arXiv · 1305.2611
Lecture Notes on Free Probability
Abstract
These lecture notes provide an introduction to free probability theory, with a focus on tools and techniques useful in the study of large random matrices. Topics include freeness, free cumulants, additive and multiplicative free convolution, the R- and S-transforms, subordination theory, and operator-valued extensions. Applications to asymptotic freeness and linearization methods are discussed in detail. The notes aim to be accessible to graduate students with a background in functional analysis and probability. The lecture notes were originally written for a graduate course. They are updated to include recent results on subordination and linearization methods in free probability.
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Vladislav Kargin. 2013-05-12. Lecture Notes on Free Probability. https://arxiv.org/abs/1305.2611
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