MHB Introducing Inner Product Spaces: Real-World Examples

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The discussion emphasizes the need for impactful examples to introduce general inner product spaces beyond Euclidean contexts. Quantum mechanics, particularly through Hilbert spaces, serves as a compelling illustration, with the Schrödinger equation exemplifying eigenvalue problems in these spaces. The eigenvectors associated with quantum systems reside in Hilbert spaces, showcasing the practical application of inner products. Additionally, the Gram-Schmidt process is highlighted as a valuable method for obtaining orthonormal bases, leveraging inner products effectively. Overall, these examples provide a tangible connection between abstract mathematical concepts and real-world applications.
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.
 

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