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Abstract The question of whether a dynamo can be triggered by gravitational collapse is of great interest, especially for the early Universe. Here, we employ supercomoving coordinates to study the magnetic field amplification from decaying turbulence during gravitational collapse. We perform 3D simulations and show that for large magnetic Reynolds numbers, there can be exponential growth of the comoving magnetic field with conformal time before the decay of turbulence impedes further amplification. The collapse dynamics only affect the nonlinear feedback from the Lorentz force, which diminishes more rapidly for shorter collapse times, allowing nearly kinematic continued growth. We confirm that helical turbulence is more efficient in driving dynamo action than nonhelical turbulence, but this difference decreases for larger collapse times. We also show that for nearly irrotational flows, dynamo amplification is still possible, but it is always associated with a growth of vorticity—even if it still remains very small. In nonmagnetic runs, the growth of vorticity is associated with viscosity and grows with the Mach number. In the presence of magnetic fields, vorticity emerges from the curl of the Lorentz force. During a limited time interval, an exponential growth of the comoving magnetic field with conformal time is interpreted as clear evidence of dynamo action. 

Abstract We study vorticity production in isothermal, subsonic, acoustic (nonvortical), and decaying turbulence due to the presence of magnetic fields. Using three-dimensional numerical simulations, we find that the resulting kinetic energy cascade follows the ordinary Kolmogorov phenomenology involving a constant spectral energy flux. The nondimensional prefactor for acoustic turbulence is larger than the standard Kolmogorov constant due to the inefficient dissipation of kinetic energy. We also find that the Lorentz force can drive vortical motions even when the initial field is uniform by converting a fraction of the acoustic energy into vortical energy. This conversion is shown to be quadratic in the magnetic field strength and linear in the acoustic flow speed. By contrast, the direct production of vortical motions by a non-force-free magnetic field is linear in the field strength. Our results suggest that magnetic fields play a crucial role in vorticity production in cosmological flows, particularly in scenarios where significant acoustic turbulence is prevalent. We also discuss the implications of our findings for the early Universe, where magnetic fields may convert acoustic turbulence generated during cosmological phase transitions into vortical turbulence. 

Abstract We numerically study axion-U(1) inflation, focusing on the regime where the coupling between axions and gauge fields results in significant backreaction from the amplified gauge fields during inflation. These amplified gauge fields not only generate high-frequency gravitational waves (GWs), but also enhance spatial inhomogeneities in the axion field. GWs serve as key probe for constraining the coupling strength between the axion and gauge fields. We find that, when backreaction is important during inflation, the constraints on the coupling strength due to GW overproduction are relaxed compared to previous studies, in which backreaction matters only after inflation. Moreover, our results suggest that the probability density function (PDF) of axion fluctuations tends toward a Gaussian distribution even in cases where gauge field backreaction is important only after inflation. This aligns with previous studies where the same effect was observed for cases with strong backreaction during inflation. This finding can be crucial for future studies of primordial black hole (PBH) formation, which can further constrain the coupling strength. We also calculate the spectrum of the produced magnetic fields in this model and find that their strength is compatible with the observed lower limits. 

Abstract The Faraday rotation effect, quantified by the rotation measure (RM), is a powerful probe of the large-scale magnetization of the Universe—tracing magnetic fields not only on galaxy and galaxy cluster scales but also in the intergalactic medium (IGM; referred to as RM_IGM). The redshift dependence of the latter has extensively been explored with observations. It has also been shown that this relation can help to distinguish between different large-scale magnetization scenarios. We study the evolution of this RM_IGMfor different primordial magnetogenesis scenarios to search for the imprints of primordial magnetic fields (PMFs; magnetic fields originating in the early Universe) on the redshift-dependence of RM_IGM. We use cosmological magnetohydrodynamic simulations for evolving PMFs during large-scale structure formation, coupled with the light-cone analysis to produce a realistic statistical sample of mock RM_IGMimages. We study the predicted behavior for the cosmic evolution of RM_IGMfor different correlation lengths of PMFs, and provide fitting functions for their dependence on redshifts. We compare these mock RM trends with the recent analysis of the the LOw-Frequency ARray RM Grid and find that large-scale-correlated PMFs should have (comoving) strengths ≲0.75 nG, if they originated during inflation with the scale-invariant spectrum and (comoving) correlation length of ∼19h⁻¹cMpc or ≲30 nG if they originated during phase-transition epochs with the comoving correlation length of ∼1h⁻¹cMpc. Our findings agree with previous observations and confirm the results of semi-analytical studies, showing that upper limits on the PMF strength decrease as their coherence scales increase. 

Powerful lasers may be used in the future to produce magnetic fields that would allow us to study turbulent magnetohydrodynamic inverse cascade behaviour. This has so far only been seen in numerical simulations. In the laboratory, however, the produced fields may be highly anisotropic. Here, we present corresponding simulations to show that, during the turbulent decay, such a magnetic field undergoes spontaneous isotropisation. As a consequence, we find the decay dynamics to be similar to that in isotropic turbulence. We also find that an initially pointwise non-helical magnetic field is unstable and develops magnetic helicity fluctuations that can be quantified by the Hosking integral. It is a conserved quantity that characterises magnetic helicity fluctuations and governs the turbulent decay when the mean magnetic helicity vanishes. As in earlier work, the ratio of the magnetic decay time to the Alfvén time is found to be approximately$$50$$in the helical and non-helical cases. At intermediate times, the ratio can even reach a hundred. This ratio determines the endpoints of cosmological magnetic field evolution. 

We present a novel approach to reconstruct gas and dark matter projected density maps of galaxy clusters using score-based generative modeling. Our diffusion model takes in mock SZ and X-ray images as conditional inputs, and generates realizations of corresponding gas and dark matter maps by sampling from a learned data posterior. We train and validate the performance of our model by using mock data from a hydrodynamical cosmological simulation. The model accurately reconstructs both the mean and spread of the radial density profiles in the spatial domain, indicating that the model is able to distinguish between clusters of different mass sizes. In the spectral domain, the model achieves close-to-unity values for the bias and cross-correlation coefficients, indicating that the model can accurately probe cluster structures on both large and small scales. Our experiments demonstrate the ability of score models to learn a strong, nonlinear, and unbiased mapping between input observables and fundamental density distributions of galaxy clusters. These diffusion models can be further fine-tuned and generalized to not only take in additional observables as inputs, but also real observations and predict unknown density distributions of galaxy clusters. 

Graph Neural Networks (GNNs) have become important tools for machine learning on graph-structured data. In this paper, we explore the synergistic combination of graph encoding, graph rewiring, and graph attention, by introducing Graph Attention with Stochastic Structures (GRASS), a novel GNN architecture. GRASS utilizes relative random walk probabilities (RRWP) encoding and a novel decomposed variant (D-RRWP) to efficiently capture structural information. It rewires the input graph by superimposing a random regular graph to enhance long-range information propagation. It also employs a novel additive attention mechanism tailored for graph-structured data. Our empirical evaluations demonstrate that GRASS achieves state-of-the-art performance on multiple benchmark datasets, including a 20.3% reduction in mean absolute error on the ZINC dataset. 

The braking torque that dictates the timing properties of magnetars is closely tied to the large-scale dipolar magnetic field on their surface. The formation of this field has been a topic of ongoing debate. One proposed mechanism, based on macroscopic principles, involves an inverse cascade within the neutron star’s crust. However, this phenomenon has not been observed in realistic simulations. In this study, we provide compelling evidence supporting the feasibility of the inverse cascading process in the presence of an initial helical magnetic field within realistic neutron star crusts and discuss its contribution to the amplification of the large-scale magnetic field. Our findings, derived from a systematic investigation that considers various coordinate systems, peak wavenumber positions, crustal thicknesses, magnetic boundary conditions, and magnetic Lundquist numbers, reveal that the specific geometry of the crustal domain–with its extreme aspect ratio–requires an initial peak wavenumber from small-scale structures for the inverse cascade to occur. However, this same aspect ratio confines the cascade to structures on the scale of the crust, making the formation of a large-scale dipolar surface field unlikely. Despite these limitations, the inverse cascade remains a significant factor in the magnetic field evolution within the crust and may help explain highly magnetized objects with weak surface dipolar fields, such as low-field magnetars and central compact objects.