ANNEALING-BASED ALGORITHM FOR SOLVING CVP AND SVP

Inspired by quantum annealing, digital annealing computers specified for computations have been realized on a large scale, such as the Digital Annealer (DA) developed Fujitsu and CMOS Annealing Machine Hitachi. With progress achieved using these computers, it has become necessary to estimate computational hardness of cryptographic problems. This paper focuses lattice problems, closest vector problem (CVP) shortest (SVP), which are class optimization These problems form basis security lattice-based cryptography, is prime candidate NIST post-quantum cryptography standardization. For we propose methods generating an Ising model solving with bit representation input, represents encodings map each integer variable in SVP into binary variables. We two SVPs, basic method variant incorporating approximately concept classical enumeration. In our experimental results obtained second-generation DA, succeeded finding nonzero 40- 45-dimensional lattices Darmstadt Challenge. The hybrid was fastest among representation, expected running time estimated 664 13,750 seconds lattices, respectively. provide benchmark computers.