Vector Space over Field of Real Numbers

In summary: No, I don't think so. I think that ##\alpha \in \Bbb C^n## is to show that there can be different spaces for the same vector set ##V## like ##\Bbb C^n## and vector space of this...complex numbers?
  • #1
Buffu
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The field of ## C## of complex numbers may be regarded as a vector space over the field of ##R##. More generally let ##F## be a field of real numbers and let ##V## be set of n-tuples ##\alpha = (x_1 , \cdots, x_n)## where ##x_1, \cdots x_n## are in ##\Bbb C##. We define addition of ##\alpha,\beta \in V## as ##\alpha + \beta = (\alpha_1 + \beta_1, ..., \alpha_n + \beta_n)## and scalar multiplication as ##c\alpha = (c\alpha_1, ... , c\alpha_n)##. This way we got a vector space over field ##R## which is quite different form the space ##C^n## and the space ##R^n##.

I am confused why is space over field ##R## not over field ##C## ? The entries in each vector is an element of ##\Bbb C## not ##\Bbb R##.
 
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  • #2
I'm confused, too. Can you sort this out? Where's the quotation from? Is ##F## meant to be a subfield of ##\mathbb{R}##? And is the scalar field of ##V## now ##F## or ##\mathbb{R}\,##? Or ##\mathbb{C}## as that's where the vector operations are defined for?

I can only guess, that the statement is: Complex and real vector spaces are different and both differ from vector spaces with a scalar field like e.g. ##F=\mathbb{Q}(\pi,\sqrt{2},e,\log 2)## or whatever. To me this statement is a total mess.
 
  • #3
fresh_42 said:
I'm confused, too. Can you sort this out? Where's the quotation from? Is ##F## meant to be a subfield of ##\mathbb{R}##? And is the scalar field of ##V## now ##F## or ##\mathbb{R}\,##? Or ##\mathbb{C}## as that's where the vector operations are defined for?
I can only guess, that the statement is: Complex and real vector spaces are different and both differ from vector spaces with a scalar field like e.g. ##F=\mathbb{Q}(\pi,\sqrt{2},e,\log 2)## or whatever. To me this statement is a total mess.

It is written ##F## is a field of ##R##. I don't think it matters if the scalar field is ##R## or ##F## since both are same. It is certainly not ##C##.
 
  • #4
Original statement :
upload_2017-6-13_2-46-31.png


This bit might also help :
upload_2017-6-13_2-47-31.png
 
  • #5
So we have ##F \subseteq \mathbb{R} \subset \mathbb{C}##. Next we have a vector space ##V_\mathbb{K}## of finite dimension ##n## and a field of scalars ##\mathbb{K} \in \{F,\mathbb{R},\mathbb{C}\}##. All versions of ##V_\mathbb{K}## lead to different vector spaces, despite the fact that they all are ##n-##dimensional.

I do not understand the remark ##\alpha = (x_1,\ldots ,x_n) \in \mathbb{C}^n##.
Essential to the vector space ##V_\mathbb{K}## is where ##c## is from, and that is ##c \in \mathbb{K}##.

E.g. let's consider ##V := \mathbb{C}^2_\mathbb{R}## and ##W:= \mathbb{C}^2_\mathbb{C}##. Then ##(i,2i)## and ##(1,2)## are two different vectors in both, but in ##V## they point in two different directions (i.e. they are linearly independent), whereas in ##W## there is an equation ##-i \cdot (i,2i) = (1,2)## which means one is a multiple of the other and thus point in the same direction (and they are linearly dependent). All because we have ##c= -i ## available for ##W## which is not available for ##V##.
 
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  • #6
fresh_42 said:
So we have ##F \subseteq \mathbb{R} \subset \mathbb{C}##. Next we have a vector space ##V_\mathbb{K}## of finite dimension ##n## and a field of scalars ##\mathbb{K} \in \{F,\mathbb{R},\mathbb{C}\}##. All versions of ##V_\mathbb{K}## lead to different vector spaces, despite the fact that they all are ##n-##dimensional.

Why ##K \in \{F, \Bbb R, \Bbb C\}## ? Should not it be just ##K = F## ?

I do not understand the remark ##\alpha = (x_1,\ldots ,x_n) \in \mathbb{C}^n##.
Essential to the vector space ##V_\mathbb{K}## is where ##c## is from, and that is ##c \in \mathbb{K}##.

Neither do I.
 
  • #7
Buffu said:
Why ##K \in \{F, \Bbb R, \Bbb C\}## ? Should not it be just ##K = F## ?
I've chosen the most general case, because the author(s) introduced a field ##F## of real numbers, e.g. ##\mathbb{Q}(\pi)##, then also spoke about the entire real number field ##\mathbb{R}## as well as of complex numbers ##\mathbb{C}##. I thought a neutral ##\mathbb{K}## would split this Gordian knot of fields.
Neither do I.
I guess it is because of the example I added in my previous post.
 
  • #8
fresh_42 said:
I've chosen the most general case, because the author(s) introduced a field ##F## of real numbers, e.g. ##\mathbb{Q}(\pi)##, then also spoke about the entire real number field ##\mathbb{R}## as well as of complex numbers ##\mathbb{C}##. I thought a neutral ##\mathbb{K}## would split this Gordian knot of fields.

I guess it is because of the example I added in my previous post.

Nevertheless I think I got it.
I think that ##\alpha \in \Bbb C^n## is to show that there can be different spaces for the same vector set ##V## like ##\Bbb C^n## and vector space of this example.
 

1. What is a vector space over a field of real numbers?

A vector space over a field of real numbers is a mathematical structure that consists of a set of vectors and a set of scalars (real numbers) that satisfy certain properties. These properties include closure under addition and scalar multiplication, associativity, commutativity, and the existence of an identity element and inverse element.

2. What are some examples of vector spaces over a field of real numbers?

Examples of vector spaces over a field of real numbers include the set of all n-dimensional real vectors, the set of all polynomials with real coefficients, and the set of all continuous real-valued functions on a given interval.

3. What is the dimension of a vector space over a field of real numbers?

The dimension of a vector space over a field of real numbers is the number of vectors in a basis for that space. It is also equal to the number of coordinates needed to uniquely describe any vector in that space.

4. How is a vector space over a field of real numbers different from a vector space over a different field?

The main difference between vector spaces over different fields is the set of scalars that can be used for scalar multiplication. In a vector space over a field of real numbers, only real numbers can be used as scalars, while in a vector space over a different field (such as a field of complex numbers), a different set of scalars can be used.

5. What is the importance of vector spaces over fields of real numbers in science?

Vector spaces over fields of real numbers are important in science because they provide a mathematical framework for representing and manipulating quantities that have both magnitude and direction. This is particularly useful in fields such as physics and engineering, where many physical quantities can be represented as vectors, such as velocity, force, and electric fields.

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