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Lecture

Scattering Theory: Quantum Mechanics

In course

PHYS-425: Quantum physics III

To introduce several advanced topics in quantum physics, including semiclassical approximation, path integral, scattering theory, and relativistic quantum mechanics ...

Description

This lecture covers the principles of scattering theory in quantum mechanics, focusing on the interaction between particles and potential barriers, tunneling phenomena, metastable states, and the concept of transmission probability. It also discusses the differential cross-section and total cross-section in scattering processes, with examples from point-like particle scattering and Coulomb potential scattering.

Instructor

Oleg Yazyev

Prof. Oleg Yazyev (Олег Язев) was born in Simferopol, Crimean peninsula. He obtained his degree in chemistry from Moscow State University in 2003. He then joined Ecole Polytechnique Fédérale de Lausanne (EPFL) completing his PhD thesis in chemistry and chemical engineering in 2007. Next two years he has spent as a postdoctoral fellow at the Institute of Theoretical Physics (ITP) and the Institute for Numerical Research in the Physics of Materials (IRRMA) of the same institution. In 2009-2011 he was a postdoctoral fellow at the Department of Physics of the University of California, Berkeley and the Lawrence Berkeley National Laboratory. In September 2011 he started an independent research group supported by the Swiss National Science Foundation professorship grant. In 2012 he was awarded an ERC Starting grant. His current research focuses on theoretical and computational physics of two-dimensional and topological materials with strong emphasis on their prospective technological applications. ResearcherID profile of Oleg Yazyev Google Scholar profile of Oleg Yazyev

Official source

Related concepts (32)

Conditional probability

In probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption, assertion or evidence) has already occurred. This particular method relies on event B occurring with some sort of relationship with another event A. In this event, the event B can be analyzed by a conditional probability with respect to A. If the event of interest is A and the event B is known or assumed to have occurred, "the conditional probability of A given B", or "the probability of A under the condition B", is usually written as P(AB) or occasionally P_B(A).

Particle

In the physical sciences, a particle (or corpuscule in older texts) is a small localized object which can be described by several physical or chemical properties, such as volume, density, or mass. They vary greatly in size or quantity, from subatomic particles like the electron, to microscopic particles like atoms and molecules, to macroscopic particles like powders and other granular materials. Particles can also be used to create scientific models of even larger objects depending on their density, such as humans moving in a crowd or celestial bodies in motion.

Probability

Probability is the branch of mathematics concerning numerical descriptions of how likely an event is to occur, or how likely it is that a proposition is true. The probability of an event is a number between 0 and 1, where, roughly speaking, 0 indicates impossibility of the event and 1 indicates certainty. The higher the probability of an event, the more likely it is that the event will occur. A simple example is the tossing of a fair (unbiased) coin.

Probability theory

Probability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations, probability theory treats the concept in a rigorous mathematical manner by expressing it through a set of axioms. Typically these axioms formalise probability in terms of a probability space, which assigns a measure taking values between 0 and 1, termed the probability measure, to a set of outcomes called the sample space.

Probability distribution

In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment. It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). For instance, if X is used to denote the outcome of a coin toss ("the experiment"), then the probability distribution of X would take the value 0.5 (1 in 2 or 1/2) for X = heads, and 0.

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