(Protocol) Determining which problems truly demand quantum computation is one of many challenges in the new quantum software business. Quantum algorithms are very different from classical algorithms, and writing them requires people who are adept at the knotty mathematics of quantum physics. That’s why quantum software companies are hiring many employees directly from academia.
Zapata Computing, a 30-person startup in Boston, creates software for quantum computers. But when a customer has a problem it would like to solve, one of Zapata’s first steps is to figure out how much it can avoid using a quantum machine.
When a client wants to model the behavior of a molecule that could become a new drug, Zapata will “divide and conquer” the problem, says its chief technology officer, Yudong Cao. The startup determines which aspects of a molecule’s behavior can be estimated well enough on a standard computer and which ones need the precise new insights of a quantum calculation. A quantum machine might be required only to simulate a tiny portion of a molecule where chemical reactions physically happen.
People who use these quantum algorithms won’t necessarily face such complexity: They will be able to make their queries from standard computers. Zapata, Cambridge Quantum, Microsoft, Google and other creators of quantum algorithms have created compilers: programs that do the nitty-gritty of encoding qubits and reading their outputs. Software developers who want applications to query a quantum computer in the cloud can write code in standard computing languages, such as Python and C++, and a compiler translates it into the steps necessary to make qubits do their thing.

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