Intro to Differential equations: Vector Spaces

In summary: Similarly, we can show that 0=0'. So there's at most one identity element.Here's the proof of the claim that each element of P has at most one inverse. Suppose that there are two. Denote them by -X and -X'. Since X⊕(-X)=0 and X⊕(-X')=0, we have -X=X⊕(-X)=0 and -X'=X⊕(-X')=0. So -X=-X'.
  • #1
Jaglowsd
7
0
Good evening everyone, I hope everyone is having a better evening than myself thanks to this homework problem.

Let P be the set of positive numbers. For a,b in P, define a+b=a x b; for a in P and a real number r, define r x a= a^r. Show that P is a vector space using ⊕ as addition and (circle dot) as scalar multiplication.
For a,b in P, define ab=a x b; for a in P and a real number r, define r x a= a^r.
My professor wants us to use these properties that are in our text,

Properties:
1. X+Y=Y+X.
2. (X+Y)+Z=X+(Y+Z).
3. 0+X=X+0=X.
4. r(sX)=(rs)X.
5. (r+s)X=rX+sX.
6. r(X+Y)=rX+rY.
7. 1X=X.


My professor introduced our class to the topic of a vector space today and when he was talking about it everything made sense. Now that I am here on my own I honestly do not know where to start. Unfortunately I was unable to go to his office hours today to ask him about it.

A brief and general description of where I should start is all I ask.
 
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  • #2
Jaglowsd said:
Good evening everyone, I hope everyone is having a better evening than myself thanks to this homework problem.

Let P be the set of positive numbers. For a,b in P, define a+b=a x b; for a in P and a real number r, define r x a= a^r. Show that P is a vector space using ⊕ as addition and (circle dot) as scalar multiplication.
For a,b in P, define ab=a x b; for a in P and a real number r, define r x a= a^r.

You mean ##r \odot a = a^r##

My professor wants us to use these properties that are in our text,

Properties:
1. X+Y=Y+X.
2. (X+Y)+Z=X+(Y+Z).
3. 0+X=X+0=X.
4. r(sX)=(rs)X.
5. (r+s)X=rX+sX.
6. r(X+Y)=rX+rY.
7. 1X=X.

My professor introduced our class to the topic of a vector space today and when he was talking about it everything made sense. Now that I am here on my own I honestly do not know where to start. Unfortunately I was unable to go to his office hours today to ask him about it
.

A brief and general description of where I should start is all I ask.

Take one step at a time. Look at property 1. What is ##x\oplus y##? What is ##y\oplus x##? Are they equal? Just continue.
 
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  • #3
One of the standard conditions is missing from your list. It's usually stated after 3 but before 4. It goes like this: X⊕(-X)=(-X)⊕X=0.

A typical beginning linear algebra student will find the axioms that involve 0 or -X confusing. Note that the full statement of axiom 3 goes like this: There's a Z in P such that for all X in P, we have X⊕Z=Z⊕X=X.

Such a Z is said to be an identity element of ⊕. So axiom 3 is telling you that ⊕ has an identity element in P. It's easy to show that ⊕ has at most one identity element (see below) so axiom 3 is really telling you that ⊕ has exactly one identity element. This identity element is denoted by 0, because that's the standard notation for the identity element of a commutative binary operation that's denoted by a symbol that's similar to a plus sign. But the identity element of ⊕ is NOT the number 0. Note that (the full statement of) axiom 3 says that 0 (the identity element) is an element of P, so it's a positive real number. You will have to figure out which one.

Similarly, the full statement of the forgotten axiom that I included at the start of this post is: For each X in P, there's a Y in P such that X⊕Y=Y⊕X=0. Here 0 denotes the identity element of ⊕, not the number 0. A positive real number Y such that X⊕Y=Y⊕X=0 is said to be an inverse of X. It's easy to prove that each element of P has at most one inverse. So the axiom is really telling us that each element of P has exactly one inverse. The standard notation for the inverse of X is -X.

Here's the proof of the claim that there's at most one identity element in P. Suppose that there are two. Denote them by 0 and 0'. Since 0'⊕X for all X in P and 0 is in P, we have 0'⊕0=0. Since X⊕0=X for all X in P, and 0' is in P, we have 0'⊕0=0'. So 0'=0'⊕0=0.
 
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1. What is the purpose of studying vector spaces in differential equations?

The concept of vector spaces is essential in understanding and solving differential equations because it provides a framework for analyzing and manipulating functions and their derivatives. Vector spaces allow us to represent and work with these functions in a more structured and organized manner, making it easier to solve differential equations.

2. How do vector spaces relate to differential equations?

Vector spaces are closely related to differential equations because they provide a way to represent and manipulate functions and their derivatives. By understanding the properties and operations of vector spaces, we can better understand and solve differential equations.

3. What are the key properties of vector spaces?

There are several key properties of vector spaces that are important to understand in the context of differential equations. These include closure under addition and scalar multiplication, existence of a zero vector, and existence of additive inverses. Additionally, vector spaces must follow the associative, commutative, and distributive laws.

4. How do vector spaces help us solve differential equations?

Vector spaces provide a way to represent functions and their derivatives in a more structured and organized manner, which makes it easier to apply mathematical techniques to solve differential equations. By understanding the properties and operations of vector spaces, we can also manipulate functions and their derivatives more effectively to solve differential equations.

5. Can you give an example of using vector spaces in solving a differential equation?

Yes, for example, in the equation y'' + 2y' + y = 0, we can represent the space of all solutions as a vector space with the functions y and y' as basis vectors. We can then use the properties of vector spaces to manipulate these functions and find a particular solution that satisfies the given initial conditions.

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