‘In 2008, Daniel Spielman told his Yale University colleague Gil Kalai about a computer science problem he was working on, concerning how to “sparsify” a network so that it has fewer connections between nodes but still preserves the essential features of the original network.
Network sparsification has applications in data compression and efficient computation, but Spielman’s particular problem suggested something different to Kalai. It seemed connected to the famous Kadison-Singer problem, a question about the foundations of quantum physics that had remained unsolved for almost 50 years.
Over the decades, the Kadison-Singer problem had wormed its way into a dozen distant areas of mathematics and engineering, but no one seemed to be able to crack it. The question “defied the best efforts of some of the most talented mathematicians of the last 50 years,” wrote Peter Casazza and Janet Tremain of the University of Missouri in Columbia, in a 2014 survey article.
As a computer scientist, Spielman knew little of quantum mechanics or the Kadison-Singer problem’s allied mathematical field, called C*-algebras. But when Kalai, whose main institution is the Hebrew University of Jerusalem, described one of the problem’s many equivalent formulations, Spielman realized that he himself might be in the perfect position to solve it. “It seemed so natural, so central to the kinds of things I think about,” he said. “I thought, ‘I’ve got to be able to prove that.’” He guessed that the problem might take him a few weeks.
Instead, it took him five years. In 2013, working with his postdoc Adam Marcus, now at Princeton University, and his graduate student Nikhil Srivastava, now at the University of California, Berkeley, Spielman finally succeeded. Word spread quickly through the mathematics community that one of the paramount problems in C*-algebras and a host of other fields had been solved by three outsiders — computer scientists who had barely a nodding acquaintance with the disciplines at the heart of the problem.
Mathematicians in these disciplines greeted the news with a combination of delight and hand-wringing. The solution, which Casazza and Tremain called “a major achievement of our time,” defied expectations about how the problem would be solved and seemed bafflingly foreign. Over the past two years, the experts in the Kadison-Singer problem have had to work hard to assimilate the ideas of the proof. Spielman, Marcus and Srivastava “brought a bunch of tools into this problem that none of us had ever heard of,” Casazza said. “A lot of us loved this problem and were dying to see it solved, and we had a lot of trouble understanding how they solved it.”
“The people who have the deep intuition about why these methods work are not the people who have been working on these problems for a long time,” said Terence Tao, of the University of California, Los Angeles, who has been following these developments. Mathematicians have held several workshops to unite these disparate camps, but the proof may take several more years to digest, Tao said. “We don’t have the manual for this magic tool yet.”
Computer scientists, however, have been quick to exploit the new techniques. Last year, for instance, two researchers parlayed these tools into a major leap forward in understanding the famously difficult traveling salesman problem. There are certain to be more such advances, said Assaf Naor, a mathematician at Princeton who works in areas related to the Kadison-Singer problem. “This is too profound to not have many more applications.”‘
H/T Geek Press.