251 citations · 942 across the 10 of their papers we have counts for
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Learning Quantum Systems
Valentin Gebhart, Raffaele Santagati, Antonio Andrea Gentile +7
The future development of quantum technologies relies on creating and manipulating quantum systems of increasing complexity, with key applications in computation, simulation and se…
Quantum Model Learning Agent: characterisation of quantum systems through machine learning
Brian Flynn, Antonio Andreas Gentile, Nathan Wiebe +2
Accurate models of real quantum systems are important for investigating their behaviour, yet are difficult to distill empirically. Here, we report an algorithm -- the Quantum Model…
Learning models of quantum systems from experiments
Antonio A. Gentile, Brian Flynn, Sebastian Knauer +6
An isolated system of interacting quantum particles is described by a Hamiltonian operator. Hamiltonian models underpin the study and analysis of physical and chemical processes th…
Magnetic-field-learning using a single electronic spin in diamond with one-photon-readout at room temperature
Raffaele Santagati, Antonio A. Gentile, Sebastian Knauer +11
Nitrogen-vacancy (NV) centres in diamond are appealing nano-scale quantum sensors for temperature, strain, electric fields and, most notably, for magnetic fields. However, the cryo…
Experimental Quantum Hamiltonian Learning
Jianwei Wang, Stefano Paesani, Raffaele Santagati +8
Efficiently characterising quantum systems, verifying operations of quantum devices and validating underpinning physical models, are central challenges for the development of quant…
Experimental Bayesian Quantum Phase Estimation on a Silicon Photonic Chip
Stefano Paesani, Andreas A. Gentile, Raffaele Santagati +5
Quantum phase estimation is a fundamental subroutine in many quantum algorithms, including Shor's factorization algorithm and quantum simulation. However, so far results have cast…