Do you want to publish a course? Click here

An underlying universal pattern in galaxy halo magnetic fields

67   0   0.0 ( 0 )
 Publication date 2021
  fields Physics
and research's language is English




Ask ChatGPT about the research

Magnetic fields in galaxy halos are in general very difficult to observe. Most recently, the CHANG-ES collaboration (Continuum HAlos in Nearby Galaxies - an EVLA Survey) investigated in detail the radio halos of 35 nearby edge-on spiral galaxies and detected large scale magnetic fields in 16 of them. We used the CHANG-ES radio polarization data to create Rotation Measure (RM) maps for all galaxies in the sample and stack them with the aim to amplify any underlying universal toroidal magnetic field pattern in the halo above and below the disk of the galaxy. We discovered a large-scale magnetic field in the central region of the stacked galaxy profile, attributable to an axial electric current that universally outflows from the center both above and below the plane of the disk. A similar symmetry-breaking has also been observed in astrophysical jets but never before in galaxy halos. This is an indication that galaxy halo magnetic fields are probably not generated by pure ideal magnetohydrodynamic (MHD) processes in the central regions of galaxies. One such promising physical mechanism is the Cosmic Battery operating in the innermost accretion disk around the central supermassive black hole. We anticipate that our discovery will stimulate a more general discussion on the origin of astrophysical magnetic fields.



rate research

Read More

We present a suite of high-resolution cosmological simulations, using the FIRE-2 feedback physics together with explicit treatment of magnetic fields, anisotropic conduction and viscosity, and cosmic rays (CRs) injected by supernovae (including anisotropic diffusion, streaming, adiabatic, hadronic and Coulomb losses). We survey systems from ultra-faint dwarf ($M_{ast}sim 10^{4},M_{odot}$, $M_{rm halo}sim 10^{9},M_{odot}$) through Milky Way masses, systematically vary CR parameters (e.g. the diffusion coefficient $kappa$ and streaming velocity), and study an ensemble of galaxy properties (masses, star formation histories, mass profiles, phase structure, morphologies). We confirm previous conclusions that magnetic fields, conduction, and viscosity on resolved ($gtrsim 1,$pc) scales have small effects on bulk galaxy properties. CRs have relatively weak effects on all galaxy properties studied in dwarfs ($M_{ast} ll 10^{10},M_{odot}$, $M_{rm halo} lesssim 10^{11},M_{odot}$), or at high redshifts ($zgtrsim 1-2$), for any physically-reasonable parameters. However at higher masses ($M_{rm halo} gtrsim 10^{11},M_{odot}$) and $zlesssim 1-2$, CRs can suppress star formation by factors $sim 2-4$, given relatively high effective diffusion coefficients $kappa gtrsim 3times10^{29},{rm cm^{2},s^{-1}}$. At lower $kappa$, CRs take too long to escape dense star-forming gas and lose energy to hadronic collisions, producing negligible effects on galaxies and violating empirical constraints from $gamma$-ray emission. But around $kappasim 3times10^{29},{rm cm^{2},s^{-1}}$, CRs escape the galaxy and build up a CR-pressure-dominated halo which supports dense, cool ($Tll 10^{6}$ K) gas that would otherwise rain onto the galaxy. CR heating (from collisional and streaming losses) is never dominant.
We present a suite of high-resolution cosmological zoom-in simulations to $z=4$ of a $10^{12},{rm M}_{odot}$ halo at $z=0$, obtained using seven contemporary astrophysical simulation codes widely used in the numerical galaxy formation community. Physics prescriptions for gas cooling, heating, and star formation, are similar to the ones used in our previous {it AGORA} disk comparison but now account for the effects of cosmological processes. In this work, we introduce the most careful comparison yet of galaxy formation simulations run by different code groups, together with a series of four calibration steps each of which is designed to reduce the number of tunable simulation parameters adopted in the final run. After all the participating code groups successfully completed the calibration steps, we reach a suite of cosmological simulations with similar mass assembly histories down to $z=4$. With numerical accuracy that resolves the internal structure of a target halo, we find that the codes overall agree well with one another in e.g., gas and stellar properties, but also show differences in e.g., circumgalactic medium properties. We argue that, if adequately tested in accordance with our proposed calibration steps and common parameters, the results of high-resolution cosmological zoom-in simulations can be robust and reproducible. New code groups are invited to join this comparison by generating equivalent models by adopting the common initial conditions, the common easy-to-implement physics package, and the proposed calibration steps. Further analyses of the simulations presented here will be in forthcoming reports from our Collaboration.
An analytical model for fully developed three-dimensional incompressible turbulence was recently proposed in the hydrodynamics community, based on the concept of multiplicative chaos. It consists of a random field represented by means of a stochastic integral, which, with only a few parameters, shares many properties with experimental and numerical turbulence, including in particular energy transfer through scales (the cascade) and intermittency (non-Gaussianity) which is most conveniently controlled with a single parameter. Here, we propose three models extending this approach to MHD turbulence. Our formulae provide physically motivated 3D models of a turbulent velocity field and magnetic field coupled together. Besides its theoretical value, this work is meant to provide a tool for observers: a dozen of physically meaningful free parameters enter the description, which is useful to characterize astrophysical data.
We present a direct comparison of the Pan-Andromeda Archaeological Survey (PAndAS) observations of the stellar halo of M31 with the stellar halos of 6 galaxies from the Auriga simulations. We process the simulated halos through the Auriga2PAndAS pipeline and create PAndAS-like mocks that fold in all observational limitations of the survey data (foreground contamination from the Milky Way stars, incompleteness of the stellar catalogues, photometric uncertainties, etc). This allows us to study the survey data and the mocks in the same way and generate directly comparable density maps and radial density profiles. We show that the simulations are overall compatible with the observations. Nevertheless, some systematic differences exist, such as a preponderance for metal-rich stars in the mocks. While these differences could suggest that M31 had a different accretion history or has a different mass compared to the simulated systems, it is more likely a consequence of an under-quenching of the star formation history of galaxies, related to the resolution of the Auriga simulations. The direct comparison enabled by our approach offers avenues to improve our understanding of galaxy formation as they can help pinpoint the observable differences between observations and simulations. Ideally, this approach will be further developed through an application to other stellar halo simulations. To facilitate this step, we release the pipeline to generate the mocks, along with the six mocks presented and used in this contribution.
The application of Bayesian techniques to astronomical data is generally non-trivial because the fitting parameters can be strongly degenerated and the formal uncertainties are themselves uncertain. An example is provided by the contradictory claims over the presence or absence of a universal acceleration scale (g$_dagger$) in galaxies based on Bayesian fits to rotation curves. To illustrate the situation, we present an analysis in which the Newtonian gravitational constant $G_N$ is allowed to vary from galaxy to galaxy when fitting rotation curves from the SPARC database, in analogy to $g_{dagger}$ in the recently debated Bayesian analyses. When imposing flat priors on $G_N$, we obtain a wide distribution of $G_N$ which, taken at face value, would rule out $G_N$ as a universal constant with high statistical confidence. However, imposing an empirically motivated log-normal prior returns a virtually constant $G_N$ with no sacrifice in fit quality. This implies that the inference of a variable $G_N$ (or g$_{dagger}$) is the result of the combined effect of parameter degeneracies and unavoidable uncertainties in the error model. When these effects are taken into account, the SPARC data are consistent with a constant $G_{rm N}$ (and constant $g_dagger$).
comments
Fetching comments Fetching comments
Sign in to be able to follow your search criteria
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا