Mou-Hsiung Chang, Mathematical Sciences Division, U.S. Army Research Office.
.PUBLICATION, DISTRIBUTION, ETC
Place of Publication, Distribution, etc.
New York :
Name of Publisher, Distributor, etc.
Cambridge University Press,
Date of Publication, Distribution, etc.
2015.
PHYSICAL DESCRIPTION
Specific Material Designation and Extent of Item
xii, 412 pages ;
Dimensions
26 cm.
SERIES
Series Title
Cambridge series in statistical and probabilistic mathematics
INTERNAL BIBLIOGRAPHIES/INDEXES NOTE
Text of Note
Includes bibliographical references (pages 397-406) and index.
CONTENTS NOTE
Text of Note
Introduction and summary -- 1. Operator algebras and topologies -- 2. Quantum probability -- 3. Quantum stochastic calculus -- 4. Quantum stochastic differential equations -- 5. Quantum Markov semigroups -- 6. Minimal QDS -- 7. Quantum Markov processes -- 8. Strong quantum Markov processes -- 9. Invariant normal states -- 10. Recurrence and transience -- 11. Ergodic theory.
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SUMMARY OR ABSTRACT
Text of Note
"It is widely known that the classical probability theory initiated by Kolmogorov and its quantum counterpart pioneered by von Neumann were both created at about the same time in1930's. However, the subsequent developments of the latter have trailed far behind the former ones. This is perhaps because development of a theory of quantum stochastics requires an unusually large number of tools from operator theory and perhaps also because the probabilistic and analytical tools for understanding sample path behaviors of quantum stochastic processes have yet to be developed"--
Text of Note
"The classical probability theory initiated by Kolmogorov and its quantum counterpart, pioneered by von Neumann, were created at about the same time in the 1930s, but development of the quantum theory has trailed far behind. Although highly appealing, the quantum theory has a steep learning curve, requiring tools from both probability and analysis and a facility for combining the two viewpoints. This book is a systematic, self-contained account of the core of quantum probability and quantum stochastic processes for graduate students and researchers. The only assumed background is knowledge of the basic theory of Hilbert spaces, bounded linear operators, and classical Markov processes. From there, the book introduces additional tools from analysis, and then builds the quantum probability framework needed to support applications to quantum control and quantum information and communication. These include quantum noise, quantum stochastic calculus, stochastic quantum differential equations, quantum Markov semigroups and processes, and large-time asymptotic behavior of quantum Markov semigroups"--