“Despite major advances in monitoring, some volcanoes erupt with little or no detectable precursors, significantly increasing the risk to nearby populations,” said Dr Yuyu Li of the University of Illinois, lead author of the study in Frontiers in Earth Science. “Some of these volcanoes are located near major air routes or close to communities: examples include Popocatépetl and Colima in Mexico, Merapi in Indonesia, Galeras in Colombia, and Stromboli in Italy.

“Our work helps explain how this happens, by identifying the key internal conditions — such as low magma supply and warm host rock — that make eruptions stealthy.”

Warning signs

Veniaminof is an ice-clad volcano in the Aleutian Arc of Alaska. It’s carefully monitored, but only two of its 13 eruptions since 1993 have been preceded by enough signs to alert observing scientists. In fact, a 2021 eruption wasn’t caught until three days after it had started.

“Veniaminof is a case study in how a volcano can appear quiet while still being primed to erupt,” said Li. “It is one of the most active volcanoes in Alaska. In recent decades, it has produced several VEI 3 eruptions — moderate-sized explosive events that can send ash up to 15 km high, disrupt air traffic, and pose regional hazards to nearby communities and infrastructure — often without clear warning signs.”

To understand Veniaminof better, the scientists used monitoring data over three summer seasons immediately before the 2018 stealthy eruption, which produced only ambiguous warning signs immediately before it happened. They created a model of the volcano’s behavior in different conditions which would change the impact of a filling magma reservoir on the ground above: six potential volumes of magma reservoir, a range of magma flow rates and reservoir depths, and three shapes of reservoir. They then compared the models to the data to see which matched best, and which conditions produced eruptions, stealthy or otherwise.

Volcano by the numbers

They found that a high flow of magma into a chamber increases the deformation of the ground and the likelihood of an eruption. If magma is flowing quickly into a large chamber, an eruption may not occur, but if one does the ground will deform enough to warn scientists first. Similarly, a high flow of magma into a small chamber is likely to produce an eruption, but not a stealthy one. Stealthy eruptions become likely when a low flow of magma enters a relatively small chamber. Compared to observational data, the results suggest that Veniaminof has a small magma chamber and a low flow of magma.

The model also suggests that different conditions could produce different warning signs. Magma flowing into larger, flatter chambers may cause minimal earthquakes, while smaller, more elongated chambers may produce little deformation of the ground. But stealthy eruptions only happen when all the conditions are in place — the right magma flow and the right chamber size, shape, and depth.

However, when the scientists added temperature to their model, they found that if magma is consistently present over time so that the rock of the chamber is warm, size and shape matters less. If the rock is warm, it’s less likely to fail in ways that cause detectable earthquakes or deformation of the ground when magma flows into the chamber, increasing the likelihood of a stealthy eruption.

What next?

“To mitigate the impact of these potential surprise eruptions, we need to integrate high-precision instruments like borehole tiltmeters and strainmeters and fiber optic sensing, as well as newer approaches such as infrasound and gas emission monitoring,” said Li. “Machine learning has also shown promise in detecting subtle changes in volcanic behavior, especially in earthquake signal picking.”

At Veniaminof, taking measures to improve the coverage of satellite monitoring and adding tiltmeters and strainmeters could improve the rate of detection. In the meantime, scientists now know which volcanoes they need to watch most closely: volcanoes with small, warm reservoirs and slow magma flows.

“Combining these models with real-time observations represents a promising direction for improving volcano forecasting,” said Li. “In the future, this approach can enable improved monitoring for these stealthy systems, ultimately leading to more effective responses to protect nearby communities.”

To put the result in perspective: a person is more likely to be struck by lightning in a given year (1 in 1.2 million) than for one of Oxford’s quantum logic gates to make a mistake.

The findings, published in Physical Review Letters, are a major advance towards having robust and useful quantum computers.

“As far as we are aware, this is the most accurate qubit operation ever recorded anywhere in the world,” said Professor David Lucas, co-author on the paper, from the University of Oxford’s Department of Physics. “It is an important step toward building practical quantum computers that can tackle real-world problems.”

To perform useful calculations on a quantum computer, millions of operations will need to be run across many qubits. This means that if the error rate is too high, the final result of the calculation will be meaningless. Although error correction can be used to fix mistakes, this comes at the cost of requiring many more qubits. By reducing the error, the new method reduces the number of qubits required and consequently the cost and size of the quantum computer itself.

Co-lead author Molly Smith (Graduate Student, Department of Physics, University of Oxford), said: “By drastically reducing the chance of error, this work significantly reduces the infrastructure required for error correction, opening the way for future quantum computers to be smaller, faster, and more efficient. Precise control of qubits will also be useful for other quantum technologies such as clocks and quantum sensors.”

This unprecedented level of precision was achieved using a trapped calcium ion as the qubit (quantum bit). These are a natural choice to store quantum information due to their long lifetime and their robustness. Unlike the conventional approach, which uses lasers, the Oxford team controlled the quantum state of the calcium ions using electronic (microwave) signals.

This method offers greater stability than laser control and also has other benefits for building a practical quantum computer. For instance, electronic control is much cheaper and more robust than lasers, and easier to integrate in ion trapping chips. Furthermore, the experiment was conducted at room temperature and without magnetic shielding, thus simplifying the technical requirements for a working quantum computer.

The previous best single-qubit error rate, also achieved by the Oxford team, in 2014, was 1 in 1 million. The group’s expertise led to the launch of the spinout company Oxford Ionics in 2019, which has become an established leader in high-performance trapped-ion qubit platforms.

Whilst this record-breaking result marks a major milestone, the research team caution that it is part of a larger challenge. Quantum computing requires both single- and two-qubit gates to function together. Currently, two-qubit gates still have significantly higher error rates — around 1 in 2000 in the best demonstrations to date — so reducing these will be crucial to building fully fault-tolerant quantum machines.

The experiments were carried out at the University of Oxford’s Department of Physics by Molly Smith, Aaron Leu, Dr Mario Gely and Professor David Lucas, together with a visiting researcher, Dr Koichiro Miyanishi, from the University of Osaka’s Centre for Quantum Information and Quantum Biology.

The Oxford scientists are part of the UK Quantum Computing and Simulation (QCS) Hub, which was a part of the ongoing UK National Quantum Technologies Programme.