Surface flux transport, or SFT, models are among the most important tools solar physicists use to monitor and forecast the behavior of the Sun. These models track how magnetic flux emerges on the solar surface and how it is subsequently carried around by large-scale flows, including the differential rotation of the Sun and the meridional circulation that transports magnetic material toward the poles. By simulating the evolution of the surface magnetic field over weeks, months, and years, SFT models allow researchers to understand how solar activity builds up and decays across the roughly eleven-year solar cycle. That understanding, in turn, feeds into predictions of sunspots, flares, and coronal mass ejections, the explosive events that can send bursts of radiation and charged particles toward Earth and disrupt communications, navigation systems, and electrical infrastructure.

The central challenge the SwRI-led team set out to solve is a fundamental observational one: at any given moment, half of the Sun is facing away from Earth. Unlike the Moon, which is tidally locked and shows us the same face forever, the Sun rotates completely on its axis roughly every 27 days, so every patch of the solar surface eventually swings into view. But between those appearances, active regions can form, evolve, and decay entirely out of sight. Earlier SFT models, lacking simultaneous data from the hidden hemisphere, were often caught off guard. In some cases, as the Sun rotated, a sunspot would emerge unexpectedly from the far side, forcing researchers into quick recalculations of their magnetic maps and degrading the reliability of forecasts built on them.

To fill this observational gap, scientists have since the 1970s turned to helioseismology, a technique that studies the Sun’s interior and its far side using acoustic waves. Just as geologists probe what lies deep beneath the Earth’s crust by analyzing how seismic waves travel through the planet, solar physicists analyze sound waves reverberating through the Sun’s interior. Active regions on the far side perturb these acoustic signals in characteristic ways, allowing researchers to infer the presence of magnetically active areas before they rotate into view. Helioseismic far-side imaging has led to vast improvements in space weather forecasting, giving forecasters days of advance warning about emerging sunspot groups that would otherwise appear without notice.

Yet even helioseismic models have been hampered by bad information. The acoustic signatures that betray an active region are not always what they seem. Dr. Bibhuti Jha, a research scientist in SwRI’s Solar System Science and Exploration Division in Boulder, Colorado, and the lead author of the new paper, described the problem in vivid terms. Acoustic data can sometimes indicate an active region on the far side, he explained, but when the area finally comes into view, nothing is there. It is almost like a false positive, and the team calls these phantom features ghost active regions. When such false detections are folded into an SFT model, they inject spurious magnetic flux that then propagates through the simulation, contaminating the map of the solar surface and any forecasts derived from it.

The new framework tackles this problem directly by introducing a probabilistic treatment of far-side detections. Rather than accepting every helioseismic detection at face value, the model systematically evaluates the accuracy of each candidate active region before it is incorporated into the surface flux transport simulation. Dr. Lisa Upton, an SwRI lead scientist also based in the Boulder office and a co-author of the paper, explained the approach: before far-side helioseismology data are added to the model, the team associates a probability with each far-side active region based on its properties. Detections with characteristics that closely match confirmed active regions earn high confidence, while ambiguous or weak signals are weighted accordingly or filtered out. The result is a model that weeds out ghost active regions and delivers a more accurate map of the entire solar surface at any given time.

To build and validate this framework, the team studied near-simultaneous maps of the whole solar surface from 2010 to 2014, a period that spans the rise to the maximum of Solar Cycle 24. During this window, observations from Earth-based instruments could be combined with data from space-based assets positioned to view the opposite hemisphere, providing ground truth against which far-side helioseismic detections could be checked. By comparing what the acoustic methods predicted with what was actually observed when each region rotated into view, the researchers could quantify the reliability of far-side detections and calibrate their probabilistic assignments. The resulting SFT models are more complete and accurate than any previous effort, according to the team.

The significance of this work extends well beyond the technical details of magnetic cartography. Solar activity drives space weather, and space weather is increasingly recognized as a practical hazard with economic and security implications. Strong solar flares can degrade high-frequency radio communications used by aviation and maritime operations, while coronal mass ejections can induce currents in long power lines and damage transformers, as demonstrated by historic geomagnetic storms. Satellites in Earth orbit face elevated radiation risks during active periods, and crewed missions beyond low Earth orbit require accurate forecasts to protect astronauts from energetic particle events. A more faithful representation of the Sun’s global magnetic field, including the half that cannot be seen directly, gives forecasters a firmer foundation for anticipating when and where the next eruption might occur.

The probabilistic framework also provides a practical pathway for incorporating helioseismic data into SFT models more broadly, something that has been difficult to do rigorously in the past because of the noise and false positives inherent in far-side imaging. By treating each detection as a probability rather than a certainty, the method allows models to benefit from far-side information without being misled by its errors, a balance that previous approaches struggled to strike. Jha characterized the advance as a step toward a more realistic modeling of the magnetic field of both the visible and invisible hemispheres of the Sun, a goal that has motivated solar physicists for decades.

Looking ahead, the team hopes that better surface maps will translate into better predictions of the solar cycle itself. As Jha noted, modeling the surface of the Sun to see how the magnetic field behaves helps scientists understand how solar activity varies over the cycle, and if the next solar cycle can be plotted out in advance, researchers will have a much better idea of how the Sun is going to behave in the coming years. The study, titled A Probabilistic Framework for Incorporating Helioseismic Far-Side Active Regions into SFT Models, was published on October 8, 2026, in The Astrophysical Journal Supplement Series, and it arrives at a moment of growing public and governmental attention to space weather readiness. As society’s dependence on technology vulnerable to solar storms continues to grow, tools that make the Sun’s hidden half visible, even probabilistically, represent a meaningful stride toward a more predictable star.

Subject of Research: Probabilistic incorporation of helioseismic far-side active region data into solar surface flux transport models

Article Title: SwRI-led team develops improved model for mapping the Sun

Article References: SwRI-led team develops improved model for mapping the Sun. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Sun, solar magnetic field, surface flux transport, helioseismology, far-side imaging, space weather, solar cycle, sunspots, SwRI, solar forecasting, active regions, The Astrophysical Journal Supplement Series

The partnership is not starting from a blank page. Under the memorandum, a joint research team has already completed first-phase, hands-on evaluations of superconducting quantum RF sensors for signals intelligence applications, conducted at the Jesper Munch Quantum Laboratories at Adelaide University in South Australia. Signals intelligence, the discipline of collecting, intercepting and analyzing electronic signals, underpins defense planning, secure communications and emergency response, and the sensors at the heart of this collaboration are designed to give analysts more usable information from the same crowded electromagnetic environment.

The physics behind the approach is rooted in the behavior of electrons inside superconducting materials. In such materials, RF signals have a dramatic effect on the dynamics of electrons, the negatively charged building blocks of atoms. Ultrasensitive, longer-range quantum RF sensing devices exploit changes in electron trajectory to extract more information from the RF environment than conventional antennas can manage. Precision circuits fabricated from superconducting materials convert those microscopic responses into raw data that yields accurate signal measurements, forming the basis of a sensing architecture that its developers argue outperforms traditional hardware in both sensitivity and information content.

Superconducting quantum RF systems leverage the unique properties of superconducting materials to detect and characterize signals across a broad swath of the electromagnetic spectrum. That breadth matters because the practical alternative, especially aboard military ships and aircraft where every cubic meter is contested, is a collection of bulky antennas each tuned to a portion of the spectrum. Compact quantum systems offer the potential to replace those installations outright, collapsing multiple frequency-specific apertures into a single small package.

Staff Engineer Michael Quinn, who leads quantum RF research and development in SwRI’s Defense and Intelligence Solutions Division offices in Warner Robins, Georgia, framed the size advantage as fundamental rather than incremental. Unlike conventional antennas, which grow bulkier as frequencies get lower, quantum RF device size is independent of frequency, he explained. According to Quinn, these systems achieve broad coverage from kilohertz to terahertz with the same compact hardware, providing more critical information while occupying less space. That combination, he noted, is a major advantage for defense and intelligence missions where size, weight and power are critical considerations, the classic SWaP constraints that shape nearly every airborne and shipboard system design.

The hardware that makes this possible is grown, in a literal sense, at Adelaide University. The university’s quantum laboratories house a state-of-the-art molecular beam epitaxy system, or MBE, that builds advanced superconductor and quantum materials one atomic layer at a time, a process its researchers liken to a 3D printer operating at the atomic scale. The MBE transforms raw materials into a Superconducting QUantum Interference Device, better known as a SQUID, which is then supercooled to minus 452.47 degrees Fahrenheit to activate its superconducting properties and its characteristic RF wave response. At those cryogenic temperatures, the device becomes sensitive to extraordinarily faint electromagnetic signals.

Cryogenics remains one of the technology’s biggest practical hurdles, and reducing that burden is an explicit goal of the collaboration. Researchers are exploring new material architectures designed to raise SQUID operating temperatures, cut cooling requirements and improve portability and operational practicality. Every degree by which the operating temperature can climb translates into smaller, lighter and less power-hungry cooling systems, which in turn determines whether quantum RF sensors can leave the laboratory and fly on real platforms. The partnership deliberately pairs Adelaide University’s expertise in superconducting quantum materials and sensor development with SwRI’s strengths in advanced RF engineering, signals processing and operational applications, covering the full chain from atomic-scale fabrication to fielded mission use.

Professor Giuseppe C. Tettamanzi, director of the Jesper Munch Quantum Laboratories and leader of Adelaide University’s superconducting quantum technologies research program, described how the first phase of joint work unfolded. The SwRI team tested and assessed selected performance metrics of the superconducting quantum RF technology developed by Adelaide University, he said. By combining their complementary expertise, he added, the two institutions are accelerating the development and maturation of quantum RF technologies with the potential to address the challenges of increasingly congested electromagnetic environments and complex operational scenarios. Tettamanzi also positioned the project as an example of the value of deep scientific alliances between Australia and the United States in advancing technologies critical to future security and economic prosperity.

The timing of the agreement reflects a broader surge of public investment in quantum science, which spans computing, communications and sensing and is being backed worldwide as well as at state and federal levels in the United States. In Texas, the recent Texas Quantum Initiative supports strategic planning for quantum technology funding and workforce training, an effort that gives in-state organizations such as SwRI a policy backdrop for expanding their quantum portfolios. At the federal level, the U.S. Department of War announced in June a Post Quantum Cryptography Strategy aimed at protecting critical government and military systems from emerging quantum threats, underscoring how quantum technologies are simultaneously viewed as an opportunity for new capabilities and a risk requiring defensive preparation.

For the engineers involved, the collaboration represents a rare chance to work at the frontier of an emerging discipline before it hardens into standard practice. Institute Engineer David Brown, based in Warner Robins and part of SwRI’s quantum technology exploration team, called quantum RF sensing an incredible new area of technology and described the project as a once-in-a-lifetime opportunity to be on the absolute cutting edge of science and explore the application of the most advanced technology of our lifetime. SwRI, he said, is eager to add these groundbreaking capabilities for its government and industry clients. With the memorandum of understanding now in place, the two institutions have established a foundation for future research, technology maturation and opportunities in quantum sensing, advanced RF systems and related mission applications, and the first-phase evaluations suggest the compact, cryogenically cooled sensors they are refining could eventually do the work of antenna farms many times their size.

Subject of Research: Superconducting quantum radio frequency sensing for signals intelligence applications

Article Title: SwRI, Adelaide University sign quantum RF research and development MOU

Article References: SwRI, Adelaide University sign quantum RF research and development MOU. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: quantum sensing, radio frequency, superconductors, SQUID, signals intelligence, SwRI, Adelaide University, molecular beam epitaxy, defense technology, electromagnetic spectrum, quantum materials, research partnership