I ##L^2## - space equivalence classes and norm

Click For Summary
The ##L^2##-space is defined as equivalence classes of squared integrable measurable functions on the measure space ##(\Omega, \mathcal A, \mu)##, where the equivalence relation states that two functions are equivalent if they are equal almost everywhere. The norm is defined as the square root of the integral of the square of the function, specifically $$||f|| = \left( \int_{\Omega} |f|^2 \, d{\mu} \right)^{1/2}$$. It is established that if two functions are equal almost everywhere, their norms are equal, but the converse does not hold, as shown with the counterexample of constant functions differing on a set of measure zero. The discussion emphasizes the necessity of working with equivalence classes to address the issue of functions having zero norm despite being distinct. Ultimately, the equivalence relation is refined to state that two functions are equivalent if their difference has zero norm.
cianfa72
Messages
2,880
Reaction score
302
TL;DR
##L^2##-space as set of equivalence classes of squared integrable measurable functions
##L^2##-space is defined as equivalence classes on the set ##\mathcal L^2## of squared integrable measurable functions ##f## defined on the measure space ##(\Omega, \mathcal A, \mu)##.

The equivalence relation ##\sim## is: ##f \sim g## iff ##f=g## almost everywhere (a.e.).

Prove that the above is equivalent to ##||f|| = ||g||##. The norm ##|| \, . ||## is defined as $$\int_{\Omega} {| \, . |}^2 \, d{\mu}$$
My attempt
Consider the map ##|f| - |g|## that is measurable since ##f,g## are. ##|f| - |g| \neq 0## on a subset of the (measurable) set ##A## where ##(f - g)## is, therefore such subset (that is measurable itself) has measure 0. Hence $$\int_{\Omega} {|f| - |g|} \, d{\mu} = 0$$ i.e. by linearity $$\int_{\Omega} {|f|} \, d{\mu} = \int_{\Omega} {|g|} \, d{\mu}$$
Same argument applies to ##|f|^2 - |g|^2##.

Does the above make sense ? Thanks.
 
Last edited:
Physics news on Phys.org
cianfa72 said:
TL;DR Summary: ##L^2##-space as set of equivalence classes of squared integrable measurable functions

##L^2##-space is defined as equivalence classes on the set ##\mathcal L^2## of squared integrable measurable functions ##f## defined on the measure space ##(\Omega, \mathcal A, \mu)##.

The equivalence relation ##\sim## is: ##f \sim g## iff ##f=g## almost everywhere (a.e.).

Prove that the above is equivalent to ##||f|| = ||g||##. The norm ##|| \, . ||## is defined as $$\int_{\Omega} {| \, . |}^2 \, d{\mu}$$

This is not a norm: you need to take the square root of it for it to satisfy the property \|af\| = |a|\|f\| for constant a.

I think the equivalence that you are looking for is that f = g a.e. is equivalent to \|f - g\| = 0.

f = g almost everywhere implies \|f\| = \|g\|, but the converse does not hold: Take f = 1, g = -1 and \Omega = [0,1] for a counterexample.

One of the axioms of a norm is that \|f\| = 0 if and only if f is the zero vector; for functions under pointwise addition the zero vector is the function which is identically zero. But for the L^2 norm, a function which is different from zero on a set of measure zero - and is therefore distinct from the zero vector - will have zero norm. We fix this by working instead with equivalance classes, with functions defined to be equivalent if and only if they differ from each other by a function with zero norm, i.e. f \sim g \quad\Leftrightarrow \quad \|f - g\| = 0.
 
pasmith said:
This is not a norm: you need to take the square root of it for it to satisfy the property \|af\| = |a|\|f\| for constant a.
Ok yes, definitely. It is actually $$\left( \int_{\Omega} {| \, . |}^2 \, d{\mu} \right)^{\frac 1 2}$$
pasmith said:
f = g almost everywhere implies \|f\| = \|g\|, but the converse does not hold: Take f = 1, g = -1 and \Omega = [0,1] for a counterexample.
Ok, yes.

pasmith said:
One of the axioms of a norm is that \|f\| = 0 if and only if f is the zero vector; for functions under pointwise addition the zero vector is the function which is identically zero. But for the L^2 norm, a function which is different from zero on a set of measure zero - and is therefore distinct from the zero vector - will have zero norm. We fix this by working instead with equivalance classes, with functions defined to be equivalent if and only if they differ from each other by a function with zero norm, i.e. f \sim g \quad\Leftrightarrow \quad \|f - g\| = 0.
Ok, in the specific case the latter equivalence boils down to ##{|f - g|}^2 \neq 0## if and only if ##f \neq g##. Therefore both hold true on the same (measurable) set ##A## with measure 0. This is true for any p-norm.
 
Last edited:
pasmith said:
We fix this by working instead with equivalance classes, with functions defined to be equivalent if and only if they differ from each other by a function with zero norm, i.e. f \sim g \quad\Leftrightarrow \quad \|f - g\| = 0.
BTW, I'd say they are defined to be equivalent iff they differ each other by a function with zero "semi-norm" i.e. w.r.t. the map that will be promoted to a full norm when considering the set of equivalence classes being defined.
 
Last edited:
cianfa72 said:
BTW, I'd say they are defined to be equivalent iff they differ each other by a function with zero "semi-norm" i.e. w.r.t. the map that will be promoted to a full norm when considering the set of equivalence classes being defined.

Technically yes, although in general usage one refers to \|\cdot\|_p : \mathcal{L}^p \to [0, \infty) : f \mapsto \left(\int_\Omega |f|^p\,d\mu\right)^{1/p} as a norm and writes \|f\|_p for what is technically \|[f]\|_p. It's also possible to find that both the set of functions for which \int_{\Omega} |f|^p\,d\mu exists and the set of equivalence classes of such functions are denoted by \mathcal{L}^p(\Omega).
 
Thread 'Problem with calculating projections of curl using rotation of contour'
Hello! I tried to calculate projections of curl using rotation of coordinate system but I encountered with following problem. Given: ##rot_xA=\frac{\partial A_z}{\partial y}-\frac{\partial A_y}{\partial z}=0## ##rot_yA=\frac{\partial A_x}{\partial z}-\frac{\partial A_z}{\partial x}=1## ##rot_zA=\frac{\partial A_y}{\partial x}-\frac{\partial A_x}{\partial y}=0## I rotated ##yz##-plane of this coordinate system by an angle ##45## degrees about ##x##-axis and used rotation matrix to...

Similar threads

  • · Replies 11 ·
Replies
11
Views
3K
  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 5 ·
Replies
5
Views
3K
  • · Replies 1 ·
Replies
1
Views
1K
  • · Replies 1 ·
Replies
1
Views
3K
Replies
3
Views
2K
  • · Replies 4 ·
Replies
4
Views
2K
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
3K