Inside the Underground Lab in China Tasked with Solving a Physics Mystery

A view of the soon-to-be-completed and sealed central detector at the Jiangmen Underground Neutrino Observatory (JUNO), during an organized media tour by the Chinese foreign ministry and the Chinese Academy of Sciences (CAS), in Kaiping, Guangdong province, China October 11, 2024. (Reuters)
A view of the soon-to-be-completed and sealed central detector at the Jiangmen Underground Neutrino Observatory (JUNO), during an organized media tour by the Chinese foreign ministry and the Chinese Academy of Sciences (CAS), in Kaiping, Guangdong province, China October 11, 2024. (Reuters)
TT

Inside the Underground Lab in China Tasked with Solving a Physics Mystery

A view of the soon-to-be-completed and sealed central detector at the Jiangmen Underground Neutrino Observatory (JUNO), during an organized media tour by the Chinese foreign ministry and the Chinese Academy of Sciences (CAS), in Kaiping, Guangdong province, China October 11, 2024. (Reuters)
A view of the soon-to-be-completed and sealed central detector at the Jiangmen Underground Neutrino Observatory (JUNO), during an organized media tour by the Chinese foreign ministry and the Chinese Academy of Sciences (CAS), in Kaiping, Guangdong province, China October 11, 2024. (Reuters)

A giant sphere 700 m (2,300 ft) underground with thousands of light-detecting tubes will be sealed in a 12-storey cylindrical pool of water in coming months for an experiment that will shine new light on elusive subatomic particles known as neutrinos.

After years of construction, the $300 million Jiangmen Underground Neutrino Observatory (JUNO) in China's southern Guangdong province will soon start gathering data on neutrinos, a product of nuclear reactions, to help solve one of the biggest mysteries in particle physics.

Every second, trillions of extremely small neutrinos pass through matter, including the human body. In mid-flight, a neutrino, of which there are three known varieties, could transform into other types. Determining which types are the lightest and the heaviest would offer clues to subatomic processes during the early days of the universe and to explaining why matter is the way it is.

To that end, Chinese physicists and collaborating scientists from all over the world will analyze the data on neutrinos emitted by two nearby Guangdong nuclear power plants for up to six years.

JUNO would also be able to observe neutrinos from the sun, gaining a real-time view of solar processes. It could also study neutrinos given off by the radioactive decay of uranium and thorium in the Earth to better understand mantle convection driving tectonic plates.

Due to go operational in the latter half of 2025, JUNO will outpace the far larger Deep Underground Neutrino Experiment (DUNE) under construction in the United States. DUNE, backed by the Long-Baseline Neutrino Facility (LBNF) under the US Department of Energy's (DOE) top particle physics laboratory, Fermilab, will come online around 2030.

The race to understand neutrinos and advance the study of particle physics, which has transformed medical imaging technologies and developed new energy sources, intensified when the DOE abruptly cut funding for US institutes collaborating on JUNO. It instead focused on building DUNE, which has since been plagued by delays and budget overruns, with costs skyrocketing to more than $3 billion.

"China had supported Fermilab's LBNF at the time, but later the cooperation could not continue," Wang Yifang, chief scientist and project manager of JUNO, told Reuters during a recent government-backed media tour of the facility.

"Around 2018-2019, the US DOE asked all national laboratories not to cooperate with China, so Fermilab was forced to stop working with us."

The DOE, the largest US funding agency for particle physics, did not respond to Reuters' request for comment.

Sino-US tensions have risen sharply over the past decade. A trade war erupted during the Trump administration and President Joe Biden later cracked down on the sale of advanced technology to China.

In August, a bilateral science and technology cooperation pact signed in 1979 lapsed, potentially pushing more scientists to seek alternative partners, creating duplication in research and missing out on collaboration that otherwise might have led to beneficial discoveries.

In the 2010s, the countries jointly produced a nuclear reactor that could use low-enriched uranium, minimizing the risk of any fuel being weaponized.

China's foreign ministry said Beijing was "in communication" with Washington about the lapsed science agreement. The US State Department did not comment.

SOLE US COLLABORATOR

Institutions collaborating on JUNO hail from locations including France, Germany, Italy, Russia and the US, and even self-governed Taiwan, which China claims as part of its territory.

Neutrino observatories are also being constructed in other places.

"The one in the US will be six years behind us. And the one in the France and in Japan, they will be two or three years later than us. So we believe that we can get the result of mass hierarchy (of neutrinos) ahead of everybody," Wang said.

So far, real-life neutrino applications remain a distant prospect. Some scientists have mulled the possibility of relaying long-distance messages via neutrinos, which pass through solid matter such as the Earth at near light speed.

Researchers are keeping their distance from politics to focus on science, although they remain at the mercy of governments providing the funding.

One US group remains in JUNO, backed by the National Science Foundation, which recently renewed its funding for its collaboration for another three years, the group's leading physicist told Reuters.

In contrast, more than a dozen US institutes participated in the predecessor to JUNO, the Daya Bay experiment, also in Guangdong.

"Despite any political differences, I believe that through our collaboration on this scientific endeavor, we are setting a positive example that may contribute, even in a small way, to bringing our countries closer together," said J. Pedro Ochoa-Ricoux of the University of California, Irvine.

DATA INTEGRITY

The passage of neutrinos from the two power stations will be logged by JUNO's 600 metric ton spherical detector, which will immediately transmit the data to Beijing electronically. The data will be simultaneously relayed to Russia, France and Italy, where it can be accessed by all of the collaborating institutions, said Cao Jun, JUNO's deputy manager.

Data integrity has been a concern among foreign companies in China since a law was enacted in 2021 on the use, storage and transfer of data in the name of safeguarding national security.

"We have a protocol to make sure that no data is missing," Cao said.

For data on the more crucial aspects of the experiment, at least two independent teams will conduct analyses, with their results cross-checked.

"When these two groups get a consistent result, we can publish it," Cao said.

US-based Ochoa-Ricoux, who previously collaborated on China's Daya Bay experiment, will lead the data analysis for JUNO. He will also be involved in the DUNE data analysis.

"We welcome the Americans," said Wang, also director of the Institute of High Energy Physics, the Chinese counterpart of Fermilab.



AI Enhances Flood Warnings but Cannot Erase Risk of Disaster

A view shows a flooded schoolyard in Bamako, Mali, September 23, 2024. (Reuters)
A view shows a flooded schoolyard in Bamako, Mali, September 23, 2024. (Reuters)
TT

AI Enhances Flood Warnings but Cannot Erase Risk of Disaster

A view shows a flooded schoolyard in Bamako, Mali, September 23, 2024. (Reuters)
A view shows a flooded schoolyard in Bamako, Mali, September 23, 2024. (Reuters)

When floods ripped through parts of Europe in September, the scale of the destruction took people by surprise. The intense rains should not have, because those had been predicted by sophisticated forecasting systems enhanced with artificial intelligence.

But forewarned did not mean forearmed. Though the rains were accurately predicted, the effects in the deluged areas were not - a fact that highlights the difficulties of dealing with ever more common extreme weather.

AI has supercharged weather forecasting, using a range of statistical tools to analyze years of historical data and predict patterns, and at a lower cost than traditional numerical weather predictions.

AI technology can create more specific predictions ahead of events such as urban flooding or in complex terrain such as mountainous areas.

For example, Google-funded GraphCast, a machine learning–based method trained directly from reanalysis data, was found to outperform traditional models. Reanalysis data relies on past forecasts rerun with modern forecasting models to provide the most complete picture of past weather and climate.

But there are still gaps in knowledge, in how the information is used and in investment to strengthen data gathering models, experts say.

"In some cases and for some variables, AI models can beat physics-based models, but in other cases vice versa," said Andrew Charlton-Perez, professor of meteorology at the University of Reading in the UK.

One issue is that the effectiveness of an AI model is only as good as the information it is fed. If there is little input data, or extreme events happen more frequently at different times of the year or in different regions, weather disasters become more challenging to predict.

"A good use of the AI-based weather forecasts would be to complement and enhance our forecasting toolbox, perhaps by allowing us to produce larger ensembles of forecasts that enable accurate assessment and interpretation of the likelihood of extreme events," Charlton-Perez added.

COMMUNICATION IS KEY

Since January, the European Center for Medium-Range Weather Forecasts (ECMWF), an independent organization that provides predictions four times per day to European countries, has been using the Artificial Intelligence/Integrated Forecasting System (AIFS).

This data-driven forecasting model makes multiple predictions rapidly and delivers long-term forecasts of weather events like cyclones and heatwaves.

The ECMWF readings ahead of the September floods were accurate, experts say.

Thomas Wostal, press officer for meteorological observatory GeoSphere Austria, told Context/the Thomson Reuters Foundation that their numerical models - including the ECMWF's predictions - foresaw 300-400 millimeters (11.8-15.7 inches) of rain locally, which came to pass.

But even with accurate forecasts, scientists say communication is key, especially in an era when climate change means extreme weather is becoming more frequent.

"I think what happened with (the recent floods) ... is that it's so rare - a one in 150- to 200-year event - that even if the weather models capture it, there's a reasonable degree of uncertainty," said Shruti Nath, a postdoctoral research assistant in predicting weather and climate at Oxford University.

"You have to produce the warning in a way that is communicative, in the degree of severity it could possibly have on people, then people could see the cost of inaction versus the cost of action is actually much greater. So then they would actually put (in) more resources," she said.

EUROPE BEHIND THE CURVE?

Europe faces urgent climate risks that are outpacing policies and adaptation actions, a report from the European Environment Agency has warned.

Extreme heat, drought, wildfires and flooding will worsen in Europe even under optimistic global warming scenarios and affect living conditions throughout the continent, the EEA says.

After the floods, the European commissioner for crisis management, Janez Lenarčič, said the disaster was not an anomaly.

"These extreme weather events that used to be once in a lifetime are now an almost annual occurrence. The global reality of climate breakdown has moved into the everyday lives of Europeans," he said.

Some tech entrepreneurs say Europe is not ready.

Jonas Torland, co-founder of Norway-based 7Analytics, which develops models for predicting floods and landslides, said governments and businesses in the United States had risk managers who were more accustomed to assessing environmental hazards, while in Europe, authorities lacked readiness.

"We often see substantial expenditures with minimal data support for informed decision-making", Torland, whose models are used in the cities of Oslo, Bergen and Kristiansand, told the Thomson Reuters Foundation.

"While AI is a crucial component of these models, unfortunately, governments are not investing in or purchasing these advanced AI solutions," he said adding that he believed governments "stick to their old data providers and consultants.”

Data processing is also a challenge because these complex AI models need to run updates every hour as forecasts change.

That requires both a lot of computing power, and a lot of time - especially at more minute scales.

A 1-by-1 meter grid, which 7Analytics uses for its predictions, is 100 times more detailed than a 10-by-10 meter grid, but requires more than 100 times as long to process.

High computing power also means huge amounts of energy and water are needed, which makes AI models part of the problem because they are adding to the planet-heating emissions driving the climate emergency.

Some big technology companies, like Microsoft and Google, are exploring the use of nuclear power to run their huge data storage centers.

Other scientists stress that beyond refining their forecasting abilities, authorities need to invest in physical solutions, like developing areas where floodwater can safely be stored, and early warning systems.

They also need to minimize development in flood-prone areas, given the likelihood of more intense climate change-driven floods, and meet their commitments to limit emissions.

"It's not a question of data or technology or knowledge. It's a question of implementation, political will," Friederike Otto, a senior lecturer at Imperial College in London, said in an email response to questions.

"As long as the world burns fossil fuels, the root cause of climate change, extreme weather events will continue to intensify, killing people and destroying homes. To curb this trend, we need to replace oil, gas and coal with renewable energy."