The institute, an internal research division of the Simons Foundation, is a community of scientists who are working to use modern computational tools to advance our understanding of science, both through the analysis of large, rich datasets and through the simulations of physical process.
Algorithms made him a Wall Street billionaire. His new research center helps scientists mine data for the common good.
By D. T. Max
A visit to a scientific-research center usually begins at a star professor’s laboratory that is abuzz with a dozen postdocs collaborating on various experiments. But when I recently toured the Flatiron Institute, which formally opened in September, in lower Manhattan, I was taken straight to a computer room. The only sound came from a susurrating climate-control system. I was surrounded by rows of black metal cages outfitted, from floor to ceiling, with black metal shelves filled with black server nodes: boxes with small, twinkling lights and protruding multicolored wires. Tags dangled from some of the wires, notes that the tech staff had written to themselves. I realized that I’d seen a facility like this only in movies. Nick Carriero, one of the directors of what the institute calls its “scientific-computing core,” walked me around the space. He pointed to a cage with empty shelves. “We’re waiting for the quantum-physics people to start showing up,” he said.
The Flatiron Institute, which is in an eleven-story fin-de-siècle building on the corner of Twenty-first Street and Fifth Avenue, is devoted exclusively to computational science—the development and application of algorithms to analyze enormous caches of scientific data. In recent decades, university researchers have become adept at collecting digital information: trillions of base pairs from sequenced human genomes; light measurements from billions of stars. But, because few of these scientists are professional coders, they have often analyzed their hauls with jury-rigged code that has been farmed out to graduate students. The institute’s aim is to help provide top researchers across the scientific spectrum with bespoke algorithms that can detect even the faintest tune in the digital cacophony.
I first visited the Flatiron Institute in June. Although the official opening was still a few months away, the lobby was complete. It had that old-but-new look of expensively renovated interiors; every scratch in the building’s history had been polished away. Near the entrance hangs a Chagall-like painting, “Eve and the Creation of the Universe,” by Aviva Green. Green’s son happened to be spending the year at the institute, as a fellow in astrophysics. “Every day, he walks into the lobby and sees his mother’s picture,” Jim Simons, the institute’s founder, told me.
Simons, a noted mathematician, is also the founder of Renaissance Technologies, one of the world’s largest hedge funds. His income last year was $1.6 billion, the highest in the hedge-fund industry. You might assume that he had to show up every day at Renaissance in order to make that kind of money, but Simons, who is seventy-nine, retired eight years ago from the firm, which he started in the late seventies. His Brobdingnagian compensation is a result of a substantial stake in the company. He told me that, although he has little to do with Renaissance’s day-to-day activities, he occasionally offers ideas. He said, “I gave them one three months ago”—a suggestion for simplifying the historical data behind one of the firm’s trading algorithms. Beyond saying that it didn’t work, he wouldn’t discuss the details—Renaissance’s methods are proprietary and secret—but he did share with me the key to his investing success: he “never overrode the model.” Once he settled on what should happen, he held tight until it did.
The Flatiron Institute can be seen as replicating the structure that Simons established at Renaissance, where he hired researchers to analyze large amounts of data about stocks and other financial instruments, in order to detect previously unseen patterns in their fluctuations. These discoveries gave Simons a conclusive edge. At the Flatiron, a nonprofit enterprise, the goal is to apply Renaissance’s analytical strategies to projects dedicated to expanding knowledge and helping humanity. The institute has three active divisions—computational biology, computational astronomy, and computational quantum physics—and has plans to add a fourth.
Simons works out of a top-floor corner office across the street from the institute, in a building occupied by its administrative parent, the Simons Foundation. We sat down to talk there, in front of a huge painting of a lynx that has killed a hare—a metaphor, I assumed, for his approach to the markets. I was mistaken, Simons said: he liked it, and his wife, Marilyn, did not, so he had removed it from their mansion in East Setauket, on Long Island. (Marilyn, who has a Ph.D. in economics, runs the business side of the foundation, and the institute, from two floors below.) An Archimedes screw that he enjoyed fiddling with sat on a table next to a half-filled ashtray. Simons smokes constantly, even in enclosed conference rooms. He pointed out that, whatever the potential fine for doing so is, he can pay it.
Simons has an air of being both pleased with himself and ready to be pleased by others. He dresses in expensive cabana wear: delicate cotton shirts paired with chinos that are hiked high and held up by an Indian-bead belt. He grew up in the suburbs of Boston, and speaks with the same light Massachusetts accent as Michael Bloomberg, with frequent pauses and imprecisions. He sometimes uses the words “et cetera” instead of finishing a thought, perhaps because he is abstracted, or because he has learned that the intricacies of his mind are not always interesting to others, or because, when you are as rich as Simons, people always wait for you to finish what you are saying.
On a wall, Simons had hung a framed slide from a presentation on the Chern-Simons theory. He helped develop the theory when he was in his early thirties, in collaboration with the famed mathematician Shiing-Shen Chern. The theory captures the subtle properties of three-dimensional spaces—for example, the shape that is left if you cut out a complicated knot. It became a building block of string theory, quantum computing, and condensed-matter physics. “I have to point out, none of these applications ever occurred to me,” he told me. “I do the math, they do the physics.”…
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