5 papers
Nonlocal Monte Carlo via Reinforcement Learning
Dmitrii Dobrynin, Masoud Mohseni, John Paul Strachan
Optimizing or sampling complex cost functions of combinatorial optimization problems is a longstanding challenge across disciplines and applications. When employing family of conve…
Hardware-Compatible Single-Shot Feasible-Space Heuristics for Solving the Quadratic Assignment Problem
Haesol Im, Chan-Woo Yang, Moslem Noori +10
Research into the development of special-purpose computing architectures designed to solve quadratic unconstrained binary optimization (QUBO) problems has flourished in recent year…
Compressed-sensing Lindbladian quantum tomography with trapped ions
Dmitrii Dobrynin, Lorenzo Cardarelli, Markus Müller +1
Characterizing the dynamics of quantum systems is a central task for the development of quantum information processors (QIPs). It serves to benchmark different devices, learn about…
Energy landscapes of combinatorial optimization in Ising machines
Dmitrii Dobrynin, Adrien Renaudineau, Mohammad Hizzani +3
Physics-based Ising machines (IM) have been developed as dedicated processors for solving hard combinatorial optimization problems with higher speed and better energy efficiency. G…
Memristor-based hardware and algorithms for higher-order Hopfield optimization solver outperforming quadratic Ising machines
Mohammad Hizzani, Arne Heittmann, George Hutchinson +6
Ising solvers offer a promising physics-based approach to tackle the challenging class of combinatorial optimization problems. However, typical solvers operate in a quadratic energ…