arXiv subjects

Aaron Goodman

Publications and source records attributed to Aaron Goodman.

4 recordsLinked to original sources

arXiv2023

Laboratory study of the failed torus mechanism in arched, line-tied, magnetic flux ropes

Coronal mass ejections (CMEs) are some of the most energetic and violent events in our solar system. The prediction and understanding of CMEs is of particular importance due to the impact that they can have on Earth-based satellite systems, and in extreme cases, ground-based electronics. CMEs often occur when long-lived magnetic flux ropes (MFRs) anchored to the solar surface destabilize and erupt away from the Sun. One potential cause for these eruptions is an ideal magnetohydrodynamic (MHD) instability such as the kink or torus instability. Previous experiments on the Magnetic Reconnection eXperiment (MRX) revealed a class of MFRs that were torus-unstable but kink-stable, which failed to erupt. These "failed-tori" went through a process similar to Taylor relaxation where the toroidal current was redistributed before the eruption ultimately failed. We have investigated this behavior through additional diagnostics that measure the current distribution at the foot points and the energy distribution before and after an event. These measurements indicate that ideal MHD effects are sufficient to explain the energy distribution changes during failed torus events. This excludes Taylor relaxation as a possible mechanism of current redistribution during an event. A new model that only requires non-ideal effects in a thin layer above the electrodes is presented to explain the observed phenomena. This work broadens our understanding of the stability of MFRs and the mechanism behind the failed torus through the improved prediction of the torus instability and through new diagnostics to measure the energy inventory and current profile at the foot points.

astro-ph.SR↗

arXiv2022

Two-dimensional plasma density evolution local to the inversion layer during sawtooth crash events using Beam Emission Spectroscopy

We present methods for analyzing Beam Emission Spectroscopy (BES) data to obtain the plasma density evolution associated with rapid sawtooth crash events at the DIII-D tokamak. BES allows coverage over a 2-D spatial plane, inherently local measurements, with fast time responses, and therefore provides a valuable new channel for data during sawtooth events. A method is developed to remove sawtooth-induced edge-light pulses contained in the BES data. The edge light pulses appear to be from the $\rm{D}_{\alpha}$ emission produced by edge recycling during sawtooth events, and are large enough that traditional spectroscopic filtering and data analysis techniques are insufficient to deduce physically meaningful quantities. A cross-calibration of 64 BES channels is performed using a novel method to ensure accurate measurements. For the large-amplitude density oscillations observed, we discuss and use the non-linear relationship between BES signal $\delta I/I_{0}$ and plasma density variation $\delta n_{e}/n_{e0}$. 2-D BES images cover a 8~cm~$\times$~20~cm region around the sawtooth inversion layer and show large-amplitude density oscillations, with additional significant spatial variations across the inversion layer, which grows and peaks near the time of the temperature crash. The edge light removal technique and method of converting large-amplitude $\delta I/I_{0}$ to $\delta n_{e}/n_{e0}$ presented here may help analyze other impulsive MHD phenomena in tokamaks.

physics.plasm-ph↗

arXiv2020

Laboratory study of the torus instability threshold in solar-relevant, line-tied magnetic flux ropes

Coronal mass ejections (CME) occur when long-lived magnetic flux ropes (MFR) anchored to the solar surface destabilize and erupt away from the Sun. This destabilization is often described in terms of an ideal magnetohydrodynamic (MHD) instability called the torus instability. It occurs when the external magnetic field decreases sufficiently fast such that its decay index, $n=-z\,\partial\,(\ln B)/\partial z$ is larger than a critical value, $n>n_{\rm cr}$, where $n_{\rm cr}=1.5$ for a full, large aspect ratio torus. However, when this is applied to solar MFRs, a range of conflicting values for $n_{\rm cr}$ is found in the literature. To investigate this discrepancy, we have conducted laboratory experiments on arched, line-tied flux ropes and have applied a theoretical model of the torus instability. Our model describes an MFR as a partial torus with footpoints anchored in a conducting surface and numerically calculates various magnetic forces on it. This calculation yields a better prediction of $n_{\rm cr}$ which takes into account the specific parameters of the MFR. We describe a systematic methodology to properly translate laboratory results to their solar counterparts, provided that the MFRs have sufficiently small edge safety factor, or equivalently, large enough twist. After this translation, our model predicts that $n_{\rm cr}$ in solar conditions often falls near $n_{\rm cr}^{\rm Sol}\sim0.9$ and within a larger range of $n_{\rm cr}^{\rm Sol}\sim(0.7,1.2)$ depending on the parameters. The methodology of translating laboratory MFRs to their solar counterparts enables quantitative investigations of the initiation of CMEs through laboratory experiments. These experiments allow for new physics insights that are required for better predictions of space weather events but are difficult to obtain otherwise.

astro-ph.SR↗

arXiv2018

Learning multiagent coordination in the absence of communication channels

In this work, we develop a reinforcement learning protocol for a multiagent coordination task in a discrete state and action space: an iterated prisoner's dilemma game extended into a team based, winner-take all tournament, which forces the agents to collude in order to maximize their reward. By disallowing extra communication channels, the agents are forced to embed their coordination strategy into their actions in the prisoner's dilemma game. We develop a representation of the iterated prisoners dilemma that makes it amenable to Q-learning. We find that the reinforcement learning strategy is able to consistently train agents that can win the winner take all iterated prisoners dilemma tournament. By using a game with discrete state and action space, we are able to better analyze and understand both the dynamics and the communication protocols that are established between the agents. We find that the agents adapt a number of interesting behaviors, such as the formation of benevolent dictators, that minimize inequality of scores. We also find that the agents settle on a remarkably consistent symbology in their actions, such that agents from independent trials are able to collude with each other without further training.

cs.GT↗