This line is devoted to the study of the theoretical and practical foundations of quantum computation, including algorithm design and hardware-level noise mitigation. At its core lies the goal of building architectures and methods that protect quantum information against decoherence and other errors, using advanced techniques in error correction and dynamical control. It spans the dynamics of individual quantum systems and the control of trajectories that avoid information loss, as well as algorithms for solving partial differential equations, constructive methods based on block encoding, and hybrid digital–analog and machine-learning approaches. Together, this research line aim to develop tools for assessing algorithm performance in the NISQ era and to extend their applicability to more realistic physical scenarios, moving towards scalable and robust quantum computation.
