Gregory's question at Yahoo Answers (Inner product space)

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In summary, to prove that T is linear, we use the axioms of inner product space and show that T satisfies the properties of linearity. This is done by showing that T preserves scalar multiplication and vector addition.
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Hello Gregory,

If $V$ is the given vector space over the field $\mathbb{F}\;(\mathbb{R}$ or $\mathbb{C}$), for all $\lambda,\mu\in\mathbb{F}$ scalars, for all $u,v\in V$ vectors and using the axioms of inner product: $$\begin{aligned}T(\lambda u+\mu v)&=<\lambda u+\mu v,y>z\\&=(\lambda<u,y>+\mu<v,y>)z\\&=\lambda<u,y>z+\mu<v,y>z\\&=\lambda T(u)+\mu T(v)\\&\Rightarrow T\mbox{ is linear}\end{aligned}$$
 

Related to Gregory's question at Yahoo Answers (Inner product space)

What is an inner product space?

An inner product space is a mathematical concept that consists of a vector space and a defined inner product operation that satisfies certain properties. It is used to study the properties of vectors and vector spaces in a more abstract and general way.

What is the significance of inner product spaces in mathematics?

Inner product spaces are important in mathematics because they provide a framework for studying vectors and vector spaces in a more abstract and general way. They also have many practical applications in fields such as physics, engineering, and computer science.

What are some examples of inner product spaces?

Examples of inner product spaces include Euclidean spaces, function spaces, and Hilbert spaces. In Euclidean spaces, the inner product is the dot product. In function spaces, the inner product is defined as the integral of the product of two functions. In Hilbert spaces, the inner product is defined as an infinite-dimensional generalization of the dot product.

What are the properties of inner product spaces?

The properties of inner product spaces include linearity, symmetry, and positive definiteness. Linearity means that the inner product is distributive and follows the rules of scalar multiplication. Symmetry means that the order of the vectors in the inner product does not matter. Positive definiteness means that the inner product of a vector with itself is always positive.

How are inner product spaces related to other mathematical concepts?

Inner product spaces are closely related to other mathematical concepts such as norms, orthogonality, and projections. Norms are used to measure the length of a vector and can be defined using the inner product. Orthogonality is a concept that arises from inner products, where two vectors are considered orthogonal if their inner product is equal to zero. Projections, which are used in linear algebra and geometry, can also be defined using inner products.

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