Cosmic rays and random magnetic traps

The spatial distribution of cosmic ray (CR) particles in the interstellar medium (ISM) is of major importance in radio astronomy, where its knowledge is essential for the interpretation of observations, and in theoretical astrophysics, where CRs contribute to the structure and dynamics of the ISM. Local inhomogeneities in interstellar magnetic field strength and structure can affect the local diffusivity and ensemble dynamics of the CR particles. Magnetic traps (regions between magnetic mirrors located on the same magnetic line) can lead to especially strong and persistent features in the CR spatial distribution. Using test particle simulations, we study the spatial distribution of an ensemble of CR particles (both protons and electrons) in various magnetic field configurations, from an idealized axisymmetric trap to those that emerge in intermittent (dynamo-generated) random magnetic fields. We demonstrate that both the inhomogeneity in the CR sources and the energy losses by the CR particles can lead to persistent local inhomogeneities in the CR distribution and that the protons and electrons have different spatial distributions. Our results can have profound implications for the interpretation of the synchrotron emission from astronomical objects, and in particular its random fluctuations.

Simulations of cosmic ray propagation

We review numerical methods for simulations of cosmic ray (CR) propagation on galactic and larger scales. We present the development of algorithms designed for phenomenological and self-consistent models of CR propagation in kinetic description based on numerical solutions of the Fokker–Planck equation. The phenomenological models assume a stationary structure of the galactic interstellar medium and incorporate diffusion of particles in physical and momentum space together with advection, spallation, production of secondaries and various radiation mechanisms. The self-consistent propagation models of CRs include the dynamical coupling of the CR population to the thermal plasma. The CR transport equation is discretized and solved numerically together with the set of MHD equations in various approaches treating the CR population as a separate relativistic fluid within the two-fluid approach or as a spectrally resolved population of particles evolving in physical and momentum space. The relevant processes incorporated in self-consistent models include advection, diffusion and streaming propagation as well as adiabatic compression and several radiative loss mechanisms. We discuss, applications of the numerical models for the interpretation of CR data collected by various instruments. We present example models of astrophysical processes influencing galactic evolution such as galactic winds, the amplification of large-scale magnetic fields and instabilities of the interstellar medium.

Biased dispersal can explain fast human range expansions

Some human fronts spread faster than expected by models based on dispersal and reproduction. The only explanation proposed so far assumes that some autochthonous individuals are incorporated by the expanding populations, leading to faster front speeds. Here we show that simple models without this effect are also consistent with the observed speeds of two fronts (a Khoi-khoi expansion of herders and a Bantu expansion of farmers), provided that the dispersal of individuals is biased (i.e., more probable) in directions closer to the front propagation direction. The physical models presented may also be applied to other kinds of social phenomena, including innovation diffusion, rumor propagation, linguistic fronts, epidemic spread, diffusion in economic space and the evolution of cooperation in spatial systems. They can be also adapted to non-human systems with biased dispersal, including biological invasions, cancer tumors and virus treatment of tumors.

Revisiting the Equipartition Assumption in Star-Forming Galaxies

Energy equipartition between cosmic rays and magnetic fields is often assumed to infer magnetic field properties from the synchrotron observations of star-forming galaxies. However, there is no compelling physical reason to expect the same. We aim to explore the validity of the energy equipartition assumption. After describing popular arguments in favour of the assumption, we first discuss observational results that support it at large scales and how certain observations show significant deviations from equipartition at scales smaller than ≈ 1 kpc , probably related to the propagation length of the cosmic rays. Then, we test the energy equipartition assumption using test-particle and magnetohydrodynamic (MHD) simulations. From the results of the simulations, we find that the energy equipartition assumption is not valid at scales smaller than the driving scale of the ISM turbulence (≈ 100 pc in spiral galaxies), which can be regarded as the lower limit for the scale beyond which equipartition is valid. We suggest that one must be aware of the dynamical scales in the system before assuming energy equipartition to extract magnetic field information from synchrotron observations. Finally, we present ideas for future observations and simulations to investigate in more detail under which conditions the equipartition assumption is valid or not.

IMAGINE: Modeling the Galactic Magnetic Field

The IMAGINE Consortium aims to bring modeling of the magnetic field of the Milky Way to the next level by using Bayesian inference. IMAGINE includes an open-source modular software pipeline that optimizes parameters in a user-defined galactic magnetic field model against various selected observational datasets. Bayesian priors can be added as external probabilistic constraints of the model parameters. These conference proceedings describe the science goals of the IMAGINE consortium, the software pipeline and its inputs, namely observational data sets, galactic magnetic field models, and Bayesian priors.