Understanding Adjoint Operators: A Helpful Explanation and Example

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In summary, an adjoint operator is a linear map that allows for moving an operator from one side of an inner product to the other. It is defined on an inner product space and has the property that the inner product of a vector and the result of applying the original operator to another vector is equal to the inner product of the adjoint of the original operator and the first vector.
  • #1
member 428835
hey pf!

can you help me understand what an adjoint operator is? I've read lots of threads and other sites, but am having trouble. maybe you could give me an example?

for example, does the operator d/dx have an adjoint? is asking this question completely stupid of me?

thanks!
 
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  • #2
First of all you need to have an inner product space (there are other ways to define it, in my functional analysis class we defined adjoints on general Banach spaces. But don't worry about that). We generally assume that the inner product space is "complete" or Hilbert. Don't worry about it now if you don't know. We will just consider inner product spaces.

An inner product space is a vector space, ##V## over ##\mathbb{C}## (or ##\mathbb{R}##) with a function defined on it.
$$(,)\colon V \times V \rightarrow \mathbb{C}$$
(or ##\mathbb{R}##)

such that:
##(v,v)\geq 0## for all ##v \in V##
##(v,v)=0## iff ##v=0##
##(u,av+bw)=a(u,v)+b(u,w)## for all ##a,b\in \mathbb{C}## and ##u,v \in V##
##(u,v)=\overline{(v,u)}## for all ##u,v\in V##

If you have a linear map, ##A\colon V\rightarrow V##, the adjoint ##A^{\ast}## is a linear map such that:
##(u,Av)=(A^{\ast}u,v)## for all ##u,v\in V##

Basically, the adjoint is what allows you to move an operator from one side of an inner product to the other. So in your question, what is the adjoint of ##\frac{d}{dx}##? First of all you need an inner product space. Let ##V=C^{\infty}_{c}(\mathbb{R})## be the vector space of all compactly supported smooth functions (for simplicity, let's consider only real functions). You can check that this is a vector space (proof is LTR =) ), let the inner product be:
$$(f,g)=\int_{-\infty}^{\infty} f(x) g(x) dx$$
So
$$(f,\frac{dg}{dx})=\int_{-\infty}^{\infty} f(x)\frac{dg}{dx}(x) dx$$
We may integrate by parts
$$(f,\frac{dg}{dx})= f(x)g(x)|_{-\infty}^{\infty}-\int_{-\infty}^{\infty} \frac{df}{dx}(x) g(x)dx$$
Since the functions are compactly supported, end terms disappear, so
$$(f,\frac{dg}{dx})= -\int_{-\infty}^{\infty} \frac{df}{dx}(x) g(x)dx$$
Therefore
$$(f,\frac{dg}{dx})=(-\frac{df}{dx},g)$$
So on this space, the adjoint of ##\frac{d}{dx}## is ##-\frac{d}{dx}##.
However this is just on this space! If we assumed that there are boundary terms, it gets more complicated, if we are over complex numbers it gets more complicated. If functions aren't smooth, or even differentiable, it gets way more complicated.
 
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  • #3
thanks! i really appreciate that! i have a much better idea what is going on. could you help me on a very remaining points?

johnqwertyful said:
##V=C^{\infty}_{c}(\mathbb{R})## be the vector space of all compactly supported smooth functions
sorry, but what does this notation mean and what do you mean my "compactly supported smooth functions"?

johnqwertyful said:
Since the functions are compactly supported, end terms disappear
maybe i'll know why once i understand compactly supported, but why is ## f(x)g(x)|_{-\infty}^{\infty}=0##?

thanks again!
 
  • #4
Compactly supported means that the function is 0 outside of some interval.
Smooth means infinitely differentiable.
 
  • #5
johnqwertyful said:
Compactly supported means that the function is 0 outside of some interval.
i see. does this relate to closed and bounded at all, or are you speaking of some other compact definition?
 
  • #6
Compactly supported means the function is 0 outside of some compact set.
 
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  • #7
Also compact means that every open cover has a finite subcover. "closed and bounded" is not a definition, but a theorem. A set of real numbers is compact iff it is closed and bounded.
 
  • #8
Yea, the HB theorem I think (it's been a while since analysis). Weird, why do they call it compactly supported? (I know that's more of a history buff)
 
  • #9
http://en.wikipedia.org/wiki/Support_(mathematics )

The support of a function is where it doesn't vanish. I was being loose at first, because I didn't think you knew what compact meant. Compactly supported means that it vanishes on all but a compact set. I said "vanishes outside of an interval" because if the function vanishes outside of a compact set, there is an interval around the compact set.

None of this matters to the point I was making. The point was that the end terms vanish.
 
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  • #10
joshmccraney said:
hey pf!

can you help me understand what an adjoint operator is? I've read lots of threads and other sites, but am having trouble. maybe you could give me an example?

for example, does the operator d/dx have an adjoint? is asking this question completely stupid of me?

thanks!

Think of the Riesz rep. theorem as related/motivation. Maybe a good exercise to show that
in R^n, if the map is described by a matrix A, then the adjoint is A^T, the transpose. Note that in the infinite-dimensional case, the adjoint may not exist.
 
  • #11
I'm using the physicist's convention for inner products, so my inner product is linear in the second variable and antilinear (=conjugate linear) in the first.

Let H be a Hilbert space over ##\mathbb C##. For each ##x\in H##, I will use the notation ##\langle x,\cdot\rangle## for the map ##y\mapsto \langle x,y\rangle## with domain H. The Riesz representation theorem tells us that for each ##\phi\in H^*## (where H* is the set of bounded linear maps from ##H## into ##\mathbb C##), there's a unique ##x\in H## such that ##\phi=\langle x,\cdot\rangle##.

Let A be a bounded linear operator on H. For each ##x\in H##, the map ##y\mapsto\langle x,Ay\rangle## with domain A is linear and bounded. (It's elementary to show linearity. Boundedness follows from the Cauchy-Schwartz inequality). Let's denote this map by ##\phi_{x,A}##. The Riesz representation theorem tells us that there's a unique ##z\in H## such that ##\phi_{x,A}=\langle z,\cdot\rangle##. The map ##x\mapsto z## with domain H is what we call the adjoint of A. It's denoted by ##A^*## or ##A^\dagger##, so we can write ##A^*x=z##.

What I said in the preceding paragraph implies that for all ##x,y\in H##, we have
$$\langle x,Ay\rangle =\phi_{x,A}(y) =\langle z,y\rangle =\langle A^*x,y\rangle.$$
This isn't super easy, but it can't be made much easier than this if you want it done rigorously.

The definition, and proof of existence, for not necessarily bounded operators (like d/dx) is similar to the above, but it's more complicated, because we have to pay attention to the domains of both ##A## and ##A^*##.
 

1. What is an adjoint operator?

An adjoint operator is a mathematical concept used to describe the relationship between two vector spaces. It is a linear map that takes a vector from one space and maps it to another space.

2. How is an adjoint operator different from a regular operator?

An adjoint operator is different from a regular operator because it is defined on two different vector spaces, while a regular operator is defined on a single vector space. Additionally, the adjoint operator has unique properties that make it useful in various mathematical applications.

3. What are some examples of adjoint operators?

Some common examples of adjoint operators include the transpose of a matrix, the complex conjugate of a complex number, and the Hermitian conjugate of a quantum mechanical operator.

4. How is the adjoint operator related to the inner product?

The adjoint operator is closely related to the inner product, as it is defined using the inner product. In fact, the adjoint operator can be thought of as a generalization of the transpose, which is used to calculate the inner product for matrices.

5. What is the importance of understanding adjoint operators?

Understanding adjoint operators is crucial in various fields of mathematics, physics, and engineering. They are used in many applications, such as solving differential equations, optimizing functions, and studying quantum mechanics. Having a grasp on adjoint operators can greatly enhance one's understanding and problem-solving abilities in these areas.

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