Absolutely Continuous Measures: Difference between revisions

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==Examples==
==Examples==
Recall that if <math> f:X\rightarrow [0,\infty]</math> is a measurable function, then the set function <math> \mu_2(T) = \int_{T} f \,d\mu_1</math> for <math> T\in \mathcal{M}</math> is a measure on <math> (X,\mathcal{M},\mu_1) </math>. Observe that if <math> \mu_1(T) = 0</math>, then <math> \mu_2(T) = \int_{X} f\cdot \chi_T \,d\mu_1 = 0</math> so that <math> \mu_2 \ll \mu_1 </math>.
Recall that if <math> f:X\rightarrow [0,\infty]</math> is a measurable function, then the set function <math> \mu_2(T) = \int_{T} f \,d\mu_1</math> for <math> T\in \mathcal{M}</math> is a measure on <math> (X,\mathcal{M},\mu_1) </math>. Observe that if <math> \mu_1(T) = 0</math>, then <math> \mu_2(T) = \int_{X} f\cdot \chi_T \,d\mu_1 = 0</math> so that <math> \mu_2 \ll \mu_1 </math> (see [3] for further details on this example and others).
==Properties==
==Properties==
It was previously established on a homework problem that for some nonnegative measurable <math> f\in L^1(\mu_1)</math> defined on the measure space <math> (X,\mathcal{M},\mu_1) </math> and some arbitrarily chosen <math> \epsilon > 0</math>, there exists <math> \delta > 0 </math> such that <math> \int_{T} f \,d\mu_1 < \epsilon</math> whenever <math> \mu_1(T) < \delta</math> (see [2]). The method that was used to establish this result can also be used to show that, in a finite measure space, if <math> \mu_2 \ll \mu_1</math>, then for some arbitrarily chosen <math> \epsilon > 0</math>, there exists <math> \delta > 0 </math> such that <math> \mu_2(T) < \epsilon </math> whenever <math> \mu_1(T) < \delta</math>.  
It was previously established on a homework problem that for some nonnegative measurable <math> f\in L^1(\mu_1)</math> defined on the measure space <math> (X,\mathcal{M},\mu_1) </math> and some arbitrarily chosen <math> \epsilon > 0</math>, there exists <math> \delta > 0 </math> such that <math> \int_{T} f \,d\mu_1 < \epsilon</math> whenever <math> \mu_1(T) < \delta</math> (see [2]). The method that was used to establish this result can also be used to show that, in a finite measure space, if <math> \mu_2 \ll \mu_1</math>, then for some arbitrarily chosen <math> \epsilon > 0</math>, there exists <math> \delta > 0 </math> such that <math> \mu_2(T) < \epsilon </math> whenever <math> \mu_1(T) < \delta</math>.  


:In particular, we proceed by contradiction and suppose there exists <math> \epsilon > 0</math> so that for any <math> \delta > 0 </math> and <math> \mu_1(T) < \delta</math>, we have <math> \mu_2(T) \geq \epsilon </math>. Now, define a sequence of sets <math> \{T_n\}_{n\in \mathbb{N}}\subseteq \mathcal{M}</math> such that <math> \mu_1(T_n) < \frac{\epsilon}{2^n}</math> and denote <math> T=\limsup{T_n}=\cap_{n=1}^{\infty} G_n \in \mathcal{M}</math> where <math> G_n = \cup_{k=n}^{\infty}T_k</math>. We have from countable subadditivity that <math> \mu_1(G_n) \leq \sum_{k=n}^{\infty} \mu_1(T_k)<\sum_{k=n}^{\infty} \frac{\epsilon}{2^k} = \frac{\epsilon}{2^{n+1}}\,\forall n\in\mathbb{N}</math>. The monotonicity of the measure <math> \mu_1 </math> then implies that <math> \mu_1(\cap_{n=1}^{\infty} G_n)=\mu_1(\limsup{T_n}) = \mu_1(T) = 0 < \delta</math> while <math> \mu_2(T) \geq \epsilon </math>. However, this contradicts the definition of <math>\mu_2 \ll \mu_1</math>.
:In particular, we proceed by contradiction and suppose there exists <math> \epsilon > 0</math> so that for any <math> \delta > 0 </math> and <math> \mu_1(T) < \delta</math>, we have <math> \mu_2(T) \geq \epsilon </math>. Now, define a sequence of sets <math> \{T_n\}_{n\in \mathbb{N}}\subseteq \mathcal{M}</math> such that <math> \mu_1(T_n) < \frac{\epsilon}{2^n}</math> and denote <math> T=\limsup{T_n}=\cap_{n=1}^{\infty} G_n \in \mathcal{M}</math> where <math> G_n = \cup_{k=n}^{\infty}T_k</math>. We have from countable subadditivity that <math> \mu_1(G_n) \leq \sum_{k=n}^{\infty} \mu_1(T_k)<\sum_{k=n}^{\infty} \frac{\epsilon}{2^k} = \frac{\epsilon}{2^{n+1}}\,\forall n\in\mathbb{N}</math>. We have from monotonicity that <math> \mu_2(G_n) \geq \epsilon \, \forall n\in \mathbb{N} </math>. The monotonicity of the measure <math> \mu_1 </math> implies that <math> \mu_1(\cap_{n=1}^{\infty} G_n)=\mu_1(\limsup{T_n}) = \mu_1(T) = 0 < \delta</math>. Using continuity from above, we also have <math> \mu_2(T) \geq \epsilon </math>. However, this contradicts the definition of <math>\mu_2 \ll \mu_1</math>.
 
In fact, the converse to the above result also holds (see [3]). Namely, if we have <math> \forall \epsilon > 0</math> that there exists <math> \delta > 0</math> so that <math> \mu_2(T) < epsilon</math> whenever <math> \mu_1(T) < \delta</math>, then <math> \mu_2 \ll \mu_1</math>.
==References==
==References==
[1]: Taylor, M. "Measure Theory and Integration". 50-51.
[1]: Taylor, M. "Measure Theory and Integration". 50-51.


[2]: Craig, K. "Math 201a: Homework 8". Refer to question 2.
[2]: Craig, K. "Math 201a: Homework 8". Refer to question 2.
[3]: Rana, I. K. "Introduction to Measure and Integration". Second Edition. 311-313.

Revision as of 19:24, 18 December 2020

Definitions

Let be a measure space. The measure is said to be absolutely continuous with respect to the measure if we have that for such that (see [1]). In this case, we denote that is absolutely continuous with respect to by writing .

Examples

Recall that if is a measurable function, then the set function for is a measure on . Observe that if , then so that (see [3] for further details on this example and others).

Properties

It was previously established on a homework problem that for some nonnegative measurable defined on the measure space and some arbitrarily chosen , there exists such that whenever (see [2]). The method that was used to establish this result can also be used to show that, in a finite measure space, if , then for some arbitrarily chosen , there exists such that whenever .

In particular, we proceed by contradiction and suppose there exists so that for any and , we have . Now, define a sequence of sets such that and denote where . We have from countable subadditivity that . We have from monotonicity that . The monotonicity of the measure implies that . Using continuity from above, we also have . However, this contradicts the definition of .

In fact, the converse to the above result also holds (see [3]). Namely, if we have that there exists so that whenever , then .

References

[1]: Taylor, M. "Measure Theory and Integration". 50-51.

[2]: Craig, K. "Math 201a: Homework 8". Refer to question 2.

[3]: Rana, I. K. "Introduction to Measure and Integration". Second Edition. 311-313.