Maarit J. Kapyla

Magnetic fields are critical at many scales to galactic dynamics and structure, including multiphase pressure balance, dust processing, and star formation. Dynamo action determines their dynamical structure and strength. Simulations of combined large- and small-scale dynamos have successfully developed mean fields with strength and topology consistent with observations, but with turbulent fields much weaker than observed, while simulations of small-scale dynamos with parameters relevant to the interstellar medium yield turbulent fields 1 order of magnitude below the values observed or expected theoretically. We use the Pencil Code accelerated on GPUs with A staroth to perform high-resolution simulations of a supernova-driven galactic dynamo, including heating and cooling in a periodic domain. Our models show that the strength of the turbulent field produced by the small-scale dynamo approaches an asymptote at only modest magnetic Prandtl numbers. This allows us to use these models to suggest the essential characteristics of this constituent of the magnetic field for inclusion in global galactic models. The asymptotic limit occurs already at a magnetic Prandtl number of only a few hundred, many orders of magnitude below physical values in the interstellar medium and consistent with previous findings for isothermal compressible flows.

Epidemics, apart from affecting the health of populations, can have large impacts on their social and economic behavior and subsequently feed back to and influence the spreading of the disease. This calls for systematic investigation which factors affect significantly and either beneficially or adversely the disease spreading and regional socio-economics. Based on our recently developed hybrid agent-based socio-economy and epidemic spreading model we perform extensive exploration of its six-dimensional parameter space of the socio-economic part of the model, namely, the attitudes towards the spread of the pandemic, health and the economic situation for both, the population and government agents who impose regulations. We search for significant patterns from the resulting simulated data using basic classification tools, such as self-organizing maps and principal component analysis, and we monitor different quantities of the model output, such as infection rates, the propagation speed of the epidemic, economic activity, government regulations, and the compliance of population on government restrictions. Out of these, the ones describing the epidemic spreading were resulting in the most distinctive clustering of the data, and they were selected as the basis of the remaining analysis. We relate the found clusters to three distinct types of disease spreading: wave-like, chaotic, and transitional spreading patterns. The most important value parameter contributing to phase changes and the speed of the epidemic was found to be the compliance of the population agents towards the government regulations. We conclude that in compliant populations, the infection rates are significantly lower and the infection spreading is slower, while the population agents’ health and economical attitudes show a weaker effect.

Galaxies are observed to host magnetic fields with a typical total strength of around 15microgauss. A coherent large-scale field constitutes up to a few microgauss of the total, while the rest is built from strong magnetic fluctuations over a wide range of spatial scales. This represents sufficient magnetic energy for it to be dynamically significant. Several questions immediately arise: What is the physical mechanism that gives rise to such magnetic fields? How do these magnetic fields affect the formation and evolution of galaxies? In which physical processes do magnetic fields play a role, and how can that role be characterized? Numerical modelling of magnetized flows in galaxies is playing an ever-increasing role in finding those answers. We review major techniques used for these models. Current results strongly support the conclusion that field growth occurs during the formation of the first galaxies on timescales shorter than their accretion timescales due to small-scale turbulent dynamos. The saturated small-scale dynamo maintains field strengths at a few percent of equipartition with turbulence. The subsequent action of large-scale dynamos in differentially rotating discs produces observed modern field strengths in equipartition with the turbulence and having power at large scales. The field structure resulting appears consistent with observations including Faraday rotation and polarisation from synchrotron and dust thermal emission. Major remaining challenges include scaling numerical models toward realistic scale separations and Prandtl and Reynolds numbers.

A global disaster, such as the recent Covid-19 pandemic, affects every aspect of our lives and there is a need to investigate these highly complex phenomena if one aims to diminish their impact in the health of the population, as well as their socio-economic stability. In this paper we present an attempt to understand the role of the governmental authorities and the response of the rest of the population facing such emergencies. We present a mathematical model that takes into account the epidemiological features of the pandemic and also the actions of people responding to it, focusing only on three aspects of the system, namely, the fear of catching this serious disease, the impact on the economic activities and the compliance of the people to the mitigating measures adopted by the authorities. We apply the model to the specific case of Spain, since there are accurate data available about these three features. We focused on tourism as an example of the economic activity, since this sector of economy is one of the most likely to be affected by the restrictions imposed by the authorities, and because it represents an important part of Spanish economy. The results of numerical calculations agree with the empirical data in such a way that we can acquire a better insight of the different processes at play in such a complex situation, and also in other different circumstances.

Magnetic fields are now widely recognized as critical at many scales to galactic dynamics and structure, including multiphase pressure balance, dust processing, and star formation. Using imposed magnetic fields cannot reliably model the interstellar medium's (ISM) dynamical structure nor phase interactions. Dynamos must be modeled. ISM models exist of turbulent magnetic fields using small-scale dynamo (SSD). Others model the large-scale dynamo (LSD) organizing magnetic fields at the scale of the disk or spiral arms. Separately, neither can fully describe the galactic magnetic field dynamics nor topology. We model the LSD and SSD together at a sufficient resolution to use the low explicit Lagrangian resistivity required. The galactic SSD saturates within 20 Myr. We show that the SSD is quite insensitive to the presence of an LSD and is even stronger in the presence of a large-scale shear flow. The LSD grows more slowly in the presence of SSD, saturating after 5 Gyr versus 1–2 Gyr in studies where the SSD is weak or absent. The LSD primarily grows in warm gas in the galactic midplane. Saturation of the LSD occurs due to α-quenching near the midplane as the growing mean-field produces a magnetic α that opposes the kinetic α. The magnetic energy in our models of the LSD shows a slightly sublinear response to increasing resolution, indicating that we are converging toward the physical solution at 1 pc resolution. Clustering supernovae in OB associations increases the growth rates for both the SSD and the LSD, compared to a horizontally uniform supernova distribution.

In this article we review small-scale dynamo processes that are responsible for magnetic field generation on scales comparable to and smaller than the energy carrying scales of turbulence. We provide a review of critical observation of quiet Sun magnetism, which have provided strong support for the operation of a small-scale dynamo in the solar photosphere and convection zone. After a review of basic concepts we focus on numerical studies of kinematic growth and non-linear saturation in idealized setups, with special emphasis on the role of the magnetic Prandtl number for dynamo onset and saturation. Moving towards astrophysical applications we review convective dynamo setups that focus on the deep convection zone and the photospheres of solar-like stars. We review the critical ingredients for stellar convection setups and discuss their application to the Sun and solar-like stars including comparison against available observations.

In this article we review small-scale dynamo processes that are responsible for magnetic field generation on scales comparable to and smaller than the energy carrying scales of turbulence. We provide a review of critical observation of quiet Sun magnetism, which have provided strong support for the operation of a small-scale dynamo in the solar photosphere and convection zone. After a review of basic concepts we focus on numerical studies of kinematic growth and non-linear saturation in idealized setups, with special emphasis on the role of the magnetic Prandtl number for dynamo onset and saturation. Moving towards astrophysical applications we review convective dynamo setups that focus on the deep convection zone and the photospheres of solar-like stars. We review the critical ingredients for stellar convection setups and discuss their application to the Sun and solar-like stars including comparison against available observations.

Magnetic fields grow quickly, even at early cosmological times, suggesting the action of a small-scale dynamo (SSD) in the interstellar medium (ISM) of galaxies. Many studies have focused on idealized, isotropic, homogeneous, turbulent driving of the SSD. Here we analyze more realistic simulations of supernova-driven turbulence to understand how it drives an SSD. We find that SSD growth rates are intermittently variable as a result of the evolving multiphase ISM structure. Rapid growth in the magnetic field typically occurs in hot gas, with the highest overall growth rates occurring when the fractional volume of hot gas is large. SSD growth rates correlate most strongly with vorticity and fluid Reynolds number, which also both correlate strongly with gas temperature. Rotational energy exceeds irrotational energy in all phases, but particularly in the hot phase while SSD growth is most rapid. Supernova rate does not significantly affect the ISM average kinetic energy density. Rather, higher temperatures associated with high supernova rates tend to increase SSD growth rates. SSD saturates with total magnetic energy density around 5% of equipartition to kinetic energy density, increasing slightly with magnetic Prandtl number. While magnetic energy density in the hot gas can exceed that of the other phases when SSD grows most rapidly, it saturates below 5% of equipartition with kinetic energy in the hot gas, while in the cold gas it attains 100%. Fast, intermittent growth of the magnetic field appears to be a characteristic behavior of supernova-driven, multiphase turbulence.