Machine learning tagged posts

Artificial Intelligence Reduces a 100,000-equation Quantum Physics problem to only Four Equations

A visualization of a mathematical apparatus used to capture the physics and behavior of electrons moving on a lattice. Each pixel represents a single interaction between two electrons. Until now, accurately capturing the system required around 100,000 equations — one for each pixel. Using machine learning, scientists reduced the problem to just four equations. That means a similar visualization for the compressed version would need just four pixels. Domenico Di Sante/Flatiron Institute

Researchers trained a machine learning tool to capture the physics of electrons moving on a lattice using far fewer equations than would typically be required, all without sacrificing accuracy.

Using artificial intelligence, physicists have compressed a daunting quantum problem that until now requir...

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Machine Learning Generates 3D Model from 2D Pictures

Researchers from the McKelvey School of Engineering at Washington University in St. Louis have developed a machine learning algorithm that can create a continuous 3D model of cells from a partial set of 2D images that were taken using the same standard microscopy tools found in many labs today.

Their findings were published Sept. 16 in the journal Nature Machine Intelligence.

“We train the model on the set of digital images to obtain a continuous representation,” said Ulugbek Kamilov, assistant professor of electrical and systems engineering and of computer science and engineering. “Now, I can show it any way I want. I can zoom in smoothly and there is no pixelation.”

The key to this work was the use of a neural field network, a particular kind of machine learning system that...

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Hey Siri: How much does this Galaxy Cluster Weigh?

It’s been nearly a century since astronomer Fritz Zwicky first calculated the mass of the Coma Cluster, a dense collection of almost 1,000 galaxies located in the nearby universe. But estimating the mass of something so huge and dense, not to mention 320 million light-years away, has its share of problems—then and now. Zwicky’s initial measurements, and the many made since, are plagued by sources of error that bias the mass higher or lower.

Now, using tools from machine learning, a team led by Carnegie Mellon University physicists has developed a deeplearning method that accurately estimates the mass of the Coma Cluster and effectively mitigates the sources of error.

“People have made mass estimates of the Coma Cluster for many, many years...

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AI reveals unsuspected Math underlying Search for Exoplanets

chart explaining gravitational microlensing
This infographic explains the light curve astronomers detect when viewing a microlensing event, and the signature of an exoplanet: an additional uptick in brightness when the exoplanet lenses the background star. (Image Credit: NASA / ESA / K. Sahu / STScI)

Artificial intelligence (AI) algorithms trained on real astronomical observations now outperform astronomers in sifting through massive amounts of data to find new exploding stars, identify new types of galaxies and detect the mergers of massive stars, accelerating the rate of new discovery in the world’s oldest science.

But AI, also called machine learning, can reveal something deeper, University of California, Berkeley, astronomers found: Unsuspected connections hidden in the complex mathematics arising from general relativity—...

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