Quantum Modeling

We present a modification of Simon’s Algorithm 2 that in some cases is able to fit experimentally obtained data to appropriately chosen trial functions with high probability. Modulo constants pertaining to the reliability and probability of success of the algorithm, the algorithm runs using only O(polylog(|Y |)) queries to the quantum database and O(polylog(|X |, |Y |)) elementary quantum gates where |X | is the size of the experimental data set and |Y | is the size of the parameter space. We discuss heuristics for good performance, analyze the performance of the algorithm in the case of linear regression, both one-dimensional and multidimensional, and outline the algorithm’s limitations.