2 citations · 2 across the 3 of their papers we have counts for
3 papers
Nearly optimal algorithms to learn sparse quantum Hamiltonians in physically motivated distances
Amira Abbas, Nunzia Cerrato, Francisco Escudero Gutiérrez +3
We study the problem of learning Hamiltonians that are -sparse in the Pauli basis, given access to their time evolution. Although Hamiltonian learning has been extensively i…
Statistical Characterization of Entanglement Degradation Under Markovian Noise in Composite Quantum Systems
Nunzia Cerrato, Sauro Succi, Giacomo De Palma +1
Understanding how noise degrades entanglement is crucial for the development of reliable quantum technologies. While the Markovian approximation simplifies the analysis of noise, i…
Entanglement Degradation in the Presence of Markovian Noise: a Statistical Analysis
Nunzia Cerrato, Giacomo De Palma, Vittorio Giovannetti
Adopting a statistical approach we study the degradation of entanglement of a quantum system under the action of an ensemble of randomly distributed Markovian noise. This enables u…