Magnetogenesis and the Cosmic Web: A Joint Challenge for Radio Observations and Numerical Simulations
Abstract
:1. Introduction
1.1. The Puzzling Origin of Cosmic Magnetism
1.2. The Magnetic Cosmic Web and Its Radio Observations
2. Methods and Materials: Cosmological Simulations of the Cosmic Web
- P: a baseline primordial model in which we initialised a spatially uniform seed field at the start of the simulation;
- DYN5: a run starting from a negligible and spatially uniform seed field, in which we used a sub-grid model for turbulent dynamo amplification (see Appendix A), for cells with a gas density , i.e., basically already within filaments;
- CSF2: a run including radiative cooling, star formation and feedback, starting from a negligible and spatially uniform seed field. Magnetic fields are released at every episode of thermal feedback from star formation (with a fixed small conversion efficiency per event, ≤10%), to reproduce an astrophysical seeding scenario in which winds from supernova remnant magnetise the large-scale structures.
- CSFBH2: similar to CSF2, but also including the formation, growth, merger and feedback events of supermassive black holes. In addition, in this case, magnetic energy is released by SMBH feedback events (∼10% of the feedback energy) mimicking an astrophysical seeding scenario in which active galactic nuclei magnetise large-scale structures. The model parameters for baryon physics were tuned in previous work to reproduce cosmic star formation history and galaxy groups/clusters scaling relations (see Appendix A).
- P01: a simple primordial model in which we initialised a spatially uniform seed field at the start of the simulation, and in which we allowed for the sub-grid dynamo amplification of magnetic fields only for cells with a gas density , which approximately marks region within the virial radius of halos, where turbulence is predicted to be well developed and mostly solenoidal [106]. As a further relevant difference with the “old” DYN5, the amplification efficiency is increased by a factor 10 for , leading to more realistic magnetic fields in low-redshift clusters and groups.
- CMB2, CMB3, and CMB4: we simulated primordial magnetic fields derived from the constraints by the Cosmic Microwave Background observations following our recent work [105]. In detail, the fields scale dependence is described by a power law spectrum: characterised by a constant spectral index and an amplitude, commonly referred by smoothing the fields within a scale , and therefore in the remainder of the paper we will use to refer to the smoothed magnetic field amplitude. In this work, we used the three models outlined in [105], which resulted as the least challenged by low-redshift radio observations of the cosmic web: we assumed (CMB2), (CMB3) and (CMB4) and , and (comoving), respectively. All runs also adopted the same run-time sub-grid model for dynamo amplification, as in the P01 model.
3. Results
- none of these simulations is optimal to simulate the ICM or intracluster bridges in detail because their modest resolution prevents us from properly resolving the “MHD scale” which is key for the development of a small-scale dynamo e.g., [14]. Hence, the comparison is not very informative here.
- in the very low-density Universe, the P and the DYN5 models have some tension with CMB limits. This problem is not as severe for astrophysical models. Vice versa, both CSF2 and CSFBH2 models produce a too low magnetisation in very low-density regions, in disagreement with blazar limits [54].
- the non-detection of diffuse emission in cluster–cluster filaments with LOFAR-HBA [86] is consistent with all models. The non-detection of the galaxy-synchrotron cross-correlation [88] is in disagreement with the primordial model as well as on the DYN5 model because an excess cross-correlated signal is to be expected, as we discussed in [104].
- likewise, the upper limits on Faraday Rotation by [97], and even more the RM difference between pairs of giant radio galaxies by [100], appear hard to reconcile with the large primordial seed field of the P model, as well as with the widespread amplification of magnetic fields in filaments included in the DYN5 model.
- the stacking detection of flat spectrum synchrotron emission between pairs of halos by [70] is only apparently consistent with all models. However, in that work, the detailed analysis of these simulations also showed that the DYN5 and CSFBH2 models are incapable of producing enough radio emission compatible with the observed extend of the stacking excess. In all astrophysical scenarios, some patches of high magnetic field can be found within filaments. These are typically confined to the active galaxies, from which they were released, and cannot efficiently fill the most peripheral layers of filaments, where most of the emission from the shocked gas comes from in our models.
4. Discussion and Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
AGN | Active Galactic Nucleus |
AMR | Adaptive Mesh Refinement |
CMB | Cosmic Microwave Background |
FRB | Fast Radio Bursts |
GLEAM | The Galactic and Extra Galactic All Sky MWA Survey |
GPU | Graphics Processing Unit |
HBA | High Band Antenna |
HLL | Harten-Lax van Leer |
ICM | Intra Cluster Medium |
IGM | Inter Galactic Medium |
IR | Infa Red |
JVLA | Karl G. Jansky Very Large Array |
KAT | Karoo Array Telescope |
LOFAR | Low Frequency Array |
LOS | Line-of-Sight |
MAGOCW | The Magnetised Cosmic Web |
MeerKAT | MeerKAT |
MHD | Magneto Hydro Dynamics |
MWA | Murchison Widefield Array |
PLM | Piecewise Linear Method |
RK | Runge–Kutta |
RM | Rotation Measure |
SDSS | Sloan Digital Sky Survey |
SKA | Square Kilometer Array |
SMBH | Super Massive Black Hole |
TVD | Total Variation Dininishing |
UHECR | Ultra High Energy Cosmic Rays |
WHIM | Warm Hot Interagalactic Medium |
CDM | Lambda Cold Dark Matter |
Appendix A. Numerical Simulations
- Sub-grid dynamo amplification: in most runs, we estimated at run-time the unresolvable amplification of magnetic fields with an approximate sub-grid approach to incorporate small-scale dynamo amplification and overcome the impossibility of employing adaptive mesh refinement everywhere in the simulation. This is done by measuring the gas vorticity at run-time and using it to guess the dissipation rate of solenoidal turbulence into magnetic field amplification. We assume that a small fraction, , of such kinetic power gets channeled into the amplification of magnetic fields, , where L is the stencil of cells to compute the vorticity. The fraction of turbulent kinetic power that gets converted into magnetic energy, , sets the amplified magnetic energy as . For a reasonable guess on , we followed the fitting formulas given by [149], and set the saturation level and the typical growth time of magnetic fields as a function of the local Mach number of the flow (), and set , where is the ratio between magnetic and kinetic energy at saturation, and is the growth rate, taken from [149]. The topology of the newly created magnetic fields is for simplicity taken to be parallel to the local gas vorticity. Manifestly, this procedure is much simpler than more sophisticated subgrid models [150]. However, this simplistic method reproduced the results obtained by other methods e.g., [7,65,130]. In these runs, we adopt the same amplification efficiency calibrated in [65] for the DYN5 run, but in all other new runs (P, CMB2, CMB3, CMB4), we allowed the sub-grid model to be activated only for , i.e., only within the virial radius of halos, where turbulence is predicted to be well developed and mostly solenoidal, and we increased by a factor 10 the amplification for , where the virialisation of halos is also expected to maximise the amplification of magnetic fields via small-scale dynamo e.g., [16,151].
- Astrophysical sources of magnetisation: in runs including radiative (equilibrium) cooling, gas undergoes collapse and can form stars, or supermassive black holes. We resorted here to the numerical recipes in the public version of ENZO [101] to further release of magnetic dipoles, with a total magnetic energy per event which is a fixed fraction of the feedback energy. The injection of additional magnetic energy via bipolar jets happens with an efficiency with respect to the feedback energy, the latter being times the energy accreted by star forming particles. Likewise, we use the prescriptions by ENZO [152] to inject and grow SMBH and attach magnetic feedback to their thermal feedback. We assume accretion for SMBH following from the spherical Bondi–Hoyle formula with a fixed accretion rate, and a fixed “boost” factor to the mass growth rate of SMBH () to balance the effect of coarse resolution, properly resolving the mass accretion rate onto our simulated SMBH particles. The injection of additional magnetic energy via bipolar jets happens with an efficiency and efficiency with respect to the thermal feedback energy, which is set to be . The only run presented here which features magnetisation by stars and supermassive black hole feedback is CSFBH2, which was shown to yield the most realistic results on the cosmic star formation history, as well as on scaling relations of galaxy clusters and groups in earlier work [65,104]. We also showed results from the CSF2 run, which only contains feedback from the star forming phase.
1 | The full list of acronyms used in this work is given in the Abbreviations section at the end of the paper. |
2 | |
3 | The volume rendering was realised using the CG Animation Software Blender in which we imported the ENZO simulation data previously converted in the openVDB format. This data format is optimised to maximise the shading of the volume rendering (and so the resolution and contrast of quantities’ small details) using light tracing not reachable with standard scientific visualisation tools such as Paraview. |
4 | https://cosmosimfrazza.myfreesites.net/erc-magcow, accessed on 12 November 2021. |
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Observation | Estimate on | Approx. Density Range | Instrument(s) | References |
---|---|---|---|---|
Sync.in cluster bridges | ∼0.2–0.5 μG | –200 | LOFAR-HBA (120 MHz) | [82,84] |
Sync. in cluster pairs | ≤0.25 μG | –50 | LOFAR-HBA (120 MHz) | [86] |
Optical-radio cross-corr. | ≤0.25 μG | – | MWA-EoR0 (180 MHz) | [87,88] |
Sync. stacking of cluster pairs | ∼10–20 nG | –50 | MWA+LWA (50–120 MHz) | [70] |
of radio gal. pairs | ≤40 nG | –10 | VLA-NVSS (1400 MHz) | [98] |
of radio gal. pairs | ≤4 nG | –10 | LOFAR-HBA (120 MHz) | [99,100] |
cross-correlation | ≤30 nG | –10 | VLA-NVSS (1400 MHz) | [97] |
Excess across z | ≤1.7 nG | VLA-NVSS (1400 MHz) | [94] | |
CMB anisotropies T&P | ≤2.8 nG | PLANCK2018+BK15+SPTPol | [49] | |
CMB heating | ≤0.83 nG | PLANCK-2015 | [59] | |
Excess Sync. Radiation | ≤– | ARCADE2+LW1 (78 MHz) | [63] | |
Blazar Inv. Compton | ≥– | –1 | VERITAS, HAWC, FERMI | [50,51,52,53,54] |
Astroph. Seeding | Initial | Sub-Grid Dynamo | ID | ||||
---|---|---|---|---|---|---|---|
[kpc] | [Mpc] | [nG] | |||||
10243 | 83.3 | 85 | no | 1.0 | - | no | P |
10243 | 83.3 | 85 | no | 10−9 | - | dynamo mod.1 | DYN5 |
10243 | 83.3 | 85 | stellar feedback | 10−9 | - | no | CSF2 |
10243 | 83.3 | 85 | stellar & SMBH feedback | 10−9 | - | no | CSFBH2 |
10243 | 83.3 | 85 | no | 0.1 | - | dynamo mod.2 | P01 |
10243 | 83.3 | 85 | no | 1.87 | −1.0 | dynamo mod.2 | CMB2 |
10243 | 83.3 | 85 | no | 0.35 | 0.0 | dynamo mod.2 | CMB3 |
10243 | 83.3 | 85 | no | 0.042 | 1.0 | dynamo mod.2 | CMB4 |
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Vazza, F.; Locatelli, N.; Rajpurohit, K.; Banfi, S.; Domínguez-Fernández, P.; Wittor, D.; Angelinelli, M.; Inchingolo, G.; Brienza, M.; Hackstein, S.; et al. Magnetogenesis and the Cosmic Web: A Joint Challenge for Radio Observations and Numerical Simulations. Galaxies 2021, 9, 109. https://doi.org/10.3390/galaxies9040109
Vazza F, Locatelli N, Rajpurohit K, Banfi S, Domínguez-Fernández P, Wittor D, Angelinelli M, Inchingolo G, Brienza M, Hackstein S, et al. Magnetogenesis and the Cosmic Web: A Joint Challenge for Radio Observations and Numerical Simulations. Galaxies. 2021; 9(4):109. https://doi.org/10.3390/galaxies9040109
Chicago/Turabian StyleVazza, Franco, Nicola Locatelli, Kamlesh Rajpurohit, Serena Banfi, Paola Domínguez-Fernández, Denis Wittor, Matteo Angelinelli, Giannandrea Inchingolo, Marisa Brienza, Stefan Hackstein, and et al. 2021. "Magnetogenesis and the Cosmic Web: A Joint Challenge for Radio Observations and Numerical Simulations" Galaxies 9, no. 4: 109. https://doi.org/10.3390/galaxies9040109
APA StyleVazza, F., Locatelli, N., Rajpurohit, K., Banfi, S., Domínguez-Fernández, P., Wittor, D., Angelinelli, M., Inchingolo, G., Brienza, M., Hackstein, S., Dallacasa, D., Gheller, C., Brüggen, M., Brunetti, G., Bonafede, A., Ettori, S., Stuardi, C., Paoletti, D., & Finelli, F. (2021). Magnetogenesis and the Cosmic Web: A Joint Challenge for Radio Observations and Numerical Simulations. Galaxies, 9(4), 109. https://doi.org/10.3390/galaxies9040109