31 Search Results

In experiments performed with the OMEGA EP laser system, proton deflectometry captured magnetic field dynamics consistent with collisionless shock formation driven by strongly magnetized relativistic electrons. During laser-foil interactions, shocks can form as relativistic electrons and strong surface magnetic fields generated by a short-pulse laser impinge on a cooler plasma produced by a longer-pulse laser. Three-dimensional particle-in-cell simulations reproduce the magnetic draping and fast formation speeds measured in the experiment and reveal that this relativistic-electron-driven shock forms at an interface that is unstable to shear and streaming instabilities. The simulation results provide insight into the microphysics that may influence high-energymore » shocks observed in extreme astrophysical environments.« less

Kinetic approaches are generally accurate in dealing with microscale plasma physics problems but are computationally expensive for large-scale or multiscale systems. One of the long-standing problems in plasma physics is the integration of kinetic physics into fluid models, which is often achieved through sophisticated analytical closure terms. In this paper, we successfully construct a multimoment fluid model with an implicit fluid closure included in the neural network using machine learning. The multimoment fluid model is trained with a small fraction of sparsely sampled data from kinetic simulations of Landau damping, using the physics-informed neural network (PINN) and the gradient-enhanced physics-informedmore » neural network (gPINN). The multimoment fluid model constructed using either PINN or gPINN reproduces the time evolution of the electric field energy, including its damping rate, and the plasma dynamics from the kinetic simulations. In addition, we introduce a variant of the gPINN architecture, namely, gPINN $$\mathcal{p}$$, to capture the Landau damping process. Instead of including the gradients of all the equation residuals, gPINN $$\mathcal{p}$$ only adds the gradient of the pressure equation residual as one additional constraint. Among the three approaches, the gPINN $$\mathcal{p}$$-constructed multimoment fluid model offers the most accurate results. This work sheds light on the accurate and efficient modeling of large-scale systems, which can be extended to complex multiscale laboratory, space, and astrophysical plasma physics problems.« less

ABSTRACT Magnetic reconnection is prevalent in magnetized plasmas in space and laboratories. Despite significant investigations on reconnection in electron–ion plasmas, studies of reconnection in magnetized plasmas with negatively charged dust grains are quite sparse. Here, we report the first fully kinetic simulations of collisionless reconnection in a three-species (i.e. electron, proton, and negatively charged dust grain) dusty plasma, through which the discovery of double Hall pattern is made. The double Hall pattern consists of a traditional Hall quadruple current in between the ion and electron diffusion region and a reversed Hall current in between the boundary of the ion andmore » dust diffusion region. The analysis of the reconnection rate is also given. This study may be applicable to explain observations of planetary magnetospheres and the astrophysical objects, and may be realized in the laboratory studies of dusty plasmas.« less

Collisionless magnetic reconnection typically requires kinetic treatment that is, in general, computationally expensive compared to fluid-based models. In this study, we use the magnetohydrodynamics with an adaptively embedded particle-in-cell (MHD-AEPIC) model to study the interaction of two magnetic flux ropes. This innovative model embeds one or more adaptive PIC regions into a global MHD simulation domain such that the kinetic treatment is only applied in regions where the kinetic physics is prominent. We compare the simulation results among three cases: (1) MHD with adaptively embedded PIC regions, (2) MHD with statically (or fixed) embedded PIC regions, and (3) a fullmore » PIC simulation. The comparison yields good agreement when analyzing their reconnection rates and magnetic island separations as well as the ion pressure tensor elements and ion agyrotropy. In order to reach good agreement among the three cases, large adaptive PIC regions are needed within the MHD domain, which indicates that the magnetic island coalescence problem is highly kinetic in nature, where the coupling between the macro-scale MHD and micro-scale kinetic physics is important.« less

Magnetohydrodynamic turbulence regulates the transfer of energy from large to small scales in many astrophysical systems, including the solar atmosphere. We perform three-dimensional magnetohydrodynamic simulations with unprecedentedly large magnetic Reynolds number to reveal how rapid reconnection of magnetic field lines changes the classical paradigm of the turbulent energy cascade. By breaking elongated current sheets into chains of small magnetic flux ropes (or plasmoids), magnetic reconnection leads to a previously undiscovered range of energy cascade, where the rate of energy transfer is controlled by the growth rate of the plasmoids. As a consequence, the turbulent energy spectra steepen and attain amore » spectral index of -2.2 that is accompanied by changes in the anisotropy of turbulence eddies. The omnipresence of plasmoids and their consequences on, for example, solar coronal heating, can be further explored with current and future spacecraft and telescopes.« less

A large number of heliophysicists from across career levels, institution types, and job titles came together to support a poster at Heliophysics 2050 and the position papers for the 2024 Heliophysics decadal survey titled “Cultivating a Culture of Inclusivity in Heliophysics,” “The Importance of Policies: It’s not just a pipeline problem,” and “Mentorship within Heliophysics.” While writing these position papers, the number of people who privately shared disturbing stories and experiences of bullying and harassment was shocking. The number of people who privately expressed how burned out they were was staggering. The number of people who privately spoke about howmore » they considered leaving the field for their and their family’s health was astounding. And for as much good there is in our community, it is still a toxic environment for many. If we fail to do something now, our field will continue to suffer. While acknowledging the ongoing growth that we as individuals must work toward, we call on our colleagues to join us in working on organizational, group, and personal levels toward a truly inclusive culture, for the wellbeing of our colleagues and the success of our field. This work includes policies, processes, and commitments to promote: accountability for bad actors; financial security through removing the constant anxiety about funding; prioritization of mental health and community through removing constant deadlines and constant last-minute requests; a collaborative culture rather than a hyper-competitive one; and a community where people can thrive as whole persons and do not have to give up a healthy or well-rounded life to succeed.« less

Deriving governing equations of complex physical systems based on first principles can be quite challenging when there are certain unknown terms and hidden physical mechanisms in the systems. In this work, we apply a deep learning architecture to learn fluid partial differential equations (PDEs) of a plasma system based on the data acquired from a fully kinetic model. Here, the learned multi-moment fluid PDEs are demonstrated to incorporate kinetic effect such as Landau damping. Based on the learned fluid closure, the data-driven, multi-moment fluid modeling can well reproduce all the physical quantities derived from the fully kinetic model. The calculatedmore » damping rate of Landau damping is consistent with both the fully kinetic simulation and the linear theory. The data-driven fluid modeling of PDEs for complex physical systems may be applied to improve the fluid closure and reduce the computational cost of multi-scale modeling of global systems.« less

In this work, we investigate Mars-ward planetary ions (O⁺ and O₂⁺) in the Martian magnetotail that potentially reduce the amount of escaping ions. The global properties of Mars-ward flows in the Martian magnetotail are characterized, based on over 13-years of ion data (May 2007–December 2020) collected by the Analyzer of Space Plasma and Energetic Atoms instrument on Mars Express. We find that Mars-ward flows are frequently observed in the vicinity of the crustal fields, implying that crustal fields may play a key role in producing such flows. The occurrence rate and sunward flux are found higher during solar maximum thanmore » solar minimum. However, the occurrence rate and flux of Mars-ward flows are relatively low. This is different from the case at Venus, where the planetward flows can significantly decrease the total escape rates of ions.« less

Mercury’s southern inner magnetosphere is an unexplored region as it was not observed by earlier space missions. In October 2021, BepiColombo mission has passed through this region during its first Mercury flyby. Here, we describe the observations of SERENA ion sensors nearby and inside Mercury’s magnetosphere. An intermittent high-energy signal, possibly due to an interplanetary magnetic flux rope, has been observed downstream Mercury, together with low energy solar wind. Low energy ions, possibly due to satellite outgassing, were detected outside the magnetosphere. The dayside magnetopause and bow-shock crossing were much closer to the planet than expected, signature of a highlymore » eroded magnetosphere. Different ion populations have been observed inside the magnetosphere, like low latitude boundary layer at magnetopause inbound and partial ring current at dawn close to the planet. These observations are important for understanding the weak magnetosphere behavior so close to the Sun, revealing details never reached before.« less

Exoplanets orbiting M dwarfs within habitable zones are exposed to stellar environments more extreme than that terrestrial planets experience in our solar system, which can significantly impact the atmospheres of the exoplanets and affect their habitability and sustainability. This study provides the first prediction of hot oxygen corona structure and the associated photochemical loss from a 1 bar CO₂-dominated atmosphere of a Venus-like rocky exoplanet, where dissociative recombination of O₂⁺ ions is assumed to be the major source reaction for the escape of neutral O atoms and formation of the hot O corona (or exospheres) as on Mars and Venus.more » We employ a 3D Monte Carlo code to simulate the exosphere of Proxima Centauri b (PCb) based on the ionosphere simulated by a 3D magnetohydrodynamic model. Our simulation results show that variability of the stellar wind dynamic pressure over one orbital period of PCb does not affect the overall spatial structure of the hot O corona but contributes to the change in the global hot O escape rate that varies by an order of magnitude. The escape increases dramatically when the planet possesses its intrinsic magnetic fields as the ionosphere becomes more extended with the presence of a global magnetic field. Furthermore, the extended hot O corona may lead to a more extended H exosphere through collisions between thermal H and hot O, which exemplifies the importance of considering nonthermal populations in exospheres to interpret future observations.« less