- Università di Trento
Monday, February 25, 2019
Quantum annealers (QA) are specialized quantum computers that minimize objective functions over discrete variables by physically exploiting quantum effects. Current QA platforms allow for the optimization of quadratic objectives defined over binary variables, that is, they solve quadratic unconstrained binary optimization (QUBO) problems. In the last decade, QA systems as implemented by D-Wave have scaled with Moore-like growth. Current architectures provide 2048 sparsely-connected qubits, and continued exponential growth is anticipated.
In this talk we first present a brief introduction to D-Wave's QAs, given from a computer science perspective, and to our collaboration with D-Wave. Then we present recently-published work in collaboration with D-Wave, in which we explore the feasibility of such architectures for solving SAT and MaxSAT problems as QA systems scale. We develop techniques for effectively encoding SAT and MaxSAT into QUBO compatible with sparse QA architectures. We provide the theoretical foundations for this mapping, and present encoding techniques that combine offline Satisfiability and Optimization Modulo Theories with on-the-fly placement and routing. Preliminary empirical tests on a current generation 2048-qubit D-Wave system support the feasibility of the approach. We will complete the presentation by discussing some features of the novel D-Wave Pegasus architecture, under development.
Contact Person: Lorenzo Bottarelli
- Programme Director
- Publication date
January 24, 2019