We present a random forests machine learning model for prediction of plasmaspheric hiss spectral classes from the Van Allen Probes dataset. The random forests model provides accurate prediction of plasmaspheric hiss spectral classes obtained by the self organizing map (SOM) unsupervised machine learning classification technique. The high predictive skill of the random forests model is largely determined by the distinct and different locations of a given spectral class (“no hiss”, “regular hiss”, and “low-frequency hiss”) in (MLAT, MLT, L) coordinate space, which are the main predictors of the simplest and most accurate base model. Adding to such a base model any other single predictor among different magnetospheric, geomagnetic, and solar wind conditions provides only minor and similarly incremental improvements in predictive skill, which is comparable to the one obtained when including all possible predictors, and thus confirming major role of spatial location for accurate prediction.

Previous statistical studies of plasmaspheric hiss investigated the averaged shape of the magnetic field power spectra at various points in the magnetosphere. However, this approach does not consider the fact that very diverse spectral shapes exist at a given L-shell and magnetic local time. Averaging the data together means that important features of the spectral shapes are lost. In this paper, we use an unsupervised machine learning technique to categorize plasmaspheric hiss. In contrast to the previous studies, this technique allows us to identify power spectra that have "similar" shapes and study their spatial distribution without averaging together vastly different spectral shapes. We show that strong negative correlations exist between the hiss frequency and bandwidth, which suggests that the observed patterns are consistent with in situ wave growth.

During its first five orbits, the FIELDS plasma wave investigation on board Parker Solar Probe (PSP) has observed a multitude of plasma waves, including electrostatic whistler and electron Bernstein waves (Malaspina et al. 2020), sunward propagating whistlers (Agapitov et al. 2020), ion-scale electromagnetic waves (Verniero et al. 2020, Bowen et al. 2020) and Alfven, slow and fast mode waves (Chaston et al. 2020).

Context. The first studies with Parker Solar Probe (PSP) data have made significant progress toward understanding of the fundamental properties of ion cyclotron waves in the inner heliosphere. The survey mode particle measurements of PSP, however, did not make it possible to measure the coupling between electromagnetic fields and particles on the time scale of the wave periods. Aims. We present a novel approach to study wave-particle energy exchange with PSP. Methods. We used the Flux Angle operation mode of the Solar Probe Cup in conjunction with the electric field measurements and present a case study when the Flux Angle mode measured the direct interaction of the proton velocity distribution with an ion cyclotron wave. Results. Our results suggest that the energy transfer from fields to particles on the timescale of a cyclotron period is equal to approximately 3–6% of the electromagnetic energy flux. This rate is consistent with the hypothesis that the ion cyclotron wave was locally generated in the solar wind.

In this paper we study electrostatic waves with time‐dependent frequency features in the terrestrial foreshock. These short (0.1–0.3 s) duration waves are characterized by a significant frequency drift where the peak wave power shifts from a few hundred Hz to 2–4,000 Hz in a few hundred milliseconds. Based on the electric field data from the Magnetospheric Multiscale Mission (MMS) we have identified 46 of these wave packets. Using four spacecraft timing approach we find that these waves have a propagation direction pointing upstream. However, their plasma frame velocity is less than the solar wind speed, therefore they are eventually convected downstream toward the bow shock. We use the double‐probes of MMS and present an interferometric analysis, which allows us to obtain the dispersion relation of these waves and directly compare them to theoretical ones. We show that the measured dispersion relations are in good agreement with Doppler shifted ion acoustic waves and discuss potential mechanisms related to impulsive reflected ions that may allow the growth of these waves and cause time‐dependent frequency features.

Context: The analysis of the thermal part of velocity distribution functions (VDF) is fundamentally important for understanding the kinetic physics that governs the evolution and dynamics of space plasmas. However, calculating the proton core, beam and alpha-particle parameters for large data sets of VDFs is a time consuming and computationally demanding process that always requires supervision by a human expert. Aims: We developed a machine learning tool that can extract proton core, beam and alpha-particle parameters using images (2-D grid consisting pixel values) of VDFs. Methods: A database of synthetic VDFs is generated, which is used to train a convolutional neural network that infers bulk speed, thermal speed and density for all three particle populations. We generate a separate test data set of synthetic VDFs that we use to compare and quantify the predictive power of the neural network and a fitting algorithm. Results: The neural network achieves significantly smaller root-mean-square errors to infer proton core, beam and alpha-particle parameters than a traditional fitting algorithm. Conclusion: The developed machine learning tool has the potential to revolutionize the processing of particle measurements since it allows the computation of more accurate particle parameters than previously used fitting procedures.

During its first five orbits, the FIELDS plasma wave investigation on board Parker Solar Probe (PSP) has observed a multitude of plasma waves, including electrostatic whistler and electron Bernstein waves (Malaspina et al. 2020), sunward propagating whistlers (Agapitov et al. 2020), ion-scale electromagnetic waves (Verniero et al. 2020, Bowen et al. 2020) and Alfven, slow and fast mode waves (Chaston et al. 2020). The importance of these waves lies in their potential to redistribute the energy of the solar wind among different particles species (wave-particle interactions) or different types of waves (wave-wave interactions). The abundance of waves and instabilities observed with PSP points to their central role in the regulation of this energy exchange. Here we present first observations of an intermittent, electrostatic and broadband plasma wave that is ubiquitous in the range of distances that PSP has probed so far. A unique feature of these waves (FDWs) is a frequency shift that occurs on millisecond timescales. In the frame of the spacecraft, FDWs usually appear between the electron cyclotron and electron plasma frequencies. We develop a detection algorithm that identifies the FDWs in low cadence spectra. We analyze them using various statistical techniques. We establish their phenomenology and compare the magnetic fluctuations of the background magnetic field at times of FDWs and at times without FDWs. We establish their polarization with respect to the background magnetic field and search for correlations with various plasma parameters and features in the electron, proton and alpha particle distribution moments. We also investigate possible plasma wave modes that could be responsible for the growth of FDWs and the instability mechanisms that could be generating them. Lily Kromyda*(1), David M. Malaspina (1,2), Robert E. Ergun(1,2) , Jasper Halekas(3), Michael L. Stevens(4) , Jennifer Verniero(5), Alexandros Chasapis(2) , Daniel Vech(2) , Stuart D. Bale(5,6) , John W. Bonnell(5) , Thierry Dudok de Wit(7) , Keith Goetz(8) , Katherine Goodrich(5) , Peter R. Harvey(5) , Robert J. MacDowall(9) , Marc Pulupa(5) , Anthony W. Case(4) , Justin C. Kasper(10) , Kelly E. Korreck(4) , Davin Larson(5) , Roberto Livi(5) , Phyllis Whittlesey(5) (1) Astrophysical and Planetary Sciences Department, University of Colorado, Boulder, CO, USA (2) Laboratory for Atmospheric and Space Physics, University of Colorado, Boulder, CO, USA (3) University of Iowa, Iowa City, IA, USA (4) Harvard-Smithsonian Center for Astrophysics, Cambridge, MA, USA (5) Space Sciences Laboratory, University of California, Berkeley, CA, USA (6) Physics Department, University of California, Berkeley, CA, USA (7) LPC2E, CNRS, and University of Orleans, Orleans, France (8) School of Physics and Astronomy, University of Minnesota, Minneapolis, MN, USA (9) NASA Goddard Space Flight Center, Greenbelt, MD, USA (10) University of Michigan, Ann Arbor, MI, USA

The available magnetic field data from the terrestrial magnetosphere, solar wind and planetary magnetospheres exceeds over $10^6$ hours. Identifying plasma waves in these large data sets is a time consuming and tedious process. In this Paper, we propose a solution to this problem. We demonstrate how Self-Organizing Maps can be used for rapid data reduction and identification of plasma waves in large data sets. We use 72,000 fluxgate and 110,000 search coil magnetic field power spectra from the Magnetospheric Multiscale Mission (MMS$_1$) and show how the Self-Organizing Map sorts the power spectra into groups based on their shape. Organizing the data in this way makes it very straightforward to identify power spectra with similar properties and therefore this technique greatly reduces the need for manual inspection of the data. We suggest that Self-Organizing Maps offer a time effective and robust technique, which can significantly accelerate the processing of magnetic field data and discovery of new wave forms.

In this work, we present the first results from the flux angle (FA) operation mode of the Faraday Cup instrument on board the Parker Solar Probe ( PSP ). The FA mode allows rapid measurements of phase space density fluctuations close to the peak of the proton velocity distribution function with a cadence of 293 Hz. This approach provides an invaluable tool for understanding kinetic-scale turbulence in the solar wind and solar corona. We describe a technique to convert the phase space density fluctuations into vector velocity components and compute several turbulence parameters, such as spectral index, residual energy, and cross helicity during two intervals when the FA mode was used in PSP ’s first encounter at 0.174 au distance from the Sun.

We present a technique for deriving the temperature anisotropy of solar wind protons observed by the Parker Solar Probe (PSP) mission in the near-Sun solar wind. The radial proton temperature measured by the Solar Wind Electrons, Alphas, and Protons (SWEAP) Solar Probe Cup is compared with the orientation of local magnetic field measured by the FIELDS fluxgate magnetometer, and the proton temperatures parallel and perpendicular to the magnetic field are extracted. This procedure is applied to different data products, and the results are compared and optimum timescales for data selection and trends in the uncertainty in the method are identified. We find that the moment-based proton temperature anisotropy is more physically consistent with the expected limits of the mirror and firehose instabilities, possibly because the nonlinear fits do not capture a significant non-Maxwellian shape to the proton velocity distribution function near the Sun. The proton beam has a small effect on total proton temperature anisotropy owing to its much smaller density relative to the core compared to what was seen by previous spacecraft farther from the Sun. Several radial trends in the temperature components and the variation of the anisotropy with parallel plasma beta are presented. Our results suggest that we may see stronger anisotropic heating as PSP moves closer to the Sun, and that a careful treatment of the shape of the proton distribution may be needed to correctly describe the temperature.

Magnetic field fluctuations in the solar wind are commonly observed to follow a power-law spectrum. Near proton-kinetic scales, a spectral break occurs that is commonly interpreted as a transition to kinetic turbulence. However, this transition is not yet entirely understood. By studying the scaling of the break with various plasma properties, it may be possible to constrain the processes leading to the onset of kinetic turbulence. Using data from the Parker Solar Probe, we measure the proton-scale break over a range of heliocentric distances, enabling a measurement of the transition from inertial to kinetic-scale turbulence under various plasma conditions. We find that the break frequency fb increases as the heliocentric distance r decreases in the slow solar wind following a power law of fb ∼ r−1.11. We also compare this to the characteristic plasma ion scales to relate the break to the possible physical mechanisms occurring at this scale. The ratio fb/fc (fc for Doppler-shifted ion cyclotron resonance scale) is close to unity and almost independent of plasma βp. While fb/fρ (fρ for Doppler-shifted proton thermal gyroradius) increases with βp approaching to unity at larger βp, fb/fd (fd for Doppler-shifted proton inertial length) decreases with βp from unity at small βp. Due to the large comparable Alfvén and solar wind speeds, we analyze these results using both the standard and modified Taylor hypotheses, demonstrating the robust statistical results.

Field and plasma variations during the first perihelion pass of the Parker Solar Probe (PSP) from 53 into 35 solar radii (RS) from the Sun and over a frequency range in the spacecraft frame (fSC) from 0.0002 to 0.2 Hz are decomposed into constituent magnetohydrodynamic (MHD) modes. The analysis operates on measurements of the MHD variables recorded between impulsive, large amplitude rotations of the magnetic field to reveal the dominance of a broad spectrum of shear Alfvén waves propagating antiparallel (backward) to the background magnetic field (B0) with a significant fraction of spectral energy density in the backward slow mode and, to a lesser extent, fast mode waves. While all three MHD modes provide Poynting flux directed outward from the Sun the impulsive rotations of B0 from inward to outward radial orientations provide intervals of outward and inward propagation in the plasma frame, respectively. This morphology is suggestive of outward wave propagation from a near Sun source along kinked field lines that provide alternating radial B0 orientations as the magnetic field is advected with the flow over the spacecraft. Shear Alfvén and slow mode spectral energy density is generally largest within intervals of reversed radial B0, while the fast mode tends to occur outside these regions, albeit with lower intensity. The spectral energy density in the forward propagating modes increases with fSC above 0.01 Hz, which is suggestive of back scatter in the plasma frame of the dominant backward modes from the radial field reversals and associated inhomogeneities of the embedded plasmas.

The solar wind shows periods of highly Alfvenic activity, where velocity fluctuations and magnetic fluctuations are aligned or antialigned with each other. It is generally agreed that solar wind plasma velocity and magnetic field fluctuations observed by the Parker Solar Probe (PSP) during the first encounter are mostly highly Alfvenic. However, quantitative measures of Alfvenicity are needed to understand how the characterization of these fluctuations compares with standard measures from prior missions in the inner and outer heliosphere, in fast wind and slow wind, and at high and low latitudes. To investigate this issue, we employ several measures to quantify the extent of Alfvenicity-the Alfven ratio r(A), the normalized cross helicity sigma(c), the normalized residual energy sigma(r), and the cosine of angle between velocity and magnetic fluctuations cos theta(vb). We show that despite the overall impression that the Alfvenicity is large in the solar wind sampled by PSP during the first encounter, during some intervals the cross helicity starts decreasing at very large scales. These length scales (often >1000d(i)) are well inside inertial range, and therefore, the suppression of cross helicity at these scales cannot be attributed to kinetic physics. This drop at large scales could potentially be explained by large scale shears present in the inner heliosphere sampled by PSP. In some cases, despite the cross helicity being constant down to the noise floor, the residual energy decreases with scale in the inertial range. These results suggest that it is important to consider all these measures to quantify Alfvenicity.

The power spectral density of magnetic fluctuations in the solar wind exhibits several power-law-like frequency ranges with a well defined break between approximately 0.1 and 1 Hz in the spacecraft frame. The exact dependence of this break on solar wind parameters has been extensively studied but is not yet fully understood. Recent studies have suggested that reconnection may induce a break in the spectrum at a scale $\lambda_D$, which may be larger than the fundamental ion kinetic scales, producing an unusually steep spectrum just below the break. We present a statistical investigation of the dependence of the break on the proton gyroradius $\rho_i$, ion inertial length $d_i$, ion sound radius $\rho_s$, proton-cyclotron resonance $\rho_c$ and disruption $\lambda_D$ as a function of $\beta_{\perp i}$. We find that the steepest spectral indices of the dissipation range occur when $\beta_e$ is in the range of 0.1-1 and the break is only slightly larger than the ion sound (a situation occurring 41% of the time at 1 AU), in qualitative agreement with the reconnection model. In this range the break shows remarkably good correlation with $\lambda_D$. Our findings suggest that, at least at low $\beta_e$, reconnection may play an important role in the development of the dissipation range turbulent cascade and causes unusually steep (steeper than -3) spectral indices.