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Astronomers detect a distant young super-Jupiter exoplanet

An international team of astronomers has reported the detection of a new super-Jupiter exoplanet as part of the Next Generation Transit Survey (NGTS). The newfound alien world, located some 1,430 light years away, is nearly four times as massive as Jupiter and is estimated to be only millions of years old. The discovery was detailed in a paper published November 13 on the pre-print server arXiv.

NGTS is a wide-field photometric survey focused mainly on the search for Neptune-sized and smaller exoplanets transiting bright stars. The project uses an array of small, fully robotic telescopes at the Paranal Observatory in Chile, operating at red-optical wavelengths. It uses the transit photometry method to find new exoworlds, which precisely measures the dimming of a star to detect the presence of a planet crossing in front of it.

Now, a group of astronomers led by Douglas R. Alves has found another extrasolar world with NGTS photometry. The new planet was identified around NGTS-33—a fast-rotating massive hot star.

Photon qubits challenge AI, enabling more accurate quantum computing without error-correction techniques

In an era where AI and data are driving the scientific revolution, quantum computing technology is emerging as another game-changer in the development of new drugs and new materials.

Dr. Hyang-Tag Lim’s research team at the Center for Quantum Technology at the Korea Institute of Science and Technology (KIST) has implemented a quantum computing algorithm that can estimate interatomic bond distances and ground state energies with chemical accuracy using fewer resources than conventional methods, and has succeeded in performing accurate calculations without the need for additional quantum error mitigation techniques.

The work is published in the journal Science Advances.

New language encodes shape and structure to help machine learning models predict nanopore properties

A large number of 2D materials like graphene can have nanopores—small holes formed by missing atoms through which foreign substances can pass. The properties of these nanopores dictate many of the materials’ properties, enabling the latter to sense gases, filter out seawater, and even help in DNA sequencing.

“The problem is that these 2D materials have a wide distribution of nanopores, both in terms of shape and size,” says Ananth Govind Rajan, Assistant Professor at the Department of Chemical Engineering, Indian Institute of Science (IISc). “You don’t know what is going to form in the material, so it is very difficult to understand what the property of the resulting membrane will be.”

Machine learning models can be a powerful tool to analyze the structure of nanopores in order to uncover tantalizing new properties. But these models struggle to describe what a looks like.

Managing Japan’s Shrinking Labor Force With AI and Robots

Japan’s combination of artificial intelligence and robotics may be the answer to its rapidly shrinking labor force

Todd Schneider, Gee Hee Hong, and Anh Van Le

While automation will eliminate very few occupations entirely in the coming decades, it is likely to have an impact on portions of almost all jobs to some degree—depending on the type of work and the tasks involved. Set to move beyond routine and repetitive manufacturing activities, automation has the potential to appear in a much broader range of activities than seen until now, and to redefine human labor and work style in services and other sectors. In Japan, the rapid decline in the labor force and the limited influx of immigrants create a powerful incentive for automation, which makes the country a particularly useful laboratory for the study of the future landscape of work.

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