Linear algebra

Tensors are used all over math and science to reveal hidden geometric truths. What are they?

By eliminating a hidden inefficiency, computer scientists have come up with a new way to multiply large matrices that’s faster than ever.

Terence Tao, who has been called the “Mozart of Mathematics,” wrote an essay in 2007 about the common ingredients in “good” mathematical research. In this episode, the Fields Medalist joins Steven Strogatz to revisit the topic.

Integer linear programming can help find the answer to a variety of real-world problems. Now researchers have found a much faster way to do it.

Inspired by the results of a game-playing neural network, mathematicians have been making unexpected advances on an age-old math problem.

The mathematician Federico Ardila takes a creative approach to the search for useful answers hiding among inconceivably huge numbers of possible ones.

A recent paper set the fastest record for multiplying two matrices. But it also marks the end of the line for a method researchers have relied on for decades to make improvements.

By harnessing randomness, a new algorithm achieves a fundamentally novel — and faster — way of performing one of the most basic computations in math and computer science.

A landmark proof in computer science has also solved an important problem called the Connes embedding conjecture. Mathematicians are working to understand it.