Exploring Inner Products in Vector Spaces: The Impact on Geometry

In summary, the conversation discusses the concept of inner products and how they define distance in a vector space. The question of how changing the inner product would affect the geometry of the space is raised, specifically if a shape defined by vectors in the standard inner product would still be the same shape in a space with a non-standard inner product. The solution suggests trying to define a new norm and seeing if orthogonality is preserved, and also explains that changing the inner product is equivalent to changing the basis and coordinate system. Ultimately, it is concluded that changing the inner product would result in a different shape, as demonstrated by the example given.
  • #1
talolard
125
0

Homework Statement


Hey, I ahve a curioisity (not homework )question.
We learned that there are an infinite number of inner products that can be defined ona vector space and that inner product space is what gives us the notion of distance within a given space.
So if we defined some non standard inner product on R^n what would that mean in terms of geoemtry?
For example, say I looked at R^2 with the standard inner product and defined a square with vectors. Then I "took a new space" in R^2 but with some other inner product and plotted the same vectors, what would they still be a square?


Thanks
Tal

Homework Equations





The Attempt at a Solution

 
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  • #2
Try to define a new norm on R^2 and see if it preserves orthogonality, for example.
 
  • #3
talolard said:

Homework Statement


Hey, I ahve a curioisity (not homework )question.
We learned that there are an infinite number of inner products that can be defined ona vector space and that inner product space is what gives us the notion of distance within a given space.
So if we defined some non standard inner product on R^n what would that mean in terms of geoemtry?
For example, say I looked at R^2 with the standard inner product and defined a square with vectors. Then I "took a new space" in R^2 but with some other inner product and plotted the same vectors, what would they still be a square?


Thanks
Tal

Homework Equations





The Attempt at a Solution

Changing the inner product is essentially the same as changing your basis which, in [itex]R^n[/itex] is the same as changing your coordinate system. In particular, if you chose <(x,y),(u,v)> = xu+ 2yv as your inner product, an orthonormal basis would be [itex]\{(1, 0), (0, \sqrt{2}/2)\}[/itex] so your vertical axis would be squashed compared to your horizontal axis. No, it would not still be a square.
 
  • #4
Cool.
Thank you.
 

FAQ: Exploring Inner Products in Vector Spaces: The Impact on Geometry

What is an inerr product space?

An inerr product space is a mathematical concept used in functional analysis to describe a collection of functions or vectors that satisfy certain properties. It is a space in which all elements are considered perfect or error-free.

What are the properties of an inerr product space?

An inerr product space must satisfy three main properties: closure, associativity, and distributivity. Closure means that the space is closed under addition and scalar multiplication. Associativity means that the order in which operations are performed does not matter. Distributivity means that scalar multiplication and vector addition can be interchanged.

What is the difference between an inerr product space and a normed space?

An inerr product space is a specific type of normed space in which the norm is defined by an inner product. This means that the distance between two points is measured using the dot product. In contrast, a normed space can use various types of norms, such as the Euclidean norm, to measure distance.

What are some examples of inerr product spaces?

One example of an inerr product space is the space of real-valued continuous functions on a closed interval, where the inner product is defined as the integral of the product of two functions. Another example is the space of n-dimensional vectors with the standard dot product as the inner product.

How are inerr product spaces used in practical applications?

Inerr product spaces are commonly used in functional analysis and linear algebra to study properties of various mathematical structures. They also have applications in signal processing, quantum mechanics, and machine learning, where they are used to represent and analyze data or signals.

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