From the 1 of 9 linked papers with an AI index.
9 papers
Quantum model reduction based on Oja's flow
Miguel Casanova, Kentaro Ohki, Francesco Ticozzi
The paper introduces two non‑perturbative algorithms based on Oja's continuous‑time principal component flow to obtain reduced dynamical models for Markovian open quantum systems,…
Reconstructing Quantum States and Expectations via Dynamical Tomography
Marco Peruzzo, Tommaso Grigoletto, Francesco Ticozzi
When the dynamics of a quantum system of interest is known, an informationally-complete set of observables is not needed for state reconstruction via tomographic techniques: lettin…
Context-Selective State Space Models: Feedback is All You Need
Riccardo Zattra, Giacomo Baggio, Umberto Casti +2
Transformers, powered by the attention mechanism, are the backbone of most foundation models, yet they suffer from quadratic complexity and difficulties in dealing with long-range…
Robust, positive and exact model reduction via monotone matrices
Marco Cortese, Tommaso Grigoletto, Francesco Ticozzi +1
This work focuses on the problem of exact model reduction of positive linear systems, by leveraging minimal realization theory. While determining the existence of a positive reacha…
Quantum model reduction for continuous-time quantum filters
Tommaso Grigoletto, Clément Pellegrini, Francesco Ticozzi
The use of quantum stochastic models is widespread in dynamical reduction, simulation of open systems, feedback control and adaptive estimation. In many applications only part of t…
Obtaining Structural Network Controllability with Higher-Order Local Dynamics
Marco Peruzzo, Giacomo Baggio, Francesco Ticozzi
We consider a network of identical, first-order linear systems, and investigate how replacing a subset of the systems composing the network with higher-order ones, either taken to…