Scale-Dependent Statistics of Coherent Magnetic Structures in Early IMAP Observations

We analyze early Interstellar Mapping and Acceleration Probe (IMAP) magnetic field observations (November 2025 to May 2026) to quantify the statistical properties of helical magnetic structures and their relationship with turbulence intermittency. Intermittent structures, such as current sheets, are identified using the Partial Variance of Increments (PVI) method, and the scale-dependent normalized magnetic helicity is computed over scales corresponding to 0.5-3 correlation lengths. Prior studies have typically applied the PVI-helicity method to individual events; here we extend this technique to the ensemble statistics of a multi-month sample spanning many correlation times. To separate coherent helical structures from random turbulent fluctuations, significance thresholds for helicity are determined using phase-randomized surrogate realizations. We find a clear scale dependence in the occurrence, duration, and waiting time of coherent magnetic helicity, reminiscent of the scale-transfer arguments underlying inverse cascade, selective decay, and Taylor relaxation theories. Event duration and waiting-time distributions are well described by power-law and exponential models over different ranges, consistent with previous findings. In addition, PVI and magnetic helicity are anticorrelated, suggesting that high-PVI regions are preferentially associated with the boundaries of flux ropes, while their interiors tend to exhibit lower PVI and stronger magnetic helicity.

Authors

Publication Details

Journal
arXiv (Cornell University)
Published
2026-10-26
DOI
https://doi.org/10.48550/arxiv.2610.35634
Primary Topic
Solar and Space Plasma Dynamics
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

Scale-Dependent Statistics of Coherent Magnetic Structures in Early IMAP Observations

Eric Christian, William H. Matthaeus, T. S. Horbury, William Taranto et al.
arXiv (Cornell University)
Solar and Space Plasma Dynamics
preprint

Scale-Dependent Statistics of Coherent Magnetic Structures in Early IMAP Observations

Eric Christian, William H. Matthaeus, T. S. Horbury, William Taranto, Riddhi Bandyopadhyay, Drew L. Turner, Sujan Prasad Gautam, Subash Adhikari, Joshua Goodwill, Francesco Pecora, Savvas Raptis, David J. McComas, Rayta A. Pradata, Jiaming Wang, Nathan Schwadron, Matina Gkioulidou, Jamie Rankin
preprint en

Abstract

We analyze early Interstellar Mapping and Acceleration Probe (IMAP) magnetic field observations (November 2025 to May 2026) to quantify the statistical properties of helical magnetic structures and their relationship with turbulence intermittency. Intermittent structures, such as current sheets, are identified using the Partial Variance of Increments (PVI) method, and the scale-dependent normalized magnetic helicity is computed over scales corresponding to 0.5-3 correlation lengths. Prior studies have typically applied the PVI-helicity method to individual events; here we extend this technique to the ensemble statistics of a multi-month sample spanning many correlation times. To separate coherent helical structures from random turbulent fluctuations, significance thresholds for helicity are determined using phase-randomized surrogate realizations. We find a clear scale dependence in the occurrence, duration, and waiting time of coherent magnetic helicity, reminiscent of the scale-transfer arguments underlying inverse cascade, selective decay, and Taylor relaxation theories. Event duration and waiting-time distributions are well described by power-law and exponential models over different ranges, consistent with previous findings. In addition, PVI and magnetic helicity are anticorrelated, suggesting that high-PVI regions are preferentially associated with the boundaries of flux ropes, while their interiors tend to exhibit lower PVI and stronger magnetic helicity.

arXiv (Cornell University)
Solar and Space Plasma Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon