🔭 astrophysics

Evidence of global periodicity in PSP data: can they be linked to long-period oscillations in solar active regions?

This study utilizes spectral analysis of Parker Solar Probe (PSP) SWEAP data to identify statistically significant, coherent periodicities in the 2–20 hour range (peaking at 4–8 hours) within solar wind datasets, suggesting a potential link to long-period oscillations observed in solar active regions while confirming the absence of these signals in non-encounter orbital trajectories.

Original authors: G. Dumbadze, B. M. Shergelashvili, M. Khodachenko, L. Westrich, H. Fichtner, A. Reza, S. Poedts

Published 2026-06-30

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CC BY 4.0

Original authors: G. Dumbadze, B. M. Shergelashvili, M. Khodachenko, L. Westrich, H. Fichtner, A. Reza, S. Poedts

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

The Big Picture: Listening to the Sun's "Heartbeat"

Imagine the Sun isn't just a burning ball of gas, but a giant, living drum. For a long time, scientists thought this drum only beat in a chaotic, random way. However, this paper suggests that the Sun actually has a very specific, rhythmic "heartbeat" that repeats itself every few hours.

The researchers wanted to know two things:

Does this heartbeat happen in the solar wind (the stream of particles blowing away from the Sun) just like it does on the Sun's surface?
Is this rhythm the same whether the spaceship is flying straight toward the Sun or skimming past it?

The Detective Work: The Parker Solar Probe (PSP)

To find the answer, the scientists used data from the Parker Solar Probe (PSP). You can think of this spacecraft as a high-tech weather station that flies incredibly close to the Sun—closer than any human-made object has ever gone.

The team looked at data from 17 different "encounters" (trips where the probe got very close to the Sun). They analyzed three main things the probe measured:

Density: How crowded the particles are.
Speed: How fast the particles are moving.
Temperature: How hot the particles are.

They used two different mathematical "listening devices" (spectral analysis methods) to sift through the noise and find any repeating patterns, much like how a music producer uses software to find a specific drum beat hidden inside a noisy song.

The Main Discovery: A Rhythm in the Wind

The researchers found something surprising. Just like the Sun's surface (specifically the active regions where sunspots live) has a rhythmic pulse every 4 to 8 hours, the solar wind blowing past the probe has the exact same rhythm.

The Analogy: Imagine you are standing on a beach (the Sun's surface) and you see waves hitting the shore every 5 minutes. If you swim out into the ocean (the solar wind), you would expect the waves to be messy and random. But this paper says that if you swim out, you still feel those same waves hitting you every 5 minutes. The rhythm travels with the wind.

The "Horizontal" vs. "Vertical" Test

A key part of the study was checking if this rhythm only happens when the probe is flying sideways across the Sun's surface (at its closest point, called perihelion), or if it also happens when the probe is flying straight toward or away from the Sun.

The Finding: The rhythm is there in both cases. Whether the probe is flying "horizontally" across the Sun's face or "vertically" toward it, the 4-to-8-hour heartbeat is detectable.
The Contrast: When the probe flew far away from the Sun (more than 100 times the Sun's radius), this rhythm disappeared. The data there was just random noise. This proves the "heartbeat" is a feature of the Sun's immediate neighborhood, not a random glitch in the instrument.

Why Do Different Measurements Show Slight Differences?

The scientists noticed that the rhythm wasn't perfectly identical for every measurement. For example, the "density" might pulse at 4.5 hours, while the "temperature" might pulse at 6 hours.

The Analogy: Think of the solar wind as a crowd of people running.
- The density is like counting how many people are in a specific area.
- The temperature is like measuring how fast the people on the very edge of the crowd are running.
- The paper suggests that the "core" of the crowd (the main group) might be moving in one rhythm, while the "tails" (the faster, more energetic people on the edges) are moving in a slightly different rhythm. Because the probe measures both the core and the tails, it sees slightly different beats.

What Does This Mean?

The paper concludes that the Sun's surface and the solar wind are deeply connected. The "heartbeat" seen on the Sun's surface (active regions) seems to drive the rhythm of the solar wind.

The Big Takeaway: The Sun isn't just blowing random wind; it's sending out structured, rhythmic waves that travel through the solar system. This suggests that the magnetic fields and processes happening on the Sun's surface are the "conductors" keeping the solar wind in time.

Important Note: The authors are careful to say they found the rhythm, but they haven't fully figured out the mechanism (the exact physics of how the Sun's surface pushes that rhythm into the wind). They are raising the question, not answering every detail of the "how." They also note that rhythms shorter than 3 hours were too hard to trust because of gaps in the data, so they focused on the longer, clearer 4-to-8-hour beats.

Technical Summary: Evidence of Global Periodicity in PSP Data

Problem Statement
This study addresses the question of whether coherent oscillatory signatures identified in Parker Solar Probe (PSP) Solar Wind Electrons Alphas and Protons (SWEAP) datasets are linked to long-period oscillations previously observed in Solar Dynamic Observatory (SDO)/Helioseismic and Magnetic Imager (HMI) datasets of solar active regions (ARs). While previous work (e.g., Dumbadze et al., 2021, 2017) established characteristic periodicities of 2–20 hours (peaking at ~4.5 and 6 hours) in AR magnetic structures, and Bale et al. (2021) reported similar periodicities in PSP data specifically during perihelion flybys, it remains unclear if these are local attributes of AR structures or manifestations of a global, coherent dynamic process extending into the inner heliosphere. Furthermore, it is unknown if these signatures persist during the radial approach and recession phases of PSP's orbit, or if they are unique to the horizontal motion near perihelion.

Methodology
The authors performed a systematic spectral analysis of SWEAP/PSP in-situ measurements across 17 orbital encounters (Encounters 1, 2, 4–9, 11–19). The analysis focused on physical quantities derived from proton velocity distribution functions (VDFs), including proton number density ( $n_p$ ), bulk radial velocity ( $V$ ), temperature ( $T$ ), mass flux ( $M_f$ ), specific entropy ( $S$ ), and pressure ( $p$ ). Two distinct VDF reconstruction methods were utilized: the Direct Moment Method (DMM) and the Fitted Moment Method (FMM).

To handle the unevenly sampled nature of the original PSP time series, two complementary spectral analysis techniques were employed:

Lomb-Scargle Periodogram: Applied directly to the original, gap-filled (by removing gaps and merging data) unevenly spaced datasets to detect periodic signals without interpolation artifacts.
Continuous Wavelet Transform (CWT): Applied to time series interpolated to a constant sampling rate using linear interpolation. This method utilized both Morse and Bump mother wavelets.

The data were segmented into four distinct flight epochs for each encounter:

Approaching phase: Radial inbound flight.
Perihelion phase: Near-horizontal flight relative to the solar surface.
Receding phase: Radial outbound flight.
Far-flight phase: Distances $> 100 R_\odot$ (including aphelion), serving as a control group.

Statistical significance was evaluated by constructing Probability Distribution Functions (PDFs) of spectral peak occurrences across all encounters. Peaks were tested against background noise models (white noise for Lomb-Scargle; power-law fits for CWT) using confidence thresholds (68.2% and 95.4%) and a Relative Statistical Significance (RSS) metric to distinguish true signals from noise.

Key Contributions and Results
The analysis reveals several statistically proven periodicities in the range of 2–20 hours, with the highest confidence in the 4–8 hour range.

Global Coherence: Significant periodicities (specifically in the 3–10 hour range) are consistently detected across all three close-flyby phases (approaching, perihelion, and receding). This confirms that the coherent signal is not limited to the horizontal perihelion trajectory but is detectable during radial motion as well.
Correlation with Active Regions: The detected periods in the solar wind (particularly ~4.5 and ~6 hours) align closely with the characteristic oscillation periods previously identified in SDO/HMI active region magnetograms. The spectral structure in both datasets exhibits similar discrete harmonic features embedded in strong background noise.
Absence in Far-Flights: In datasets collected far from the Sun ( $> 100 R_\odot$ ), the coherent signatures systematically disappear. While some peaks appear above noise thresholds, they lack statistical consistency (RSS < 1) and are attributed to spurious noise or data artifacts, particularly in the sub-3-hour range.
Physical Quantity Variance: The periodicities are most robust in density, bulk velocity, mass flux, and pressure. Temperature and specific entropy show similar periodicities but with reduced statistical power. The authors note discrepancies in the exact periods detected between DMM and FMM reconstructions, suggesting that different particle populations (e.g., the Maxwellian core vs. suprathermal tails) may be driven by distinct oscillatory mechanisms.

Significance and Claims
The paper concludes that the solar wind exhibits fundamental, coherent, fixed periodicities in the 2–20 hour range, which are most prominent in the inner heliosphere (source region) and absent at large heliocentric distances. The structural similarity between these solar wind oscillations and those in solar active regions suggests a global physical link, potentially mediated by magnetic field structures extending from the photosphere into the corona and inner wind.

The authors modestly state that while they identify this global coherence and propose that it may be driven by photospheric/lower atmospheric processes (possibly via Alfvénic fluctuations or MHD turbulence), they do not definitively identify the specific physical mechanism responsible for this coupling. They emphasize that the observed discrepancies between different physical moments (density vs. temperature) likely arise from the complex, non-Maxwellian nature of the solar wind plasma, where different particle populations respond differently to oscillatory driving. The study establishes a foundation for future theoretical modeling and numerical simulations to elucidate the causal relationship between solar atmospheric oscillations and inner solar wind dynamics.