Elementary Sets and their Measures

In summary: I'm not sure what to call it, but if I say each collection of boxes then I am afraid that the statement is not true because the notation ##X=B_1 \cup \ldots \cup B_k## and ##Y=B'_1 \cup \ldots \cup B'_{k'}## is not unique.
  • #1
jamilmalik
14
0

Homework Statement


I am struggling with what seems like a very simple problem from Terrence Tao's Introduction to Measure Theory book (which is available for free online by the way). What I am trying to prove is the following:
Give an alternate proof of Lemma 1.1.2(ii) by showing that any two partitions of ##E## into boxes admit a mutual refinement into boxes that arise from taking Cartesian products of elements from finite collections of disjoint intervals.

Homework Equations


The referenced Lemma is provided below:

**Lemma 1.1.2** (Measure of an elementary set). Let ##E \subset \mathbb{R}^d## be an elementary set.

1. ##E## can be expressed as the finite union of disjoint boxes.
2. If ##E## is partitioned as the finite union ##B_1 \cup \ldots \cup B_k## of disjoint boxes, then the quantity ##m(E):=|B_1|+ \ldots + |B_k|## is independent of the partition. In other words, given any other partition ##B'_1 \cup \ldots \cup B'_{k'}## of ##E##, one has
##|B_1|+ \ldots + |B_k| = |B'_1|+ \ldots + |B'_{k'}|##.

The Attempt at a Solution


The proof that is provided in the text uses a discretization argument that I do not understand, but the problem at hand is to show the same result holds regardless of the partition used. My approach was to let ##X=B_1 \cup \ldots \cup B_k## and ##Y=B'_1 \cup \ldots \cup B'_{k'}## and then show that ##X=Y##. I can rewrite both of these sets as
##X=\bigcup\limits _{i=1}^kB_i## and ##Y=\bigcup\limits_{j=1}^{k'}B'_j##, but then I am confused on how to proceed to show their measures are equivalent. The problem states to use Cartesian products, but I notice that my attempt does not seem to use it which is why I am starting to think that I am on the wrong path. Any assistance, suggestions, and/or advice on this would be greatly appreciated. Many thanks in advance.
 
Last edited:
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  • #2
jamilmalik said:

Homework Statement


I am struggling with what seems like a very simple problem from Terrence Tao's Introduction to Measure Theory book (which is available for free online by the way). What I am trying to prove is the following:
Give an alternate proof of Lemma 1.1.2(ii) by showing that any two partitions of ##E## into boxes admit a mutual refinement into boxes that arise from taking Cartesian products of elements from finite collections of disjoint intervals.


Homework Equations


The referenced Lemma is provided below:

**Lemma 1.1.2** (Measure of an elementary set). Let ##E \subset \mathbb{R}^d## be an elementary set.

1. ##E## can be expressed as the finite union of disjoint boxes.
2. If ##E## is partitioned as the finite union ##B_1 \cup \ldots \cup B_k## of disjoint boxes, then the quantity ##m(E):=|B_1|+ \ldots + |B_k|## is independent of the partition. In other words, given any other partition ##B'_1 \cup \ldots \cup B'_{k'}## of ##E##, one has
##|B_1|+ \ldots + |B_k| = |B'_1|+ \ldots + |B'_{k'}|##.


The Attempt at a Solution


The proof that is provided in the text uses a discretization argument that I do not understand, but the problem at hand is to show the same result holds regardless of the partition used. My approach was to let ##X=B_1 \cup \ldots \cup B_k## and ##Y=B'_1 \cup \ldots \cup B'_{k'}## and then show that ##X=Y##. I can rewrite both of these sets as
##X=\bigcup\limits _{i=1}^kB_i## and ##Y=\bigcup\limits_{j=1}^{k'}B'_j##, but then I am confused on how to proceed to show their measures are equivalent. The problem states to use Cartesian products, but I notice that my attempt does not seem to use it which is why I am starting to think that I am on the wrong path. Any assistance, suggestions, and/or advice on this would be greatly appreciated. Many thanks in advance.

Does this help? Consider the set ##\{x \cap y : x \in X \land y \in Y\}##. (Sorry, I meant intersection here.) Try to push this all the way to success.

I think I can't give more help, unfortunately.
 
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  • #3
Please don't post the same thing in two different forums. If you feel that you have posted something in the wrong forum, use the report button to ask the moderators to move it. I understand that you wanted to add the template as well, but you could at least have made a comment about it in the original thread.

This is what I said in the other thread:

It would be easier to answer if you explained your notation and terminology more, and linked to the book. How do you define "elementary set"? (Is your point 1 the definition?) What is a "box"? What does the notation |B| mean?

jamilmalik said:
My approach was to let ##X=B_1 \cup \ldots \cup B_k## and ##Y=B'_1 \cup \ldots \cup B'_{k'}## and then show that ##X=Y##.
Wouldn't these two by definition be equal to E?
 
  • #4
Thanks for the responses. As noted above, I should add some more information regarding the terminology being used. A box in ##\mathbb{R}^d## is a Cartesian product ##B:=I_i \times \ldots \times I_d## of ##d## intervals ##I_1, \ldots , I_d##. The volume ##|B|## of such a box ##B## is defined as ##|B|:= |I_1|\times \cdots \times |I_d|.## An elementary set is any subset of ##\mathbb{R}^d## which is the union of a finite number of boxes.

As for the link, here it is below:
http://terrytao.files.wordpress.com/2011/01/measure-book1.pdf
 
  • #5
verty said:
Does this help? Consider the set ##\{x \cap y : x \in X \land y \in Y\}##. (Sorry, I meant intersection here.) Try to push this all the way to success.

I think I can't give more help, unfortunately.

What do you mean by an intersection was intended there?
 
  • #6
Fredrik said:
Wouldn't these two by definition be equal to E?

Yes, I think it would be equal to ##E##. However I am skeptical if it was really that simple. I don't think I actually proved anything, but rather assigned a variable for each collection of unions.
 
  • #7
jamilmalik said:
Yes, I think it would be equal to ##E##. However I am skeptical if it was really that simple. I don't think I actually proved anything, but rather assigned a variable for each collection of unions.
Right, if you prove that X=Y, you have proved nothing, since they're both equal to E by assumption.

You need to prove that if ##\bigcup_i B_i =E=\bigcup_j B'_j##, then ##\sum_i|B_i|=\sum_j|B'_j|##.

So the equality ##\bigcup_i B_i =\bigcup_j B'_j## is your starting point, not a result to be proved. I would try to use the fact that for each i and each j, ##B_i\cap B'_j## is a box.
 

Related to Elementary Sets and their Measures

1. What are sets and how are they defined?

Sets are a fundamental concept in mathematics and refer to a collection of distinct elements or objects. They can be defined as a well-defined collection of objects, and each object in the set is called an element. Sets are typically denoted by capital letters and their elements are listed within curly brackets.

2. What is the cardinality of a set?

The cardinality of a set refers to the number of elements in the set. It can be finite (a set with a specific number of elements) or infinite (a set with an uncountable number of elements). The cardinality of a set is denoted by the symbol |A|, where A is the set.

3. How are sets related to measures?

Sets and measures are closely related in mathematics. Measures are used to quantify the size of a set or the amount of a particular property or attribute within a set. For example, the measure of a set of numbers could be its sum, average, or range. Measures are important in understanding the properties and characteristics of a set.

4. What is the difference between a finite and infinite set?

A finite set is a set with a specific and countable number of elements, while an infinite set has an uncountable number of elements. Finite sets are typically denoted by using a comma to separate their elements, while infinite sets are often denoted using ellipses or the infinity symbol (∞).

5. How are sets and their measures used in real-world applications?

Sets and their measures have various applications in the real world, including data analysis, statistics, and probability. They are used to classify and organize data, determine patterns and relationships, and make predictions and decisions. For example, measures such as mean, median, and standard deviation are commonly used in data analysis to understand and interpret data sets.

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