000			02855nam a2200385 i 4500
001			CR9781107706545
003			UkCbUP
005			20240919171226.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			131105s2015||||enk o ||1 0|eng|d
020			_a9781107706545 (ebook)
020			_z9781107069190 (hardback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aQA274 _b.C44 2015
082	0	0	_a519.2/3 _223
100	1		_aChang, Mou-Hsiung, _eauthor.
245	1	0	_aQuantum stochastics / _cMou-Hsiung Chang, Mathematical Sciences Division, U.S. Army Research Office.
264		1	_aCambridge : _bCambridge University Press, _c2015.
300			_a1 online resource (xii, 412 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	1		_aCambridge series on statistical and probabilistic mathematics ; _v37
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505	8		_aMachine generated contents 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.
520			_aThe 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.
650		0	_aStochastic processes.
650		0	_aProbabilities.
650		0	_aQuantum theory.
776	0	8	_iPrint version: _z9781107069190
830		0	_aCambridge series on statistical and probabilistic mathematics ; _v37.
856	4	0	_uhttps://doi.org/10.1017/CBO9781107706545
942			_2ddc _cEB
999			_c8853 _d8853