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Abstract The use of supervised methods in space science have demonstrated powerful capability in classification tasks, but purely unsupervised methods have been less utilized for the classification of spacecraft observations. We use a combination of unsupervised methods, being principal component analysis, Self‐Organizing Maps, and hierarchical agglomerative clustering, to classify THEMIS and MMS observations as having occurred in the magnetosphere, magnetosheath, or the solar wind. The resulting classification are validated visually by analyzing the distribution of classifications and studying individual time series as well as by comparison to the labeled data set of a previous model, against which ours has an accuracy of 99.4. The model has a variety of applications beyond region classification such as deeper hierarchical analysis, magnetopause and bow shock crossing identification, and identification of bursty bulk flows, hot flow anomalies, and foreshock bubbles. 

Abstract Observational data at heliocentric distances of tens of solar radii suggest that fast magnetosonic modes make up a considerable fraction of the solar wind fluctuations. Furthermore, this fraction appears to increase closer to the Sun. We carry out three-dimensional kinetic simulations with particle ions and fluid electrons to evaluate the proton and alpha-particle heating produced by the damping of the fast waves in the solar corona. Realistic parameters at 5 solar radii, including the fluctuation amplitude, are used. We show that, due to the cyclotron resonance, the alphas are heated preferentially perpendicularly to the magnetic field and much more strongly than the protons. The presence of the alpha particles alters the energy partition by reducing the heating of the protons. Nevertheless, the proton heating is sufficient to account for the solar wind acceleration. 

Abstract EUropean Heliospheric FORecasting Information Asset (EUHFORIA) is a physics‐based data‐driven solar wind and coronal mass ejections (CMEs) propagation model designed for space weather forecasting and event analysis investigations. Although EUHFORIA can predict the solar wind plasma and magnetic field properties at Earth, it is not equipped to quantify the geo‐effectiveness of the solar transients in terms of geomagnetic indices like the disturbance storm time (Dst) index and the auroral indices, that quantify the impact of the magnetized plasma encounters on Earth's magnetosphere. Therefore, we couple EUHFORIA with the Open Geospace General Circulation Model (OpenGGCM), a magnetohydrodynamic model of the response of Earth's magnetosphere, ionosphere, and thermosphere to transient solar wind characteristics. In this coupling, OpenGGCM is driven by the solar wind and interplanetary magnetic field obtained from EUHFORIA simulations to produce the magnetospheric and ionospheric response to the CMEs. This coupling is validated with two observed geo‐effective CME events driven with the spheromak flux‐rope CME model. We compare these simulation results with the indices obtained from OpenGGCM simulations driven by the measured solar wind data from spacecraft. We further employ the dynamic time warping (DTW) technique to assess the model performance in predicting Dst. The main highlight of this study is to use EUHFORIA simulated time series to predict the Dst and auroral indices 1–2 days in advance, as compared to using the observed solar wind data at L1, which only provides predictions 1–2 hr before the actual impact. 

Abstract We investigate a secondary proton beam instability coexisting with the ambient solar wind turbulence at 50R_☉. Three-dimensional hybrid numerical simulations (particle ions and a quasi-neutralizing electron fluid) are carried out with the plasma parameters in the observed range. In the turbulent background, the particle distribution function, in particular the slope of the “bump-on-tail” responsible for the instability, is time-dependent and inhomogeneous. The presence of the turbulence substantially reduces the growth rate and saturation level of the instability. We derive magnetic power spectra from the observational data and perform a statistical analysis to evaluate the average turbulence intensity at 50R_☉. This information is used to link the observed frequency spectrum to the wavenumber spectrum in the simulations. We verify that Taylor’s frozen-in hypothesis is valid for this purpose to a sufficient extent. To reproduce the typical magnetic power spectrum of the instability observed concurrently with the background turbulence, an artificial spacecraft probe is run through the simulation box. The thermal-ion instabilities are often seen as power elevations in the kinetic range of scales above an extrapolation of the turbulence spectrum from larger scales. We show that the elevated power in the simulations is much higher than the background level. Therefore, the turbulence at the average intensity does not obscure the secondary proton beam instability, as opposed to the solar wind at 1 au, in which the ambient turbulence typically obscures thermal-ion instabilities. 

Abstract Some of the most common processes in the solar wind, such as turbulence and wave generation by instabilities, are associated with spectral magnetic helicity. Therefore, the helicity is a convenient tool to investigate these processes. We use three-dimensional nonlinear kinetic simulations with particle ions and fluid electrons to analyze the magnetic helicity produced by proton temperature anisotropy instabilities coexisting with an ambient turbulence. The symmetry of the unstable system is violated by alpha-particle streaming with respect to protons along the mean magnetic field. At the same time, the turbulent fluctuations are also imbalanced by a nonzero cross-helicity. We show that in the nonlinear phase of the instability the resulting helicity structure is different from the prediction of the linear theory. In particular, it contains sign reversals and multiple domains of nonzero helicity. The turbulence generates its own magnetic helicity signature, which extends over a wide range of angles around the direction perpendicular to the mean magnetic field, and can have a sign the same as or opposite to that of the instability. These findings are consistent with the observed helicity spectra in the solar wind. 

Abstract We present the implementation of a two-moment-based general-relativistic multigroup radiation transport module in theGeneral-relativisticmultigridnumerical (Gmunu) code. On top of solving the general-relativistic magnetohydrodynamics and the Einstein equations with conformally flat approximations, the code solves the evolution equations of the zeroth- and first-order moments of the radiations in the Eulerian-frame. An analytic closure relation is used to obtain the higher order moments and close the system. The finite-volume discretization has been adopted for the radiation moments. The advection in spatial space and frequency-space are handled explicitly. In addition, the radiation–matter interaction terms, which are very stiff in the optically thick region, are solved implicitly. The implicit–explicit Runge–Kutta schemes are adopted for time integration. We test the implementation with a number of numerical benchmarks from frequency-integrated to frequency-dependent cases. Furthermore, we also illustrate the astrophysical applications in hot neutron star and core-collapse supernovae modelings, and compare with other neutrino transport codes. 

Abstract We revisit the question of how the unstable scattering of interstellar pickup ions (PUIs) may drive turbulence in the outer solar wind and why the energy released into fluctuations by this scattering appears to be significantly less than the standard bispherical prediction. We suggest that energization of the newly picked-up ions by the ambient turbulence during the scattering process can result in a more spherical distribution of PUIs and reduce the generated fluctuation energy to a level consistent with the observations of turbulent intensities and core solar wind heating. This scenario implies the operation of a self-regulation mechanism that maintains the observed conditions of turbulence and heating in the PUI-dominated solar wind. 

Abstract We introduce a new framework called Machine Learning (ML) based Auroral Ionospheric electrodynamics Model (ML‐AIM). ML‐AIM solves a current continuity equation by utilizing the ML model of Field Aligned Currents of Kunduri et al. (2020,https://doi.org/10.1029/2020JA027908), the FAC‐derived auroral conductance model of Robinson et al. (2020,https://doi.org/10.1029/2020JA028008), and the solar irradiance conductance model of Moen and Brekke (1993,https://doi.org/10.1029/92gl02109). The ML‐AIM inputs are 60‐min time histories of solar wind plasma, interplanetary magnetic fields (IMF), and geomagnetic indices, and its outputs are ionospheric electric potential, electric fields, Pedersen/Hall currents, and Joule Heating. We conduct two ML‐AIM simulations for a weak geomagnetic activity interval on 14 May 2013 and a geomagnetic storm on 7–8 September 2017. ML‐AIM produces physically accurate ionospheric potential patterns such as the two‐cell convection pattern and the enhancement of electric potentials during active times. The cross polar cap potentials (Φ_PC) from ML‐AIM, the Weimer (2005,https://doi.org/10.1029/2004ja010884) model, and the Super Dual Auroral Radar Network (SuperDARN) data‐assimilated potentials, are compared to the ones from 3204 polar crossings of the Defense Meteorological Satellite Program F17 satellite, showing better performance of ML‐AIM than others. ML‐AIM is unique and innovative because it predicts ionospheric responses to the time‐varying solar wind and geomagnetic conditions, while the other traditional empirical models like Weimer (2005,https://doi.org/10.1029/2004ja010884) designed to provide a quasi‐static ionospheric condition under quasi‐steady solar wind/IMF conditions. Plans are underway to improve ML‐AIM performance by including a fully ML network of models of aurora precipitation and ionospheric conductance, targeting its characterization of geomagnetically active times. 

Abstract The recent detections of the ∼10 s longγ-ray bursts (GRBs) 211211A and 230307A followed by softer temporally extended emission (EE) and kilonovae point to a new GRB class. Using state-of-the-art first-principles simulations, we introduce a unifying theoretical framework that connects binary neutron star (BNS) and black hole–NS (BH–NS) merger populations with the fundamental physics governing compact binary GRBs (cbGRBs). For binaries with large total masses,M_tot≳ 2.8M_⊙, the compact remnant created by the merger promptly collapses into a BH surrounded by an accretion disk. The duration of the pre-magnetically arrested disk (MAD) phase sets the duration of the roughly constant power cbGRB and could be influenced by the disk mass,M_d. We show that massive disks (M_d≳ 0.1M_⊙), which form for large binary mass ratiosq≳ 1.2 in BNS orq≲ 3 in BH–NS mergers, inevitably produce 211211A-like long cbGRBs. Once the disk becomes MAD, the jet power drops with the mass accretion rate as $\dot{M}\sim t^{-2}$, establishing the EE decay. Two scenarios are plausible for short cbGRBs. They can be powered by BHs with less massive disks, which form for otherqvalues. Alternatively, for binaries withM_tot≲ 2.8M_⊙, mergers should go through a hypermassive NS (HMNS) phase, as inferred for GW170817. Magnetized outflows from such HMNSs, which typically live for ≲1 s, offer an alternative progenitor for short cbGRBs. The first scenario is challenged by the bimodal GRB duration distribution and the fact that the Galactic BNS population peaks at sufficiently low masses that most mergers should go through an HMNS phase. 

Abstract We present the first numerical simulations that track the evolution of a black hole–neutron star (BH–NS) merger from premerger tor≳ 10¹¹cm. The disk that forms after a merger of mass ratioq= 2 ejects massive disk winds (3–5 × 10⁻²M_⊙). We introduce various postmerger magnetic configurations and find that initial poloidal fields lead to jet launching shortly after the merger. The jet maintains a constant power due to the constancy of the large-scale BH magnetic flux until the disk becomes magnetically arrested (MAD), where the jet power falls off asL_j∼t⁻². All jets inevitably exhibit either excessive luminosity due to rapid MAD activation when the accretion rate is high or excessive duration due to delayed MAD activation compared to typical short gamma-ray bursts (sGRBs). This provides a natural explanation for long sGRBs such as GRB 211211A but also raises a fundamental challenge to our understanding of jet formation in binary mergers. One possible implication is the necessity of higher binary mass ratios or moderate BH spins to launch typical sGRB jets. For postmerger disks with a toroidal magnetic field, dynamo processes delay jet launching such that the jets break out of the disk winds after several seconds. We show for the first time that sGRB jets with initial magnetizationσ₀> 100 retain significant magnetization (σ≫ 1) atr> 10¹⁰cm, emphasizing the importance of magnetic processes in the prompt emission. The jet–wind interaction leads to a power-law angular energy distribution by inflating an energetic cocoon whose emission is studied in a companion paper.