Quantum Technologies and Optimal Control

Theoretical research in quantum physics is necessary for the development of applications capable of bringing quantum technologies out of the laboratory.

The central objectives of this line of research include: understanding the energy structure and temporal dynamics of quantum systems; developing constructive approaches for error correction through analytical and numerical tools; and studying methods for autonomous learning of interactions with quantum systems that are difficult to simulate.

To this end, optimal control and machine learning protocols are being developed and applied in two possible directions. The first consists of developing control strategies to suppress interaction with the environment, as it occurs in high-fidelity gates in quantum computing; the second consists of using small quantum systems (sensors) capable of providing relevant information about the environment through observation of their dynamics.

Furthermore, using analog or digital quantum simulators, it is possible to reproduce many-body phenomena beyond the traditional limits of 'natural' systems. The achievement of new 'on-demand' phases is of primary interest not only for fundamental questions concerning the field of condensed matter and quantum information, but also to respond to the growing interest in applications of quantum technologies.