Simulating TeV gamma-ray morphologies of shell-type supernova remnants

Author:

Pais Matteo1ORCID,Pfrommer Christoph1ORCID

Affiliation:

1. Leibniz-Institut für Astrophysik Potsdam, An der Sternwarte 16, D-14482 Potsdam, Germany

Abstract

ABSTRACT Supernova remnant (SNR) shocks provide favourable sites of cosmic ray (CR) proton acceleration if the local magnetic field direction is quasi-parallel to the shock normal. Using the moving-mesh magnetohydrodynamical (MHD) code arepo we present a suite of SNR simulations with CR acceleration in the Sedov–Taylor phase that combine different magnetic field topologies, density distributions with gradients and large-scale fluctuations, and – for our core-collapse SNRs – a multiphase interstellar medium with dense clumps with a contrast of 104. Assuming the hadronic gamma-ray emission model for the TeV gamma-ray emission, we find that large-amplitude density fluctuations of δρ/ρ0 ≳ 75 per cent are required to strongly modulate the gamma-ray emissivity in a straw man’s model in which the acceleration efficiency is independent of magnetic obliquity. However, this causes strong corrugations of the shock surface that are ruled out by gamma-ray observations. By contrast, magnetic obliquity-dependent acceleration can easily explain the observed variance in gamma-ray morphologies ranging from SN1006 (with a homogeneous magnetic field) to Vela Junior and RX J1713 (with a turbulent field) in a single model that derives from plasma particle-in-cell simulations. Our best-fitting model for SN1006 has a large-scale density gradient of ∇n ≃ 0.0034 cm−3 pc−1 pointing from south-west to north-east and a magnetic inclination with the plane of the sky of ≲10°. Our best-fitting model for Vela Junior and RX J1713 adopts a combination of turbulent magnetic field and dense clumps to explain their TeV gamma-ray morphologies and moderate shock corrugations.

Funder

European Research Council

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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