|
This article is cited in 14 scientific papers (total in 14 papers)
MATHEMATICS
Random quantization of Hamiltonian systems
J. E. Gougha, Yu. N. Orlovbc, V. Zh. Sakbaevbd, O. G. Smolyanove a Aberystwyth University, United Kingdom, Wales
b Keldysh Institute of Applied Mathematics of Russian Academy of Sciences, Moscow, Russian Federation
c Institute of Machines Science named after A.A. Blagonravov of the Russian Academy of Sciences, Moscow, Russian Federation
d Moscow Institute of Physics and Technology, Dolgoprudny, Russian Federation
e Lomonosov Moscow State University, Moscow, Russian Federation
Abstract:
A quantization of a Hamiltonian system is an ambiguous procedure. Accordingly, we introduce the notion of random quantization, related random variables with values in the set of self-adjoint operators, and random processes with values in the group of unitary operators. The procedures for the averaging of random unitary groups and averaging of random self-adjoint operators are defined. The generalized weak convergence of a sequence of measures and the corresponding generalized convergence in distribution of a sequence of random variables are introduced. The generalized convergence in distribution for some sequences of compositions of random mappings is obtained. In the case of a sequence of compositions of shifts by independent random vectors of Euclidean space, the obtained convergence coincides with the statement of the central limit theorem for a sum of independent random vectors. The results are applied to the dynamics of quantum systems arising in random quantization of a Hamiltonian system.
Keywords:
random linear operator, random operator-valued function, operator-valued random process, law of large numbers, central limit theorem, Markovian process, Kolmogorov equation.
Citation:
J. E. Gough, Yu. N. Orlov, V. Zh. Sakbaev, O. G. Smolyanov, “Random quantization of Hamiltonian systems”, Dokl. RAN. Math. Inf. Proc. Upr., 498 (2021), 31–36; Dokl. Math., 103:3 (2021), 122–126
Linking options:
https://www.mathnet.ru/eng/danma16 https://www.mathnet.ru/eng/danma/v498/p31
|
Statistics & downloads: |
Abstract page: | 172 | Full-text PDF : | 27 | References: | 14 |
|