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07:20 «BRICSterview»
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01.06.2617:00 Economy
Global justice in healthcare: BRICS cooperation in production of medical technologies
01.06.2612:00 Personalities
Mahasha Piet Rampedi, Editor-in-Chief, African Times: "Alternative media to drive next phase of media growth"
28.05.2617:06 Personalities
Director-General of Malaysia's National Security Council Nushirwan Zainal Abidin: "BRICS countries have great potential in digital economy to strengthen trade among us"
06.06.2610:00 Culture
TV BRICS and "Gateway to Russia" project to jointly promote Russian language and culture abroad
05.06.2614:00 Society
TV BRICS International Media Network to promote BRICS and Global South cooperation in public diplomacy
04.06.2612:00 Society
Moscow to host open Russian language lesson for foreigners from BRICS+ countries
TV BRICS
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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By clicking on the "Subscribe" button, you agree to the processing of personal data