What Are the Key Vector Spaces You Should Understand?

Click For Summary
SUMMARY

The discussion focuses on key vector spaces essential for understanding linear algebra, specifically the real vector space \(\mathbb{R}\), the polynomial space \(\mathbb{P}_n\), and the complex vector space \(\mathbb{C}\). \(\mathbb{R}\) consists of vectors with real number components, while \(\mathbb{P}_n\) represents polynomials of degree less than or equal to \(n\) with a basis of \(n + 1\) functions. The complex vector space \(\mathbb{C}\) extends the concept to complex numbers. Additionally, matrices of specific sizes also form vector spaces, highlighting the diversity of vector spaces in linear algebra.

PREREQUISITES
  • Understanding of basic vector space concepts
  • Familiarity with real numbers and complex numbers
  • Knowledge of polynomial functions and their properties
  • Basic understanding of linear algebra axioms
NEXT STEPS
  • Research the properties and applications of \(\mathbb{P}_n\) in polynomial interpolation
  • Study the axioms of vector spaces to solidify foundational knowledge
  • Explore the role of complex numbers in vector spaces and their applications
  • Investigate various types of matrix spaces and their significance in linear transformations
USEFUL FOR

Students of linear algebra, mathematicians, and anyone interested in the theoretical foundations of vector spaces and their applications in various fields.

Zhalfirin88
Messages
137
Reaction score
0
This isn't a homework question, but I thought it'd still be an appropriate place.

So this is about vector spaces. I know these are sort of abstract spaces but I'd like more explanation on them.

1) [tex]\mathbb{R}[/tex] This is the space of real vectors right, like from real numbers?

2) [tex]\mathbb{P}[/tex] What does this mean that it's a polynomial space? Like the standard basis is {1,t,t2,t3...} but how is [tex]\mathbb{P}_n[/tex] different from [tex]\mathbb{R}^n[/tex]

3) [tex]\mathbb{C}[/tex] My instructor basically showed us this one, but didn't explain it cause we don't use it in our linear algebra class.

Edit: Are there any other majors spaces that I didn't list but are important to know?
 
Physics news on Phys.org
Zhalfirin88 said:
This isn't a homework question, but I thought it'd still be an appropriate place.

So this is about vector spaces. I know these are sort of abstract spaces but I'd like more explanation on them.

1) [tex]\mathbb{R}[/tex] This is the space of real vectors right, like from real numbers?
Yes, pretty much. A vector in this space extends from the origin to a given real number. A vector space consists, naturally enough, of vectors, whose components come from some field. In this case, the field is the real numbers. Scalar multiplication means multiplication by real numbers.
Zhalfirin88 said:
2) [tex]\mathbb{P}[/tex] What does this mean that it's a polynomial space? Like the standard basis is {1,t,t2,t3...} but how is [tex]\mathbb{P}_n[/tex] different from [tex]\mathbb{R}^n[/tex]
Usually you'll see this as Pn, the (function) space of polynomials of degree <= n. A function space is structurally identical to a vector space, and must satisfy the same 10 axioms. Notice that a basis for Pn consists of n + 1 functions, while a basis for Rn consists of n vectors.
Zhalfirin88 said:
3) [tex]\mathbb{C}[/tex] My instructor basically showed us this one, but didn't explain it cause we don't use it in our linear algebra class.
This would be similar in some respects to the vector space R, but the field is the complex numbers. The components are complex numbers, and scalar multiplication is done using complex numbers.
Zhalfirin88 said:
Edit: Are there any other majors spaces that I didn't list but are important to know?
Matrices of a given size form a vector space. E.g., there's a vector space that consists of 2 x 2 matrices, another for 3 x 2 matrices, and so on. For more examples, see http://en.wikipedia.org/wiki/Examples_of_vector_spaces.
 
Thanks Mark. :)
 

Similar threads

  • · Replies 1 ·
Replies
1
Views
3K
Replies
9
Views
2K
  • · Replies 17 ·
Replies
17
Views
4K
Replies
4
Views
2K
  • · Replies 0 ·
Replies
0
Views
738
  • · Replies 18 ·
Replies
18
Views
4K
  • · Replies 6 ·
Replies
6
Views
2K
  • · Replies 9 ·
Replies
9
Views
4K
  • · Replies 12 ·
Replies
12
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K