SUMMARY
The discussion focuses on proving that the linear transformation L_A: ℝ^n -> ℝ^n defined by L_A(X) = A.X, where A is an orthogonal matrix, is an isomorphism. It is established that an orthogonal matrix satisfies A^T = A^{-1}, which ensures that L_A is both injective and surjective. The injectivity is demonstrated by showing that if X_1 ≠ X_2, then A.X_1 ≠ A.X_2, preserving length and distance. The surjectivity can be confirmed using the rank-nullity theorem, as the kernel of A is {0}.
PREREQUISITES
- Understanding of linear transformations and their properties
- Knowledge of orthogonal matrices and their characteristics
- Familiarity with the concepts of injective and surjective functions
- Proficiency in applying the rank-nullity theorem
NEXT STEPS
- Study the properties of orthogonal matrices in depth
- Learn about the rank-nullity theorem and its applications in linear algebra
- Explore examples of bijective linear transformations
- Investigate the implications of isomorphisms in vector spaces
USEFUL FOR
Students and educators in linear algebra, mathematicians interested in transformations, and anyone studying the properties of orthogonal matrices and isomorphisms in vector spaces.