Singular Vectors in Liouville CFT: Representation Theory Insights

Related lectures (24)

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Explores vector spaces, linear independence, and spanning sets in linear algebra.

Explores vector space properties, operations, linear combinations, and subspaces construction.

Explains the Wronskian and its role in determining linear independence of solutions to differential equations.

Covers the Easing model conformal theory, focusing on scaling limits and correlation functions.

Explains linear independence, basis, and matrix rank with examples and exercises.

Explores finding particular solutions for homogeneous differential equations, emphasizing linear independence and variation of constants.

Covers linear independence, bases, change of basis, and vector representation.

Covers matrix kernels, images, linear applications, independence, and bases in vector spaces.

Covers distributions, derivatives, convergence, and continuity criteria in function spaces.

Covers the weak formulation of elliptic partial differential equations and the uniqueness of solutions in Hilbert space.