Why do we need infinite dimensional vector spaces?

In summary, vector spaces with infinite dimensions are necessary in certain fields of mathematics, such as functional analysis, where functions themselves can be seen as vectors. These spaces allow for more complex and abstract mathematical concepts to be studied and analyzed.
  • #1
Ratzinger
291
0
We have x=x1(1,0,0) + x2(0,1,0) + x3(0,0,1) to represent R^3. That's a finite dimensional vector space. So what do we need infinite dimensional vector space for? Why do we need (1,0,0,...), (0,1,0,0,...), etc. bases vectors to represent R^1 ?
 
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  • #2
Ratzinger said:
We have x=x1(1,0,0) + x2(0,1,0) + x3(0,0,1) to represent R^3. That's a finite dimensional vector space. So what do we need infinite dimensional vector space for? Why do we need (1,0,0,...), (0,1,0,0,...), etc. bases vectors to represent R^1 ?
To represent R^1, you only need 1 vector. A vector space of dimension n is spanned by a basis of n vectors, just as in your example of R^3. This is because a basis needs to span the vector space (which means you need *at least* n vectors) and has to be linearly independant (which means you can only have *at most* n vectors) which makes the number of vectors in the basis exactly n.

Then, what do we need vector spaces with infinite dimension? Consider the vectorspace [itex]\mathbb{R}\left[ X \right][/itex] which is the vector space of all polynomials in x over R. This is trivially an infinite dimensional vector space since a finite number of vectors in a basis contains a vector with a maximum degree r, meaning that x^(r+1) and higher cannot be formed.
 
  • #3
"Functional Analysis" makes intensive use of "function spaces"- infinite dimensional vector spaces of functions satisfying certain conditions. TD gave a simple example- the space of all polynomials. Perhaps the most important is L2(X), the vector space of all functions whose squares are Lebesque integrable on set X.
 
  • #4
Another familiar example of an infinite dimensional vector space is functions from an infinite domain to a ring
Consider that the space of functions
[tex]f:A \rightarrow R[/tex]
from some set [itex]A[/itex] to a ring [itex]R[/itex]
is a vector space with dimensions indexed on [itex]A[/itex]
since we have a vector
[tex]f(a)=r[/tex]
or
[tex]f_a=r[/tex]
Scalar multiplication, and vector addition are performed using the ring.
 
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  • #5
I think you should reconsider that example, NateTG. How is *a* function a vector space? Over what field? And what are its elements
 

1. What is an infinite dimensional vector space?

An infinite dimensional vector space is a mathematical concept that describes a collection of vectors that can be added together and multiplied by scalars. Unlike finite dimensional vector spaces, which have a fixed number of dimensions, an infinite dimensional vector space has an infinite number of dimensions.

2. How is an infinite dimensional vector space different from a finite dimensional one?

An infinite dimensional vector space differs from a finite dimensional one in several ways. One key difference is that in an infinite dimensional vector space, there can be an infinite number of linearly independent vectors, whereas in a finite dimensional space, there is a maximum number of linearly independent vectors. Additionally, infinite dimensional vector spaces are often more abstract and can be more difficult to visualize compared to finite dimensional ones.

3. Can infinite dimensional vector spaces be used in real-world applications?

Yes, infinite dimensional vector spaces have many real-world applications, particularly in fields such as physics and engineering. For example, infinite dimensional vector spaces are used in quantum mechanics to describe the state of a system, and in signal processing to model signals with an infinite number of dimensions. They are also essential in functional analysis, a branch of mathematics that studies infinite dimensional vector spaces and their properties.

4. How are basis vectors defined in an infinite dimensional vector space?

In an infinite dimensional vector space, basis vectors are defined as a set of linearly independent vectors that span the entire space. Unlike in a finite dimensional space, where there is a finite number of basis vectors, an infinite dimensional space can have an infinite number of basis vectors. Additionally, basis vectors in an infinite dimensional space are often infinite sequences or functions, rather than just finite lists of numbers.

5. Can infinite dimensional vector spaces be finite as well?

No, by definition, an infinite dimensional vector space must have an infinite number of dimensions. A finite dimensional vector space, on the other hand, has a finite number of dimensions. It is possible for a finite dimensional vector space to have infinitely many vectors, but it would still be considered a finite dimensional space because the number of dimensions is finite.

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