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Gabor Toth

Publications and source records attributed to Gabor Toth.

At least 19 recordsLinked to original sources

Energy Partitioning at the Termination Shock

We show new results of a global 3D magnetohydrodynamic (MHD) simulation of the Boston University outer heliosphere model where we used a newly developed approach that distributes the non-adiabatic shock heating among the cold protons, electrons, and pickup-ions (PUIs), while maintaining total energy conservation of all ions (cold protons and PUIs) and electrons. In our previous simulations ( E.S. Bair et al. 2025; B. van der Holst et al. 2026), all non-adiabatic shock heating was channeled to the cold protons, resulting in a too large temperature jump at the termination shock (TS) for the thermal solar wind. Using a new methodology we improved the simulation results with respect to the temperature jump observed at the TS by Voyager 2 (V2) spacecraft. Our simulations approached the observed jump conditions of a factor 10--20 in the cold solar wind temperature V2 measurements, and we obtain improvements in the simulation results relative to the data. Because we directly estimate in this way the distribution of non-adiabatic heating at the TS, we have the opportunity to study the physical process of heating cold plasma and PUIs in the TS. The results show that having almost 100\% non-adiabatic shock heating going towards PUIs at the TS reproduces the jump conditions observed along the V2 trajectory. This information is key to understanding the physical processes that shape the heliosphere. As shown by M. Opher et al. (2020), PUIs significantly change the shape of the heliosphere, for example, the presence of hot PUIs results in a deflated inner heliosheath. Our work provides the architecture of how energy partitioning at shocks in kinetic simulations (J. Giacalone et al. 2021) can be utilized in global MHD models.

astro-ph.SR

Reconstructing the Probability Measure of a Multi-group Curie-Weiss Model with Interacting Groups

We study the problem of reconstructing the probability measure of a multi-group version of the Curie-Weiss or mean-field model of ferromagnetism from a sample of the voting behaviour the population. While originally used to study phase transitions in statistical mechanics, the Curie-Weiss or mean-field model has been applied to study phenomena where many agents interact with each other, in particular in case of a heterogeneous population with identifiable subpopulations. The degree of social cohesion within social groups manifests in the way the members of the group influence each others' decisions as well as how they behave under outside influence from voters belonging to another group. Contrary to single-group Curie-Weiss models, here we have a larger number of coupling parameters which have to be estimated. While the maximum likelihood estimator of the coupling parameters has desirable statistical properties in theory, computational challenges make applications to larger populations impractical. Therefore, we analyse an estimator based on asymptotic approximations to the behaviour of the Curie-Weiss model valid for large populations. Due to the wide applicability of models such as Curie-Weiss, the estimator is potentially useful in disciplines such as political science, sociology, automated voting, and preference aggregation.

physics.soc-ph

Smiling Regulates Emotion During Traumatic Recollection

We study when, where, and why 978 Holocaust survivors smile in video testimonies. We create an automatic smile detection model from facial features with an F1 of 85% and annotate detected smiles under two established taxonomies of smiling. We produce narrative features on 1,083,417 transcript sentences as well as emotional valence from three different modalities: audio, eye gaze, and text transcript. Smiling rates are associated with specific semantic topics, narrative structures, and temporal syntaxes across the corpus. Smiles often occur during periods of intense negative affect and we find negative-affect smiles are associated with more positive subsequent valence trajectories across all three modalities. Smiling reduces eye dynamics and blink rates, with both of these effects modulated by narrative valence. Taken together, we conclude that smiling plays a critical role in regulating emotion and social interaction during traumatic recollection.

cs.MM

Interstellar Dust Transport Through the Heliosphere Including the Sector Region

Interstellar dust has been detected in situ flowing through the heliosphere. However, our ability to derive the density and size distribution of the interstellar dust in the local interstellar medium from this directly detected dust requires modeling the transport of the grains as they interact with the solar wind magnetic field. The magnetic field in the sector region that contains the heliospheric current sheet has rapid polarity flips which can present an effectively very low averaged field strength to dust grains that have gyroradii tens of au in size. We present new calculations of dust transport through the heliosphere using models that include the sector region to assess the effects on dust transport. We show that the sector region can act as a window allowing even relatively small grains to penetrate deep into the heliosphere. We find the sector region reduces the variation in dust density with the solar cycle (as compared to models without the sector region), with very little concentration or dilution of the dust for grains larger than \sim 0.1$ $\mu$m for most of the solar cycle. We still find a substantial concentration of the dust in the ecliptic plane for a focusing overall polarity of the field at solar minimum. These models do not include the time dependence of the magnetic field during transport of grains through the heliosphere. Nevertheless, our results imply that observations of interstellar dust grains, even near Earth, could be fairly accurate in determining their size distribution in the surrounding interstellar medium.

astro-ph.GA

Evolution of Coronal Mass Ejections in Different Data-Driven Solar Wind Conditions

Numerical models of the solar wind and coronal mass ejections (CMEs) utilize photospheric magnetic field observations to prescribe the inner boundary conditions for the plasma solutions. These magnetic field data are available to the community through various observational instruments, prepared via different methodologies and/or flux-transport models. The solar wind solution driven by these maps provides the ambient plasma environment into which CMEs travel, coupling, and interacting with the surrounding plasma and governing the CME evolution and propagation in the solar corona and inner heliosphere. In this work, we use different input magnetic field maps for the same time period to drive the global Alfven Wave Solar atmosphere Model (AWSoM). We obtain the ambient solar wind conditions and compare the plasma properties and magnetic morphology in the coronal domain to study the influence of the input maps. To understand how the resulting coronal solutions impact CMEs, we launch eruptions described by analytical flux ropes into these data-driven solutions and compare their evolution in the coronal domain (up to 24 solar radii radially). The CMEs achieve varying speeds, deceleration rates, propagation directions, mass and energies while coupling with the background solar wind. We quantify these differences to show that the different input driving maps can significantly impact the simulated CME propagation in the solar wind plasma. This also highlights the importance of understanding the uncertainties associated with data-driven modeling that become increasingly important in operational models and space weather prediction.

astro-ph.SR

Reconstructing the Probability Measure of a Curie-Weiss Model Observing the Realisations of a Subset of Spins

We study the problem of reconstructing the probability measure of the Curie-Weiss model from a sample of the voting behaviour of a subset of the population. While originally used to study phase transitions in statistical mechanics, the Curie-Weiss or mean-field model has been applied to study phenomena, where many agents interact with each other. It is useful to measure the degree of social cohesion in social groups, which manifests in the way the members of the group influence each others' decisions. In practice, statisticians often only have access to survey data from a representative subset of a population. As such, it is useful to provide methods to estimate social cohesion from such data. The estimators we study have some positive properties, such as consistency, asymptotic normality, and large deviation principles. The main advantages are that they require only a sample of votes belonging to a (possibly very small) subset of the population and have a low computational cost. Due to the wide application of models such as Curie-Weiss, these estimators are potentially useful in disciplines such as political science, sociology, automated voting, and preference aggregation.

math.PR

Approximation Techniques for the Reconstruction of the Probability Measure and the Coupling Parameters in a Curie-Weiss Model for Large Populations

The Curie-Weiss model, originally used to study phase transitions in statistical mechanics, has been adapted to model phenomena in social sciences where many agents interact with each other. Reconstructing the probability measure of a Curie-Weiss model via the maximum likelihood method runs into the problem of computing the partition function which scales exponentially with the population. We study the estimation of the coupling parameters of a multi-group Curie-Weiss model using large population asymptotic approximations for the relevant moments of the probability distribution in the case that there are no interactions between groups. As a result, we obtain an estimator which can be calculated at a low and constant computational cost for any size of the population. The estimator is consistent (under the added assumption that the population is large enough), asymptotically normal, and satisfies large deviation principles. The estimator is potentially useful in political science, sociology, automated voting, and in any application where the degree of social cohesion in a population has to be identified. The Curie-Weiss model's coupling parameters provide a natural measure of social cohesion. We discuss the problem of estimating the optimal weights in two-tier voting systems.

math.ST

Evidence of Time-Dependent Diffusive Shock Acceleration in the 2022 September 5 Solar Energetic Particle Event

On 2022 September 5, a large solar energetic particle (SEP) event was detected by Parker Solar Probe (PSP) and Solar Orbiter (SolO), at heliocentric distances of 0.07 and 0.71 au, respectively. PSP observed an unusual velocity-dispersion signature: particles below $\sim$1 MeV exhibited a normal velocity dispersion, while higher-energy particles displayed an inverse velocity arrival feature, with the most energetic particles arriving later than those at lower energies. The maximum energy increased from about 20-30 MeV upstream to over 60 MeV downstream of the shock. The arrival of SEPs at PSP was significantly delayed relative to the expected onset of the eruption. In contrast, SolO detected a typical large SEP event characterized by a regular velocity dispersion at all energies up to 100 MeV. To understand these features, we simulate particle acceleration and transport from the shock to the observers with our newly developed SEP model - Particle ARizona and MIchigan Solver on Advected Nodes (PARMISAN). Our results reveal that the inverse velocity arrival and delayed particle onset detected by PSP originate from the time-dependent diffusive shock acceleration processes. After shock passage, PSP's magnetic connectivity gradually shifted due to its high velocity near perihelion, detecting high-energy SEPs streaming sunward. Conversely, SolO maintained a stable magnetic connection to the strong shock region where efficient acceleration was achieved. These results underscore the importance of spatial and temporal dependence in SEP acceleration at interplanetary shocks, and provide new insights to understand SEP variations in the inner heliosphere.

astro-ph.SR

Suppressing spurious oscillations and particle noise in particle-in-cell simulations

Particle-in-cell (PIC) simulations are essential for studying kinetic plasma processes, but they often suffer from statistical noise, especially in plasmas with fast flows. We have also found that the typical central difference scheme used in PIC codes to solve Maxwell's equations produces spurious oscillations near discontinuities, which can lead to unphysical solutions. In this work, we present numerical techniques to address these challenges within the semi-implicit PIC code FLEKS, which is based on the Gauss's Law-satisfying Energy-Conserving Semi-Implicit Particle-in-Cell method (GL-ECSIM). First, we introduce a Lax-Friedrichs-type diffusion term with a flux limiter into the Maxwell solver to suppress unphysical oscillations near discontinuities. Second, we propose a novel approach for calculating the current density in the comoving frame, which significantly reduces particle noise in simulations with fast plasma flows. Numerical tests are presented to demonstrate the effectiveness of these methods in mitigating spurious oscillations and noise in shock and magnetic reconnection simulations.

physics.comp-ph

Reconstruction of the Probability Measure and the Coupling Parameters in a Curie-Weiss Model

The Curie-Weiss model is used to study phase transitions in statistical mechanics and has been the object of rigorous analysis in mathematical physics. We analyse the problem of reconstructing the probability measure of a multi-group Curie-Weiss model from a sample of data by employing the maximum likelihood estimator for the coupling parameters of the model, under the assumption that there is interaction within each group but not across group boundaries. The estimator has a number of positive properties, such as consistency, asymptotic normality, and exponentially decaying probabilities of large deviations of the estimator with respect to the true parameter value. A shortcoming in practice is the necessity to calculate the partition function of the Curie-Weiss model, which scales exponentially with respect to the population size. There are a number of applications of the estimator in political science, sociology, and automated voting, centred on the idea of identifying the degree of social cohesion in a population. In these applications, the coupling parameter is a natural way to quantify social cohesion. We treat the estimation of the optimal weights in a two-tier voting system, which requires the estimation of the coupling parameter.

math.PR

Simulation Models for Exploring Magnetic Reconnection

Simulations have played a critical role in the advancement of our knowledge of magnetic reconnection. However, due to the inherently multiscale nature of reconnection, it is impossible to simulate all physics at all scales. For this reason, a wide range of simulation methods have been crafted to study particular aspects and consequences of magnetic reconnection. This chapter reviews many of these methods, laying out critical assumptions, numerical techniques, and giving examples of scientific results. Plasma models described include magnetohydrodynamics (MHD), Hall MHD, Hybrid, kinetic particle-in-cell (PIC), kinetic Vlasov, Fluid models with embedded PIC, Fluid models with direct feedback from energetic populations, and the Rice Convection Model (RCM).

physics.plasm-ph

A kinetic-magnetohydrodynamic model with adaptive mesh refinement for modeling heliosphere neutral-plasma interaction

The charge exchange between the interstellar medium (ISM) and the solar wind plasma is crucial for determining the structures of the heliosphere. Since both the neutral-ion and neutral-neutral collision mean free paths are either comparable to or larger than the size of the heliosphere, the neutral phase space distribution can deviate far away from the Maxwellian distribution. A kinetic description for the neutrals is crucial for accurately modeling the heliosphere. It is computationally challenging to run three-dimensional (3D) time-dependent kinetic simulations due to the large number of macro-particles. In this paper, we present the new highly efficient SHIELD-2 model with a kinetic model of neutrals and a magnetohydrodynamic (MHD) model for the ions and electrons. To improve the simulation efficiency, we implement adaptive mesh refinement (AMR) and particle splitting and merging algorithms for the neutral particles to reduce the particle number that is required for an accurate simulation. We present several tests to verify and demonstrate the capabilities of the model.

physics.space-ph

Interaction between a Coronal Mass Ejection and Comet 67P/Churyumov-Gerasimenko

The interaction between a Coronal Mass Ejection (CME) and a comet has been observed several times by in-situ observations from the Rosetta Plasma Consortium (RPC), which is designed to investigate the cometary magnetosphere of comet 67P/Churyumov-Gerasimenko (CG). Goetz et al. (2019) reported a magnetic field of up to 300 nT measured in the inner coma, which is among the largest interplanetary magnetic fields observed in the solar system. They suggested the large magnetic field observations in the inner coma come from magnetic field pile-up regions, which are generated by the interaction between a CME and/or corotating interaction region and the cometary magnetosphere. However, the detailed interaction between a CME and the cometary magnetosphere of comet CG in the inner coma has not been investigated by numerical simulations yet. In this manuscript, we will use a numerical model to simulate the interaction between comet CG and a Halloween class CME and investigate its magnetospheric response to the CME. We find that the plasma structures change significantly during the CME event, and the maximum value of the magnetic field strength is more than 500nT close to the nucleus. Virtual satellites at similar distances as Rosetta show that the magnetic field strength can be as large as 250nT, which is slightly less than what Goetz et al. (2019) reported.

astro-ph.EP

Solar Wind Driven from GONG Magnetograms in the Last Solar Cycle

In a previous study, Huang et al. (2023) used the Alfven Wave Solar atmosphere Model (AWSoM), one of the widely used solar wind models in the community, driven by ADAPT-GONG magnetograms to simulate the solar wind in the last solar cycle and found that the optimal Poynting flux parameter can be estimated from either the open field area or the average unsigned radial component of the magnetic field in the open field regions. It was also found that the average energy deposition rate (Poynting flux) in the open field regions is approximately constant. In the current study, we expand the previous work by using GONG magnetograms to simulate the solar wind for the same Carrington rotations and determine if the results are similar to the ones obtained with ADAPT-GONG magnetograms. Our results indicate that similar correlations can be obtained from the GONG maps. Moreover, we report that ADAPT-GONG magnetograms can consistently provide better comparisons with 1 AU solar wind observations than GONG magnetograms, based on the best simulations selected by the minimum of the average curve distance for the solar wind speed and density.

astro-ph.SR

Adjusting the Potential Field Source Surface Height Based on MHD Simulations

A potential field solution is widely used to extrapolate the coronal magnetic field above the Sun's surface to a certain height. This model applies the current-free approximation and assumes that the magnetic field is entirely radial beyond the source surface height, which is defined as the radial distance from the center of the Sun. Even though the source surface is commonly specified at 2.5 Rs (solar radii), previous studies have suggested that this value is not optimal in all cases. In this study, we propose a novel approach to specify the source surface height, by comparing the areas of the open magnetic field regions from the potential field solution with predictions made by a magnetohydrodynamics model, in our case the Alfven Wave Solar atmosphere Model. We find that the adjusted source surface height is significantly less than 2.5 Rs near solar minimum, and slightly larger than 2.5 Rs near solar maximum. We also report that the adjusted source surface height can provide a better open flux agreement with the observations near the solar minimum, while the comparison near the solar maximum is slightly worse.

astro-ph.SR

Sparse Variational Contaminated Noise Gaussian Process Regression with Applications in Geomagnetic Perturbations Forecasting

Gaussian Processes (GP) have become popular machine-learning methods for kernel-based learning on datasets with complicated covariance structures. In this paper, we present a novel extension to the GP framework using a contaminated normal likelihood function to better account for heteroscedastic variance and outlier noise. We propose a scalable inference algorithm based on the Sparse Variational Gaussian Process (SVGP) method for fitting sparse Gaussian process regression models with contaminated normal noise on large datasets. We examine an application to geomagnetic ground perturbations, where the state-of-the-art prediction model is based on neural networks. We show that our approach yields shorter prediction intervals for similar coverage and accuracy when compared to an artificial dense neural network baseline.

cs.LG

Analytic Model and Magnetohydrodynamic Simulations of Three-dimensional Magnetic Switchbacks

Parker Solar Probe observations reveal that the near-Sun space is almost filled with magnetic switchbacks (``switchbacks'' hereinafter), which may be a major contributor to the heating and acceleration of solar wind. Here, for the first time, we develop an analytic model of an axisymmetric switchback with uniform magnetic field strength. In this model, three parameters control the geometry of the switchback: height (length along the background magnetic field), width (thickness along radial direction perpendicular to the background field), and the radial distance from the center of switchback to the central axis, which is a proxy of the size of the switchback along the third dimension. We carry out three-dimensional magnetohydrodynamic simulations to investigate the dynamic evolution of the switchback. Comparing simulations conducted with compressible and incompressible codes, we verify that compressibility, i.e. parametric decay instability, is necessary for destabilizing the switchback. Our simulations also reveal that the geometry of the switchback significantly affects how fast the switchback destabilizes. The most stable switchbacks are 2D-like (planar) structures with large aspect ratios (length to width), consistent with the observations. We show that when plasma beta ($\beta$) is smaller than one, the switchback is more stable as $\beta$ increases. However, when $\beta$ is greater than one, the switchback becomes very unstable as the pattern of the growing compressive fluctuations changes. Our results may explain some of the observational features of switchbacks, including the large aspect ratios and nearly constant occurrence rates in the inner heliosphere.

physics.space-ph

Detection of an Arbitrary Number of Communities in a Block Spin Ising Model

We study the problem of community detection in a general version of the block spin Ising model featuring M groups, a model inspired by the Curie-Weiss model of ferromagnetism in statistical mechanics. We solve the general problem of identifying any number of groups with any possible coupling constants. Up to now, the problem was only solved for the specific situation with two groups of identical size and identical interactions. Our results can be applied to the most realistic situations, in which there are many groups of different sizes and different interactions. In addition, we give an explicit algorithm that permits the reconstruction of the structure of the model from a sample of observations based on the comparison of empirical correlations of the spin variables, thus unveiling easy applications of the model to real-world voting data and communities in biology.

math.PR