White Paper Quantum future – quantum present

The idea that we might ever achieve optimal solutions to various problems in society and business was seemingly getting away from us. Operations and processes connected over the internet lead to an ever-increasing thirst for automation, machine intelligence, and cloud computing, to name a few possibilities. And while greater connectivity opens up a new horizon of possibilities, it also generates a corresponding growth in complexity. While classical computing-based solutions have been able to contribute immensely to this growth, there are limitations when it comes to specific complex, large-scale so-called ‘combinatorial optimization’ problems – which we will define and explain in this paper.

Using classical computers to find the optimum sequence in a process that drives out inefficiencies and improves productivity is possible when the number of variables is limited. However, when the process involves too many variables, they cannot reach an accurate answer by evaluating all possibilities fast enough and accurately enough to gain any practical benefit. The total cost, energy, and time required would be unfeasible, as traditional computers, even supercomputers, are reaching their limits. This is primarily because the fundamental property of a traditional computing processor is based on sequential processing.

White Paper Quantum future – quantum present