Detalle

Among them, those using the quantum annealing approach and those based on the use of variational circuits stand out. In this course, the quantum circuit model will be introduced, with special attention to the quantum gates needed to build variational circuits, as well as the quantum annealing method. Both models will be used to show concrete applications in the field of optimization and quantum machine learning, including the construction of approximate solutions of combinatorial optimization problems (using quantum annealing and circuit-based algorithms such as the Variational Quantum Eigensolver and the Quantum Approximate Optimization Algorithm), the development of classification algorithms (Quantum Support Vector Machines, Quantum Neural Networks...), the creation of generative models (Quantum Generative Adversarial Networks) and reinforced learning.