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Context. Parker Solar Probe (PSP) counts dust impacts in the near-solar region, but modeling effort is needed to understand the dust population’s properties. Aims. We aim to constrain the dust cloud’s properties based on the flux observed by PSP. Methods. We developed a forward model for the bound dust detection rates using the formalism of 6D phase space distribution of the dust. We applied the model to the location table of different PSP solar encounter groups. We explain some of the near-perihelion features observed in the data as well as the broader characteristic of the dust flux between 0.15 AU and 0.5 AU. We compare the measurements of PSP to the measurements of Solar Orbiter near 1 AU to expose the differences between the two spacecraft. Results. We found that the dust flux observed by PSP between 0.15 AU and 0.5 AU in post-perihelia can be explained by dust on bound orbits and is consistent with a broad range of orbital parameters, including dust on circular orbits. However, the dust number density as a function of the heliocentric distance and the scaling of detection efficiency with relative speed are important to explain the observed flux variation. The data suggest that the slope of differential mass distribution, δ, is between 0.14 and 0.49. The near-perihelion observations, however, show the flux maxima, which are inconsistent with the circular dust model, and additional effects may play a role. We found an indication that the sunward side of PSP is less sensitive to the dust impacts than PSP’s other surfaces. Conclusions. We show that the dust flux on PSP can be explained by noncircular bound dust and the detection capabilities of PSP. The scaling of flux with impact speed is especially important, and shallower than previously assumed.
Context. Parker Solar Probe (PSP) counts dust impacts in the near-solar region, but modeling effort is needed to understand the dust population’s properties. Aims. We aim to constrain the dust cloud’s properties based on the flux observed by PSP. Methods. We developed a forward model for the bound dust detection rates using the formalism of 6D phase space distribution of the dust. We applied the model to the location table of different PSP solar encounter groups. We explain some of the near-perihelion features observed in the data as well as the broader characteristic of the dust flux between 0.15 AU and 0.5 AU. We compare the measurements of PSP to the measurements of Solar Orbiter near 1 AU to expose the differences between the two spacecraft. Results. We found that the dust flux observed by PSP between 0.15 AU and 0.5 AU in post-perihelia can be explained by dust on bound orbits and is consistent with a broad range of orbital parameters, including dust on circular orbits. However, the dust number density as a function of the heliocentric distance and the scaling of detection efficiency with relative speed are important to explain the observed flux variation. The data suggest that the slope of differential mass distribution, δ, is between 0.14 and 0.49. The near-perihelion observations, however, show the flux maxima, which are inconsistent with the circular dust model, and additional effects may play a role. We found an indication that the sunward side of PSP is less sensitive to the dust impacts than PSP’s other surfaces. Conclusions. We show that the dust flux on PSP can be explained by noncircular bound dust and the detection capabilities of PSP. The scaling of flux with impact speed is especially important, and shallower than previously assumed.
Abstract. This article presents the results of automatic detection of dust impact signals observed by the Solar Orbiter – Radio and Plasma Waves instrument. A sharp and characteristic electric field signal is observed by the Radio and Plasma Waves instrument when a dust particle impacts the spacecraft at high velocity. In this way, ∼ 5–20 dust impacts are daily detected as the Solar Orbiter travels through the interplanetary medium. The dust distribution in the inner solar system is largely uncharted and statistical studies of the detected dust impacts will enhance our understanding of the role of dust in the solar system. It is however challenging to automatically detect and separate dust signals from the plural of other signal shapes for two main reasons. Firstly, since the spacecraft charging causes variable shapes of the impact signals, and secondly because electromagnetic waves (such as solitary waves) may induce resembling electric field signals. In this article, we propose a novel machine learning-based framework for detection of dust impacts. We consider two different supervised machine learning approaches: the support vector machine classifier and the convolutional neural network classifier. Furthermore, we compare the performance of the machine learning classifiers to the currently used on-board classification algorithm and analyze 2 years of Radio and Plasma Waves instrument data. Overall, we conclude that detection of dust impact signals is a suitable task for supervised machine learning techniques. The convolutional neural network achieves the highest performance with 96 % ± 1 % overall classification accuracy and 94 % ± 2 % dust detection precision, a significant improvement to the currently used on-board classifier with 85 % overall classification accuracy and 75 % dust detection precision. In addition, both the support vector machine and the convolutional neural network classifiers detect more dust particles (on average) than the on-board classification algorithm, with 16 % ± 1 % and 18 % ± 8 % detection enhancement, respectively. The proposed convolutional neural network classifier (or similar tools) should therefore be considered for post-processing of the electric field signals observed by the Solar Orbiter.
Abstract. Solar Orbiter is equipped with electrical antennas performing fast measurements of the surrounding electric field. The antennas register high-velocity dust impacts through the electrical signatures of impact ionization. Although the basic principle of the detection has been known for decades, the understanding of the underlying process is not complete, due to the unique mechanical and electrical design of each spacecraft and the variability of the process. We present a study of electrical signatures of dust impacts on Solar Orbiter's body, as measured with the Radio and Plasma Waves electrical suite. A large proportion of the signatures present double-peak electrical waveforms in addition to the fast pre-spike due to electron motion, which are systematically observed for the first time. We believe this is due to Solar Orbiter's unique antenna design and a high temporal resolution of the measurements. The double peaks are explained as being due to two distinct processes. Qualitative and quantitative features of both peaks are described. The process for producing the primary peak has been studied extensively before, and the process for producing the secondary peak has been proposed before (Pantellini et al., 2012a) for Solar Terrestrial Relations Observatory (STEREO), although the corresponding delay of 100–300 µs between the primary and the secondary peak has not been observed until now. Based on this study, we conclude that the primary peak's amplitude is the better measure of the impact-produced charge, for which we find a typical value of around 8 pC. Therefore, the primary peak should be used to derive the impact-generated charge rather than the maximum. The observed asymmetry between the primary peaks measured with individual antennas is quantitatively explained as electrostatic induction. A relationship between the amplitude of the primary and the secondary peak is found to be non-linear, and the relation is partially explained with a model for electrical interaction through the antennas' photoelectron sheath.
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