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Anomalous ion heating is frequently observed to accompany magnetic reconnection, yet there is little consensus on its origin. Instead of the usual velocity-space analysis, we use phase-space analysis to exhaustively explain how ions are nonthermally energized during collisionless, antiparallel magnetic reconnection. There are both ordered and disordered aspects in the process; the former is explained in terms of conservative quantities, and the latter is explained by demonstrating chaos through a direct calculation of Lyapunov exponents. The former induces “multibeam-like heating” in all three directions, whereas the latter induces stochastic bulk heating. Profiles of the ion temperature tensor components during reconnection can be easily understood by the phase-space distributions of ions in different motional stages.

 

The matter in an accretion disk must lose angular momentum when moving radially inwards but how this works has long been a mystery. By calculating the trajectories of individual colliding neutrals, ions, and electrons in a weakly ionized 2D plasma containing gravitational and magnetic fields, we numerically simulate accretion disk dynamics at the particle level. As predicted by Lagrangian mechanics, the fundamental conserved global quantity is the total canonical angular momentum, not the ordinary angular momentum. When the Kepler angular velocity and the magnetic field have opposite polarity, collisions between neutrals and charged particles cause: (i) ions to move radially inwards, (ii) electrons to move radially outwards, (iii) neutrals to lose ordinary angular momentum, and (iv) charged particles to gain canonical angular momentum. Neutrals thus spiral inward due to their decrease of ordinary angular momentum while the accumulation of ions at small radius and accumulation of electrons at large radius produces a radially outward electric field. In 3D, this radial electric field would drive an out-of-plane poloidal current that produces the magnetic forces that drive bidirectional astrophysical jets. Because this neutral angular momentum loss depends only on neutrals colliding with charged particles, it should be ubiquitous. Quantitative scaling of the model using plausible disk density, temperature, and magnetic field strength gives an accretion rate of 3 × 10⁻⁸solar mass per year, which is in good agreement with observed accretion rates.

 

During transient instabilities in a 2 eV, highly collisional MHD-driven plasma jet experiment, evidence of a 6 keV electron tail was observed via x-ray measurements. The cause for this unexpected high energy tail is explored using numerical simulations of the Rutherford scattering of a large number of electrons and ions in the presence of a uniform electric field that is abruptly turned on as in the experiment. When the only active processes are Rutherford scattering and acceleration by the electric field, contrary to the classical Fokker–Planck theory of plasma resistivity, it is found that no steady state develops, and instead, the particle kinetic energy increases continuously. However, when a power loss mechanism is introduced mimicking atomic line radiation, a near steady state can develop and, in this case, an energetic electron tail similar to that observed in the experiment can develop. The reasons underlying this behavior are analyzed, and it is shown that an important consideration is that Rutherford scattering is dominated by the cumulative effect of grazing collisions, whereas atomic line radiation requires an approximately direct rather than a grazing collision.

 

The two-stream instability (Buneman instability) is traditionally derived as a collisionless instability with the presumption that collisions inhibit this instability. We show here via a combination of a collisional two-fluid model and associated experimental observations made in the Caltech plasma jet experiment, that in fact, a low-frequency mode of the two-stream instability is indifferent to collisions. Despite the collision frequency greatly exceeding the growth rate of the instability, the instability can still cause an exponential growth of electron velocity and a rapid depletion of particle density. Nevertheless, high collisionality has an important effect as it enables the development of a double layer when the cross section of the plasma jet is constricted by a kink-instigated Rayleigh–Taylor instability. 

Solar flares are intense bursts of electromagnetic radiation accompanied by energetic particles and hard X-rays. They occur when magnetic flux loops erupt in the solar atmosphere. Solar observations detect energetic particles and hard X-rays but cannot reveal the generating mechanism because the particle acceleration happens at a scale smaller than the observation resolution. Thus, details of the cross-scale physics that explain the generation of energetic particles and hard X-rays remain a mystery. Here, we present observations from a laboratory experiment that simulates solar coronal loop physics. Transient, localized 7.6-keV X-ray bursts and a several-kilovolt voltage spike are observed in braided magnetic flux ropes of a 2-eV plasma when the braid strand radius is choked down to be at the kinetic scale by either magnetohydrodynamic (MHD) kink or magnetic Rayleigh–Taylor instabilities. This sequence of observations reveals a cross-scale coupling from MHD to non-MHD physics that is likely responsible for generating solar energetic particles and X-ray bursts. All the essential components of this mechanism have been separately observed in the solar corona. 

Plasma jets are widely investigated both in the laboratory and in nature. Astrophysical objects such as black holes, active galactic nuclei and young stellar objects commonly emit plasma jets in various forms. With the availability of data from plasma jet experiments resembling astrophysical plasma jets, classification of such data would potentially aid in not only investigating the underlying physics of the experiments but also the study of astrophysical jets. In this work we use deep learning to process all of the laboratory plasma images from the Caltech Spheromak Experiment spanning two decades. We found that cosine similarity can aid in feature selection, classify images through comparison of feature vector direction and be used as a loss function for the training of AlexNet for plasma image classification. We also develop a simple vector direction comparison algorithm for binary and multi-class classification. Using our algorithm we demonstrate 93 % accurate binary classification to distinguish unstable columns from stable columns and 92 % accurate five-way classification of a small, labelled data set which includes three classes corresponding to varying levels of kink instability.