121 citations · 544 across the 25 of their papers we have counts for
6 papers · 2 filters
Engineering non-Markovianity from defect-phonon interactions
Francisco J. González, Diego Tancara, Hossein T. Dinani +2
Understanding defect-phonon interactions in solid-state devices is crucial for improving our current knowledge of quantum platforms. In this work, we develop first-principles calcu…
Kernel-based quantum regressor models learn non-Markovianity
Diego Tancara, Hossein T. Dinani, Ariel Norambuena +2
Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are pa…
Temperature-dependent spin-lattice relaxation of the nitrogen-vacancy spin triplet in diamond
M. C. Cambria, A. Norambuena, H. T. Dinani +8
Spin-lattice relaxation within the nitrogen-vacancy (NV) center's electronic ground-state spin triplet limits its coherence times, and thereby impacts its performance in quantum ap…
Physics-informed neural networks for quantum control
Ariel Norambuena, Marios Mattheakis, Francisco J. González +1
Quantum control is a ubiquitous research field that has enabled physicists to delve into the dynamics and features of quantum systems, delivering powerful applications for various…
Dynamical quantum phase transition in diamond: applications in quantum metrology
Francisco J. González, Ariel Norambuena, Raúl Coto
Nonequilibrium dynamics is a paramount scenario for studying quantum systems. The emergence of new features with no equilibrium counterpart, such as dynamical quantum phase transit…
Estimating the degree of non-Markovianity using variational quantum circuits
Hossein T. Dinani, Diego Tancara, Felipe F. Fanchini +2
Several applications of quantum machine learning (QML) rely on a quantum measurement followed by training algorithms using the measurement outcomes. However, recently developed QML…