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April 19, 2026Monthly Notices of the Royal Astronomical Society0 citationsOpen Access

1/ f Noise in Synthetic and Solar Wind Data: Superposition Principles

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JWJiaming WangUniversity of DelawareFPFrancesco PecoraUniversity of DelawareRCRohit Chhiber

Key Points

  • The research aims to explore the origins and explanations for 1/f noise in solar and interplanetary data using the superposition principle.
  • Investigated superposition principles relating to 1/f noise in solar and coronal dynamics.
  • Used synthetic time series with scale-invariant and log-normal distributions to analyze 1/f generation.
  • Examined historical in situ magnetic field measurements from the ACE spacecraft.
  • Demonstrated that superposition principles can effectively generate a 1/f noise regime.
  • Provided evidence for the persistence of the 1/f spectral density in solar wind data.
  • Illustrated the common presence of 1/f noise in long-duration heliospheric measurements.

Abstract

Abstract The interplanetary magnetic field exhibits a distinctive 1/f spectral density from frequencies of around 10−6 Hz to around 10−4 Hz, ranging from harmonics of the solar rotation to the reciprocal of the turbulence correlation time in the spacecraft frame. Various theories have been proposed to explain its origin, typically invoking either processes in the lower corona or in the solar interior, or local interplanetary dynamics. Here, we investigate the superposition principle that underlies explanations of the solar/coronal types, which in principle can generate the full observed range of 1/f noise. Using synthetic time series with scale-invariant or log-normal distributions of correlation times, we examine the efficacy of several superposition approaches in generating a 1/f regime. The persistence of 1/f spectrum is further illustrated with decade-long in situ magnetic field measurements from the ACE spacecraft. Together, these results help explain the ubiquity of 1/f noise under the unavoidable superposition inherent in long-duration heliospheric data.

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69e474b6010ef96374d90306https://doi.org/10.1093/mnras/stag722
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