Newly Developed Method Successfully Detects Underground Nuclear Tests with 99% Accuracy

Newly Developed Method Successfully Detects Underground Nuclear Tests with 99% Accuracy

Since the first atomic bomb detonation in 1945, over 2,000 nuclear weapons tests have been conducted by eight countries. These tests are now carried out underground for safety and secrecy, making them difficult to detect. However, a recent study published in Geophysical Journal International has developed a method to distinguish between underground nuclear tests and natural earthquakes with 99% accuracy.

The invention of nuclear weapons led to an international arms race, with countries like the Soviet Union, the UK, and France developing larger and more sophisticated devices. Early tests caused significant environmental and societal damage, such as the US’s Castle Bravo test in 1954, which resulted in radioactive fallout on nearby islands.

In 1963, the US, UK, and USSR agreed to conduct future tests underground to limit fallout. However, testing continued as more countries like China, India, Pakistan, and North Korea joined in.

Efforts have been made to monitor nuclear testing, with groups like the Comprehensive Nuclear-Test-Ban Treaty Organization running global networks of instruments. These instruments include air-testing stations, aquatic listening posts, infrasound detectors, and seismometers to detect radioactive elements, underwater tests, atmospheric explosions, and seismic waves respectively.

Seismometers are designed to measure seismic waves generated by underground energy release. The challenge lies in distinguishing between explosions and natural earthquakes. Various methods have been developed over the years, such as analyzing the location or depth of the event. However, these methods are not foolproof.

A more sophisticated approach involves calculating the ratio of energy transmitted in body waves to surface waves. Explosions tend to expend less energy in surface waves compared to earthquakes. While this method is effective, it failed to classify the 2017 North Korean nuclear test due to substantial surface waves generated inside a tunnel.

In 2023, researchers from the Australian National University and Los Alamos National Laboratory developed an improved method for classifying seismic events. By combining a new approach to represent rock displacement at the source with a statistical model, they achieved a 99% accuracy rate in distinguishing between explosions and earthquakes.

These robust techniques for identifying nuclear tests are crucial for holding governments accountable for the environmental and societal impacts of nuclear weapons testing. They will continue to be a key component of global monitoring programs.

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