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Lecture

Common Orthonormal Eigenbasis to Normal Commuting Operators

In course

PHYS-216: Mathematical methods (for SPH)

Ce cours est un complément aux cours d'analyse et d'algèbre linéaire qui apporte des méthodes et des techniques mathématiques supplémentaires requises pour les cours de physique de 3e année, notamment l'électrodynamique et la mécanique quantique. ...

Description

This lecture focuses on the condition for the existence of a common orthonormal eigenbasis to a set of two or more normal operators. It covers the proof that if two normal operators commute, there exists a common orthonormal eigenbasis. The lecture also discusses the generalization of this condition to an arbitrary number of normal operators.

Instructors (3)

Stephan Brunner

Sylvain Bréchet

Sylvain Bréchet was born on October 13th, 1981 in Moudon (legal origin Epesses, VD, Switzerland). He obtained a Master of Science in physics at EPFL in 2005. He went on to Cambridge for his PhD studies in theoretical cosmology from 2005 to 2009 under the supervision of Prof. Lasenby (FRS) and Prof. Michael Hobson at the Cavendish Laboratory of the University of Cambridge. He went back to EPFL where he is since 2010 university lecturer and research scientist in the Institute of Condensed Matter Physics. He taught classical mechanics, special relativity and thermodynamics to mechanical, electrical engineering students and physics students. He is currently writing a textbook in thermodynamics.

Jonathan Graves

Prof. Jonathan P. Graves is a Senior Scientist at EPFL and Honorary Visiting Professor at the University of York, UK. He achieved first class joint honours in Electronic Engineering and Mathematics from the University of Nottingham, UK in 1996. He completed his Ph.D. in Theoretical Mechanics from the University of Nottingham, UK, three years later in 1999. During his Ph.D. he was based in the Culham theory group of the United Kingdom Atomic Energy Authority, developing kinetic descriptions of the internal kink instability, and participating in deuterium-tritium experimental analysis in the Joint European Torus. After a short time in industry, and a postdoc at Nottingham University, he took a position at the Swiss Plasma Center at EPFL, becoming a Senior Scientist in 2014, and became an Honorary Visiting Professor at the University of York, UK, in 2020. In 2015 he became a member of the EUROfusion Scientific and Technical Advisory Committee (STAC) and a member of the EUROfusion DEMO Technical Advisory Group. He is on the editorial board for the journal Plasma Physics and Controlled Fusion, and in 2020 became Scientific Secretary of the Varenna-Lausanne International Workshop in Theory of Fusion Plasmas.

Official source

Ontological neighbourhood

Mathematics

Algebra: Linear algebra

Related concepts (24)

Eigenvalues and eigenvectors

In linear algebra, an eigenvector (ˈaɪgənˌvɛktər) or characteristic vector of a linear transformation is a nonzero vector that changes at most by a constant factor when that linear transformation is applied to it. The corresponding eigenvalue, often represented by , is the multiplying factor. Geometrically, a transformation matrix rotates, stretches, or shears the vectors it acts upon. The eigenvectors for a linear transformation matrix are the set of vectors that are only stretched, with no rotation or shear.

Normal operator

In mathematics, especially functional analysis, a normal operator on a complex Hilbert space H is a continuous linear operator N : H → H that commutes with its hermitian adjoint N*, that is: NN* = NN. Normal operators are important because the spectral theorem holds for them. The class of normal operators is well understood. Examples of normal operators are unitary operators: N = N−1 Hermitian operators (i.e., self-adjoint operators): N* = N Skew-Hermitian operators: N* = −N positive operators: N = MM* for some M (so N is self-adjoint).

Spectral theorem

In mathematics, particularly linear algebra and functional analysis, a spectral theorem is a result about when a linear operator or matrix can be diagonalized (that is, represented as a diagonal matrix in some basis). This is extremely useful because computations involving a diagonalizable matrix can often be reduced to much simpler computations involving the corresponding diagonal matrix. The concept of diagonalization is relatively straightforward for operators on finite-dimensional vector spaces but requires some modification for operators on infinite-dimensional spaces.

Generalized eigenvector

In linear algebra, a generalized eigenvector of an matrix is a vector which satisfies certain criteria which are more relaxed than those for an (ordinary) eigenvector. Let be an -dimensional vector space and let be the matrix representation of a linear map from to with respect to some ordered basis. There may not always exist a full set of linearly independent eigenvectors of that form a complete basis for . That is, the matrix may not be diagonalizable.

Spectral theory

In mathematics, spectral theory is an inclusive term for theories extending the eigenvector and eigenvalue theory of a single square matrix to a much broader theory of the structure of operators in a variety of mathematical spaces. It is a result of studies of linear algebra and the solutions of systems of linear equations and their generalizations. The theory is connected to that of analytic functions because the spectral properties of an operator are related to analytic functions of the spectral parameter.

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