Earthquakes that propagate at higher speeds make the ground move more than it would in slower but otherwise comparable earthquakes, say geophysicists. Using physics-based models, Mohamed Abdelmeguid and colleagues at the California Institute of Technology in the US showed that so-called “supershear” ruptures produce stronger and longer-duration ground motion than equivalent subshear ruptures. Because models of ground motion that underpin infrastructure standards do not account for this effect, these models may need to be updated to accurately describe hazards such as the 2025 Myanmar earthquake, which produced supershear ruptures in both directions.

Geophysicists have identified two categories of earthquake based on how fast their ruptures propagate through the Earth’s crust. Shear waves, or S waves, travel at certain expected velocities (the shear-wave velocity) depending on the stiffness and density of the ground. When a rupture travels faster than the shear-wave velocity of the surrounding ground, it is termed a supershear earthquake. Otherwise, it is subshear.

Although Abdelmeguid notes that supershear ruptures were first predicted theoretically in the 1970s, and have subsequently been observed in both laboratory experiments and the real world, most previous studies focused on their underlying mechanisms and the transition from subshear to supershear. The new study, which appears in the Bulletin of the Seismological Society of America, goes a step further by examining how the ground motion in a supershear quake differs from that of an otherwise comparable subshear one. The question is relevant, Abdelmeguid says, because nearly 36% of strike-slip earthquakes during the past 15 years contained supershear rupture, yet existing models do not factor it in.

Supershear simulations

To address this gap, Abdelmeguid and colleagues developed a dynamic rupture model that generates simulated ground motion data and used it to identify the characteristics of supershear earthquakes. They found that prolonged supershear propagation produces what they term “a distinct spatial pattern of stronger and longer-duration shaking”. However, episodic supershear segments, where rupture speed intermittently changes between supershear and subshear, produce ground motion similar to subshear ruptures.

Simulations like these are important because some supershear rupture scenarios are poorly represented in the observational record. This record is used to develop ground motion models, so simulations can “reveal physical dependencies that may not be apparent from existing observations,” Abdelmeguid says.

Characterizing the 2025 Myanmar earthquake

The 2025 Myanmar earthquake – a supershear quake in which many regions experienced higher than expected ground shaking – is a case in point. It occurred on the 1200-kilometre-long Sagaing Fault, which lies at the boundary of the Burma microplate and the Sunda plate and is not far from Mandalay, the country’s second-largest city. At magnitude 7.7, it was the largest earthquake in Myanmar in over a century, and the long rupture meant that large parts of Myanmar and Thailand were affected, with thousands of deaths and injuries as well as severe damage to infrastructure.

Initial studies were inconclusive about whether this earthquake’s rupture exhibited intermittent or sustained supershear speed. This lack of consensus is partly because recording intermittent supershear rupture is challenging when near-fault sensors are sparse, as is the case in Myanmar (and indeed most countries, with notable exceptions such as Japan, Taiwan, New Zealand and parts of the US).

A new study published in PNAS addresses this question. Using satellite earth observations, teleseismic data and CCTV footage as well as the available near-fault seismic sensor data, researchers led by Lingling Ye at the Southern University of Science and Technology (SUSTech) in China modelled the rupture process of the Myanmar quake. The result, Ye says, is a “well-resolved rupture process” that “reveals previously unrecognized dynamic rupture features”. Notably, the team’s simulations showed that the rupture transitioned between supershear and subshear as it tore through around 460 kilometres of the country.

Influence of geometry and stress distribution

To understand the cause of these variations, the researchers examined the geometry and stress distribution along the fault. Based on an existing fault model, they calculated a parameter called fault misalignment, which acts as an indicator for irregularities in the fault geometry. Higher fault misalignment, for example, indicates higher bends and branches in the fault.

When the researchers overlaid fault misalignment with the observed rupture speed, they noticed that supershear speeds coincided with fault stretches that had lower misalignment. For fault stretches with higher misalignment, subshear speed prevailed, meaning that the rupture decelerates at locations with high fault misalignment, transitioning from supershear to subshear. The researchers also found that the rupture speed, whether supershear or subshear, responded to the varying levels of local stress, with higher stress levels inducing faster rupture speed.

Although not unique in exhibiting supershear behaviour, the 2025 Myanmar earthquake rupture propagated away from the epicentre on both sides, travelling around 80 kilometres to the north and 380 kilometres to the south. Initial studies debated whether the ruptures on both sides were supershear. The researchers found that the northern rupture propagation was not supershear and claim that its shorter rupture length is caused by a combination of the fault’s complex structure and low accumulated stress resulting from the magnitude 6.8 earthquake that struck in 2012.

“Every earthquake has unique behaviour”

In future work, Ye is eager to revisit the 2023 Turkey doublet earthquakes, which she says have many more near-fault strong motion observations than the 2025 Myanmar quake, as well as a now well characterized complex fault system. “Every earthquake has unique behaviour,” she says. “Determining the key features that control their rupture processes is still underway.”

For Abdelmeguid, who recently started his own research group at the University of Houston, US, understanding these complex rupture processes is important because it will ultimately improve our understanding of geophysical processes and the ground motion models that are used for engineering applications. “We are currently extending this work to examine ground motions generated by ruptures on more complex faults, including cases in which fault geometry and heterogeneity influence both ground motion and the dynamic process, as observed during the multiple earthquakes,” he tells Physics World.

• This article was amended on 2 September 2026 to clarify the nature of the rupture propagation in the 2025 Myanmar earthquake. The researchers found that the northern rupture was subshear, not supershear as originally stated.

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Usually, when physicists want to model the merger of two black holes, they use supercomputers. Now, however, physicists in the US have found a possible shortcut. In a study published in Physical Review Letters, they show that, of the final states permitted by energy and angular momentum, the remnant of a non-spinning black hole merger ends up in a state quite close to one that maximizes the system’s entropy – a surprising and puzzling result that reinforces the deep connection between thermodynamics and black holes.

“Our group has long believed that black hole thermodynamics could provide a new perspective on binary black hole mergers,” says team member Monica Rincon-Ramirez, a postdoctoral researcher at Pennsylvania State University. “While black hole thermodynamics is well established for equilibrium systems, much less is understood in the highly dynamical regime of mergers.”

Merging black holes

Black hole mergers occur when two black holes that orbit each other spiral inward with increasing speed, losing both energy and angular momentum by emitting gravitational waves until they eventually converge in a violent clash. After the moment of merger, the remnant oscillates vigorously, “ringing down” into a quiescent, rotating object known as a Kerr black hole that can be described in terms of just two quantities: mass and spin.

Meanwhile, the gravitational waves – ripples in the fabric of spacetime – from this energetic collision propagate through space virtually uninterrupted. These gravitational waves encode information about their source, and when we detect them on Earth (millions of light-years away from their origin), we can use them to predict the remnant’s size and spin. However, doing this requires solving complex equations from Einstein’s general theory of relativity using computationally expensive numerical simulations.

Connecting black holes and thermodynamics

Thermodynamics is the branch of physics concerned with the relationships between energy, heat, work and temperature. For ordinary matter, thermodynamics can describe how energy flows from one system to another in simple terms, even for complex systems with numerous particles and degrees of freedom. For example, rather than meticulously tracking each individual particle, concepts such as entropy – a measure of a system’s disorder – can be used to describe the final state of the entire system.

Physicists have long known that black holes obey laws that closely parallel the laws of thermodynamics, with the event horizon and surface gravity of black holes being analogous to entropy and temperature, respectively. Building on this established connection, Rincon-Ramirez and colleagues at the University of Mississippi, the University of California, Berkeley, and Northwestern University as well as Penn State investigated whether black hole thermodynamics could go beyond describing the properties of isolated, stationary black holes and provide, in addition, a principle for determining the final state of a merger.

The maximum-entropy conjecture

After accounting for the energy and angular momentum carried away by gravitational waves, the researchers tracked the evolving mass and angular momentum of a binary, mapped these values to those of hypothetical Kerr black holes, and calculated the corresponding entropy. They found that the Kerr entropy reaches a maximum at a mass and spin strikingly close to the final mass and spin predicted by numerical relativity simulations. Indeed, the two methods agreed with each other to within a few percent. “The Kerr entropy turned out to be remarkably meaningful for the binary system as a whole,” Rincon-Ramirez says.

Interpreting and presenting these results proved to be a challenge, however. “What we found was completely unexpected,” says Rincon-Ramirez. After deliberating among themselves as to why the final black hole’s parameters should lie so close to those of the maximum-entropy black hole, they ultimately chose to extend the conversation to the scientific community. By presenting their puzzling results and a broad conjecture, which they term the “maximum entropy conjecture for black hole mergers”, they hope to sharpen their findings through rigorous testing and eventually place them on a firm mathematical foundation within general relativity.

In the meantime, the researchers plan to extend their conjecture to more general binary black hole systems. By studying systems such as highly spinning and eccentric binaries, they hope to gain further understanding of the role of thermodynamic quantities in general relativity. “Ultimately, we hope this work will contribute to a more complete thermodynamic framework for highly dynamical spacetimes,” Rincon-Ramirez says.

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“Solar towers” that convert sunlight into heat could play a useful role in the renewable energy transition, but high installation costs and complex requirements limit their attractiveness to commercial operators. A team of researchers from Germany’s Karlsruher Institut für Technologie (KIT) and the German Aerospace Center (DLR) is now taking steps to change that. By creating a freely accessible database of information about how these plants work, they aim to accelerate research on solar thermal energy and drive improvements that could allow the technology to be more widely deployed in the future.

Unlike photovoltaic panels, concentrating solar power (CSP) plants do not convert sunlight directly into electricity. Instead, they generate heat by using an array of movable mirrors called heliostats to funnel sunlight onto a receiver located at the top of a tower. This heat can be used to drive a turbine to produce electricity immediately, but it can also be stored and used to generate electricity at night or on cloudy days. Depending on the plant’s location and setup, the heat could even be used directly for industrial applications and district heating.

The problem, explains study leader Kaleb Phipps, is that operating solar power tower plants safely and efficiently is a complex and expensive task. “CSP technologies have the potential to help the transition to a renewable energy system,” says Phipps, a research fellow at KIT’s Scientific Computing Center. “However, they are still not financially viable and there are operating challenges associated with them.”

Before researchers can develop and reliably test new, improved processes, Phipps explains that they need access to real-world operational CSP data. “We believe that modern data-driven machine learning methods like ours can help solve a lot of these problems,” he says.

849 gigabytes of operational data

To construct their database, which is known as PAINT, researchers collected data from the CSP tower near Jülich, Germany. These data include the exact positions of the tower’s 2014 mirrors, their dimensions, how they are warped and the way they rotate and tilt. The team also obtained fine-grained weather data for the entire 2021-2024 period under study, plus a further 218 000 images to help determine whether the mirrors were efficiently directing sunlight precisely to the top of the tower.

All in all, the PAINT database contains 849 gigabytes of operational data organized using the SpatioTemporal Asset Catalog (STAC) standard. To make these data FAIR (findable, accessible, interoperable and reusable), the researchers developed software to simplify access to the database and then published the data in a way that is freely available to all users.

Their goal, they say, is for other researchers to use this FAIR database to develop “digital twins”, or virtual replicas, of real-world CSP plants. When combined with machine-learning models, such twins can be used to answer questions such as whether the mirrors are aligned for maximal light absorption (one of the most important parameters for efficient operation) in near real time.

Community reaction

“The fact that we are receiving many positive responses regarding the data and that people seem to appreciate it is our biggest success,” Phipps says. Such responses are especially gratifying, he adds, because constructing databases like PAINT can be an arduous task.

“The main difficulties were about collecting the data, cleaning and unifying it into standard formats and parsing and organising all the metadata, which was originally complete chaos,” Phipps recalls. “We therefore put a lot of time and effort into creating standardized and automated workflows so that the process is as transparent as possible and can be reused for future data.”

The team also faced challenges when trying to convince peers that this work counted as “research”, he adds. “The fact that the data itself didn’t directly result in a new algorithm or method meant that lots of people didn’t believe we would be able to publish the results or achieve anything with them,” says Phipps. “Luckily, we were able to prove the doubters wrong.”

While the PAINT database currently contains data from only one CSP, the KIT researchers, who report their work in Nature Energy, are hoping to expand it. “We really need contributions from other CSP power plants around the world to transform the database into a truly international and diverse source for researchers,” Phipps says. “As data from different facilities is added in the future, it will be possible to develop a common standard for open operational data in solar tower research. This would speed up the development and promote a widespread adoption of this technology.”

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