Credit: Tripathi et al.

All celestial bodies—planets, suns, even entire galaxies—produce magnetic fields, affecting such cosmic processes as the solar wind, high-energy particle transport, and galaxy formation. Small-scale magnetic fields are generally turbulent and chaotic, yet large-scale fields are organized, a phenomenon that plasma astrophysicists have tried explaining for decades, unsuccessfully.

New simulations reveal magnetic field mechanism

In a paper published January 21 in Nature, a team led by scientists at the University of Wisconsin–Madison have run complex numerical simulations of plasma flows that, while leading to turbulence, also develop structured flows due to the formation of large-scale jets. From their simulations, the team has identified a new mechanism to describe the generation of magnetic fields that can be broadly applied, and has implications ranging from space weather to multimessenger astrophysics.

"Magnetic fields across the cosmos are large-scale and ordered, but our understanding of how these fields are generated is that they come from some kind of turbulent motion," says the study’s lead author Bindesh Tripathi, a former UW–Madison physics graduate student and current postdoctoral researcher at Columbia University.

"Given that turbulence is known to be a destructive agent, the question remains, how does it create a constructive, large-scale field?"

Ordered magnetic fields spontaneously emerge out of chaotic, tangled fields. This finding is consistent with astrophysical observations. Streamlines of magnetic fields are 3D-rendered and are colored red–blue by the x-component of the field. Streamlines of the electric current density are shown in green; color represents magnitude. Poloidal fields are displayed on the (y,z)-plane, after averaging them over the azimuthal (x) direction. Credit: Tripathi et al.

Before working on three-dimensional (3D) magnetic fields, Tripathi investigated systems with hydrodynamic flows and two-dimensional (2D) magnetic fields. After staring at the movies and images of 3D magnetic turbulence, he noticed similarities in the shapes of large-scale flows and large-scale magnetic field structures. But it wasn’t as simple as applying fluid dynamic theory to magnetic field generation: the former may be solved as a 2D problem, whereas the latter must be solved in 3D, making it a much more complex, difficult-to-solve problem.

Key differences in research approach

Tripathi and his colleagues decided to tackle the problem with two key changes from previous research.

The first difference was the input: a constantly replenished velocity gradient. A cyclist hitting a curb head-on, say, experiences a velocity gradient: the wheels stop, but momentum can cause the cyclist to fly over the handlebars. Velocity gradients exist throughout the universe; for example, within different layers of the sun or when two neutron stars merge. The team reasoned that this gradient is likely important to include while studying 3D magnetic fields.

Second, they ran perhaps the most complex simulation to date of magnetic fields in the presence of an unstable velocity gradient—137 billion grid points in 3D space. Altogether, they ran around 90 simulations, generating 0.25 petabytes of data and using nearly 100 million CPU hours on the Anvil supercomputer at Purdue University.

"We start our simulations with a flow that has a velocity gradient, then we add some tiny perturbations, like moving one fluid particle infinitesimally, we let that perturbation propagate over the system and grow, and then analyze the data over time," Tripathi says. "Initially, these perturbations lead to turbulent flows and magnetic fields in small-scale structures, then, over time, they emerge into larger, ordered structures."

When Tripathi ran the same simulations where the initial velocity gradient had decayed over time, the simulation only produced the chaotic, small-scale patterns. "So that’s really the main key: to have a steady, large-scale gradient in velocity," he emphasizes.

Implications and experimental support

Paul Terry, physics professor at UW–Madison and senior author of the study, adds, "Magnetic field generation via dynamos has been extensively studied for 70 years, with the frustrating result that the generated fields almost always end up at small scales and highly disordered, unlike observations. This work, therefore, potentially resolves a long-standing issue."

Though the theory cannot be tested in the distant universe, a lab-based experiment does support the team’s findings: in 2012, colleagues at the Wisconsin Plasma Physics Laboratory were trying to better understand the nature of the magnetic field generation process in a laboratory experiment, but their data did not fit any of the previous models. Tripathi and colleagues’ new theory of magnetic field generation more closely matches the experimental data and helps to resolve the confounding findings.

"This work has the potential to explain the magnetic dynamics relevant in, for example, neutron star mergers and black hole formation, with direct applications to multimessenger astronomy," Tripathi says. "It may also help better understand stellar magnetic fields and predict gas ejections from the sun toward Earth."

Publication details

B. Tripathi, Large-scale dynamos driven by shear-flow-induced jets, Nature (2026). DOI: 10.1038/s41586-025-09912-0. www.nature.com/articles/s41586-025-09912-0

Journal information: Nature

Citation: Velocity gradients prove key to explaining large-scale magnetic field structure (2026, January 21) retrieved 21 January 2026 from https://phys.org/news/2026-01-velocity-gradients-key-large-scale.html

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