Title :
Quantum computation and lattice problems
Author_Institution :
Inst. for Adv. Study, Princeton, NJ, USA
Abstract :
We present the first explicit connection between quantum computation and lattice problems. Namely, we show a solution to the unique shortest vector problem (SVP) under the assumption that there exists an algorithm that solves the hidden subgroup problem on the dihedral group by coset sampling. Moreover, we solve the hidden subgroup problem on the dihedral group by using an average case subset sum routine. By combining the two results, we get a quantum reduction from Θ˜(n2.5)-unique-SVP to the average case subset sum problem. This is a better connection than the known classical results.
Keywords :
computational complexity; group theory; lattice theory; quantum computing; average case subset sum routine; coset sampling; dihedral group; hidden subgroup problem; lattice problems; quantum computation; quantum reduction; unique shortest vector problem; Application software; Computational modeling; Cryptography; Lattices; Pervasive computing; Physics computing; Polynomials; Quantum computing; Sampling methods; Vectors;
Conference_Titel :
Foundations of Computer Science, 2002. Proceedings. The 43rd Annual IEEE Symposium on
Print_ISBN :
0-7695-1822-2
DOI :
10.1109/SFCS.2002.1181976