Descripció del projecte
From the greatest intellectual challenges to the most mundane problems, an entire series of problems require, not only finding a solution to them, but also finding the best ones, in a process called optimization. In the search for ever more complete and efficient solutions to increasingly demanding and complex problems, new areas of knowledge have emerged, such as Machine Learning or Artificial Intelligence, fields in which many of the implemented algorithms can end up being reduced to optimization problems.
These problems are currently being implemented and solved by extremely powerful computers; however, the physics underlying these computers is not effective in solving optimization problems. In contrast, there are other physical systems whose behavior turns them into ideal candidates as efficient platforms for the solution of optimization problems.
In this project, the PhD candidate will study the utility of some physical systems as the foundation for new computing platforms, with a special focus on systems employing randomized trials with quantum random number generators. At the same time, the PhD candidate will implement novel optimization algorithms, which take into consideration the internal architecture of these innovative computing platforms.
