174 research outputs found
Quantifying the Effect of Non-Larmor Motion of Electrons on the Pressure Tensor
In space plasma, various effects of magnetic reconnection and turbulence
cause the electron motion to significantly deviate from their Larmor orbits.
Collectively these orbits affect the electron velocity distribution function
and lead to the appearance of the "non-gyrotropic" elements in the pressure
tensor. Quantification of this effect has important applications in space and
laboratory plasma, one of which is tracing the electron diffusion region (EDR)
of magnetic reconnection in space observations. Three different measures of
agyrotropy of pressure tensor have previously been proposed, namely,
, and . The multitude of contradictory measures has
caused confusion within the community. We revisit the problem by considering
the basic properties an agyrotropy measure should have. We show that
, and are all defined based on the sum of the
principle minors (i.e. the rotation invariant ) of the pressure tensor. We
discuss in detail the problems of -based measures and explain why they may
produce ambiguous and biased results. We introduce a new measure
constructed based on the determinant of the pressure tensor (i.e. the rotation
invariant ) which does not suffer from the problems of -based
measures. We compare with other measures in 2 and 3-dimension
particle-in-cell magnetic reconnection simulations, and show that can
effectively trace the EDR of reconnection in both Harris and force-free current
sheets. On the other hand, does not show prominent peaks in
the EDR and part of the separatrix in the force-free reconnection simulations,
demonstrating that does not measure all the non-gyrotropic
effects in this case, and is not suitable for studying magnetic reconnection in
more general situations other than Harris sheet reconnection.Comment: accepted by Phys. of Plasm
Tracing magnetic separators and their dependence on IMF clock angle in global magnetospheric simulations
A new, efficient, and highly accurate method for tracing magnetic separators
in global magnetospheric simulations with arbitrary clock angle is presented.
The technique is to begin at a magnetic null and iteratively march along the
separator by finding where four magnetic topologies meet on a spherical
surface. The technique is verified using exact solutions for separators
resulting from an analytic magnetic field model that superposes dipolar and
uniform magnetic fields. Global resistive magnetohydrodynamic simulations are
performed using the three-dimensional BATS-R-US code with a uniform
resistivity, in eight distinct simulations with interplanetary magnetic field
(IMF) clock angles ranging from 0 (parallel) to 180 degrees (anti-parallel).
Magnetic nulls and separators are found in the simulations, and it is shown
that separators traced here are accurate for any clock angle, unlike the last
closed field line on the Sun-Earth line that fails for southward IMF. Trends in
magnetic null locations and the structure of magnetic separators as a function
of clock angle are presented and compared with those from the analytic field
model. There are many qualitative similarities between the two models, but
quantitative differences are also noted. Dependence on solar wind density is
briefly investigated.Comment: 10 pages, 10 figures, Presented at 2012 AGU Fall Meeting and 2013
Geospace Environment Modeling (GEM) Worksho
Spacecraft observations and analytic theory of crescent-shaped electron distributions in asymmetric magnetic reconnection
Supported by a kinetic simulation, we derive an exclusion energy parameter
providing a lower kinetic energy bound for an electron to cross
from one inflow region to the other during magnetic reconnection. As by a
Maxwell Demon, only high energy electrons are permitted to cross the inner
reconnection region, setting the electron distribution function observed along
the low density side separatrix during asymmetric reconnection. The analytic
model accounts for the two distinct flavors of crescent-shaped electron
distributions observed by spacecraft in a thin boundary layer along the low
density separatrix.Comment: 6 pages, 3 figure
Fast Plasma Investigation for MMS: Simulation of the Burst Triggering System
The Magnetospheric Multiscale (MMS) mission will study small-scale reconnection structures and their rapid motions from closely spaced platforms using instruments capable of high angular, energy, and time resolution measurements. To meet these requirements, the Fast Plasma Instrument (FPI) consists of eight (8) identical half top-hat electron sensors and eight (8) identical ion sensors and an Instrument Data Processing Unit (IDPU). The sensors (electron or ion) are grouped into pairs whose 6 degree x 180 degree fields-of-view (FOV) are set 90 degrees apart. Each sensor is equipped with electrostatic aperture steering to allow the sensor to scan a 45 degree x 180 degree fan about the its nominal viewing (0 deflection) direction. Each pair of sensors, known as the Dual Electron Spectrometer (DES) and the Dual Ion Spectrometer (DIS), occupies a quadrant on the MMS spacecraft and the combination of the eight electron/ion sensors, employing aperture steering, image the full-sky every 30-ms (electrons) and 150-ms (ions), respectively. To probe the diffusion regions of reconnection, the highest temporal/spatial resolution mode of FPI results in the DES complement of a given spacecraft generating 6.5-Mb (raised dot) per second of electron data while the DIS generates 1.1-Mb (raised dot) per second of ion data yielding an FPI total data rate of 6.6-Mb (raised dot) per second. The FPI electron/ion data is collected by the IDPU then transmitted to the Central Data Instrument Processor (CIDP) on the spacecraft for science interest ranking. Only data sequences that contain the greatest amount of temporal/spatial structure will be intelligently down-linked by the spacecraft. This requires a data ranking process known as the burst trigger system. The burst trigger system uses pseudo physical quantities to approximate the local plasma environments. As each pseudo quantity will have a different value, a set of two scaling factors is employed for each pseudo term. These pseudo quantities are then combined at the instrument, spacecraft, and observatory level leading to a final ranking of data based on expected scientific interest. Here, we present simulations of the fixed point burst trigger system for the FPI. A variety of data sets based on previous mission data as well as analytical formulations are tested. Comparisons of floating point calculations versus the fixed point hardware simulation are shown. Analysis of the potential sources of error from overflows, quantization, etc. are examined and mitigation methods are presented. Finally a series of calibration curves are presented, showing the expected error in pseudo quantities based solely on the scale parameters chosen and the expected data range. We conclude with a presentation of the current base-lined FPI burst trigger approach
Ion-scale kinetic Alfvén turbulence: MMS measurements of the Alfvén ratio in the magnetosheath
Turbulence in the Earth's magnetosheath at ion kinetic scales is investigated with the magnetospheric multiscale spacecraft. Several possibilities in the wave paradigm have been invoked to explain plasma turbulence at ion kinetic scales such as kinetic AlfvĂ©n, slow, or magnetosonic waves. To differentiate between these different plasma waves is a challenging task, especially since some waves, in particular, kinetic slow waves and kinetic AlfvĂ©n waves, share some properties making the possibility to distinguishing between them very difficult. Using the excellent time resolution data set provided from both the fluxgate magnetometer and the Fast Plasma Instrument, the ratio of trace velocity fluctuations to the magnetic fluctuations (in AlfvĂ©n units), which is termed the AlfvĂ©n ratio, can be calculated down to ion kinetic scales. Comparison of the measured AlfvĂ©n ratio is performed with respect to the expectation from twoâfluid magnetohydrodynamic theory for the kinetic slow wave and kinetic AlfvĂ©n wave. Moreover, the plasma data also allow normalized fluctuation amplitudes of density and magnetic field to be compared differentiating between magnetosonicâlike and kinetic AlfvĂ©nâlike turbulence. Using these two different ratios, we can rule out that the fluctuations at ion scales are dominated by magnetosonicâlike fluctuations or kinetic slowâlike fluctuations and show that they are consistent with kinetic AlfvĂ©nâlike fluctuations. This suggests that in the wave paradigm, heating in the direction of the parallel magnetic field is predominantly by the Landau damping of the kinetic AlfvĂ©n wave
In Flight Calibration of the Magnetospheric Multiscale Mission Fast Plasma Investigation
The Fast Plasma Investigation (FPI) on the Magnetospheric Multiscale mission (MMS) combines data from eight spectrometers, each with four deflection states, into a single map of the sky. Any systematic discontinuity, artifact, noise source, etc. present in this map may be incorrectly interpreted as legitimate data and incorrect conclusions reached. For this reason it is desirable to have all spectrometers return the same output for a given input, and for this output to be low in noise sources or other errors. While many missions use statistical analyses of data to calibrate instruments in flight, this process is difficult with FPI for two reasons: 1. Only a small fraction of high resolution data is downloaded to the ground due to bandwidth limitations and 2: The data that is downloaded is, by definition, scientifically interesting and therefore not ideal for calibration. FPI uses a suite of new tools to calibrate in flight. A new method for detection system ground calibration has been developed involving sweeping the detection threshold to fully define the pulse height distribution. This method has now been extended for use in flight as a means to calibrate MCP voltage and threshold (together forming the operating point) of the Dual Electron Spectrometers (DES) and Dual Ion Spectrometers (DIS). A method of comparing higher energy data (which has low fractional voltage error) to lower energy data (which has a higher fractional voltage error) will be used to calibrate the high voltage outputs. Finally, a comparison of pitch angle distributions will be used to find remaining discrepancies among sensors
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