9 citations · 9 across the 3 of their papers we have counts for
5 papers
Efficient Hamiltonian, structure and trace distance learning of Gaussian states
Marco Fanizza, Cambyse Rouzé, Daniel Stilck França
In this work, we initiate the study of Hamiltonian learning for positive temperature bosonic Gaussian states, the quantum generalization of the widely studied problem of learning G…
Efficient thermalization and universal quantum computing with quantum Gibbs samplers
Cambyse Rouzé, Daniel Stilck França, Ãlvaro M. Alhambra
The preparation of thermal states of matter is a crucial task in quantum simulation. In this work, we prove that a recently introduced, efficiently implementable dissipative evolut…
Sampling (noisy) quantum circuits through randomized rounding
Victor Martinez, Omar Fawzi, Daniel Stilck França
The present era of quantum processors with hundreds to thousands of noisy qubits has sparked interest in understanding the computational power of these devices and how to leverage…
Information-theoretic generalization bounds for learning from quantum data
Matthias Caro, Tom Gur, Cambyse Rouzé +2
Learning tasks play an increasingly prominent role in quantum information and computation. They range from fundamental problems such as state discrimination and metrology over the…
Learning quantum many-body systems from a few copies
Cambyse Rouzé, Daniel Stilck França
Estimating physical properties of quantum states from measurements is one of the most fundamental tasks in quantum science. In this work, we identify conditions on states under whi…