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  • The founding team of Zapata Computing
  • Courtesy Zapata Computing
  • Intelligent Machines

    The world’s first quantum software superstore—or so it hopes—is here

    Zapata Computing plans to build the algorithms for companies that want to experiment with quantum computers.

    In quantum computing, it’s not just the computers themselves that are hard to build. They also need sophisticated quantum algorithms—specialized software that’s tailored to get the best out of the machines.

    Alán Aspuru-Guzik has gained an impressive reputation in academic circles by developing these kinds of algorithms, and now he’s taking them to a wider market. A Harvard University professor (who’s moving to the University of Toronto) and a 2010 member of MIT Technology Review’s Innovators under 35 list, he is the cofounder of a company called Zapata Computing, which launched today with $5.4 million in announced funding. Zapata’s ultimate goal is to be a kind of quantum-algorithm superstore, offering a broad range of ready-made software that companies can use to tap the immense processing power quantum computers promise to deliver. 

    Since the field of quantum computing is so new, only a small band of experts today can create advanced software that will work on the machines. Essentially, Zapata wants companies to be able to use the technology without needing an in-house quantum specialist. 

    The excitement around quantum computers stems from the fact that instead of digital bits, which represent either 1 or 0, they use “qubits,” which can be in both states at once thanks to a phenomenon known as superposition. Another almost mystical quality, called entanglement, means that qubits can influence one another even if they’re not physically connected. 

    Adding extra qubits affords an exponential increase in the computing power of quantum machines, which may soon be able to outperform even the top supercomputers at a limited range of tasks. That’s the good news; the not-so-good news is that qubits tend to lose their delicate quantum state after mere milliseconds. Changes in temperature, or even the tiniest of vibrations, can also disrupt them and throw errors into their calculations (see “Google thinks it’s close to quantum supremacy. Here’s what that really means”).

    This is where quantum algorithms come in. They run a specific calculation on a quantum machine as quickly and efficiently as possible, and they can often help mitigate errors. “Think of it like tuning a guitar,” says Aspuru-Guzik. “Just as you adjust the strings so they’re in harmony, we can play with various parameters until a quantum circuit is tuned for a particular application.” 

    Zapata has already negotiated an exclusive license with Harvard to the algorithms Aspuru-Guzik and his team developed there. The company’s goal, says Zapata CEO Chris Savoie, is to develop algorithms for a range of computers, and Aspuru-Guzik and his team have already been working with big quantum hardware makers like IBM and Google, as well as with smaller ones like Rigetti Computing and IonQ. These firms are also working on their own algorithms, but the view is that more software innovation is good for the nascent market. “This is where you want to see a lot of different ideas fill out the space,” says Jerry Chow, who heads IBM’s experimental quantum computing effort. 

    If its strategy works, Zapata could end up with a bird’s-eye view of how various applications perform on a wide range of quantum computers, giving it a big advantage in the market. Still, it’s unclear whether quantum computing is going to make a difference in some areas, such as machine learning—though there are some early signs it might. So it may take quite some time to build up a broad portfolio of algorithms.

    In the short term, Zapata plans to focus mainly on algorithms for chemistry and materials. Aspuru-Guzik has pioneered methods for modeling molecules, a notoriously difficult task even with today’s best supercomputers, and there’s hope that quantum computers will soon be able to turbocharge such simulations. That could lead to advances such as more efficient batteries and new light-emitting molecules for displays. A team at IBM has already used a quantum machine to model a small molecule made of three atoms, and some researchers have wondered about combining quantum circuits with dueling neural networks in an effort to dream up new molecules. 

    Zapata’s financial backers, which include Pillar VC and The Engine, an MIT fund that invests in companies working on “tough technologies,” are betting that more applications for quantum computing will eventually open up—and that there’ll still be too few researchers who can create the sophisticated algorithms needed. Reed Sturtevant of The Engine thinks there are “less than a hundred” of these researchers worldwide today, and Aspuru-Guzik and four former members of his research group, who are also joining him and Savoie as cofounders, are among them. If Sturtevant is right, Zapata’s talent grab could lead to a quantum leap in its future profits.

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