16 citations · 34 across the 7 of their papers we have counts for
4 papers · 1 filter
Exploring fixed points and eigenstates of quantum systems with reinforcement learning
María Laura Olivera-Atencio, Jesús Casado-Pascual, Denis Lacroix
We introduce a reinforcement learning algorithm designed to identify the fixed points of a given quantum operation. The method iteratively constructs the unitary transformation tha…
Impact of Amplitude and Phase Damping Noise on Quantum Reinforcement Learning: Challenges and Opportunities
María Laura Olivera-Atencio, Lucas Lamata, Jesús Casado-Pascual
Quantum machine learning (QML) is an emerging field with significant potential, yet it remains highly susceptible to noise, which poses a major challenge to its practical implement…
Benefits of Open Quantum Systems for Quantum Machine Learning
María Laura Olivera-Atencio, Lucas Lamata, Jesús Casado-Pascual
Quantum machine learning is a discipline that holds the promise of revolutionizing data processing and problem-solving. However, dissipation and noise arising from the coupling wit…
Quantum reinforcement learning in the presence of thermal dissipation
M. L. Olivera-Atencio, L. Lamata, M. Morillo +1
A study of the effect of thermal dissipation on quantum reinforcement learning is performed. For this purpose, a nondissipative quantum reinforcement learning protocol is adapted t…