5 papers
Quantum Bayesian Networks Can Speed up Reinforcement Learning in Partially Observable Environments
Gilberto Cunha, Alexandra Ramôa, André Sequeira +2
Reinforcement learning (RL) provides a principled framework for decision-making in partially observable environments, which can be modeled as Markov decision processes and compactl…
Bayesian Quantum Amplitude Estimation
Alexandra Ramôa, Luis Paulo Santos
We present BAE, a problem-tailored and noise-aware Bayesian algorithm for quantum amplitude estimation. In a fault tolerant scenario, BAE is capable of saturating the Heisenberg li…
Low Cost Bayesian Experimental Design for Quantum Frequency Estimation with Decoherence
Alexandra Ramôa, LuÃs Paulo Santos, Akihito Soeda
A two-level quantum system evolving under a time-independent Hamiltonian produces oscillatory measurement probabilities. The estimation of the associated frequency is a cornerstone…
Calibration of Quantum Devices via Robust Statistical Methods
Alexandra Ramôa, Raffaele Santagati, Nathan Wiebe
Bayesian inference is a widely used technique for real-time characterization of quantum systems. It excels in experimental characterization in the low data regime, and when the mea…
Learning the physics of open quantum systems from experiments
Alexandra Ramôa
This thesis explores adaptive inference as a tool to characterize quantum systems using experimental data, with applications in sensing, calibration, control, and metrology. I prop…