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A theorem for coloring a large class of “perfect” mathematical networks could ease the way for a long-sought general coloring proof.

A major advance in computational complexity reveals deep connections between the classes of problems that computers can — and can’t — possibly do.

New research suggests physicists, computers and brains employ the same procedure to tease out important features from among other irrelevant bits of data.

Subhash Khot’s bold conjecture is helping mathematicians explore the precise limits of computation.

Machine learning techniques are helping scientists pinpoint the mutations that allow bird and pig viruses to infect humans.

Studies show that computer models called “neural networks” behave strikingly similar to actual brains when performing certain tasks, suggesting the two may learn in the same way.

An infinitesimal advance in the traveling salesman problem breathes new life into the search for improved approximate solutions.

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