Dual Representation: Why Use g^{-1}?

In summary, the conversation discusses the concept of dual representation in representation theory, where the dual representation \rho^* is defined as \rho(g^{-1})^t: V^* \to V^* and how it is necessary in order to have a left representation. It is also mentioned that there are other ways to obtain a dual representation, such as taking transposes, and it is derivable from elementary linear/quadratic math. The conversation also touches on the topic of how to make a group act on the dual space, and how the composition of inverting matrices and then transposing them swaps the order of composition.
  • #1
Pietjuh
76
0
I've been starting to study some things about representation theory. I've come to the point where they introduced the dual of a representation.

Suppose that [itex]\rho[/itex] is a representation on a vector space V.
They then define the dual representation [itex]\rho^*[/itex] as:

[tex]\rho^*(g) = \rho(g^{-1})^t: V^* \to V^*[/tex]

But the thing is that I don't see why they use [itex]g^{-1}[/itex] in this definition instead of just g?
 
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  • #2
Because otherwise it would not be a representation (the map would not be a homomorphism, but an anti-homomorphism, that is denoting your notional maps as f, f(gh)=f(h)f(g))
Taking duals interchanges the order of composition, ie it makes a left representation into a right representation, fortunately groups possesses this anti-involution that makes you able to correct it and turn it into a left representation again. Left means make the matrix act on the left, right means make the matrix act on the right.

Notice they *do* actually use g to define the representation p*, ie they do tell you how to work out p*(g), and it is p(g) 'inverse transpose'.

Given some representation p, there are many things that we can do to get another representation. This is just one of them, and it so happens the vector space of the representation is V*.

You shuold check that you do indeed find that the representation

f(g)=p(g) transpose

is not generically (which means 'usually', or 'except for certain cases' such as G being abelian, or p(G) being abelian) a (left) representation, ie the map f is not a group homomorphism.
 
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  • #3
matt grime said:
Taking duals interchanges the order of composition, ie it makes a left representation into a right representation, fortunately groups possesses this anti-involution that makes you able to correct it and turn it into a left representation again. Left means make the matrix act on the left, right means make the matrix act on the right.

Is this the definition of a dual map? Or is it derivable from something else?
 
  • #4
Given a representation, p,V, how can you make G act on the dual space? if f is in the dual space then the *only* obvious action of G on f is to define

g.f(v)=f(g.v)
for all v in V.: remember it suffices to define a linear map by how it acts on vectors, so we defince g.f to be the linear map that sends v go f(g.v).

All this is saying is that End(V) maps to End(V*) by taking transposes. And and (AB)^T = (B^T)(A^T) which we all learned in our first lecture on dual spaces. So it's derivable just from elementary linear/quadratic maths.Let's prove it reverses the order (this is just revision but in a different notation, probably): if you do this (gh).f(v) = f((gh).v)=f(g(h.v))=g.f(h.v)=h.(g.f(v), so it naturally changes the order.

But there is a way to correct this for *group representations*, by making

g.f(v)=f(g^{-1}(v))

for all v.

The composition of inverting matrices and then transposing them swaps the composition over twice.
 
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FAQ: Dual Representation: Why Use g^{-1}?

What is dual representation in mathematics?

Dual representation in mathematics refers to the concept of expressing a mathematical problem or equation in two different ways, using two different mathematical structures or notations. In this case, it specifically refers to the use of the inverse function, g-1, to solve problems.

Why is g-1 used in dual representation?

The use of the inverse function, g-1, allows for a problem to be solved in a different way than the original representation, providing a different perspective and potentially leading to a simpler solution. It also allows for the connection between the two representations, providing a deeper understanding of the problem.

How does using g-1 in dual representation benefit problem-solving?

Using g-1 in dual representation can provide multiple approaches to solving a problem, allowing for more flexibility and potentially leading to more efficient solutions. It also allows for connections to be made between seemingly unrelated concepts, leading to a deeper understanding of the problem.

What are some common applications of dual representation using g-1?

Dual representation using g-1 is commonly used in calculus, where it is used to solve problems involving derivatives and integrals. It is also used in linear algebra, where it is used to solve systems of equations and find inverses of matrices.

Are there any limitations to using g-1 in dual representation?

While g-1 can be a powerful tool in problem-solving, it is not always applicable or necessary. In some cases, using g-1 may lead to more complicated solutions or may not provide any additional insight. It is important to carefully consider when and how to use g-1 in dual representation.

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