CTRW modeling of quantum measurement and fractional equations of quantum stochastic filtering and control

Initially developed in the framework of quantum stochastic calculus, the main equations of quantum stochastic filtering were later on derived as the limits of Markov models of discrete measurements under appropriate scaling. In many branches of modern physics it became popular to extend random walk...

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Bibliographic Details
Main Author: Kolokoltsov, V. (Author)
Format: Article
Language:English
Published: Springer Nature 2022
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02076nam a2200217Ia 4500
001 10.1007-s13540-021-00002-2
008 220706s2022 CNT 000 0 und d
020 |a 13110454 (ISSN) 
245 1 0 |a CTRW modeling of quantum measurement and fractional equations of quantum stochastic filtering and control 
260 0 |b Springer Nature  |c 2022 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1007/s13540-021-00002-2 
520 3 |a Initially developed in the framework of quantum stochastic calculus, the main equations of quantum stochastic filtering were later on derived as the limits of Markov models of discrete measurements under appropriate scaling. In many branches of modern physics it became popular to extend random walk modeling to the continuous time random walk (CTRW) modeling, where the time between discrete events is taken to be non-exponential. In the present paper we apply the CTRW modeling to the continuous quantum measurements yielding the new fractional in time evolution equations of quantum filtering and thus new fractional equations of quantum mechanics of open systems. The related quantum control problems and games turn out to be described by the fractional Hamilton-Jacobi-Bellman (HJB) equations on Riemannian manifolds. By-passing we provide a full derivation of the standard quantum filtering equations, in a modified way as compared with existing texts, which (i) provides explicit rates of convergence (that are not available via the tightness of martingales approach developed previously) and (ii) allows for the direct applications of the basic results of CTRWs to deduce the final fractional filtering equations. © 2022, The Author(s). 
650 0 4 |a Belavkin equation 
650 0 4 |a CTRW 
650 0 4 |a Fractional Hamilton-Jacobi-Bellman-Isaacs equation on manifolds 
650 0 4 |a Fractional quantum control 
650 0 4 |a Fractional quantum mean field games 
650 0 4 |a Fractional quantum mechanics 
650 0 4 |a Quantum stochastic filtering 
700 1 |a Kolokoltsov, V.  |e author 
773 |t Fractional Calculus and Applied Analysis