UR: Shot Noise in the Dark: Operating the Stream-biased Parker Solar Probe antennas

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Winry Ember

UC Berkeley Space Science Laboratory

Winry Ember is a junior specialist working in the UC Berkeley Space Science Laboratory during her cut-off year. She works with Dr. Mark Poluba studying the properties of heliosphere plasma using data from NASA’s Parker Solar Probe. When she’s not analyzing plasma data, she loves to crochet, play the ukulele, and lead a physics-themed yoga class.

A solar corona is seen during a total solar eclipse on Monday, August 21, 2017, over Madras, Oregon. Credit: NASA/Aubrey Geminani

NASA agency Parker Solar Probe (PSP), launched in 2018, is a revolutionary mission in heliophysics to study the Sun’s atmosphere. PSP became the first spacecraft Touch the sun when it entered the solar corona – the outer part of the sun’s atmosphere – in April of 2021. While this pioneering probe offers extraordinary insights into our host star, collecting accurate scientific data in such a unique environment can be a huge challenge – even when everything On the spacecraft is working properly. Let’s explore some of the steps being taken to more accurately assess plasma data collected by the spacecraft’s Field Experiment Kit (FIELDS), which measures electric and magnetic fields around the sun.

Plasma is an ionized gas or heated to an extreme temperature such that individual electrons separate from the gas’s atoms. Gas atoms become ions when they lose their negative charge, and we are left with a gaseous soup of negatively and positively charged particles – or plasma. Since these free electrons and ions are still attracted to each other, they oscillate around each other at a natural frequency. The denser the plasma, the greater the force of pulling them together, which leads to the higher the frequency of the plasma. By using FIELDS radio frequency spectrometry (RFS) data and a technique called quasi-thermal noise spectroscopy (QTN), we can determine the densities and temperatures of electrons in heliosphere plasma.

Schematic diagram of the Parker solar probe with indicated FIELDS antennas
Parker Solar Probe illustration with FIELDS antennas indicated by orange arrows
Credit: Spectator / Aries Ho

QTN analysis uses the measured electric field spectra to examine the location and shape of the plasma frequency peak (Fig. 1). Because QTN provides exceptionally reliable and accurate measurements of plasma electron parameters, this technique is routinely used to calibrate other instruments on the PSP. With many scientists relying on QTN measurements for successful instrument operation, it is important that our fitted electron parameters are as accurate as possible.

Figure 1. Example of a QTN spectrum (Ulysses/URAP data in the solar wind), Meyer-Vernet et al 2017. Electron temperature is calculated by checking the slope of the plasma line, and the fp peak reveals the total electron density.

Doing a QTN with a tool that’s part of a larger toolkit is a lot like having roommates, though — there are plenty of opportunities for growth and collaboration, but we have to be willing to compromise. In the case of electric field measurements on the PSP, one such compromise is between high-frequency RFS spectra and low-frequency electric field measurements performed using the same FIELDS antennas. Accurate measurements of low-frequency electric fields in the solar wind require “current bias,” a technique in which a current is applied to electric field antennas in order to approximate the antennas’ electric potential to the plasma potential. Adding a bias current generates electrons that change the antenna voltage as they leave. The high-frequency signature of these small voltage changes is called shot noise, and it makes QTN analysis more difficult by blocking the plasma line and peak frequency. Therefore, our goal is to quantify the effects of this snapshot noise on the RFS data, thus improving QTN measurements of electron density and temperature in the inner heliosphere.

The best place to start was to analyze data from a regular instrument calibration activity called Bias Sweep. During the bias scanning process, the antenna applied current rapidly changes over a wide range of negative to positive currents, allowing us to see how the plasma line responds to various applied currents, including the zero bias current (Fig. 2a). Then, by subtracting the mean of the zero bias line from each bias sweep spectra, we can isolate the effect of changing the current (Fig. 2b).

Figure 2. (Left) Spectra with different bias scan times. The average plasma line with no current applied (ideal QTN conditions) is shown in dark blue. The antenna voltage of -12 mA, shown in red, depicts a plasma line from our typical applied current.
(Right) Spectral plot with zero bias line subtraction

An alternative way to visualize the contrast of the RFS data with bias current is to plot a cut-off through the spectrum at a given frequency with the antenna current on the x-axis (Fig. 3). This plot reveals that the shot noise from our nominal bias occurs where we observe a plasma frequency peak, and importantly, it shows that it is possible to measure and understand the effect of the current bias.

Figure 3. Power cut-off versus frequency taken at 100 kHz. The frequency of the shot noise visibly diminishes as the applied current of the antenna approaches zero.

Going forward, we plan to compare data from hundreds of other bias scans performed on the PSP and fit the generated spectra with the power law models predicted by theory. As the PSP is the first spacecraft to perform QTN on a bias antenna currently, this is a unique problem that has not been fully described by contemporary antenna response models. By better documenting some of the unique challenges of collecting and modeling in situ data from the solar corona, we hope to extend existing models for QTN analysis to account for operation with biased current. While the PSP gives solar physicists an unprecedented opportunity to explore the solar corona, none of that matters if we can’t make accurate measurements with the data it collects. Doing so can often be a challenge, but there’s nothing that plasma physics and elbow grease can’t fix.

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