Determining Threshold Instrumental Resolutions for Resolving the Velocity‐Space Signature of Ion Landau Damping

Unraveling the physics of the entire turbulent cascade of energy in space and astrophysical plasmas from the injection of energy at large scales to the dissipation of that energy into plasma heat at small scales, represents an overarching, open question in heliophysics and astrophysics. The fast cadence and high phase-space resolution of particle velocity distribution measurements on modern spacecraft missions, such as the recently launched Parker Solar Probe, presents exciting new opportunities for identifying turbulent dissipation mechanisms using in situ measurements of the particle velocity distributions and electromagnetic fields. Here we demonstrate how to use data from kinetic numerical simulations of plasma turbulence to create synthetic spacecraft data; this data set can then be used to determine instrumental requirements to identify specific particle energization mechanisms. Using such synthetic data, downsampled to the velocity phase-space resolution available from the plasma instruments on several past and present missions, we compute the resulting velocity-space signature of ion Landau damping using the recently developed Field-Particle Correlation (FPC) technique. We find that only recent missions have sufficiently fine phase-space resolution to resolve the characteristic resonant features of the ion Landau damping signature. Coupled with numerical determinations of the velocity-space signatures of different proposed particle energization mechanisms, this strategy enables the specification of instrumental capabilities required to achieve science goals on the topic of plasma heating and particle acceleration in turbulent heliospheric plasmas. © 2021. American Geophysical Union. All Rights Reserved.6 month embargo; published online: 10 May 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Determining Threshold Instrumental Resolutions for Resolving the Velocity-Space Signature of Ion Landau Damping

Unraveling the physics of the entire turbulent cascade of energy in space and astrophysical plasmas from the injection of energy at large scales to the dissipation of that energy into plasma heat at small scales, represents an overarching, open question in heliophysics and astrophysics. The fast cadence and high phase-space resolution of particle velocity distribution measurements on modern spacecraft missions, such as the recently launched Parker Solar Probe, presents exciting new opportunities for identifying turbulent dissipation mechanisms using in situ measurements of the particle velocity distributions and electromagnetic fields. Here we demonstrate how to use data from kinetic numerical simulations of plasma turbulence to create synthetic spacecraft data; this data set can then be used to determine instrumental requirements to identify specific particle energization mechanisms. Using such synthetic data, downsampled to the velocity phase-space resolution available from the plasma instruments on several past and present missions, we compute the resulting velocity-space signature of ion Landau damping using the recently developed Field-Particle Correlation (FPC) technique. We find that only recent missions have sufficiently fine phase-space resolution to resolve the characteristic resonant features of the ion Landau damping signature. Coupled with numerical determinations of the velocity-space signatures of different proposed particle energization mechanisms, this strategy enables the specification of instrumental capabilities required to achieve science goals on the topic of plasma heating and particle acceleration in turbulent heliospheric plasmas. © 2021. American Geophysical Union. All Rights Reserved.6 month embargo; published online: 10 May 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

PATCH: Particle Arrival Time Correlation for Heliophysics

The ability to understand the fundamental nature of the physics that governs the heliosphere requires spacecraft instrumentation to measure energy transfer at kinetic scales. This translates to a time cadence resolving the proton kinetic timescales, typically of the order of the proton gyrofrequency. The downlinked survey-mode data from modern spacecraft are often much lower resolution than this criterion, meaning that the higher resolution, burst-mode data must be captured to study an event at kinetic time scales. Telemetry restrictions, however, prohibit a sizable fraction of this burst-mode data from being downlinked to the ground. The field-particle correlation (FPC) technique can quantify kinetic-scale energy transfer between electromagnetic fields and charged particles and identify the mechanisms responsible for mediating the transfer. In this study, we adapt the FPC technique for calculating wave-particle energy transfer onboard modern spacecraft using time-tagged particle counts simultaneous with electromagnetic field measurements. The newly developed procedure, called Particle Arrival Time Correlation for Heliophysics (PATCH), is tested using synthetic spacecraft data, where output from a gyrokinetic plasma turbulence simulation was downsampled to Parker Solar Probe (PSP) energy-angle resolution. We assess the ability of the PATCH algorithm to recover the qualitative and quantitative features of the resulting velocity-space signatures, such as ion-Landau damping, that can be used to distinguish different kinetic mechanisms of particle energization. Ultimately, we demonstrate a proof-of-concept that the PATCH method could enable calculations of onboard wave-particle correlations, with the intent of enhancing spacecraft data return by several orders of magnitude. © 2021. American Geophysical Union. All Rights Reserved.6 month embargo; published online: 10 May 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Revolutionizing Our Understanding of Particle Energization in Space Plasmas Using On-Board Wave-Particle Correlator Instrumentation

A leap forward in our understanding of particle energization in plasmas throughout the heliosphere is essential to answer longstanding questions in heliophysics, including the heating of the solar corona, acceleration of the solar wind, and energization of particles that lead to observable phenomena, such as the Earth’s aurora. The low densities and high temperatures of typical heliospheric environments lead to weakly collisional plasma conditions. Under these conditions, the energization of particles occurs primarily through collisionless interactions between the electromagnetic fields and the individual plasma particles with energies characteristic of a particular interaction. To understand how the plasma heating and particle acceleration impacts the macroscopic evolution of the heliosphere, impacting phenomena such as extreme space weather, it is critical to understand these collisionless wave-particle interactions on the characteristic ion and electron kinetic timescales. Such understanding requires high-cadence measurements of both the electromagnetic fields and the three-dimensional particle velocity distributions. Although existing instrument technology enables these measurements, a major challenge to maximize the scientific return from these measurements is the limited amount of data that can be transmitted to the ground due to telemetry constraints. A valuable, but underutilized, approach to overcome this limitation is to compute on-board correlations of the maximum-cadence field and particle measurements to improve the sampling time by several orders of magnitude. Here we review the fundamentals of the innovative field-particle correlation technique, present a formulation of the technique that can be implemented as an on-board wave-particle correlator, and estimate results that can be achieved with existing instrumental capabilities for particle velocity distribution measurements. Copyright © 2022 Howes, Verniero, Larson, Bale, Kasper, Goetz, Klein, Whittlesey, Livi, Rahmati, Chen, Wilson, Alterman and Wicks.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Project Narratives: Investigating Participatory Conservation in the Peruvian Andes

This article shares findings from a participatory assessment study of a community-based environmental monitoring project in the Peruvian Andes. The objective of the project was to generate evidence to support sustainable livelihoods through participatory knowledge generation. With the use of narrative framing, the study retrospectively reconstructs the project's trajectory as perceived by the three stakeholder groups: the community, the researchers, and the implementing NGO. This analysis reveals discrepancies between the stakeholder groups both in their view of the course of events and their understanding of the purpose of the intervention. However, while the storylines depict differing project trajectories, they often agree in terms of long-term goals. The study also uncovers some neglected positive externalities that are of considerable significance to local stakeholders. These include community-to-community knowledge transfer, inter-generational knowledge sharing and ecosystem knowledge revival. The article illustrates how assumptions and expectations about participatory projects are encapsulated in narratives of positive change despite the limited level of agreement among stakeholders about what such a change should comprise. It sheds light on development narratives and their power to shape stakeholders’ perceptions in accordance with their beliefs and priorities. This is of special importance for ecosystem governance projects, which are sensitive to normative differences and subject to competing claims

Data mining using parallel multi-objective evolutionary algorithms on graphics processing units

An important and challenging data mining application in marketing is to learn models for predicting potential customers who contribute large profits to a company under resource constraints. In this chapter, we first formulate this learning problem as a constrained optimization problem and then convert it to an unconstrained multi-objective optimization problem (MOP), which can be handled by some multi-objective evolutionary algorithms (MOEAs). However, MOEAs may execute for a long time for theMOP, because several evaluations must be performed. A promising approach to overcome this limitation is to parallelize these algorithms. Thus we propose a parallel MOEA on consumer-level graphics processing units (GPU) to tackle the MOP. We perform experiments on a real-life direct marketing problem to compare the proposed method with the parallel hybrid genetic algorithm, the DMAX approach, and a sequential MOEA. It is observed that the proposed method is much more effective and efficient than the other approaches