List some uncommon vector spaces

In summary: The set of all real numbers is a vector space.The set of all complex numbers is a vector space.The real numbers form a one-dimensional vector space over the complex numbers.
  • #1
benorin
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I'm tutoring a linear algebra/diff eqs class and we are about to start on vector spaces; the point is this, I would like to present them with a variety of unsual vector spaces (along with the usual ones) that they may understand that vectors are not just directed line segments, but rather more than that. Please list some uncommon vector spaces (or common ones with non-standard definitions of scalar multiplication and/or vector addition).

Thanks,
--Ben
 
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  • #2
I suppose you want to stick to real vector spaces, and not vs's over other fields?

Finite-dimensional:
The v.s. of all polynomials of degree less than d.
The v.s. of solutions to a second order ordinary differential equation.
R
C

Infinite-dimensional.
The v.s. of all functions R->R. (or, all continuous functions, or all polynomial functions)



You can obfuscate any vector space you like too; just pick any invertible function f:V -> V, and then the operations

[tex]s \otimes v := f(s f^{-1}(v))[/tex]
[tex]v \oplus w := f(f^{-1}(v) + f^{-1}(w))[/tex]

define a new vector space structure on V.
 
  • #3
For example, the set of all converging real sequences. Or, the set of all solutions of a homogenous system of linear equations.
 
  • #4
Thank you Hurkyl for your excellent examples.
And Thank you radou for the additional example of a v.s., namely the set of all converging real sequences (nice one).
 
  • #5
And, although Hurkyl specifically said he was restricting to vector spaces over the real numbers, you can think of the real numbers themselves as a vector space over the rational numbers. That's not only infinite dimensional, it is of uncountable dimension.

Of course, the real numbers form a very simple one dimensional vector space over themselves.
 
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  • #6
(you mean over the rational numbers)
 
  • #7
Yes, of course. Thanks, Hurkyl, I'll edit it.

(Of course, the complex numbers can be considered a two dimensional vector space over the real numbers.)
 
  • #8
The rationals themselves fail to be a subspace of the reals only for the closure under scalar multiplication axiom (was exam question).
 

1. What is a vector space?

A vector space is a mathematical structure that consists of a set of vectors and operations that can be performed on those vectors. These operations include addition and scalar multiplication, which must satisfy certain properties to qualify as a vector space.

2. Can you give an example of an uncommon vector space?

Yes, an example of an uncommon vector space is the space of polynomials of degree n or less, denoted as Pn. This vector space consists of all polynomials with a degree less than or equal to n, and the operations performed on them are polynomial addition and scalar multiplication.

3. How does a vector space differ from a vector?

A vector space is a more general concept than a vector. A vector is an element of a vector space, just like how a number is an element of a number system. A vector space, on the other hand, is a set of vectors along with operations that can be performed on those vectors.

4. What is the importance of vector spaces in science?

Vector spaces are essential in science as they provide a way to represent and manipulate physical quantities such as force, velocity, and acceleration. They are also used in various mathematical models and theories, including quantum mechanics and linear algebra.

5. Are there any real-life applications of uncommon vector spaces?

Yes, there are many real-life applications of uncommon vector spaces. For example, the space of continuous functions, denoted as C, is used in physics to study the motion of objects. The space of square integrable functions, denoted as L2, is used in signal processing to analyze sound and images. These are just a few examples, as there are numerous other applications in various fields of science and engineering.

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