Hostname: page-component-7479d7b7d-k7p5g Total loading time: 0 Render date: 2024-07-11T18:46:11.386Z Has data issue: false hasContentIssue false
  • English
  • Français

Interplay of various particle acceleration processes in astrophysical environment

Published online by Cambridge University Press:  20 January 2023

Sayan Kundu Open the ORCID record for Sayan Kundu [Opens in a new window]  and
Bhargav Vaidya
Sayan Kundu*
Affiliation:
Department of Astronomy, Astrophysics and Space Engineering Indian Institute of Technology, Indore Madhya Pradesh, India - 452020
Bhargav Vaidya
Affiliation:
Department of Astronomy, Astrophysics and Space Engineering Indian Institute of Technology, Indore Madhya Pradesh, India - 452020
*
*sayan.astronomy@gmail.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Astrophysical systems possess various sites of particle acceleration, which gives rise to the observed non-thermal spectra. Diffusive shock acceleration (DSA) and stochastic turbulent acceleration (STA) are the candidates for producing very high energy particles in weakly magnetized regions. While DSA is a systematic acceleration process, STA is a random energization process, usually modelled as a biased random walk in energy space with a Fokker-Planck equation. In astrophysical systems, different acceleration processes work in an integrated manner along with various energy losses.

Here we study the interplay of both STA and DSA in addition to various energy losses, in a simulated RMHD jet cocoon. Further, we consider a phenomenologically motivated STA timescale and discuss its effect on the emission profile of the RMHD jet. A parametric study on the turbulent acceleration timescale is also conducted to showcase the effect of turbulence damping on the emission structure of the simulated jet.

Keywords

Acceleration of particlesRadiation mechanisms: nonthermalPlasmasTurbulence
Type
Contributed Paper
Information
Proceedings of the International Astronomical Union , Volume 16 , Symposium S362: The Predictive Power of Computational Astrophysics as a Discovery Tool , June 2020 , pp. 365 - 372
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of International Astronomical Union

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Matthews, J. H., Bell, A. R., Araudo, A. T., Blundell, K. M., 2019, EPJWC, 210, 04002. doi: 10.1051/epjconf/201921004002 CrossRefGoogle Scholar
Fraschetti, F., Giacalone, J., 2012, ApJ, 755, 114. doi: 10.1088/0004-637X/755/2/114 Google Scholar
Hanasz, M., Strong, A. W., Girichidis, P., 2021, LRCA, 7, 2. doi: 10.1007/s41115-021-00011-1 CrossRefGoogle Scholar
Winner, G., Pfrommer, C., Girichidis, P., Pakmor, R., 2019, MNRAS, 488, 2235. doi: 10.1093/mnras/stz1792 Google Scholar
Vazza, F., Wittor, D., Brunetti, G., Brüggen, M., 2021, A&A, 653, A23. doi: 10.1051/0004-6361/202140513 Google Scholar
Petrosian, V., 2012, SSRv, 173, 535. doi: 10.1007/s11214-012-9900-6 Google Scholar
Vurm, I., Poutanen, J., 2009, ApJ, 698, 293. doi: 10.1088/0004-637X/698/1/293 CrossRefGoogle Scholar
Ferrand, G., Marcowith, A., 2010, A&A, 510, A101. doi: 10.1051/0004-6361/200913520 Google Scholar
Schlickeiser, R., Dermer, C. D., 2000, A&A, 360, 789 Google Scholar
O’Sullivan, S., Reville, B., Taylor, A. M., 2009, MNRAS, 400, 248. doi: 10.1111/j.1365-2966.2009.15442.x CrossRefGoogle Scholar
Fan, Z.-H., Liu, S., Wang, J.-M., Fryer, C. L., Li, H., 2008, ApJL, 673, L139. doi: 10.1086/528372 CrossRefGoogle Scholar
Donnert, J., Brunetti, G., 2014, MNRAS, 443, 3564. doi: 10.1093/mnras/stu1417 CrossRefGoogle Scholar
Asano, K., Hayashida, M., 2018, ApJ, 861, 31. doi: 10.3847/1538-4357/aac82a CrossRefGoogle Scholar
Blandford, R. D., 1994, ApJS, 90, 515. doi: 10.1086/191869 Google Scholar
Marcowith, A., Ferrand, G., Grech, M., Meliani, Z., Plotnikov, I., Walder, R., 2020, LRCA, 6, 1. doi: 10.1007/s41115-020-0007-6 Google Scholar
Webb, G. M., 1989, ApJ, 340, 1112. doi: 10.1086/167462 CrossRefGoogle Scholar
Fermi, E., 1949, PhRv, 75, 1169. doi: 10.1103/PhysRev.75.1169 Google Scholar
Vaidya, B., Mignone, A., Bodo, G., Rossi, P., Massaglia, S., 2018, ApJ, 865, 144. doi: 10.3847/1538-4357/aadd17 CrossRefGoogle Scholar
Kundu, S., Vaidya, B., Mignone, A., 2021, ApJ, 921, 74. doi: 10.3847/1538-4357/ac1ba5 CrossRefGoogle Scholar
Mukherjee, D., Bodo, G., Rossi, P., Mignone, A., Vaidya, B., 2021, MNRAS, 505, 2267. doi: 10.1093/mnras/stab1327 CrossRefGoogle Scholar
Brunetti, G., Lazarian, A., 2007, MNRAS, 378, 245. doi: 10.1111/j.1365-2966.2007.11771.x Google Scholar
Schlickeiser, R., 2002, cra.bookGoogle Scholar
Mignone, A., Bodo, G., Massaglia, S., Matsakos, T., Tesileanu, O., Zanni, C., Ferrari, A., 2007, ApJS, 170, 228. doi: 10.1086/513316 CrossRefGoogle Scholar