Abstract:Galactic dynamo models sustained by supernova (SN) driven turbulence and differential rotation have revealed that the sustenance of large scale fields requires a flux of small scale magnetic helicity to be viable. Here we generalize a minimalist analytic version of such galactic dynamos to explore some heretofore unincluded contributions from shear on the total turbulent energy and turbulent correlation time, with the helicity fluxes maintained by either winds, diffusion, or magnetic buoyancy. We construct an … Show more
“…with τ l/u the turbulent correlation time, and the quantity R κ (see below) is of order unity. Equation (3) assumes that in the kinematic regime, α τ 2 u 2 Ω/h [16], but this applies if Ωτ < 1 and α < u; otherwise the expression should be modified [19,134,135]. Equation (2) results from solving the mean induction equation along with the dynamical α-quenching formalism (Sec.…”
Section: Mean-field Strength From Dynamo Modelsmentioning
Constraining dynamo theories of magnetic field origin by observation is indispensable but challenging, in part because the basic quantities measured by observers and predicted by modelers are different. We clarify these differences and sketch out ways to bridge the divide. Based on archival and previously unpublished data, we then compile various important properties of galactic magnetic fields for nearby spiral galaxies. We consistently compute strengths of total, ordered, and regular fields, pitch angles of ordered and regular fields, and we summarize the present knowledge on azimuthal modes, field parities, and the properties of non-axisymmetric spiral features called magnetic arms. We review related aspects of dynamo theory, with a focus on mean-field models and their predictions for large-scale magnetic fields in galactic discs and halos. Further, we measure the velocity dispersion of H I gas in arm and inter-arm regions in three galaxies, M 51, M 74, and NGC 6946, since spiral modulation of the root-mean-square turbulent speed has been proposed as a driver of non-axisymmetry in large-scale dynamos. We find no evidence for such a modulation and place upper limits on its strength, helping to narrow down the list of mechanisms to explain magnetic arms. Successes and remaining challenges of dynamo models with respect to explaining observations are briefly summarized, and possible strategies are suggested. With new instruments like the Square Kilometre Array (SKA), large data sets of magnetic and non-magnetic properties from thousands of galaxies will become available, to be compared with theory.
“…with τ l/u the turbulent correlation time, and the quantity R κ (see below) is of order unity. Equation (3) assumes that in the kinematic regime, α τ 2 u 2 Ω/h [16], but this applies if Ωτ < 1 and α < u; otherwise the expression should be modified [19,134,135]. Equation (2) results from solving the mean induction equation along with the dynamical α-quenching formalism (Sec.…”
Section: Mean-field Strength From Dynamo Modelsmentioning
Constraining dynamo theories of magnetic field origin by observation is indispensable but challenging, in part because the basic quantities measured by observers and predicted by modelers are different. We clarify these differences and sketch out ways to bridge the divide. Based on archival and previously unpublished data, we then compile various important properties of galactic magnetic fields for nearby spiral galaxies. We consistently compute strengths of total, ordered, and regular fields, pitch angles of ordered and regular fields, and we summarize the present knowledge on azimuthal modes, field parities, and the properties of non-axisymmetric spiral features called magnetic arms. We review related aspects of dynamo theory, with a focus on mean-field models and their predictions for large-scale magnetic fields in galactic discs and halos. Further, we measure the velocity dispersion of H I gas in arm and inter-arm regions in three galaxies, M 51, M 74, and NGC 6946, since spiral modulation of the root-mean-square turbulent speed has been proposed as a driver of non-axisymmetry in large-scale dynamos. We find no evidence for such a modulation and place upper limits on its strength, helping to narrow down the list of mechanisms to explain magnetic arms. Successes and remaining challenges of dynamo models with respect to explaining observations are briefly summarized, and possible strategies are suggested. With new instruments like the Square Kilometre Array (SKA), large data sets of magnetic and non-magnetic properties from thousands of galaxies will become available, to be compared with theory.
“…We augment the simplified galactic dynamo model from § 4.5 of Zhou & Blackman (2017), 4 where the ‘no-’ approximation (Subramanian & Mestel 1993; Moss 1995; Phillips 2001; Sur, Shukurov & Subramanian 2007; Chamandy et al. 2014) is used.…”
Section: Galactic Dynamo and Precision For Different Fr Viewing Anglesmentioning
confidence: 99%
“…Figure 3.Similar to figure 2( a ) but using analytic dynamo solutions for from § 4.5 of Zhou & Blackman (2017) by solving equations (6.3) to (6.5). ( a ) Intrinsic error and ( b ) filtering error.…”
Section: Galactic Dynamo and Precision For Different Fr Viewing Anglesmentioning
confidence: 99%
“…The predicted line-of-sight average of the magnetic field, together with the error bars are shown in figures 2 and 3, where two different profiles of are separately considered: (i) in figure 2( a ) where is a constant, and (ii) in figure 3 the analytic solution of the mean field dynamo model from § 6.1, normalized by the equipartition field strength . The dimensionless parameters we have used for the analytic solution are the same as those in Zhou & Blackman (2017): where quantities with subscripts 0 are computed using which yields and we use . Above is the location of the Sun, and the function determines the -dependence of the dimensionless parameters and is described in detail in the appendix in Zhou & Blackman (2017).…”
Section: Galactic Dynamo and Precision For Different Fr Viewing Anglesmentioning
confidence: 99%
“…The dimensionless parameters we have used for the analytic solution are the same as those in Zhou & Blackman (2017): where quantities with subscripts 0 are computed using which yields and we use . Above is the location of the Sun, and the function determines the -dependence of the dimensionless parameters and is described in detail in the appendix in Zhou & Blackman (2017).…”
Section: Galactic Dynamo and Precision For Different Fr Viewing Anglesmentioning
Mean field electrodynamics (MFE) facilitates practical modelling of secular, large scale properties of astrophysical or laboratory systems with fluctuations. Practitioners commonly assume wide scale separation between mean and fluctuating quantities, to justify equality of ensemble and spatial or temporal averages. Often however, real systems do not exhibit such scale separation. This raises two questions: (I) What are the appropriate generalized equations of MFE in the presence of mesoscale fluctuations? (II) How precise are theoretical predictions from MFE? We address both by first deriving the equations of MFE for different types of averaging, along with mesoscale correction terms that depend on the ratio of averaging scale to variation scale of the mean. We then show that even if these terms are small, predictions of MFE can still have a significant precision error. This error has an intrinsic contribution from the dynamo input parameters and a filtering contribution from differences in the way observations and theory are projected through the measurement kernel. Minimizing the sum of these contributions can produce an optimal scale of averaging that makes the theory maximally precise. The precision error is important to quantify when comparing to observations because it quantifies the resolution of predictive power. We exemplify these principles for galactic dynamos, comment on broader implications, and identify possibilities for further work.
We discuss a mean-field theory of the generation of large-scale vorticity in a rotating density stratified developed turbulence with inhomogeneous kinetic helicity. We show that the large-scale non-uniform flow is produced due to either a combined action of a density stratified rotating turbulence and uniform kinetic helicity or a combined effect of a rotating incompressible turbulence and inhomogeneous kinetic helicity. These effects result in the formation of a large-scale shear, and in turn its interaction with the small-scale turbulence causes an excitation of the large-scale instability (known as a vorticity dynamo) due to a combined effect of the large-scale shear and Reynolds stress-induced generation of the mean vorticity. The latter is due to the effect of large-scale shear on the Reynolds stress. A fast rotation suppresses this large-scale instability.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
