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Artificial intelligence (AI) is making waves beyond the realm of digital assistants and deepfake technology. Astronomers are now harnessing AI to achieve unprecedented precision in understanding the universe’s fundamental parameters. Researchers at the Flatiron Institute’s Center for Computational Astrophysics (CCA) in New York City have leveraged AI to calculate the five cosmological parameters that characterise the universe, enhancing our knowledge of its structure and evolution.

Unveiling the Universe’s Settings

The five cosmological parameters in question are crucial as they essentially define the ‘settings’ of the universe, dictating how it operates on the largest scales. Liam Parker, an astronomer at CCA and a co-author of the study, explained that these parameters are like the universe’s operating instructions. To determine these parameters with exceptional accuracy, the research team employed AI to analyse data from over 100,000 galaxies, which were observed as part of the Sloan Digital Sky Survey (SDSS). This survey is instrumental in cosmology as it helps map out the universe by examining how galaxies are distributed across space.

Maximising Data Efficiency

The use of AI allowed the team to extract detailed insights from the SDSS data, a task previously hampered by the sheer volume of information and the limitations of traditional analysis methods. Co-author Shirley Ho, another astronomer at CCA, highlighted the enormous costs associated with such surveys, which can run into billions of dollars. With AI, the team has been able to push the boundaries of what these surveys can reveal, providing a more cost-effective means of extracting valuable knowledge from complex data.

Training AI for Precision

The process involved training the AI model on 2,000 simulated universes, each with different cosmological settings. This training set included real-world challenges such as atmospheric distortion and imperfect telescope imaging to ensure the AI’s accuracy. Once trained, the AI was applied to actual data from the SDSS Baryon Oscillation Spectroscopic Survey. The results were impressive: the AI reduced the uncertainty in measuring the universe’s ‘clumpiness’ by more than half compared to traditional methods. This achievement is akin to conducting traditional analyses with four times more data, significantly enhancing data efficiency.

Impact on Cosmic Mysteries

The advancement of AI in cosmology is not just about refining existing methods but also about addressing major cosmic questions. One such mystery is the Hubble tension, which refers to discrepancies between different estimates of the Hubble constant, a measure of the universe’s expansion rate. The improved precision provided by AI could be crucial in resolving this tension and advancing our understanding of the universe.

As new surveys like the European Euclid survey come online, the AI-powered techniques developed by the CCA team will be instrumental in extracting maximum value from these new datasets. The ability to analyse and interpret vast amounts of cosmic data efficiently represents a significant leap forward in our quest to comprehend the universe’s fundamental parameters.

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Astronomers Discover 3I/ATLAS, Largest Interstellar Comet Yet Detected

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Astronomers Discover 3I/ATLAS, Largest Interstellar Comet Yet Detected

Astronomers have discovered the third interstellar comet to pass through our solar system. Named 3I/ATLAS (initially A11pl3Z), it was first spotted July 1 by the ATLAS telescope in Chile and confirmed the same day. Pre-discovery images show it in the sky as far back as mid-June. The object is racing toward the inner system at roughly 150,000 miles per hour on a near-straight trajectory, too fast for the Sun to capture. Estimates suggest its nucleus may be 10–20 km across. Now inside Jupiter’s orbit, 3I/ATLAS will swing closest to the Sun in October and should remain observable into late 2025.

Discovery and Classification

According to NASA, in early July the ATLAS survey telescope in Chile spotted a faint moving object first called A11pl3Z, and the IAU’s Minor Planet Center confirmed the next day that it was an interstellar visitor. The object was officially named 3I/ATLAS and noted as likely the largest interstellar body yet detected. At first it appeared to be an ordinary near-Earth asteroid, but precise orbit measurements showed it speeding at ~150,000 mph – far too fast for the Sun to capture. Astronomers estimate 3I/ATLAS spans roughly 10–20 km across. Signs of cometary activity – a faint coma and short tail – have emerged, earning it the additional comet designation C/2025 N1 (ATLAS).

Studying a Pristine Comet

3I/ATLAS was spotted well before its closest approach, giving astronomers time to prepare detailed observations. It will pass within about 1.4 AU of the Sun in late October. Importantly, researchers can study it while it is still a pristine frozen relic before solar heating alters it. As Pamela Gay notes, discovering the object on its inbound leg leaves “ample time” to analyze its trajectory. Astronomers are now racing to obtain spectra and images – as Chris Lintott warns, the comet will be “baked” by sunlight as it nears perihelion.

Determining its composition and activity is considered “a rare chance” to learn how planets form in other star systems. With new facilities like the Vera C. Rubin Observatory coming online, researchers expect more such visitors in the years ahead. 3I/ATLAS offers a rare chance to study material from another star system.

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NASA’s New Horizons Proves Deep-Space Navigation via Stellar Parallax



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NASA’s New Horizons Proves Deep-Space Navigation via Stellar Parallax

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NASA's New Horizons Proves Deep-Space Navigation via Stellar Parallax

NASA’s New Horizons spacecraft carried out an unprecedented deep-space star navigation test while 438 million miles from Earth. Using its long-range camera in April 2020, it captured images of Proxima Centauri and Wolf 359, which appeared slightly shifted in the sky compared to Earth’s view – a striking demonstration of stellar parallax. It was the first-ever demonstration of deep-space stellar navigation. By comparing these images to Earth-based observations and a 3D star chart, scientists calculated New Horizons’ position to within about 4.1 million miles, only about 26 inches across the United States.

Stellar Parallax Test

According to the paper describing the results, accepted for publication in The Astronomical Journal, New Horizons’ camera imaged Proxima Centauri (4.2 light-years away) and Wolf 359 (7.86 light-years) on April 23, 2020. From the spacecraft’s distant vantage point, the two stars appear in different positions than seen from Earth – the essence of stellar parallax. By comparing those images with Earth-based data and a three-dimensional map of nearby stars, the team worked out the probe’s location to within about 4.1 million miles.

As lead author Tod Lauer explained, “Taking simultaneous Earth/Spacecraft images we hoped would make the concept of stellar parallaxes instantly and vividly clear”. He added, “It’s one thing to know something, but another to say ‘Hey, look! This really works!’”.

New Horizons and Future Missions

New Horizons, the fifth spacecraft to leave Earth and reach interstellar space, flew past Pluto and its moon Charon in 2015, sending home the first close-up images of those distant icy worlds. Now on an extended mission, the probe is studying the heliosphere.

New Horizons’ principal investigator Alan Stern called the parallax test “a pioneering interstellar navigation demonstration” that shows a spacecraft can use onboard cameras “to find its way among the stars”, in a statement. He also noted it “could be highly useful for future deep space missions in the far reaches of the Solar System and in interstellar space”

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AI Designs Ocean Gliders Inspired by Sea Creatures to Boost Underwater Research Efficiency

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AI Designs Ocean Gliders Inspired by Sea Creatures to Boost Underwater Research Efficiency

Marine animals like fish and seals have long inspired ocean engineers due to their fluid, energy-efficient movements. Now, researchers are turning to these sea animals to create a new class of underwater gliders that requires very little energy, according to a team led by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the University of Wisconsin-Madison. They used artificial intelligence to design forms that slide through the water with less resistance, making long-term ocean exploration more efficient. These gliders, fabricated via 3D printing, promise better data collection on currents, salt levels, and climate impacts.

AI-Powered 3D Designs Create Energy-Efficient Underwater Gliders Inspired by Marine Life Forms

As per a study published on the arXiv preprint server, the team used machine learning to create and simulate numerous novel 3D glider shapes. By comparing traditional models—like submarines and sharks—with digitally altered versions, their algorithm learnt how different designs behaved at various “angles-of-attack.” A neural network then evaluated the lift-to-drag ratio of each shape, identifying those most likely to glide efficiently through water. These shapes were then fabricated using lightweight materials that minimised energy use.

In tests, two AI-generated prototypes—one shaped like a two-winged plane and the other like a four-finned flatfish—were built and tested both in wind tunnels and underwater. Key hardware was integrated with the gliders, including buoyancy control by a pump and a mass shifter to move the angle during displacements. The new gliders, with better shapes and lift-to-drag ratios, could travel farther on less power than traditional torpedo-shaped types.

The team added that what they are doing not only makes new types of designs possible but also reduces design times and cuts the cost since it doesn’t require physical prototyping. “This high degree of shape diversity hasn’t been investigated before,” Peter Yichen Chen, an MIT postdoc and co-lead author on the project, mentioned. He also noted that their AI pipeline allows testing forms that would be “very taxing” for humans to manually design.

The future plans are to produce slimmer and more manoeuvrable gliders and to improve the AI system with more configurable options. Intelligent bioinspired vehicles like these, the researchers say, will be essential in studying dynamic ocean environments that are changing quickly with the intensifying demands of industrial activity, ultimately offering more flexible and efficient ways for us to explore Earth’s last frontier.

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Hubble Observations Give Forgotten Globular Cluster Its Moment to Shine



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