An efficient quantum algorithm for lattice problems achieving subexponential approximation factor (2201.13450v1)

Abstract: We give a quantum algorithm for solving the Bounded Distance Decoding (BDD) problem with a subexponential approximation factor on a class of integer lattices. The quantum algorithm uses a well-known but challenging-to-use quantum state on lattices as a type of approximate quantum eigenvector to randomly self-reduce the BDD instance to a random BDD instance which is solvable classically. The running time of the quantum algorithm is polynomial for one range of approximation factors and subexponential time for a second range of approximation factors. The subclass of lattices we study has a natural description in terms of the lattice's periodicity and finite abelian group rank. This view makes for a clean quantum algorithm in terms of finite abelian groups, uses very relatively little from lattice theory, and suggests exploring approximation algorithms for lattice problems in parameters other than dimension alone. A talk on this paper sparked many lively discussions and resulted in a new classical algorithm matching part of our result. We leave it as a challenge to give a classcial algorithm matching the general case.