activity
20072025
most citedExistence, uniqueness and approximation of a stochastic Schrödinger equation: the diffusive case

72 citations · 442 across the 37 of their papers we have counts for

collaborators

38 papers

quant-ph2025★ 2 cited

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…

quant-ph2023

A physical noise model for quantum measurements

Faedi Loulidi, Ion Nechita, Clément Pellegrini

In this paper we introduce a novel noise model for quantum measurements motivated by an indirect measurement scheme with faulty preparation. Averaging over random dynamics governin…

math.PR2023

Limit theorems for Quantum Trajectories

Tristan Benoist, Jan-Luka Fatras, Clément Pellegrini

Quantum trajectories are Markov processes modeling the evolution of a quantum system subjected to repeated independent measurements. Under purification and irreducibility assumptio…

math.PR2022

To spike or not to spike: the whims of the Wonham filter in the strong noise regime

Cédric Bernardin, Reda Chhaibi, Joseph Najnudel +1

We study the celebrated Shiryaev-Wonham filter (1964) in its historical setup where the hidden Markov jump process has two states. We are interested in the weak noise regime for th…

quant-ph2022★ 4 cited

The Asymmetric Quantum Cloning Region

Ion Nechita, Clément Pellegrini, Denis Rochette

Quantum cloning is a fundamental protocol of quantum information theory. Perfect universal quantum cloning is prohibited by the laws of quantum mechanics, only imperfect copies bei…

quant-ph2022

Parameter Estimation for Quantum Trajectories: Convergence Result

Maël Bompais, Nina H. Amini, Clément Pellegrini

A quantum trajectory describes the evolution of a quantum system undergoing indirect measurement. In the discrete-time setting, the state of the system is updated by applying Kraus…