Asymptotic stochastic transformations for nonlinear quantum dynamical systems
نویسندگان
چکیده
منابع مشابه
Quantum Dynamical Entropies for Classical Stochastic Systems
We compare two proposals for the dynamical entropy of quantum deterministic systems (CNT and AFL) by studying their extensions to classical stochastic systems. We show that the natural measurement procedure leads to a simple explicit expression for the stochastic dynamical entropy with a clear informationtheoretical interpretation. Finally, we compare our construction with other recent proposals.
متن کاملMultistage Modified Sinc Method for Solving Nonlinear Dynamical Systems
The sinc method is known as an ecient numerical method for solving ordinary or par-tial dierential equations but the system of dierential equations has not been solved by this method which is the focus of this paper. We have shown that the proposed version of sinc is able to solve sti system while Runge-kutta method can not able to solve. Moreover, Due to the great attention to mathematical mod...
متن کاملLinear Stochastic Models of Nonlinear Dynamical Systems
We investigate in this work the validity of linear stochastic models for nonlinear dynamical systems. We exploit as our basic tool a previously proposed Rayleigh-Ritz approximation for the effective action of nonlinear dynamical systems started from random initial conditions. The present paper discusses only the case where the PDF-Ansatz employed in the variational calculation is “Markovian”, i...
متن کاملStochastic modelling of nonlinear dynamical systems
We develop a general theory dealing with stochastic models for dynamical systems that are governed by various nonlinear, ordinary or partial differential, equations. In particular, we address the problem how flows in the random medium (related to driving velocity fields which are generically bound to obey suitable local conservation laws) can be reconciled with the notion of dispersion due to a...
متن کاملLearning Stable Stochastic Nonlinear Dynamical Systems
A data-driven identification of dynamical systems requiring only minimal prior knowledge is promising whenever no analytically derived model structure is available, e.g., from first principles in physics. However, meta-knowledge on the system’s behavior is often given and should be exploited: Stability as fundamental property is essential when the model is used for controller design or movement...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Reports on Mathematical Physics
سال: 1999
ISSN: 0034-4877
DOI: 10.1016/s0034-4877(00)87242-0