 The proposed method solves the unstructured search problem in constant time by using a non-linearity of the Gross-Bitevsky type and jointly optimizing resource requirements, resulting in an overall scaling of n-1-quarter, which is a significant improvement over Grover's algorithm's n-1-half scaling. This result leads to a quantum information theoretic lower bound on the number of particles needed for the multi-particle, linear, scroting a equation approximation to hold, asymptotically. This article was authored by David A. Meier and Thomas G. Wong.