General Quantum Meet-in-the-Middle Search Algorithm Based on Target Solution of Fixed Weight

摘要

Similar to the classical meet-in-the-middle algorithm,the storage and computation complexity are the key factors that decide the efficiency of the quantum meet-in-the-middle algorithm.Aiming at the target vector of fixed weight,based on the quantum meet-in-the-middle algorithm,the algorithm for searching all n-product vectors with the same weight is presented,whose complexity is better than the exhaustive search algorithm.And the algorithm can reduce the storage complexity of the quantum meet-in-the-middle search algorithm.Then based on the algorithm and the knapsack vector of the Chor-Rivest public-key crypto of fixed weight d,we present a general quantum meet-in-th√e-middle search algorithm based on the target solution of fixed weight,whose computational complexity is∑(d to j=0)(O((1/2)(C^(d-j)_(n-k+1))+O(C^j_klog C^j_k))with∑(d to i=0)C^i_k memory cost.And the optimal value of k is given.Compared to thequantum meet-in-the-middle search algorithm for knapsack problem and the quantum algorithm for searching a target solution of fixed weight,the computational complexity of the algorithm is lower.And its storage complexity is smaller than the quantum meet-in-the-middle-algorithm.