How can isomorphism be used to show equivalence between sets in linear space?

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Homework Help Overview

The discussion revolves around demonstrating the equivalence between the set of all row vectors in a linear space and the set of all functions with values in that space, both defined in the context of n-dimensional vector spaces. The original poster attempts to use isomorphism to establish this equivalence but struggles with showing that the isomorphism is onto.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants explore the definition of isomorphism and its application to the problem. Some question the validity of the original poster's proposition, suggesting that the dimensions of the sets in question do not match. Others provide clarifications on how to define the mapping between the two sets and discuss the necessary conditions for isomorphism.

Discussion Status

The discussion is ongoing, with participants providing insights into the definitions and properties of isomorphism. Some have offered guidance on how to structure the proof and clarify the original problem statement. There is a recognition of differing interpretations of the problem, and participants are actively engaging with the concepts involved.

Contextual Notes

There is mention of confusion stemming from the original problem statement in the textbook, which has led to varying interpretations among participants. The discussion highlights the need for clarity regarding the definitions of the sets involved and the properties of the functions mapping between them.

wurth_skidder_23
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Sets in Linear Space

I am trying to show the set of all row vectors in some set K with dimension n is the same as the set of all functions with values in K, defined on an arbitrary set S with dimension n. I am using isomorphism to show this, but I can't determine how to show that the isomorphism is onto.

My work so far:


G := Functions with values in K

f: G -> K

(g(s1),...,g(sn))


one to one

f(G) = f(H)

(g(s1),...,g(sn)) = (h(s1),...,h(sn))

therefore, g(s1) = h(s1), ..., g(sn) = h(sn)


preserves structure

f(c1*G + c2*H) = (c1*g(s1) + c2*h(s1),...,c1*g(sn) + c2*h(sn))
= c1*(g(s1),...,g(sn)) + c2*(h(s1),...,h(sn))
= c1*f(G) + c2*f(H)
 
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No one out there is familiar with isomorphism?
 
:confused: Huh? This is not very clear. Is this the statement you are trying to prove?

Proposition: Let K,S be n-dimensional vector spaces over a Field F. Let G be the set of all functions mapping S to K. Then G is isomorphic to K.

If so, then it's false. For one the set of all linear transformations mapping S to K is a subspace of G of dimension n^2, so G can't possibly have the same dimension as K which is a necessary and sufficient condition for finite vector spaces to be isomorphic.
 
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Sorry, my book isn't very clear, either. That was part of the problem. Here is the full problem statement.

Examples of Linear Spaces.
(i) Set of all row vectors: (a1,...,an), aj in K; addition, multiplication defined componentwise. This space is denoted as K^n.
(iii) Set of all functions with values in K, defined on an arbitrary set S.
Show that if S has n elements, (i) is the same as (iii).
 
wurth_skidder_23 said:
Sorry, my book isn't very clear, either. That was part of the problem. Here is the full problem statement.

Examples of Linear Spaces.
(i) Set of all row vectors: (a1,...,an), aj in K; addition, multiplication defined componentwise. This space is denoted as K^n.
(iii) Set of all functions with values in K, defined on an arbitrary set S.
Show that if S has n elements, (i) is the same as (iii).
The books version makes a little more sense :-p

You have the right idea: Demonstrate an Isomorphism between these two vector spaces. I have added some notes.

wurth_skidder_23 said:
G := Functions with values in K

f: G -> K

(g(s1),...,g(sn))
This is pretty poorly defined. I can guess what you mean but I shouldn't have to. Here's one way to phrase this:

Suppose S is a set of n elements [itex]s_i[/itex] for i =1,2,...,n.
Let G be the vector space of all functions mapping S into K.

Define [tex]f:G \rightarrow K^n[/tex] such that [tex]\forall g \in G, g \mapsto (g(s_1),\ldots,g(s_n))[/tex]

We show f is an isomorphism.
---------
My modifications are in bold.
we show f is one to one:

let g,h be elements of G such that f(g) = f(h)

by definition of f we get, (g(s1),...,g(sn)) = (h(s1),...,h(sn))

therefore, g(s1) = h(s1), ..., g(sn) = h(sn)
a cleaner way to assert this is that [tex]g(s_i) = h(s_i)[/tex] for all i
Therefore g = h
To show f is onto, you let y = (a1, a2, ... , an) be an arbitrary element of K^n and show that there is some element of G that gets mapped to y by f. This is trivial, but if you want you could write something like this: let g be the function [itex]s_i \mapsto a_i[/itex], then g is a function mapping S into K and thus is an element of G. By the definition of f we have f(g) = y.

We show Linearity:
let c1, c2 be in K and let g,h be in G

f(c1*g + c2*h) = (c1*g(s1) + c2*h(s1),...,c1*g(sn) + c2*h(sn))
= c1*(g(s1),...,g(sn)) + c2*(h(s1),...,h(sn))
= c1*f(g) + c2*f(h)

Therefore G is isomorphic to K^n

Another way to prove G is isomorphic to K^n is to show that
dim(G) = dim(K^n) = n. You can do this by showing that a basis for G has n elements. As an exercise (if you feel like it), give a basis for G, ie: provide a subset of G which is linearly independent and spans G .
 
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wurth_skidder_23 said:
Sorry, my book isn't very clear, either. That was part of the problem. Here is the full problem statement.

Examples of Linear Spaces.
(i) Set of all row vectors: (a1,...,an), aj in K; addition, multiplication defined componentwise. This space is denoted as K^n.
(iii) Set of all functions with values in K, defined on an arbitrary set S.
Show that if S has n elements, (i) is the same as (iii).

As nocturnal said, this is quite different, and much clearer than what you said. I imagine your book also said, earlier, that K is a field. If S is a set with n elements, say k1, k2, ... kn, then the "functions" are functions that assign f(k[subthe]i[/sub]= ap, etc., members of K.
Do you understand that the set of vectors {(1, 0, 0, ..., 0), (0, 1, 0, ..., 0), ... , (0, 0, ..., 1)} form a basis for K^n? What about the function
f(k1= 1, f(kn)= 0 for n n[itex]\ne[/itex] 1?
What about the function g(k2)= 1, g(kn)= 0 is n[itex]\ne[/itex] 2?
 

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