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Context. Ultrahigh-energy cosmic rays (UHECRs) are charged particles with energies surpassing 1018 eV. Their sources remain elusive because they are obscured by deflections caused by the Galactic magnetic field (GMF). This challenge is further complicated by our limited understanding of the 3D structure of the GMF because current GMF observations primarily consist of quantities that are integrated along the line of sight (LOS). Nevertheless, data from upcoming stellar polarization surveys along with Gaia stellar parallax data are expected to yield local GMF measurements. Aims. This study is the second entry in our exploration of a Bayesian inference approach to the local GMF that uses synthetic local GMF observations that emulate forthcoming local GMF measurements, and attempts to use them to reconstruct its 3D structure. The ultimate aim is to trace back observed UHECRs and thereby update our knowledge about their possible origin. Methods. In this proof-of-concept work, we assumed as ground truth a magnetic field produced by a dynamo simulation of the Galactic ISM. We employed methods of Bayesian statistical inference in order to sample the posterior distribution of the GMF within part of the Galaxy. By assuming a known rigidity and arrival direction of an UHECR, we traced its trajectory back through various GMF configurations drawn from the posterior distribution. Our objective was to rigorously evaluate the performance of our algorithm in scenarios that closely mirror the setting of expected future applications. In pursuit of this, we conditioned the posterior to synthetically integrated LOS measurements of the GMF, in addition to synthetic local plane of sky-component measurements. Results. Our results demonstrate that for all locations of the observed arrival direction on the plane of sky, our algorithm is able to substantially update our knowledge on the original arrival direction of UHECRs with a rigidity of E/Z = 5 × 1019 eV, even without any LOS information. When the integrated data are included in the inference, the regions of the celestial sphere in which the maximum error occurs are greatly reduced. The maximum error is diminished by a factor of about 3 even in these regions in the specific setting we studied. Additionally, we are able to identify the regions in which the largest error is expected to occur. [ABSTRACT FROM AUTHOR]

We describe a novel method to compute the components of dynamo tensors from direct magnetohydrodynamic (MHD) simulations. Our method relies upon an extension and generalization of the standard Högbom CLEAN algorithm widely used in radio astronomy to systematically remove the impact of the strongest beams on to the corresponding image. This generalization, called the Iterative Removal of Sources (IROS) method, has been adopted here to model the turbulent electromotive force (EMF) in terms of the mean magnetic fields and currents. Analogous to the CLEAN algorithm, IROS treats the time series of the mean magnetic field and current as beams that convolve with the dynamo coefficients which are treated as (clean) images to produce the EMF time series (the dirty image). We apply this method to MHD simulations of galactic dynamos, to which we have previously employed other methods of computing dynamo coefficients such as the test-field method, the regression method, as well as local and non-local versions of the singular value decomposition (SVD) method. We show that our new method reliably recovers the dynamo coefficients from the MHD simulations. It also allows priors on the dynamo coefficients to be incorporated easily during the inversion, unlike in earlier methods. Moreover, using synthetic data, we demonstrate that it may serve as a viable post-processing tool in determining the dynamo coefficients, even when the power of additive noise to the EMF is twice as much the actual EMF. [ABSTRACT FROM AUTHOR]

We study the magneto-rotational instability (MRI) dynamo in a geometrically thin disc (H / R ≪ 1) using stratified zero net (vertical) flux shearing box simulations. We find that mean fields and electromotive forces (EMFs) oscillate with a primary frequency f dyn = 0.017 Ω (approximately nine orbital period), but also have higher harmonics at 3 f dyn. Correspondingly, the current helicity has two frequencies 2 f dyn and 4 f dyn, which appear to be the beat frequencies of mean fields and EMFs, respectively, as expected from the magnetic helicity density evolution equation. Further, we adopt a novel inversion algorithm called the 'Iterative Removal Of Sources', to extract the turbulent dynamo coefficients in the mean-field closure using the mean magnetic fields and EMFs obtained from the shearing box simulation. We show that an α-effect (α yy ) is predominantly responsible for the creation of the poloidal field from the toroidal field, while shear generates back a toroidal field from the poloidal field, indicating that an α–Ω-type dynamo is operative in MRI-driven accretion discs. We also find that both strong outflow (⁠|$\bar{v}_z$|⁠) and turbulent pumping (γ z ) transport mean fields away from the mid-plane. Instead of turbulent diffusivity, they are the principal sink terms in the mean magnetic energy evolution equation. We find encouraging evidence that a generative helicity flux is responsible for the effective α-effect. Finally, we point out potential limitations of horizontal (x − y) averaging in defining the 'mean' on the extraction of dynamo coefficients and their physical interpretations. [ABSTRACT FROM AUTHOR]

Stratified discs with strong horizontal magnetic fields, are susceptible to magnetic buoyancy instability (MBI). Modifying the magnetic field and gas distributions, this can play an important role in galactic evolution. The MBI and the Parker instability, in which MBI is exacerbated by cosmic rays, are often studied using an imposed magnetic field. However, in galaxies and accretion discs, the magnetic field is continuously replenished by a large-scale dynamo action. Using non-ideal MHD equations, we model a section of the galactic disc (we neglect rotation and cosmic rays considered elsewhere), in which the large-scale field is generated by an imposed α-effect of variable intensity to explore the interplay between dynamo instability and MBI. The system evolves through three distinct phases: the linear (kinematic) dynamo stage, the onset of linear MBI when the magnetic field becomes sufficiently strong and the non-linear, statistically steady state. Non-linear effects associated with the MBI introduce oscillations which do not occur when the field is produced by the dynamo alone. The MBI initially accelerates the magnetic field amplification but the growth is quenched by the vertical motions produced by MBI. We construct a 1D model, which replicates all significant features of 3D simulations to confirm that magnetic buoyancy alone can quench the dynamo and is responsible for the magnetic field oscillations. Unlike similar results obtained with an imposed magnetic field, the non-linear interactions do not reduce the gas scale height, so the consequences of the magnetic buoyancy depend on how the magnetic field is maintained. [ABSTRACT FROM AUTHOR]

We analyse the observational signatures of galactic magnetic fields that are self-consistently generated in magnetohydrodynamic simulations of the interstellar medium through turbulence driven by supernova (SN) explosions and differential rotation. In particular, we study the time evolution of the Faraday rotation measure (RM), synchrotron radiation, and Stokes parameters by characterizing the typical structures formed in the plane of observation. We do this by defining two distinct models for both thermal and cosmic ray (CR) electron distributions. Our results indicate that the maps of RM have structures that are sheared and rendered anisotropically by differential rotation and that they depend on the choice of the thermal electron model as well as the SN rate. Synchrotron maps are qualitatively similar to the maps of the mean magnetic field along the line of sight and structures are only marginally affected by the CR model. Stokes parameters and related quantities, such as the degree of linear polarization, are highly dependent on both frequency and resolution of the observation. [ABSTRACT FROM AUTHOR]

The generation of large-scale magnetic fields (⁠|$\overline{\boldsymbol {B}}$|⁠) in astrophysical systems is driven by the mean turbulent electromotive force (⁠|$\overline{\rm{\boldsymbol {\cal E}} {}}$|⁠), the cross-correlation between local fluctuations of velocity and magnetic fields. This can depend non-locally on |$\overline{\boldsymbol {B}}$| through a convolution kernel Kij. In a new approach to find Kij , we directly fit the time-series data of |$\overline{\rm{\boldsymbol {\cal E}} {}}$| versus |$\overline{\boldsymbol {B}}$| from a galactic dynamo simulation using singular value decomposition. We calculate the usual turbulent transport coefficients as moments of Kij , and show the importance of including non-locality over eddy length-scales to fully capture their amplitudes and that higher order corrections to the standard transport coefficients are small in this case. [ABSTRACT FROM AUTHOR]

Coherent magnetic fields in disc galaxies are thought to be generated by a large-scale (or mean-field) dynamo operating in their interstellar medium. A key driver of mean magnetic field growth is the turbulent electromotive force (EMF), which represents the influence of correlated small-scale (or fluctuating) velocity and magnetic fields on the mean field. The EMF is usually expressed as a linear expansion in the mean magnetic field and its derivatives, with the dynamo tensors as expansion coefficients. Here, we adopt the singular value decomposition (SVD) method to directly measure these turbulent transport coefficients in a simulation of the turbulent interstellar medium that realizes a large-scale dynamo. Specifically, the SVD is used to least-square fit the time series data of the EMF with that of the mean field and its derivatives, to determine these coefficients. We demonstrate that the spatial profiles of the EMF reconstructed from the SVD coefficients match well with that taken directly from the simulation. Also, as a direct test, we use the coefficients to simulate a 1D mean-field dynamo model and find an overall similarity in the evolution of the mean magnetic field between the dynamo model and the direct simulation. We also compare the results with those which arise using simple regression and the ones obtained previously using the test-field method, to find reasonable qualitative agreement. Overall, the SVD method provides an effective post-processing tool to determine turbulent transport coefficients from simulations. [ABSTRACT FROM AUTHOR]