Researchers at Tokyo University of Science have introduced a new approach to combinatorial optimisation problems (COPs) via the dual scalable annealing processing system (DSAPS). COPs present challenges in scenarios like shift scheduling and drug development, requiring solutions that are currently time-prohibitive. The Ising machine framework, utilizing magnetic spins and constraints for modeling, can either leverage sparse or fully coupled models. The DSAPS innovatively allows for simultaneous scaling of capacity and precision, offering a significant advancement in the ability to effectively address complex COPs that traditional models struggle with.
The development of the dual scalable annealing processing system (DSAPS) enables simultaneous scaling of both capacity and precision in solving combinatorial optimisation problems.
Researchers from Tokyo University of Science have advanced Ising machine technology, resulting in a novel approach to tackle computationally difficult combinatorial optimisation problems using their DSAPS.
#combinatorial-optimisation #ising-machine #quantum-computing #tokyo-university-of-science #annealing-processors
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