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China
25.02.26 13:00
Technology

China unveils AI breakthrough to advance deep-space exploration

Tsinghua University researchers unveil an AI model that detects galaxies 13 billion light years away and advances deep-space astronomy

Photo: Jay_Zynism / iStock

Researchers in China have developed a new artificial intelligence model designed to significantly improve astronomical imaging and extend humanity’s view into the earliest epochs of the universe, as reported by China Daily, a partner of TV BRICS.

A cross-disciplinary team created the model, known as Astronomical Spatiotemporal Enhancement and Reconstruction for Image Synthesis, combining computational optics with advanced AI algorithms.

According to the research team, the model can extract extremely faint astronomical signals, identify galaxies located more than 13 billion light years away and generate some of the deepest deep-space images produced to date.

Observing distant and faint celestial bodies remains one of astronomy’s greatest technical challenges. Signals emitted by remote objects are often masked by background sky noise and thermal radiation generated by telescopes themselves, limiting detection capabilities.

Using the model, the team identified more than 160 candidate high-redshift galaxies dating back to the “Cosmic Dawn” period, roughly 200 million to 500 million years after the Big Bang.

Unlike traditional noise-reduction approaches, which rely on stacking multiple exposures and assume uniform or correlated noise, reconstructs astronomical data as a three-dimensional spatiotemporal volume. Through what researchers describe as a photometric adaptive screening mechanism, the model distinguishes subtle fluctuations in noise from the ultra-faint signals of distant stars and galaxies.

The team says the AI system is capable of processing vast volumes of space telescope data and is compatible with multiple observational platforms, positioning it as a potential universal enhancement tool for deep-space research.

Experts reviewing the study described the work as highly relevant with the potential for significant impact across the field of astronomy. Researchers expect the technology to support next-generation telescopes and contribute to investigations into dark energy, dark matter, cosmic origins and the study of exoplanets.

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