scholarly journals Determining the Bulk Parameters of Plasma Electrons from Pitch-Angle Distribution Measurements

Entropy ◽  
2020 ◽  
Vol 22 (1) ◽  
pp. 103 ◽  
Author(s):  
Georgios Nicolaou ◽  
Robert Wicks ◽  
George Livadiotis ◽  
Daniel Verscharen ◽  
Christopher Owen ◽  
...  
Keyword(s):  
Solar Wind ◽  
Distribution Function ◽  
High Resolution ◽  
Velocity Distribution ◽  
Pitch Angle ◽  
Velocity Distribution Function ◽  
Local Magnetic Field ◽  
Magnetic Field Direction ◽  
Angle Distribution ◽  
Bulk Parameters

Electrostatic analysers measure the flux of plasma particles in velocity space and determine their velocity distribution function. There are occasions when science objectives require high time-resolution measurements, and the instrument operates in short measurement cycles, sampling only a portion of the velocity distribution function. One such high-resolution measurement strategy consists of sampling the two-dimensional pitch-angle distributions of the plasma particles, which describes the velocities of the particles with respect to the local magnetic field direction. Here, we investigate the accuracy of plasma bulk parameters from such high-resolution measurements. We simulate electron observations from the Solar Wind Analyser’s (SWA) Electron Analyser System (EAS) on board Solar Orbiter. We show that fitting analysis of the synthetic datasets determines the plasma temperature and kappa index of the distribution within 10% of their actual values, even at large heliocentric distances where the expected solar wind flux is very low. Interestingly, we show that although measurement points with zero counts are not statistically significant, they provide information about the particle distribution function which becomes important when the particle flux is low. We also examine the convergence of the fitting algorithm for expected plasma conditions and discuss the sources of statistical and systematic uncertainties.

Particle-In-Cell simulations of resonant interactions between whistler waves and electrons in the near-Sun solar wind: scattering of the strahl into the halo and heat flux regulation.

2021 ◽  
Author(s):  
Alfredo Micera ◽  
Andrei Zhukov ◽  
Rodrigo A. López ◽  
Maria Elena Innocenti ◽  
Marian Lazar ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Heat Flux ◽  
Solar Wind ◽  
Velocity Distribution ◽  
Pitch Angle ◽  
Electron Velocity ◽  
Magnetic Field Direction ◽  
Whistler Waves ◽  
Electron Velocity Distribution ◽  
Particle In Cell

<p>Electron velocity distribution functions, initially composed of core and strahl populations as typically encountered in the near-Sun solar wind and as recently observed by Parker Solar Probe, have been modeled via fully kinetic Particle-In-Cell simulations. It has been demonstrated that, as a consequence of the evolution of the electron velocity distribution function, two branches of the whistler heat flux instability can be excited, which can drive whistler waves propagating in the direction parallel or oblique to the background magnetic field. First, the strahl undergoes pitch-angle scattering with oblique whistler waves, which provokes the reduction of the strahl drift velocity and the simultaneous broadening of its pitch angle distribution. Moreover, the interaction with the oblique whistler waves results in the scattering towards higher perpendicular velocities of resonant strahl electrons and in the appearance of a suprathermal halo population which, at higher energies, deviates from the Maxwellian distribution. Later on, the excited whistler waves shift towards smaller angles of propagation and secondary scattering processes with quasi-parallel whistler waves lead to a redistribution of the scattered particles into a more symmetric halo. All processes are accompanied by a significant decrease of the heat flux carried by the strahl population along the magnetic field direction, although the strongest heat flux rate decrease is simultaneous with the propagation of the oblique whistler waves.</p>

Possible instrumental effects on moments computation of the solar wind proton velocity distribution function: Helios observations

2020 ◽  
Vol 639 ◽  
pp. A82 ◽  
Author(s):  
R. De Marco ◽  
R. Bruno ◽  
R. D’Amicis ◽  
D. Telloni ◽  
D. Perrone
Keyword(s):  
Magnetic Field ◽  
Solar Wind ◽  
Distribution Function ◽  
Velocity Distribution ◽  
Field Data ◽  
Velocity Distribution Function ◽  
Instrumental Effects ◽  
Solar Wind Proton ◽  
Magnetic Field Data ◽  
Density Values

The solar wind is a highly turbulent medium in which most of the energy is carried by Alfvénic fluctuations. These fluctuations have a wide range of scales whose high-frequency tail can be relevant for the sampling techniques commonly used to detect the particle distribution in phase space in situ. We analyze the effect of Alfvénic fluctuations on moments computation of the solar wind proton velocity distribution for a plasma sensor, whose sampling time is comparable or even longer than the typical timescale of the velocity fluctuations induced by these perturbations. In particular, we numerically simulated the sampling procedure used on board Helios 2. We directly employed magnetic field data recorded by the Helios 2 magnetometer, when the s/c was immersed in fast wind during its primary mission to the Sun, to simulate Alfvénic fluctuations. More specifically, we used magnetic field data whose cadence of 4 Hz is considerably higher than that the plasma sensor needed to sample a full velocity distribution function, and we average these data to 1 Hz, which is the spin period of Helios. Density values, which are necessary to build Alfvénic fluctuations at these scales, are not available because the cadence of the Helios plasma data is 40.5 s. The adopted solution is based on the assumption that the available Helios plasma density power spectrum can be extended to the same frequencies as the magnetic field spectrum by extrapolating the power-law fit of the low-frequency range to the frequencies relevant for this study. Surrogate density values in the time domain are then obtained by inverse transforming this spectrum. We show that it cannot be excluded that relevant instrumental effects strongly contribute to generate interesting spectral and kinetic features that have been interpreted in the past literature as exclusively due to physical mechanisms.

scholarly journals The auroral O<sup>+</sup> non-Maxwellian velocity distribution function revisited

1997 ◽  
Vol 15 (2) ◽  
pp. 249-254 ◽  
Author(s):  
D. Hubert ◽  
F. Leblanc
Keyword(s):  
Magnetic Field ◽  
Distribution Function ◽  
Velocity Distribution ◽  
Polar Angle ◽  
Velocity Distribution Function ◽  
Distribution Functions ◽  
Field Direction ◽  
Magnetic Field Direction ◽  
Velocity Distribution Functions ◽  
The Magnetic Field

Abstract. New characteristics of O+ ion velocity distribution functions in a background of atomic oxygen neutrals subjected to intense external electromagnetic forces are presented. The one dimensional (1-D) distribution function along the magnetic field displays a core-halo shape which can be accurately fitted by a two Maxwellian model. The Maxwellian shape of the 1-D distribution function around a polar angle of 21 ± 1° from the magnetic field direction is confirmed, taking into account the accuracy of the Monte Carlo simulations. For the first time, the transition of the O+ 1-D distribution function from a core halo shape along the magnetic field direction to the well-known toroidal shape at large polar angles, through the Maxwellian shape at polar angle of 21 ± 1° is properly explained from a generic functional of the velocity moments at order 2 and 4.

scholarly journals Velocity distribution function of hydrogen atoms in ion source discharges

2021 ◽  
Author(s):  
Tatsuhiro Tokai ◽  
Yuji Shimabukuro ◽  
Hidenori Takahashi ◽  
Keita Bito ◽  
Motoi Wada
Keyword(s):  
Distribution Function ◽  
Velocity Distribution ◽  
Velocity Distribution Function ◽  
Ion Source ◽  
Hydrogen Atoms

scholarly journals Velocity distribution function of spontaneously evaporating atoms

2020 ◽  
Vol 5 (10) ◽  
Author(s):  
Sergiu Busuioc ◽  
Livio Gibelli ◽  
Duncan A. Lockerby ◽  
James E. Sprittles
Keyword(s):  
Distribution Function ◽  
Velocity Distribution ◽  
Velocity Distribution Function
Sign in / Sign up

Export Citation Format

Share Document