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Archive for the ‘physics’ category: Page 18

Sep 13, 2023

Motion of stars near Milky Way’s central black hole is only predictable for a few hundred years

Posted by in categories: computing, cosmology, physics

The orbits of 27 stars orbiting closely around the black hole at the center of our Milky Way are so chaotic that researchers cannot predict with confidence where they will be in about 462 years. This finding emerges from simulations by three astronomers based in the Netherlands and the United Kingdom. The researchers have published their findings in two papers in the International Journal of Modern Physics D and in the Monthly Notices of the Royal Astronomical Society.

Simulating 27 stars and their interactions with each other and with the black hole is easier said than done. For centuries, for example, it was impossible to predict the motions of more than two interacting stars, planets, rocks, or other objects. It was only in 2018 that Leiden researchers developed a computer program in which rounding errors no longer play a role in the calculations. With this, they were able to calculate the motions of three imaginary stars. Now the researchers have expanded their program to deal with 27 stars that, by astronomical standards, move close to the black hole at the center of the Milky Way.

The simulations of the 27 and the black hole resulted in a surprise. Although the stars remain in their orbits around the black hole, the interactions between the stars show that the orbits are chaotic. This means that small perturbations caused by the underlying interactions change the orbits of the stars. These changes grow exponentially and, in the long run, make the star orbits unpredictable.

Sep 12, 2023

Black Holes ‘Burp’ Years After Shredding Stars, And We Don’t Know Why

Posted by in categories: cosmology, physics

For a few hours after a star smashes into a supermassive black hole, some of the brightest light in the Universe is produced.

The subsequent flash of radio waves were thought to simmer down within weeks or months of a collision. It turns out we might have been a little impatient to turn our gaze elsewhere.

Continue reading “Black Holes ‘Burp’ Years After Shredding Stars, And We Don’t Know Why” »

Sep 12, 2023

The universe caught suppressing cosmic structure growth

Posted by in categories: cosmology, physics

As the universe evolves, scientists expect large cosmic structures to grow at a certain rate: dense regions such as galaxy clusters would grow denser, while the void of space would grow emptier.

But University of Michigan researchers have discovered that the rate at which these grow is slower than predicted by Einstein’s Theory of General Relativity.

They also showed that as dark energy accelerates the ’s global expansion, the suppression of the cosmic structure growth that the researchers see in their data is even more prominent than what the theory predicts. Their results are published in Physical Review Letters.

Sep 11, 2023

Meta’s AI Agents Learn Via Toddler-Like “Motor Babbling”

Posted by in categories: neuroscience, physics, robotics/AI

Similarly, allowing the MyoLegs to flail around for a while in a seemingly aimless fashion gave them better performance with locomotion tasks, as the researchers described in another paper presented at the recent Robotics Science and Systems meeting. Vittorio Caggiano, a Meta researcher on the project who has a background in both AI and neuroscience, says that scientists in the fields of neuroscience and biomechanics are learning from the MyoSuite work. “This fundamental knowledge [of how motor control works] is very generalizable to other systems,” he says. “Once they understand the fundamental mechanics, then they can apply those principles to other areas.”

This year, MyoChallenge 2023 (which will also culminate at the NeurIPS meeting in December) requires teams to use the MyoArm to pick up, manipulate, and accurately place common household objects and to use the MyoLegs to either pursue or evade an opponent in a game of tag.

Emo Todorov, an associate professor of computer science and engineering at the University of Washington, has worked on similar biomechanical models as part of the popular Mujoco physics simulator. (Todorov was not involved with the current Meta research but did oversee Kumar’s doctoral work some years back.) He says that MyoSuite’s focus on learning general representations means that control strategies can be useful for “a whole family of tasks.” He notes that their generalized control strategies are analogous to the neuroscience principle of muscle synergies, in which the nervous system activates groups of muscles at once to build up to larger gestures, thus reducing the computational burden of movement. “MyoSuite is able to construct such representations from first principles,” Todorov says.

Sep 6, 2023

Self-Replicating Robots and Galactic Domination

Posted by in categories: physics, robotics/AI, space

To check out any of the lectures available from Great Courses Plus go to http://ow.ly/dweH302dILJ

We’ll soon be capable of building self-replicating robots. This will not only change humanity’s future but reshape the galaxy as we know it.

Continue reading “Self-Replicating Robots and Galactic Domination” »

Sep 6, 2023

Major Milestone for Large Hadron Collider

Posted by in category: physics

Experts at Berkeley Lab finished winding more than 2000 kilometers of superconducting wire into cables for new magnets that will help upgrade the Large Hadron Collider and the search for new physics.

Sep 5, 2023

The Missing Link in Cognitive Processing? Scientists Discover Swirling Spirals in the Brain

Posted by in categories: computing, neuroscience, physics

Scientists from the University of Sydney and Fudan University have found human brain signals traveling across the outer layer of neural tissue that naturally arrange themselves to resemble swirling spirals.

Published in the journal Nature Human Behaviour, the study suggests that these widespread spiral patterns, seen during both rest and cognitive activity, play a role in organizing brain function and cognitive processes.

Senior author Associate Professor Pulin Gong, from the School of Physics in the Faculty of Science, said the discovery could have the potential to advance powerful computing machines inspired by the intricate workings of the human brain.

Sep 4, 2023

Physicists solve mysteries of microtubule movers

Posted by in categories: biological, physics, robotics/AI

Active matter is any collection of materials or systems composed of individual units that can move on their own, thanks to self-propulsion or autonomous motion. They can be of any size—think clouds of bacteria in a petri dish, or schools of fish.

Roman Grigoriev is mostly interested in the emergent behaviors in active matter systems made up of units on a molecular scale—tiny systems that convert stored energy into directed motion, consuming energy as they move and exert mechanical force.

“Active matter systems have garnered significant attention in physics, biology, and due to their and potential applications,” Grigoriev, a professor in the School of Physics at Georgia Tech, explains.

Sep 3, 2023

‘Doubly magic’ form of oxygen may challenge a fundamental law of physics

Posted by in category: physics

After scientists created oxygen-28 in the lab, it almost immediately degraded, baffling physicists around the world.

Sep 2, 2023

An AI pilot has beaten three champion drone racers at their own game

Posted by in categories: drones, information science, physics, robotics/AI, space

In what can only bode poorly for our species’ survival during the inevitable robot uprisings, an AI system has once again outperformed the people who trained it. This time, researchers at the University of Zurich in partnership with Intel, pitted their “Swift” AI piloting system against a trio of world champion drone racers — none of whom could best its top time.

Swift is the culmination of years of AI and machine learning research by the University of Zurich. In 2021, the team set an earlier iteration of the flight control algorithm that used a series of external cameras to validate its position in space in real-time, against amateur human pilots, all of whom were easily overmatched in every lap of every race during the test. That result was a milestone in its own right as, previously, self-guided drones relied on simplified physics models to continually calculate their optimum trajectory, which severely lowered their top speed.

This week’s result is another milestone, not just because the AI bested people whose job is to fly drones fast, but because it did so without the cumbersome external camera arrays= of its predecessor. The Swift system “reacts in real time to the data collected by an onboard camera, like the one used by human racers,” an UZH Zurich release reads. It uses an integrated inertial measurement unit to track acceleration and speed while an onboard neural network localizes its position in space using data from the front-facing cameras. All of that data is fed into a central control unit — itself a deep neural network — which crunches through the numbers and devises a shortest/fastest path around the track.

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