Abstract Details

Name: Subham Ghosh
Affiliation: International Centre for Theoretical Sciences
Conference ID : ASI2024_485
Title : Reconnection driven particle acceleration to understand the non-thermal emission in galaxy clusters
Authors : Subham Ghosh, Pallavi Bhat
Authors Affiliation: International Centre for Theoretical Sciences, Bangalore, 560089, India
Mode of Presentation: Poster
Abstract Category : High Energy Phenomena, Fundamental Physics and Astronomy
Abstract : From observations [1], we see non-thermal emissions, mainly in radio and X-ray extended over a large region (∼ megaparsec) in galaxy clusters. To explain this, the electrons should be energized or accelerated. One explanation is that the energy released during the merger event could be channeled to accelerate electrons through turbulence [2] or shock [3]. However, it is not clear if these methods of acceleration can provide sufficient energization. We look for another particle acceleration mechanism: magnetic reconnection in collisionless plasma. Recently, magnetic reconnection in high-energy collisionless plasmas has been studied using Particle-in-cell (PIC) simulations [4] and observed to give rise to efficient particle acceleration. These PIC simulations are, nevertheless, for relativistic plasmas. On the contrary, the plasma in the intra-cluster medium (ICM) is non-relativistic while being only weakly collisional. Our aim, therefore, is to explore particle acceleration due to reconnection using PIC simulations for non-relativistic, electron-positron plasma. For that, we use the publicly available PIC code WARPX [5,6]. We observe from our simulations that the kinetic energy of the particles increases by around two orders of magnitude due to acceleration in a system with tearing mode reconnection. We obtain the slope of the kinetic energy spectra to be around -1, which is consistent with the previous literature [7]. We find that the energy cut-off is around 100 KeV, which is also consistent with the available energy of the particles in the ICM. References: 1. Bonafede et al., 2014, MNRAS, 444, L44-L48 2. Brunetti et al., 2001, ApJ, 561, L157-L160 3. Ensslin et al., 1998, AA, 332, 395-409 4. Sironi & Spitkovsky, 2014, ApJ, L21 5. https://github.com/ECP-WarpX/WarpX 6. Fedeli et al., 2022, International Conference for High Performance Computing, Networking, Storage and Analysis (SC). ISSN:2167-4337, pp. 25-36, Dallas, TX, US 7. Guo et at., 2015, ApJ, 806, 167