MHB Introducing Inner Product Spaces: Real-World Examples

matqkks
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What is the most motivating way to introduce general inner product spaces? I am looking for examples which have a real impact. For Euclidean spaces we relate the dot product to the angle between the vectors which most people find tangible. How can we extend this idea to the inner product of general vectors spaces such as the set of matrices, polynomials, functions?
 
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matqkks said:
What is the most motivating way to introduce general inner product spaces? I am looking for examples which have a real impact. For Euclidean spaces we relate the dot product to the angle between the vectors which most people find tangible. How can we extend this idea to the inner product of general vectors spaces such as the set of matrices, polynomials, functions?

You can't do better than quantum mechanics and Hilbert space, which is a particular kind of inner product space. If you look at the hydrogen atom, for example, the Schrodinger equation is an eigenvalue problem. The eigenvectors are functions that live in a Hilbert space. You can use the Gram-Schmidt process to reduce the eigenvectors to an orthonormal basis, which is probably the most useful kind of basis. The Gram-Schmidt process makes use of the inner product extensively.
 
The world of 2\times 2 complex matrices is very colorful. They form a Banach-algebra, they act on spinors, they contain the quaternions, SU(2), su(2), SL(2,\mathbb C), sl(2,\mathbb C). Furthermore, with the determinant as Euclidean or pseudo-Euclidean norm, isu(2) is a 3-dimensional Euclidean space, \mathbb RI\oplus isu(2) is a Minkowski space with signature (1,3), i\mathbb RI\oplus su(2) is a Minkowski space with signature (3,1), SU(2) is the double cover of SO(3), sl(2,\mathbb C) is the...

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