Understanding Vector Spaces with Mysterious Coefficients

In summary, the student is trying to determine if a vector space V with the operations defined by the two equalities (x+x'+1,y+y'+1) and (λx+λ-1,λy+y-1) is a space.
  • #1
vampyric
9
0

Homework Statement



Hi there, I'm very new to vector spaces and just can't seem to figure this one problem out.

The question ask's to determine if (V,+,*) is a vector space.

I am given

V=R^2

(x,y)+(x',y')=(x+x'+1,y+y'+1)

for addition on V

and

λ*(x,y)=(λx+λ-1,λy+y-1) (λ∈ℝ)

for scalar multiplication

The Attempt at a Solution



I think I can work through the axioms simple enough but I cannot figure out where the +1's and -1's have come from.

I have looked at https://www.physicsforums.com/showthread.php?t=388909

and it seems to explain everything I need to know except where these mysterious [itex]\pm[/itex]1's have come from.

Please haallp!
 
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  • #2
Sorry, I don't know what your question is. What are you asking?
 
  • #3
They didn't come from anywhere. Those equalities are (the key parts of) definitions of a non-standard addition operation on ℝ2 and a non-standard scalar multiplication operation on ℝ2. I assume that the problem is asking you to find out if ℝ2 with the operations defined by these equalities is a vector space.

A tip for next time: When you start a thread about a problem, you should at least mention what the problem is asking for.
 
  • #4
Sorry about that, I was in a rush to get to class.

So I'm not sure if I get this
For an addition operation (x,y)+(x',y')
from definition you just simply add +1 to each coefficient...is this what you mean?

I haven't noticed it being done for the case (x,y,z), is this because it is in R^3?

Thanks! Apologies once again for my vagueness.
 
  • #5
Fredrik said:
They didn't come from anywhere. Those equalities are (the key parts of) definitions of a non-standard addition operation on ℝ2 and a non-standard scalar multiplication operation on ℝ2. I assume that the problem is asking you to find out if ℝ2 with the operations defined by these equalities is a vector space.

A tip for next time: When you start a thread about a problem, you should at least mention what the problem is asking for.

So taking this with respect to axiom 1: v+w=w+v for all v,w ∈ V

(x',y')+(x,y)=(x'+x+1,y'+y+1)

Is this correct?
 
  • #6
vampyric said:
Sorry about that, I was in a rush to get to class.

So I'm not sure if I get this
For an addition operation (x,y)+(x',y')
from definition you just simply add +1 to each coefficient...is this what you mean?

I haven't noticed it being done for the case (x,y,z), is this because it is in R^3?
A vector space is defined by a set of things and two operations - one that defines addition between two members of the set, and another that defines multiplication of things in the set by a scalar.

In your problem, the set is R2, and the operations are as you showed them in post 1. Since the set is R2, which consists of ordered pairs, elements of R3 aren't relevant to the problem, so there is no case for (x, y, z).
 
  • #7
vampyric said:
So taking this with respect to axiom 1: v+w=w+v for all v,w ∈ V

(x',y')+(x,y)=(x'+x+1,y'+y+1)

Is this correct?
This is correct for (x',y')+(x,y). Now you need to show that (x, y) + (x', y') is equal to the same value. Some texts use special characters to indicate the defined operations, with ##\bigoplus## for the addition and ##\bigodot## for scalar multiplication.

For this problem you would have these definitions:
(x, y) ##\bigoplus## (x', y') = (x + x' + 1, y + y' + 1)
λ ##\bigodot## (x, y) = (λx + λ - 1, λy + y - 1)

In LaTeX these are \bigoplus and \bigodot, respectively. (I had to look them up.)


The ordinary + operator behaves as you would expect, and expressions such as λx indicate ordinary multiplication.
 
  • #8
Mark44 said:
This is correct for (x',y')+(x,y). Now you need to show that (x, y) + (x', y') is equal to the same value. Some texts use special characters to indicate the defined operations, with ##\bigoplus## for the addition and ##\bigodot## for scalar multiplication.

For this problem you would have these definitions:
(x, y) ##\bigoplus## (x', y') = (x + x' + 1, y + y' + 1)
λ ##\bigodot## (x, y) = (λx + λ - 1, λy + y - 1)

In LaTeX these are \bigoplus and \bigodot, respectively. (I had to look them up.)


The ordinary + operator behaves as you would expect, and expressions such as λx indicate ordinary multiplication.

Ohhhhh right. This is actually making sense now. Thank you so much!

As for

Mark44 said:
In your problem, the set is R2, and the operations are as you showed them in post 1. Since the set is R2, which consists of ordered pairs, elements of R3 aren't relevant to the problem, so there is no case for (x, y, z).

Nevermind, I was interpreting it to apply to all ordinary + as well and was confused as to why I hadn't seen this in R^3.

I will never underestimate the significance of notation again :)
Thanks!
 
  • #9
Mark44 said:
with ##\bigoplus## for the addition and ##\bigodot## for scalar multiplication.

For this problem you would have these definitions:
(x, y) ##\bigoplus## (x', y') = (x + x' + 1, y + y' + 1)
λ ##\bigodot## (x, y) = (λx + λ - 1, λy + y - 1)

In LaTeX these are \bigoplus and \bigodot, respectively. (I had to look them up.)
You should probably use \oplus and \odot in situations like this, and \bigoplus as a replacement for the summation sigma: $$\bigoplus_{i=1}^2 x_i =x_1\oplus x_2.$$
 
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  • #10
vampyric said:
So taking this with respect to axiom 1: v+w=w+v for all v,w ∈ V

(x',y')+(x,y)=(x'+x+1,y'+y+1)

Is this correct?
The left-hand side is defined to be equal to the right-hand side, but this is just the definition of an addition operation on ℝ2. If you want to show that v+w=w+v for all v,w ∈ V, you need to do more than just write down the definition of +. Since V=ℝ2, what you have to do is to use that definition to show that for all x,x',y,y' ∈ ℝ, we have (x',y')+(x,y)=(x,y)+(x',y').
 
  • #11
Fredrik said:
You should probably use \oplus and \odot in situations like this, and \bigoplus as a replacement for the summation sigma: $$\bigoplus_{k=1}^2 x_i =x_1\oplus x_2.$$
My biggest concern was to help the OP distinguish between the usual definitions for addition and multiplication, and the ones in this problem.
 
  • #12
Yes, and that was what Fredrik was doing. Part of the OP's difficulty was that sign for "normal" addition was being used for this new definition. It can clarify things to use a different symbol for this "new" addition.
 
  • #13
Yes, I think we all agree about everything. I was just trying to offer a little LaTeX tip there, not suggest that anyone was wrong.
 

1. What is a vector space?

A vector space is a mathematical structure consisting of a set of vectors and operations that allow for the addition and scalar multiplication of those vectors. It is a fundamental concept in linear algebra and has applications in many branches of science and engineering.

2. How do you determine if a set is a vector space?

To determine if a set is a vector space, it must satisfy certain properties. These include closure under addition and scalar multiplication, existence of a zero vector, existence of additive inverses, and the distributive and associative properties. If a set satisfies all of these properties, it is a vector space.

3. Can a vector space have an infinite number of dimensions?

Yes, a vector space can have an infinite number of dimensions. This means that the vectors in the space have an infinite number of components, which can make it difficult to visualize. However, the same principles and properties of vector spaces still apply regardless of the number of dimensions.

4. What is the basis of a vector space?

The basis of a vector space is a set of linearly independent vectors that span the entire space. This means that any vector in the space can be written as a linear combination of the basis vectors. The number of basis vectors is equal to the dimension of the vector space.

5. How is a vector space used in scientific research?

Vector spaces are used in many areas of scientific research, including physics, engineering, and computer science. They are particularly useful in representing and analyzing physical quantities and their relationships, such as forces, velocities, and electromagnetic fields. Vector spaces also have applications in data analysis, machine learning, and optimization problems.

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