Previously, scientists would have to convert non-Boolean problems such as this into ones with Boolean outputs.
“You’d set a threshold and say any state below this threshold is bad, and any state above this threshold is good,” Shyamsundar said. In our jazz record example, that would be the equivalent of saying anything rated between 1 and 5 isn’t jazz, while anything between 5 and 10 is.
But Shyamsundar has extended this computation such that a Boolean conversion is no longer necessary. He calls this new technique the non-Boolean quantum amplitude amplification algorithm.
“If a problem requires a yes-or-no answer, the new algorithm is identical to the previous one,” Shyamsundar said. “But this now becomes open to more tasks; there are a lot of problems that can be solved more naturally in terms of a score rather than a yes-or-no output.”
A second algorithm introduced in the paper, dubbed the quantum mean estimation algorithm, allows scientists to estimate the average rating of all the records. In other words, it can assess how “jazzy” the stack is as a whole.
Both algorithms do away with having to reduce scenarios into computations with only two types of output, and instead allow for a range of outputs to more accurately characterize information with a quantum speedup over classical computing methods.
Procedures like these may seem primitive and abstract, but they build an essential foundation for more complex and useful tasks in the quantum future. Within physics, the newly introduced algorithms may eventually allow scientists to reach target sensitivities