7 citations · 17 across the 6 of their papers we have counts for
6 papers
Variational Dynamics of Open Quantum Spin Systems in Phase Space
Jacopo Tosca, Zejian Li, Francesco Carnazza +1
We introduce a variational method for simulating the dynamics of interacting open quantum spin systems. The method is based on the spin phase-space representation and variationally…
Detecting nonequilibrium phase transitions via continuous monitoring of space-time trajectories and autoencoder-based clustering
Erik Fitzner, Francesco Carnazza, Federico Carollo +1
The characterization of collective behavior and nonequilibrium phase transitions in quantum systems is typically rooted in the analysis of suitable system observables, so-called or…
Variational Multi-Gaussian Phase-Space Dynamics via Automatic Differentiation
Jacopo Tosca, Francesco Carnazza, Luca Giacomelli +1
We introduce a variational method for simulating the dynamics of interacting open quantum bosonic systems deep in the quantum regime. The method is based on a multi-dimensional Wig…
Machine learning stochastic differential equations for the evolution of order parameters of classical many-body systems in and out of equilibrium
Francesco Carnazza, Federico Carollo, Sabine Andergassen +3
We develop a machine learning algorithm to infer the emergent stochastic equation governing the evolution of an order parameter of a many-body system. We train our neural network t…
Inferring interpretable dynamical generators of local quantum observables from projective measurements through machine learning
Giovanni Cemin, Francesco Carnazza, Sabine Andergassen +3
To characterize the dynamical behavior of many-body quantum systems, one is usually interested in the evolution of so-called order-parameters rather than in characterizing the full…
Inferring Markovian quantum master equations of few-body observables in interacting spin chains
Francesco Carnazza, Federico Carollo, Dominik Zietlow +3
Full information about a many-body quantum system is usually out-of-reach due to the exponential growth -- with the size of the system -- of the number of parameters needed to enco…