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Findings at Fermilab show discrepancy between theory and experiment, which may lead to new physics beyond the Standard Model.

Physicists now have a brand-new measurement of a property of the muon called the anomalous magnetic moment that improves the precision of their previous result by a factor of 2.

An international collaboration of scientists working on the Muon g-2 experiment at the U.S. Department of Energy’s Fermi National Accelerator Laboratory announced the much-anticipated updated measurement on August 10. This new value bolsters the first result they announced in April 2021, and sets up a showdown between theory and experiment over 20 years in the making.

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The innovative tweak will allow scientists to directly observe molecular behavior over a much longer period, opening a window onto pivotal biological processes like cell division.

“The living cell is a busy place with proteins bustling here and there,” explains University of Michigan biomedical engineer Guangjie Cui. “Our superresolution is very attractive for viewing these dynamic activities.”

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Black holes seem to get all the attention. But what about their mirror twins, white holes? Do they exist? And, if so, where are they?

To understand the nature of white holes, first we have to examine the much more familiar black holes. Black holes are regions of complete gravitational collapse, where gravity has overwhelmed all other forces in the universe and compressed a clump of material all the way down to an infinitely tiny point known as a singularity. Surrounding that singularity is an event horizon, which is not a physical, solid boundary, but simply the border around a singularity where the gravity is so strong that nothing, not even light, can escape.

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When Fourier Intelligence unveiled its lanky, jet-black humanoid robot GR-1 at the World Artificial Intelligence Conference (WAIC) in Shanghai in July, it instantly stole the show.

While the global technology community has been fixated on artificial intelligence (AI) software since the launch of OpenAI’s ChatGPT in November, the Chinese-made GR-1 — said to be capable of walking on two legs at a speed of 5km an hour while carrying a 50kg load — reminded people of the potential of bipedal robots, which are being pursued by global companies from Tesla to Xiaomi.

For Fourier, a Shanghai-based start-up, GR-1 was an unlikely triumph.

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In science, the simplest explanations often hold the most truth, a concept known as “Occam’s Razor.” This principle has shaped scientific thought for centuries, but when dealing with abstract ideas, how do we evaluate them?

In a new paper, philosophers from UC Santa Barbara and UC Irvine discuss how to weigh the complexity of scientific theories by comparing their underlying mathematics. They aim to characterize the amount of structure a theory has using symmetry — or the aspects of an object that remain the same when other changes are made.

After much discussion, the authors ultimately doubt that symmetry will provide the framework they need. However, they do uncover why it’s such an excellent guide for understanding structure. Their paper appears in the journal Synthese.

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A comprehensive new study provides evidence that various personality traits and cognitive abilities are connected. This means that if someone is good at a certain cognitive task, it can give hints about their personality traits, and vice versa.

For example, being skilled in math could indicate having a more open-minded approach to new ideas, but might also be associated with lower levels of politeness. These connections can help us understand why people are different in how they think and act.

The research has been published in the Proceedings of the National Academy of Sciences.

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