Set theory
Suppose we have a predicate φ(x) with a domain D. It seems quite natural to group all x from D which satisfy φ together to form a new object. For example, if φ(x) means x is even and D means all natural numbers, such an object would be ‘all even natural numbers’. Clearly, this is a ‘part’ of the domain D carved by the property φ (also known as the extension of the predicate φ). Such a ‘part’, which may consist of many individuals (e. g., numbers) but is to be treated as a unitary object, is an example of what mathematicians call a set.
Intuitively, a set is an assembly (collection, multitude) of some individuals of arbitrary nature. Clearly, this does not comprise a rigorous definition since assembly and objects are still to be defined. The main mission of the notion of set is to be the uniform object of mathematics, generalizing numbers of various kinds (integer, real, complex etc.), functions, geometric figures and many others.
Apparently, we cannot define such a basic notion via any other. However we can avoid any definition but postulate some rules how sets do ‘behave’. Thus, set is nothing more than a code name for a piece in our game, whose ‘meaning’ is just its part in the game rules. (Much like a bishop in the game of chess retaining the very same ‘meaning’ if we call it an elephant or an officer.) This is the essence of the axiomatic method.
Yet which behavior of sets do we define? Basically, one set A can be an element of another set B. Then we also say that A belongs to B and write A ∈ B. Intuitively, this means that the ‘individual’ A is in the ‘collection’ B. But do not allow this intuition to fool you: our sets are just an abstract model (of mathematical or other realities) and are fully entitled to behave counter-intuitively.
For example, in our model everything is a set, which is not in a good accord with the ‘individual– collection’ interpretation because there is no essential difference between the former and the latter.
Hence, any element of any set is a set itself having some sets as elements and so on. We shall see that there exists an empty set that has no elements at all. But anyway, we postulate that there are no infinite chains of the form
The statement
Lemma 1. For all sets A, B, and C,
A ⊆ A;
if A ⊆ B and B ⊆ C, then A ⊆ C;
A = B iff A ⊆ B and B ⊆ A.
Proof. Let’s prove just the second statement. We need to show that
Corollary. For all sets A, B, and C,
A = A;
if A = B and B = C, then A = C;
if A = B, then B = A.
Are there any sets in existence? Obviously, if there weren’t any, our model would make no sense. We won’t seek a formal reason for this, but rather assume that there exist the well-known sets N = {
If we have some sets (like N and Z), can we define any other? Indeed, the most important mission of our model is to provide (hopefully) safe ways to do so. (Here safe means logically consistent; the explanation shall follow).
“Out of many, one.” Let
Subset specification. Let us recall that we write φ(x) if x satisfies a property (or predicate) φ. For example, even(
Symbols like {x ∈ A | φ(x)} are widely known as set-builder notation.
As was mentioned before, x = x for each x. By definition, x
Lemma 2.
If E is an empty set, then E ⊆ A for each set A.
If sets E1 and E2 are empty, then E1 = E2.
Hence, we have a corollary from lemma
Sets and predicates.
As we have just seen, the subset specification principle allows to form a set of all those elements of some given set A which satisfy a predicate φ. This is one of the most important ideas behind sets indeed. Often, we will replace predicates with sets in mathematical arguments.
For example, assume that we want to formalize the statement “every even number equals the sum of two odd numbers”. Stating from the formalization
we may transform it to
where A and B stand for the sets of even and odd numbers, respectively. Please notice how “satisfying a predicate” has been replaced by “belonging to a set” here. Usually, they would employ a more concise notation (so called bounded quantifiers) in this case:
(to be read as “for each x from A there exist y and z from B such that. . . ” which sounds very intuitive and natural, does not it?).
Bounded quantifiers come in many varieties (∀x ∈ A, ∀x <
Clearly, we can only specify subsets of a given set A via {x ∈ A | φ(x)}. But could not we put together all x in existence (i. e. not only from A) such that x satisfies φ? Historically, this was the first intuition backing the notion of set: any collection of objects having something in common or satisfying some property.
As we shall see in a moment, this intuition proves to be logically inconsistent.
Russell's Paradox. There is no set R such that
Proof. Suppose there is such a set R. At first, assume R
So, one cannot define a set {x | x ∉ x} comprising all sets x satisfying quite a natural condition x
Power set. Let A be a set. Then there exists a set P(A) such that x ∈ P(A)
As ∅ ⊆ A, ∅ ∈ P(A) for any set A. We have P(∅) = {∅}, P(
Union. Let A be a set. Then there exists a set ∪A such that x ∈ ∪A
Algebra of sets.
For arbitrary sets A and B, by A ∪ B we denote the set ∪{A, B}, which is called the union of the sets A and B. It is easy to prove that x
x
Also, we define the intersection
Lemma 3. For any sets A and B, one has A ∩ B ⊆ X ⊆ A ∪ B if X ∈ {A, B}. Also, A
Lemma 4. For any sets A and B, the following statements are equivalent:
Proof. It suffices to show that the first one implies the second, the second implies the third, and the third one implies the first statement.
Suppose that A ⊆ B. By Lemma 3, we get A ∩ B ⊆ A. Let us check if A ⊆ A ∩ B. Consider an arbitrary x ∈ A. Then x ∈ B as A ⊆ B. Hence, x ∈ A ∩ B. By Lemma 1, from A ∩ B ⊆ A and A ⊆ A ∩ B it follows that A ∩ B = A.
Now assume that A ∩ B = A. By Lemma 3, B ⊆ A ∪ B. It remains to prove that A ∪ B ⊆ B. If x ∈ A ∪ B, then x ∈ A or x ∈ B. In the former case, obtain x ∈ A ∩ B from A = A ∩ B, whence x ∈ B. In the latter one, x ∈ B is immediate.
Finally, suppose that A ∪ B = B. By Lemma 3, we have A ⊆ A ∪ B. By assumption, we get A ∪ B ⊆ B, hence A ⊆ B.
Let's set algebra identities. For all sets U and A, B, C ⊆ U:
1. A ∩ B = B ∩ A; A ∪ B = B ∪ A;
2. (A ∩ B) ∩ C = A ∩ (B ∩ C); (A ∪ B) ∪ C = A ∪ (B ∪ C)
3. A ∩ A = A; A ∪ A = A;
4. A ∩ (A ∪ B) = A; A ∪ (A ∩ B) = A;
5. A ∩ (B ∪ C) = (A ∩ B) ∪ (A ∩ C); A ∪ (B ∩ C) = (A ∪ B) ∩ (A ∪ C);
6. A ∩ ∅ = ∅; A ∪ ∅ = A;
The proof is just a rephrasing of logical equivalences for conjunction, disjunction, and negation, which follow from the respective truth tables.
Cartesian product. Most branches of mathematics employ ordered “pairs”, “triplets” etc. E. g., points of the plain are routinely identified with their coordinates, whose order does matter. Indeed, (
For arbitrary sets a and b consider the set (a, b) = {{a}, {a, b}}, which is called an (ordered) pair of sets a и b. The main property of such a pair is the following:
For all sets a, b, c, d, (a, b) = (c, d) ⇐⇒ a = c ∧ b = d.
Proof. Assume that {{a}, {a, b}} = {{c}, {c, d}}. Then {a} ∈ {{c}, {c, d}}, i. e., {a} = {c} or {a} = {c, d}. In the first case, a ∈ {c}, hence a = c. In the second case, c ∈ {a} and c = a again. Thus, a = c.
From the assumption, it also follows that {a, b} = {c} or {a, b} = {c, d}.
In the former case, b ∈ {c}, whence b = c = a. By the assumption, {c, d} = {a} or {c, d} = {a, b}. Therefore, d = a or d = b. Anyway, b = d.
Now suppose that {a, b} = {c, d}. If d = b, there is nothing to prove. Otherwise, d = a = c, i. e., {a, b} = {d}, whence b = d again.
For the other implication, it suffices to recall that equal sets are fully interchangeable; so, from (a, b) = (a, b), a = c and b = d, it follows that (a, b) = (c, d).