4 papers
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…
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, Álvaro 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…
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…