Volume 484, Number 1, June II 2008
|Page(s)||267 - 273|
|Section||Interstellar and circumstellar matter|
|Published online||16 April 2008|
High-energy neutrino emission from shell-type supernova remnants
Department of Physics, Yunnan University, Kunming, PR China e-mail: firstname.lastname@example.org
2 Department of Physics, Zhaotong College, Zhaotong, PR China
Accepted: 26 March 2008
Based on a time-dependent model of particle production and non-thermal photon emission, we study high-energy neutrino emission from shell-type supernova remnants (SNRs). In such a model, particles are accelerated to relativistic energies through the shock acceleration mechanism and evolve with time in an SNR. For a given SNR, therefore, the temporal evolution of the particle energy distribution, the non-thermal spectrum of photons, and the spectrum of neutrinos can be calculated numerically. We apply the model to two young SNRs, G347.3-0.5 and G266.2-1.2, and two old ones, G8.7-0.1 and G23.3-0.3. For each SNR, we determine the parameters involved in the model by comparing the predicted non-thermal spectrum with the observed radio, X-ray and γ-ray data. We study the properties of the corresponding neutrino emission, including the neutrino spectrum and the event rates expected in the next-generation km3-scale neutrino telescope, KM3NeT. Our results indicate that the high-energy TeV γ-rays from the four SNRs are produced predominately via hadronic interaction and that young SNRs such as G266.2-1.2 and G347.3-0.5 are the potential neutrino sources whose neutrinos are most likely to be identified by next-generation km3 neutrino telescopes.
Key words: gamma rays: theory / neutrinos / radiation mechanisms: non-thermal / supernova remnants
© ESO, 2008
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.