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강연자 지운식
소속 충북대학교
date 2011-04-14
We start with the famous Heisenberg uncertainty principle to give the idea of the probability in quantum mechanics. The Heisenberg uncertainty principle states by precise inequalities that the product of uncertainties of two physical quantities, such as momentum and position (operators), must be greater than certain (strictly positive) constant, which means that if we know one of the quantities more precisely, then we know the other one less precisely. Therefore, in quantum mechanics, predictions should be probabilistic, not deterministic, and then position and momentum should be considered as random variables to measure their probabilities.
In mathematical framework, the noncommutative probability is another name of quantum probability, and a quantum probability space consists of an -algebra of operators on a Hilbert space and a state (normalized positive linear functional) on the operator algebra. We study the basic notions in quantum probability theory comparing with the basic notions in classical (commutative) probability theory, and we also study the fundamental theory of quantum stochastic calculus motivated by the classical stochastic calculus.
Finally, we discuss several applications with future prospects of classical and quantum probability theory.
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List of Articles
카테고리 제목 소속 강연자
수학강연회 <학부생을 위한 ɛ 강연> Convergence of Fourier series and integrals in Lebesgue spaces file 서울대 이상혁
수학강연회 An introduction to hyperplane arrangements file 서울대 이승진
수학강연회 Creation of concepts for prediction models and quantitative trading file Haafor 이승환
수학강연회 On function field and smooth specialization of a hypersurface in the projective space file KAIST 이용남
수학강연회 Global result for multiple positive radial solutions of p-Laplacian system on exterior domain file 부산대학교 이용훈
수학강연회 <정년퇴임 기념강연> Hardy, Beurling, and invariant subspaces file 서울대학교 이우영
수학강연회 Averaging formula for Nielsen numbers file 서강대학교 이종범
수학강연회 The Mathematics of the Bose Gas and its Condensation file KAIST 이지운
수학강연회 Role of Computational Mathematics and Image Processing in Magnetic Resonance Electrical Impedance Tomography (MREIT) file KAIST 이창옥
수학강연회 Heavy-tailed large deviations and deep learning's generalization mystery file Northwestern University 이창한
수학강연회 Analysis and computations of stochastic optimal control problems for stochastic PDEs file 아주대 이형천
수학강연회 Non-commutative Lp-spaces and analysis on quantum spaces file 서울대학교 이훈희
수학강연회 Alice and Bob meet Banach and von Neumann file 서울대 이훈희
수학강연회 Cloaking via Change of Variables file KAIST 임미경
수학강연회 Volume entropy of hyperbolic buildings file 서울대 임선희
수학강연회 Randomness of prime numbers file 서울대학교 임선희
수학강연회 Brownian motion and energy minimizing measure in negative curvature file 서울대학교 임선희
수학강연회 <학부생을 위한 ɛ 강연> Mathematics and music: Pythagoras, Bach, Fibonacci and AI file 피아니스트 임현정
수학강연회 Fixed points of symplectic/Hamiltonian circle actions file 부산대 수학과 장동훈
수학강연회 <학부생을 위한 ɛ 강연> Mathematical Aspects of Machine Learning and Deep Learning AI file 서울대학교 컴퓨터공학부 장병탁
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