Assessing Solution Quality of 3SAT on a Quantum Annealing Platform When solving propositional logic satisfiability (specifically 3SAT) using quantum annealing, we analyze the effect the difficulty of different instances of the problem has on the quality of the answer returned by the quantum annealer. A highquality response from the annealer in this case is defined by a high percentage of correct solutions among the returned answers. We show that the phase transition regarding the computational complexity of the problem, which is wellknown to occur for 3SAT on classical machines (where it causes a detrimental increase in runtime), persists in some form (but possibly to a lesser extent) for quantum annealing.

AmoebaInspired Hardware SAT Solver with Effective Feedback Control In this paper, we focus on an amoebainspired algorithm, AmoebaSAT, to solve Boolean satisfiability (SAT) problems. A hardware SAT solver is useful for a variety of control applications in InternetofThings edgecomputing systems whose control constraints can be reduced to a SAT problem. We develop efficient AmoebaSAT solvers on an FPGA by realizing various feedback controls to find a solution quickly. To extract the inherent parallelism of the AmoebaSAT, a highlevel design approach (i.e., highlevel synthesis and its pragmas) is applied together with hardwarefriendly code transformationsalgorithmic extensions. We demonstrate that our FPGAbased AmoebaSAT solvers can achieve significant iterations reduction and speedup to find a solution compared with stateoftheart SAT solvers. Furthermore, we show the effectiveness of our work in the scalability (i.e., resource utilization in FPGA) and the parallelism.