Pseudo-Differential Operators and Markov Processes

This comprehensive work delves into the intricate relationship between pseudo-differential operators and Markov processes, spanning multiple volumes. The first volume focuses on Fourier analysis and semigroups, providing readers with foundational knowledge that serves as a stepping stone into more complex theories. Through clear explanations and rigorous mathematical frameworks, the authors aim to equip readers with the tools needed to navigate the various applications of these operators.

Subsequent volumes venture into advanced topics, such as generators of Markov processes and their connections to potential theory. By exploring the interplay between these mathematical constructs, the authors illuminate the underlying structures that govern stochastic processes. The structured progression through the subjects fosters a deeper understanding, making this work a critical resource for mathematicians and researchers interested in the theory and applications of pseudo-differential operators in stochastic analysis.