relative to the second one, evolution of the bridge emission, near-constant phase positions of peaks, and narrowing of pulses with increasing energy. We can explain the first of these trends because we find that the curvature radii of the particle trajectories in regions where the second $\gamma$-ray light curve peak originates are systematically larger than those associated with the first peak, implying that the spectral cutoff of the second peak is correspondingly larger. However, an unknown azimuthal dependence of the $E$-field as well as uncertainty in the precise spatial origin of the GeV emission, precludes a simplistic discrimination of emission mechanisms.

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Monica Barnard, Christo Venter, Alice K. Harding, Constantinos Kalapotharakos, Tyrel J. Johnson. 2021-11-05. Probing the High-energy $\gamma$-ray Emission Mechanism in the Vela Pulsar via Phase-resolved Spectral and Energy-dependent Light Curve Modeling. https://doi.org/10.3847/1538-4357%2Fac2a3d

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