Closing the divide between theoretical and practical quantum computation


Implementing Business Use Cases

Optimization is challenging because the problem sizes scale exponentially with the number of independent variables. The well-known Traveling Salesman Problem, in which one determines the shortest possible route via multiple cities, is notoriously difficult: even with just ten cities there are 362,880 possible combinations.

Solving combinatorial and discrete optimization problems is hard (and often intractable) for classical computers, and so today, practitioners commonly employ heuristics to yield approximate solutions. Because many of these optimization challenges are directly tied to the economics of business operations, better heuristics could translate to significant resource and economic savings.

Quantinuum develops quantum-based heuristics, enabling fast and accurate convergence to optimal solutions on real quantum computers. We have innovated methods to scale up those heuristics, paving the way for solving problems of realistic sizes and practical relevance on today’s quantum computers.

Finding New Solutions

As the quantum computers improve, the ability to solve real-world business problems grows.