Solving low-density multiple subset sum problems with SVP oracle

It is well known that almost all subset sum problems with density less than 0.9408 ··· can be solved in polynomial time with an SVP oracle that can find a shortest vector in a special lattice. In this paper, the authors show that a similar result holds for the k-multiple subset sum problem which has k subset sum problems with exactly the same solution. Specially, for the single subset sum problem (k = 1), a modified lattice is introduced to make the proposed analysis much simpler and the bound for the success probability tighter than before. Moreover, some extended versions of the multiple subset sum problem are also considered.