Revision as of 10:18, 30 December 2016 edit Danawr (talk \| contribs) 68 edits ←Created page with '==Semidefinite Programming== * SDP has wide range applications, problems are scaling so it's important to find more efficient ways to solve them. * The SDP pro...'		Revision as of 12:31, 30 December 2016 edit undo Danawr (talk \| contribs) 68 edits No edit summary Next edit →
Line 6: Input format Output format The quantum algorithm reduces the problem to a [[~~feasibility~~Mathematical optimization#Feasibility problem \| Feasibility problem]], performing a binary search on the solution. One algorithm ~~run~~iteration can either output a feasible solution with an objective smaller than some value, or indicate that the optimal objective is larger than an other value, when these values are determined by chosen input parameters. Therefore, it can be run again with different parameters, binary searching the optimal objective value and solution. The algorithm takes use in a [[Gibbs sampling \|Gibbs sampler]], as a probabilistic oracle for estimating

Quantum optimization algorithms: Difference between revisions