From the 1 of 393 papers with an AI index.
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- Scuola Internazionale Superiore di Studi AvanzatiIT103 papers
- University of TriesteIT97 papers
- Elettra-Sincrotrone Trieste S.C.p.A.IT93 papers
- The Abdus Salam International Centre for Theoretical Physics (ICTP)IT71 papers
- Centre National de la Recherche ScientifiqueFR64 papers
- Istituto Officina dei MaterialiIT57 papers
- Scuola Normale SuperioreIT34 papers
- Istituto NanoscienzeIT33 papers
- Sapienza University of RomeIT32 papers
- Istituto Nazionale di Fisica Nucleare, Sezione di TriesteIT24 papers
- National Enterprise for NanoScience and NanoTechnologyIT23 papers
- University of FlorenceIT23 papers
5 papers · 2 filters
Information flow and error scaling for fully-quantum control
Stefano Gherardini, Matthias M. Müller, Simone Montangero +2
The optimally designed control of quantum systems is playing an increasingly important role to engineer novel and more efficient quantum technologies. Here, in the scenario represe…
Thermalization processes induced by quantum monitoring in multi-level systems
Stefano Gherardini, Guido Giachetti, Stefano Ruffo +1
We study the heat statistics of a multi-level -dimensional quantum system monitored by a sequence of projective measurements. The late-time, asymptotic properties of the heat ch…
Mutual information for fermionic systems
Luca Lepori, Simone Paganelli, Fabio Franchini +1
We study the behavior of the mutual information (MI) in various quadratic fermionic chains, with and without pairing terms and both with short- and long-range hoppings. The models…
Information Theoretical Limits for Quantum Optimal Control Solutions: Error Scaling of Noisy Channels
Matthias M. Müller, Stefano Gherardini, Tommaso Calarco +2
Accurate manipulations of an open quantum system require a deep knowledge of its controllability properties and the information content of the implemented control fields. By using…
Reinforcement Learning assisted Quantum Optimization
Matteo M. Wauters, Emanuele Panizon, Glen B. Mbeng +1
We propose a reinforcement learning (RL) scheme for feedback quantum control within the quan-tum approximate optimization algorithm (QAOA). QAOA requires a variational minimization…