Calculating an integral norm in L2

In summary, to calculate the operator norm of $T$, we can use the relation $||T||\leq \left ( \int_0^1\int_0^1 |(5s^2t^2+2)|^2dtds\right ) ^{\frac{1}{2}}$ and find the largest eigenvalue of the matrix of coefficients of $T$ when restricted to the two-dimensional subspace spanned by $f_1(s)=1$ and $f_2(s)=\frac32\sqrt5\bigl(s^2-\frac13\bigr)$. This reduces the problem to finding the norm of a $2\times2$-matrix, which can
  • #1
hmmmmm
28
0
If I have the following operator for $H=L^2(0,1)$:$$Tf(s)=\int_0^1 (5s^2t^2+2)(f(t))dt$$ and I wish to calculate $||T||$, how do I go about doing this:
I know that in $L^2(0,1)$ we have that relation:$$||T||\leq \left ( \int_0^1\int_0^1 |(5s^2t^2+2)|^2dtds\right ) ^{\frac{1}{2}}=\sqrt{\frac{50}{6}}.$$I also have that $||T||=\sup_{||f||_2\leq1} ||Tf(s)||$ so if I take $f=1$ then this gives equality above and I am done, is that correct?Thanks for any help
 
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  • #2
hmmm16 said:
If I have the following operator for $H=L^2(0,1)$: $$Tf(s)=\int_0^1 (5s^2t^2+2)(f(t))dt$$ and I wish to calculate $||T||$, how do I go about doing this:

I know that in $L^2(0,1)$ we have that relation: $$||T||\leq \left ( \int_0^1\int_0^1 |(5s^2t^2+2)|^2dtds\right ) ^{\frac{1}{2}}=\sqrt{\frac{50}{6}}.$$
Check that you have done this correctly! I make the answer $\dfrac{\sqrt{65}}3$.

hmmm16 said:
I also have that $||T||=\sup_{||f||_2\leq1} ||Tf(s)||$ so if I take $f=1$ then this gives equality above and I am done, is that correct?
I do not understand that at all, and I don't believe it.

To find the operator norm of $T$, notice first that because the kernel $k(s,t) = 5s^2t^2+2$ is real-valued and symmetric in $s$ and $t$, it follows that $T$ is selfadjoint. Next, notice that, for any $f\in L^2(0,1)$, $$Tf(s) = \int_0^1 (5s^2t^2+2)(f(t))\,dt = s^2\int_0^15t^2f(t)\,dt + \int_0^12f(t)\,dt,$$ so that $T(f)$ lies in the two-dimensional subspace of $L^2(0,1)$ spanned by the functions $f(s) = s^2$ and $f(s) = 1$. Since $T$ is selfadjoint, its norm will be the norm of its restriction to that subspace.

So the strategy for finding $\|T\|$ is (1) use Gram–Schmidt to find an orthonormal basis for that subspace (I think that you can take the functions $f_1(s) = 1$ and $f_2(s) = \frac32\sqrt5\bigl(s^2-\frac13\bigr)$, but check that I got that right); (2) find what $T$ does to the two vectors in that basis, expressing $T(f_1)$ and $T(f_2)$ as linear combinations of $f_1$ and $f_2$.

That way, you reduce the problem to finding the norm of the $2\times2$-matrix of those coefficients. What's more, the matrix will be hermitian (because $T$ is selfadjoint), and the norm of the matrix will be equal to the size of its larger eigenvalue (in absolute value).

Operators given by integral kernels are always compact, and in this case the operator $T$ has finite rank 2. That is what makes it possible to find its norm explicitly.
 

FAQ: Calculating an integral norm in L2

What is the L2 norm?

The L2 norm is a mathematical concept used to measure the size or magnitude of a vector. In the context of calculating an integral norm in L2, it refers to the length of a function in the L2 space.

How is the L2 norm calculated?

The L2 norm is calculated by taking the square root of the sum of the squared values of all the elements in a vector or function.

Why is the L2 norm important?

The L2 norm is important because it allows us to measure the distance between two functions or vectors in the L2 space. It also plays a crucial role in various mathematical and statistical applications, such as signal processing, data compression, and machine learning.

What is the difference between the L2 norm and other norms?

The main difference between the L2 norm and other norms is how they measure the size or magnitude of a vector. The L2 norm considers the squared values of the elements, while other norms may use absolute values or higher powers of the elements. Additionally, the L2 norm is commonly used in applications that require a measure of distance or similarity, while other norms may be more suitable for specific purposes.

How is the L2 norm used in calculating integrals?

In the context of calculating an integral norm in L2, the L2 norm is used to measure the size of a function in the L2 space, which is necessary to determine the convergence of an integral. By comparing the L2 norm of the function with a given threshold, we can determine if the integral is convergent or not.

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