Despite their ubiquity, the origin of cosmic magnetic fields remains unknown. Various mechanisms have been proposed for their existence, including primordial fields generated by inflation and amplification and injection by compact astrophysical objects. Separating the potential impact of each magnetogenesis scenario on the magnitude and orientation of the magnetic field and their impact on gas dynamics may give insight into the physics that magnetized our Universe. In this work, we demonstrate that because the induction equation and solenoidal constraint are linear with B, the contribution from different sources of magnetic fields can be separated in cosmological magnetohydrodynamic (MHD) simulations and their evolution and influence on the gas dynamics can be tracked. Exploiting this property, we develop a magnetic field tracer algorithm for cosmological simulations that can track the origin and evolution of different components of the magnetic field. We present a suite of cosmological magnetohydrodynamical RAMSES simulations that employ this algorithm where the primordial field strength is varied to determine the contributions of the primordial and supernova-injected magnetic fields to the total magnetic energy as a function of time and spatial location. We find that, for our specific model, the supernova-injected fields rarely penetrate far from haloes, despite often dominating the total magnetic energy in the simulations. The magnetic energy density from the supernova-injected field scales with density with a power-law slope steeper than 4/3 and often dominates the total magnetic energy inside haloes. However, the star formation rates in our simulations are not affected by the presence of magnetic fields, for the ranges of primordial field strengths examined. These simulations represent a first demonstration of the magnetic field tracer algorithm, which we suggest will be an important tool for future cosmological MHD simulations.
Bibliographical noteFunding Information:
We thank the anonymous referee for their comments that improved the manuscript. This work made considerable use of the open source analysis software PYNBODY (Pontzen et al. 2013). HK thanks Brasenose College and the support of the Nicholas Kurti Junior Fellowship as well as the Beecroft Fellowship. This work was supported by the Oxford Centre for Astrophysical Surveys, which is funded through generous support from the Hintze Family Charitable Foundation. TK acknowledges support by the National Research Foundation of Korea to the Center for Galaxy Evolution Research (No. 2017R1A5A1070354) and in part by the Yonsei University Future-leading Research Initiative of 2017 (RMS2-2017-22-0150).
This work used the DiRAC Data Centric system at Durham University, operated by the Institute for Computational Cosmology on behalf of the STFR DiRAC HPC Facility (www.dirac.ac.uk). This equipment was funded by the BIS National E-infrastructure capital grant ST/K00042X/1, STFC capital grant ST/K00087X/1, DiRAC operations grant ST/K003267/1 and Durham University. DiRAC is part of the National E-Infrastructure.
All Science Journal Classification (ASJC) codes
- Astronomy and Astrophysics
- Space and Planetary Science