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    Home»Health & Medicine»Research & Innovation»Massive supercomputer simulations unlock cosmic magnetic mystery
    Research & Innovation

    Massive supercomputer simulations unlock cosmic magnetic mystery

    AdminBy AdminMay 26, 2026No Comments5 Mins Read0 Views
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    Magnetic fields are found everywhere in the universe, from planets and stars to entire galaxies. These invisible forces influence major cosmic events and processes, including solar storms, the movement of high energy particles, and even galaxy formation. While small magnetic fields are often chaotic and turbulent, much larger magnetic structures appear surprisingly organized. For decades, scientists have struggled to explain how disorder in space could create such large-scale order.

    Now, researchers led by scientists at the University of Wisconsin-Madison believe they may have uncovered the missing piece of the puzzle.

    In a new study published in Nature, the team used extremely detailed computer simulations to study plasma flows. Their results suggest that large magnetic fields can emerge when turbulent plasma develops organized jet-like flows. The discovery introduces a new explanation for how cosmic magnetic fields form and could help scientists better understand everything from black hole formation to space weather near Earth.

    “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?”

    Searching for Order in Cosmic Turbulence

    Before focusing on three-dimensional (3D) magnetic fields, Tripathi had studied systems involving fluid flows and two-dimensional (2D) magnetic fields. While examining images and videos of 3D magnetic turbulence, he noticed that large-scale magnetic structures resembled the shapes of large-scale flows.

    However, applying fluid dynamics directly to magnetic fields was not straightforward. Fluid flow problems can often be simplified into two dimensions, but magnetic field generation must be solved in full 3D space, making the calculations far more difficult.

    To tackle the challenge, the researchers changed two important aspects of previous studies.

    The first involved adding a constantly renewed velocity gradient into the simulations. A velocity gradient occurs when different parts of a system move at different speeds. For example, a cyclist who suddenly hits a curb experiences a sharp velocity gradient when the bike stops but the rider’s momentum continues forward. Similar effects occur throughout the universe, including inside the Sun and during neutron star mergers. The team suspected these gradients could play a major role in shaping magnetic fields.

    Massive Supercomputer Simulations Reveal a Pattern

    The second major step was computational power. The researchers carried out what may be the most detailed simulation yet of magnetic fields interacting with unstable velocity gradients. Their model used 137 billion grid points in 3D space.

    In total, the team performed roughly 90 simulations, producing 0.25 petabytes of data and consuming nearly 100 million CPU hours on Purdue University’s Anvil supercomputer.

    “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 the researchers repeated the simulations without maintaining the large-scale velocity gradient, the organized magnetic structures never formed. Instead, the system remained chaotic and disordered.

    “So that’s really the main key: to have a steady, large-scale gradient in velocity,” he emphasizes.

    Solving a Long-Standing Magnetic Field Problem

    Scientists have studied magnetic dynamos, the processes that generate magnetic fields, for roughly 70 years. Yet most theoretical models have struggled to produce the large, ordered magnetic structures that astronomers actually observe in space.

    Adds Paul Terry, physics professor at UW-Madison and senior author of the study: “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.”

    Although the new theory cannot be directly tested in distant cosmic environments, earlier laboratory experiments appear to support the findings. In 2012, researchers at the Wisconsin Plasma Physics Laboratory observed magnetic field behavior that existing theories could not explain. The new model developed by Tripathi and his colleagues aligns more closely with those puzzling experimental results.

    Implications for Black Holes, Neutron Stars, and Space Weather

    The findings could have important implications across astrophysics.

    “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 the Earth.”

    The research was supported by the National Science Foundation (2409206) and U.S. Department of Energy (DE-SC0022257) through the DOE/NSF Partnership in Basic Plasma Science and Engineering. The Anvil supercomputer at Purdue University was used through allocation TG-PHY130027 from the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, supported by the National Science Foundation (2138259, 2138286, 2138307, 2137603 and 2138296).



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