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List of set identities and relations

This article lists mathematical properties and laws of sets, involving the set-theoretic operations of union, intersection, and complementation and the relations of set equality and set inclusion. It also provides systematic procedures for evaluating expressions, and performing calculations, involving these operations and relations.

The binary operations of set union () and intersection () satisfy many identities. Several of these identities or "laws" have well established names.

Notation

Throughout this article, capital letters (such as and ) will denote sets. On the left hand side of an identity, typically,

  • will be the Left most set,
  • will be the M iddle set, and
  • will be the R ight most set.

This is to facilitate applying identities to expressions that are complicated or use the same symbols as the identity.[note 1] For example, the identity may be read as:

Elementary set operations

For sets and define: and where the symmetric difference is sometimes denoted by and equals:[1][2]

One set is said to intersect another set if Sets that do not intersect are said to be disjoint.

The power set of is the set of all subsets of and will be denoted by

Universe set and complement notation

The notation may be used if is a subset of some set that is understood (say from context, or because it is clearly stated what the superset is). It is emphasized that the definition of depends on context. For instance, had been declared as a subset of with the sets and not necessarily related to each other in any way, then would likely mean instead of

If it is needed then unless indicated otherwise, it should be assumed that denotes the universe set, which means that all sets that are used in the formula are subsets of In particular, the complement of a set will be denoted by where unless indicated otherwise, it should be assumed that denotes the complement of in (the universe)

One subset involved

Assume

Identity:[3]

Definition: is called a left identity element of a binary operator if for all and it is called a right identity element of if for all A left identity element that is also a right identity element if called an identity element.

The empty set is an identity element of binary union and symmetric difference and it is also a right identity element of set subtraction

but is not a left identity element of since so if and only if

Idempotence[3] and Nilpotence :

Domination[3]/Absorbing element:

Definition: is called a left absorbing element of a binary operator if for all and it is called a right absorbing element of if for all A left absorbing element that is also a right absorbing element if called an absorbing element. Absorbing elements are also sometime called annihilating elements or zero elements.

A universe set is an absorbing element of binary union The empty set is an absorbing element of binary intersection and binary Cartesian product and it is also a left absorbing element of set subtraction

but is not a right absorbing element of set subtraction since where if and only if

Double complement or involution law:

[3]

[3]

Two sets involved

In the left hand sides of the following identities, is the L eft most set and is the R ight most set. Assume both are subsets of some universe set

Formulas for binary set operations ⋂, ⋃, \, and ∆

In the left hand sides of the following identities, is the L eft most set and is the R ight most set. Whenever necessary, both should be assumed to be subsets of some universe set so that

De Morgan's laws

De Morgan's laws state that for

Commutativity

Unions, intersection, and symmetric difference are commutative operations:[3]

Set subtraction is not commutative. However, the commutativity of set subtraction can be characterized: from it follows that: Said differently, if distinct symbols always represented distinct sets, then the only true formulas of the form that could be written would be those involving a single symbol; that is, those of the form: But such formulas are necessarily true for every binary operation (because must hold by definition of equality), and so in this sense, set subtraction is as diametrically opposite to being commutative as is possible for a binary operation. Set subtraction is also neither left alternative nor right alternative; instead, if and only if if and only if Set subtraction is quasi-commutative and satisfies the Jordan identity.

Other identities involving two sets

Absorption laws:

Other properties

Intervals:

Subsets ⊆ and supersets ⊇

The following statements are equivalent for any [3]

    • Definition of subset: if then
  1. and are disjoint (that is, )
  2. (that is, )

The following statements are equivalent for any

  1. There exists some

Set equality

The following statements are equivalent:

  • If then if and only if
  • Uniqueness of complements: If then
Empty set

A set is empty if the sentence is true, where the notation is shorthand for

If is any set then the following are equivalent:

  1. is not empty, meaning that the sentence is true (literally, the logical negation of " is empty" holds true).
  2. (In classical mathematics) is inhabited, meaning:
    • In constructive mathematics, "not empty" and "inhabited" are not equivalent: every inhabited set is not empty but the converse is not always guaranteed; that is, in constructive mathematics, a set that is not empty (where by definition, " is empty" means that the statement is true) might not have an inhabitant (which is an such that ).
  3. for some set

If is any set then the following are equivalent:

  1. is empty (), meaning:
  2. for every set
  3. for every set
  4. for some/every set

Given any the following are equivalent:

Moreover,

Meets, Joins, and lattice properties

Inclusion is a partial order: Explicitly, this means that inclusion which is a binary operation, has the following three properties:[3]

  • Reflexivity:
  • Antisymmetry:
  • Transitivity:

The following proposition says that for any set the power set of ordered by inclusion, is a bounded lattice, and hence together with the distributive and complement laws above, show that it is a Boolean algebra.

Existence of a least element and a greatest element:

Joins/supremums exist:[3]

The union is the join/supremum of and with respect to because:

  1. and and
  2. if is a set such that and then

The intersection is the join/supremum of and with respect to

Meets/infimums exist:[3]

The intersection is the meet/infimum of and with respect to because:

  1. if and and
  2. if is a set such that and then

The union is the meet/infimum of and with respect to

Other inclusion properties:

  • If then
  • If and then [3]

Three sets involved

In the left hand sides of the following identities, is the L eft most set, is the M iddle set, and is the R ight most set.

Precedence rules

There is no universal agreement on the order of precedence of the basic set operators. Nevertheless, many authors use precedence rules for set operators, although these rules vary with the author.

One common convention is to associate intersection with logical conjunction (and) and associate union with logical disjunction (or) and then transfer the precedence of these logical operators (where has precedence over ) to these set operators, thereby giving precedence over So for example, would mean since it would be associated with the logical statement and similarly, would mean since it would be associated with

Sometimes, set complement (subtraction) is also associated with logical complement (not) in which case it will have the highest precedence. More specifically, is rewritten so that for example, would mean since it would be rewritten as the logical statement which is equal to For another example, because means which is equal to both and (where was rewritten as ), the formula would refer to the set moreover, since this set is also equal to (other set identities can similarly be deduced from propositional calculus identities in this way). However, because set subtraction is not associative a formula such as would be ambiguous; for this reason, among others, set subtraction is often not assigned any precedence at all.

Symmetric difference is sometimes associated with exclusive or (xor) (also sometimes denoted by ), in which case if the order of precedence from highest to lowest is then the order of precedence (from highest to lowest) for the set operators would be There is no universal agreement on the precedence of exclusive disjunction with respect to the other logical connectives, which is why symmetric difference is not often assigned a precedence.

Associativity

Definition: A binary operator is called associative if always holds.

The following set operators are associative:[3]

For set subtraction, instead of associativity, only the following is always guaranteed: where equality holds if and only if (this condition does not depend on ). Thus if and only if where the only difference between the left and right hand side set equalities is that the locations of have been swapped.

Distributivity

Definition: If are binary operators then left distributes over if while right distributes over if The operator distributes over if it both left distributes and right distributes over In the definitions above, to transform one side to the other, the innermost operator (the operator inside the parentheses) becomes the outermost operator and the outermost operator becomes the innermost operator.

Right distributivity:[3]

Left distributivity:[3]

Distributivity and symmetric difference ∆

Intersection distributes over symmetric difference:

Union does not distribute over symmetric difference because only the following is guaranteed in general:

Symmetric difference does not distribute over itself: and in general, for any sets (where represents ), might not be a subset, nor a superset, of (and the same is true for ).

Distributivity and set subtraction \

Failure of set subtraction to left distribute:

Set subtraction is right distributive over itself. However, set subtraction is not left distributive over itself because only the following is guaranteed in general: where equality holds if and only if which happens if and only if

For symmetric difference, the sets and are always disjoint. So these two sets are equal if and only if they are both equal to Moreover, if and only if

To investigate the left distributivity of set subtraction over unions or intersections, consider how the sets involved in (both of) De Morgan's laws are all related: always holds (the equalities on the left and right are De Morgan's laws) but equality is not guaranteed in general (that is, the containment might be strict). Equality holds if and only if which happens if and only if

This observation about De Morgan's laws shows that is not left distributive over or because only the following are guaranteed in general: where equality holds for one (or equivalently, for both) of the above two inclusion formulas if and only if

The following statements are equivalent:

  1. that is, left distributes over for these three particular sets
  2. that is, left distributes over for these three particular sets
  3. and

Quasi-commutativity: always holds but in general, However, if and only if if and only if

Set subtraction complexity: To manage the many identities involving set subtraction, this section is divided based on where the set subtraction operation and parentheses are located on the left hand side of the identity. The great variety and (relative) complexity of formulas involving set subtraction (compared to those without it) is in part due to the fact that unlike and set subtraction is neither associative nor commutative and it also is not left distributive over or even over itself.

Two set subtractions

Set subtraction is not associative in general: since only the following is always guaranteed:

(L\M)\R

L\(M\R)

  • If
  • with equality if and only if

One set subtraction

(L\M) ⁎ R

Set subtraction on the left, and parentheses on the left

[4]

L\(M ⁎ R)

Set subtraction on the left, and parentheses on the right

where the above two sets that are the subjects of De Morgan's laws always satisfy

(L ⁎ M)\R

Set subtraction on the right, and parentheses on the left

L ⁎ (M\R)

Set subtraction on the right, and parentheses on the right

[4]

Three operations on three sets

(L • M) ⁎ (M • R)

Operations of the form :

(L • M) ⁎ (R\M)

Operations of the form :

(L\M) ⁎ (L\R)

Operations of the form :

Other simplifications

Other properties:

  • If then [4]
  • If then
  • if and only if for any belongs to at most two of the sets

Symmetric difference ∆ of finitely many sets

Given finitely many sets something belongs to their symmetric difference if and only if it belongs to an odd number of these sets. Explicitly, for any if and only if the cardinality is odd. (Recall that symmetric difference is associative so parentheses are not needed for the set ).

Consequently, the symmetric difference of three sets satisfies:

Cartesian products ⨯ of finitely many sets

Binary ⨯ distributes over ⋃ and ⋂ and \ and ∆

The binary Cartesian productdistributes over unions, intersections, set subtraction, and symmetric difference:

But in general, ⨯ does not distribute over itself:

Binary ⋂ of finite ⨯

Binary ⋃ of finite ⨯

Difference \ of finite ⨯

and

Finite ⨯ of differences \

Symmetric difference ∆ and finite ⨯

In general, need not be a subset nor a superset of

Arbitrary families of sets

Let and be indexed families of sets. Whenever the assumption is needed, then all indexing sets, such as and are assumed to be non-empty.

Definitions

A family of sets or (more briefly) a family refers to a set whose elements are sets.

An indexed family of sets is a function from some set, called its indexing set, into some family of sets. An indexed family of sets will be denoted by where this notation assigns the symbol for the indexing set and for every index assigns the symbol to the value of the function at The function itself may then be denoted by the symbol which is obtained from the notation by replacing the index with a bullet symbol explicitly, is the function: which may be summarized by writing

Any given indexed family of sets (which is a function) can be canonically associated with its image/range (which is a family of sets). Conversely, any given family of sets may be associated with the -indexed family of sets which is technically the identity map However, this is not a bijective correspondence because an indexed family of sets is not required to be injective (that is, there may exist distinct indices such as ), which in particular means that it is possible for distinct indexed families of sets (which are functions) to be associated with the same family of sets (by having the same image/range).

Arbitrary unions defined[3]

(Def. 1)

If then which is somethings called the nullary union convention (despite being called a convention, this equality follows from the definition).

If is a family of sets then denotes the set:

Arbitrary intersections defined

If then[3]

(Def. 2)

If is a non-empty family of sets then denotes the set:

Nullary intersections

If then where every possible thing in the universe vacuously satisfied the condition: "if then ". Consequently, consists of everything in the universe.

So if and:

  1. if you are working in a model in which there exists some universe set then
  2. otherwise, if you are working in a model in which "the class of all things " is not a set (by far the most common situation) then is undefined because consists of everything, which makes a proper class and not a set.
Assumption: Henceforth, whenever a formula requires some indexing set to be non-empty in order for an arbitrary intersection to be well-defined, then this will automatically be assumed without mention.

A consequence of this is the following assumption/definition:

A finite intersection of sets or an intersection of finitely many sets refers to the intersection of a finite collection of one or more sets.

Some authors adopt the so called nullary intersection convention, which is the convention that an empty intersection of sets is equal to some canonical set. In particular, if all sets are subsets of some set then some author may declare that the empty intersection of these sets be equal to However, the nullary intersection convention is not as commonly accepted as the nullary union convention and this article will not adopt it (this is due to the fact that unlike the empty union, the value of the empty intersection depends on so if there are multiple sets under consideration, which is commonly the case, then the value of the empty intersection risks becoming ambiguous).

Multiple index sets

Distributing unions and intersections

Binary ⋂ of arbitrary ⋃'s

(Eq. 3a)

and[4]

(Eq. 3b)
  • If all are pairwise disjoint and all are also pairwise disjoint, then so are all (that is, if then ).

  • Importantly, if then in general, (an example of this is given below). The single union on the right hand side must be over all pairs The same is usually true for other similar non-trivial set equalities and relations that depend on two (potentially unrelated) indexing sets and (such as Eq. 4b or Eq. 7g[4]). Two exceptions are Eq. 2c (unions of unions) and Eq. 2d (intersections of intersections), but both of these are among the most trivial of set equalities (although even for these equalities there is still something that must be proven[note 2]).
  • Example where equality fails: Let and let Let and let Then Furthermore,

Binary ⋃ of arbitrary ⋂'s

(Eq. 4a)

and[4]

(Eq. 4b)
  • Importantly, if then in general, (an example of this is given above). The single intersection on the right hand side must be over all pairs

Arbitrary ⋂'s and arbitrary ⋃'s

Incorrectly distributing by swapping ⋂ and ⋃

Naively swapping and may produce a different set

The following inclusion always holds:

(Inclusion 1 ∪∩ is a subset of ∩∪)

In general, equality need not hold and moreover, the right hand side depends on how for each fixed the sets are labelled; and analogously, the left hand side depends on how for each fixed the sets are labelled. An example demonstrating this is now given.

  • Example of dependence on labeling and failure of equality: To see why equality need not hold when and are swapped, let and let and Then If and are swapped while and are unchanged, which gives rise to the sets and then In particular, the left hand side is no longer which shows that the left hand side depends on how the sets are labelled. If instead and are swapped while and are unchanged, which gives rise to the sets and then both the left hand side and right hand side are equal to which shows that the right hand side also depends on how the sets are labeled.

Equality in Inclusion 1 ∪∩ is a subset of ∩∪ can hold under certain circumstances, such as in 7e, which is the special case where is (that is, with the same indexing sets and ), or such as in 7f, which is the special case where is (that is, with the indexing sets and swapped). For a correct formula that extends the distributive laws, an approach other than just switching and is needed.

Correct distributive laws

Suppose that for each is a non-empty index set and for each let be any set (for example, to apply this law to use for all and use for all and all ). Let denote the Cartesian product, which can be interpreted as the set of all functions such that for every Such a function may also be denoted using the tuple notation where for every and conversely, a tuple is just notation for the function with domain whose value at is both notations can be used to denote the elements of Then

(Eq. 5 ∩∪ to ∪∩)
(Eq. 6 ∪∩ to ∩∪)

where

Applying the distributive laws

Example application: In the particular case where all are equal (that is, for all which is the case with the family for example), then letting denote this common set, the Cartesian product will be which is the set of all functions of the form The above set equalities Eq. 5 ∩∪ to ∪∩ and Eq. 6 ∪∩ to ∩∪, respectively become:[3]

which when combined with Inclusion 1 ∪∩ is a subset of ∩∪ implies: where

  • on the left hand side, the indices range over (so the subscripts of range over )
  • on the right hand side, the indices range over (so the subscripts of range over ).


Example application: To apply the general formula to the case of and use and let for all and let for all Every map can be bijectively identified with the pair (the inverse sends to the map defined by and this is technically just a change of notation). Recall that Eq. 5 ∩∪ to ∪∩ was Expanding and simplifying the left hand side gives and doing the same to the right hand side gives:

Thus the general identity Eq. 5 ∩∪ to ∪∩ reduces down to the previously given set equality Eq. 3b:

Distributing subtraction over ⋃ and ⋂

(Eq. 7a)
(Eq. 7b)

The next identities are known as De Morgan's laws.[4]

(Eq. 7c)
(Eq. 7d)

The following four set equalities can be deduced from the equalities 7a - 7d above.

(Eq. 7e)
(Eq. 7f)
(Eq. 7g)
(Eq. 7h)

In general, naively swapping and may produce a different set (see this note for more details). The equalities found in Eq. 7e and Eq. 7f are thus unusual in that they state exactly that swapping and will not change the resulting set.

Commutativity and associativity of ⋃ and ⋂

Commutativity:[3]

Unions of unions and intersections of intersections:[3]

and[3]

(Eq. 2a)
(Eq. 2b)

and if then also:[note 2][3]

(Eq. 2c)
(Eq. 2d)

Cartesian products Π of arbitrarily many sets

Intersections ⋂ of Π

If is a family of sets then

(Eq. 8)
  • Moreover, a tuple belongs to the set in Eq. 8 above if and only if for all and all

In particular, if and are two families indexed by the same set then So for instance, and

Intersections of products indexed by different sets

Let and be two families indexed by different sets.

Technically, implies However, sometimes these products are somehow identified as the same set through some bijection or one of these products is identified as a subset of the other via some injective map, in which case (by abuse of notation) this intersection may be equal to some other (possibly non-empty) set.

  • For example, if and with all sets equal to then and where unless, for example, is identified as a subset of through some injection, such as maybe for instance; however, in this particular case the product actually represents the -indexed product where
  • For another example, take and with and all equal to Then and which can both be identified as the same set via the bijection that sends to Under this identification,

Binary ⨯ distributes over arbitrary ⋃ and ⋂

The binary Cartesian productdistributes over arbitrary intersections (when the indexing set is not empty) and over arbitrary unions:

Distributing arbitrary Π over arbitrary ⋃

Suppose that for each is a non-empty index set and for each let be any set (for example, to apply this law to use for all and use for all and all ). Let denote the Cartesian product, which (as mentioned above) can be interpreted as the set of all functions such that for every . Then

(Eq. 11 Π∪ to ∪Π)

where

Unions ⋃ of Π

For unions, only the following is guaranteed in general: where is a family of sets.

  • Example where equality fails: Let let let and let Then More generally, if and only if for each at least one of the sets in the -indexed collections of sets is empty, while if and only if for each at least one of the sets in the -indexed collections of sets is not empty.

However,

Difference \ of Π

If and are two families of sets then: so for instance, and

Symmetric difference ∆ of Π

Functions and sets

Let be any function.

Let be completely arbitrary sets. Assume

Definitions

Let be any function, where we denote its domain by and denote its codomain by

Many of the identities below do not actually require that the sets be somehow related to 's domain or codomain (that is, to or ) so when some kind of relationship is necessary then it will be clearly indicated. Because of this, in this article, if is declared to be "any set," and it is not indicated that must be somehow related to or (say for instance, that it be a subset or ) then it is meant that is truly arbitrary.[note 3] This generality is useful in situations where is a map between two subsets and of some larger sets and and where the set might not be entirely contained in and/or (e.g. if all that is known about is that ); in such a situation it may be useful to know what can and cannot be said about and/or without having to introduce a (potentially unnecessary) intersection such as: and/or

Images and preimages of sets

If is any set then the image of under is defined to be the set: while the preimage of under is: where if is a singleton set then the fiber or preimage of under is

Denote by or the image or range of which is the set:

Saturated sets

A set is said to be -saturated or a saturated set if any of the following equivalent conditions are satisfied:[3]

  1. There exists a set such that
    • Any such set necessarily contains as a subset.
    • Any set not entirely contained in the domain of cannot be -saturated.
  2. and
    • The inclusion always holds, where if then this becomes
  3. and if and satisfy then
  4. Whenever a fiber of intersects then contains the entire fiber. In other words, contains every -fiber that intersects it.
    • Explicitly: whenever is such that then
    • In both this statement and the next, the set may be replaced with any superset of (such as ) and the resulting statement will still be equivalent to the rest.
  5. The intersection of with a fiber of is equal to the empty set or to the fiber itself.
    • Explicitly: for every the intersection is equal to the empty set or to (that is, or ).

For a set to be -saturated, it is necessary that

Compositions and restrictions of functions

If and are maps then denotes the composition map with domain and codomain defined by

The restriction of to denoted by is the map with defined by sending to that is, Alternatively, where denotes the inclusion map, which is defined by

(Pre)Images of arbitrary unions ⋃'s and intersections ⋂'s

If is a family of arbitrary sets indexed by then:[5]

So of these four identities, it is only images of intersections that are not always preserved. Preimages preserve all basic set operations. Unions are preserved by both images and preimages.

If all are -saturated then be will be -saturated and equality will hold in the first relation above; explicitly, this means:

(Conditional Equality 10a)

If is a family of arbitrary subsets of which means that for all then Conditional Equality 10a becomes:

(Conditional Equality 10b)

(Pre)Images of binary set operations

Throughout, let and be any sets and let be any function.

Summary

As the table below shows, set equality is not guaranteed only for images of: intersections, set subtractions, and symmetric differences.

Image Preimage Additional assumptions on sets
[6] [3] None
[3] None
[5][3] None
[note 4] None
None

Preimages preserve set operations

Preimages of sets are well-behaved with respect to all basic set operations:

In words, preimages distribute over unions, intersections, set subtraction, and symmetric difference.

Images only preserve unions

Images of unions are well-behaved:

but images of the other basic set operations are not since only the following are guaranteed in general:

In words, images distribute over unions but not necessarily over intersections, set subtraction, or symmetric difference. What these latter three operations have in common is set subtraction: they either are set subtraction or else they can naturally be defined as the set subtraction of two sets:

If then where as in the more general case, equality is not guaranteed. If is surjective then which can be rewritten as: if and

Counter-examples: images of operations not distributing

Picture showing failing to distribute over set intersection:
The map is defined by where denotes the real numbers. The sets and are shown in blue immediately below the -axis while their intersection is shown in green.

If is constant, and then all four of the set containments are strict/proper (that is, the sets are not equal) since one side is the empty set while the other is non-empty. Thus equality is not guaranteed for even the simplest of functions. The example above is now generalized to show that these four set equalities can fail for any constant function whose domain contains at least two (distinct) points.

Example: Let be any constant function with image and suppose that are non-empty disjoint subsets; that is, and which implies that all of the sets and are not empty and so consequently, their images under are all equal to

  1. The containment is strict: In words: functions might not distribute over set subtraction
  2. The containment is strict:
  3. The containment is strict: In words: functions might not distribute over symmetric difference (which can be defined as the set subtraction of two sets: ).
  4. The containment is strict: In words: functions might not distribute over set intersection (which can be defined as the set subtraction of two sets: ).

What the set operations in these four examples have in common is that they either are set subtraction (examples (1) and (2)) or else they can naturally be defined as the set subtraction of two sets (examples (3) and (4)).

Mnemonic: In fact, for each of the above four set formulas for which equality is not guaranteed, the direction of the containment (that is, whether to use ) can always be deduced by imagining the function as being constant and the two sets ( and ) as being non-empty disjoint subsets of its domain. This is because every equality fails for such a function and sets: one side will be always be and the other non-empty − from this fact, the correct choice of can be deduced by answering: "which side is empty?" For example, to decide if the in should be pretend[note 5] that is constant and that and are non-empty disjoint subsets of 's domain; then the left hand side would be empty (since ), which indicates that should be (the resulting statement is always guaranteed to be true) because this is the choice that will make true. Alternatively, the correct direction of containment can also be deduced by consideration of any constant with and

Furthermore, this mnemonic can also be used to correctly deduce whether or not a set operation always distribute over images or preimages; for example, to determine whether or not always equals or alternatively, whether or not always equals (although was used here, it can replaced by ). The answer to such a question can, as before, be deduced by consideration of this constant function: the answer for the general case (that is, for arbitrary and ) is always the same as the answer for this choice of (constant) function and disjoint non-empty sets.

Conditions guaranteeing that images distribute over set operations

Characterizations of when equality holds for all sets:

For any function the following statements are equivalent:

  1. is injective.
    • This means: for all distinct
  2. (The equals sign can be replaced with ).
  3. (The equals sign can be replaced with ).
  4. (The equals sign can be replaced with ).
  5. (The equals sign can be replaced with ).
  6. Any one of the four statements (b) - (e) but with the words "for all" replaced with any one of the following:
    1. "for all singleton subsets"
      • In particular, the statement that results from (d) gives a characterization of injectivity that explicitly involves only one point (rather than two): is injective if and only if
    2. "for all disjoint singleton subsets"
      • For statement (d), this is the same as: "for all singleton subsets" (because the definition of "pairwise disjoint" is satisfies vacuously by any family that consists of exactly 1 set).
    3. "for all disjoint subsets"

In particular, if a map is not known to be injective then barring additional information, there is no guarantee that any of the equalities in statements (b) - (e) hold.

An example above can be used to help prove this characterization. Indeed, comparison of that example with such a proof suggests that the example is representative of the fundamental reason why one of these four equalities in statements (b) - (e) might not hold (that is, representative of "what goes wrong" when a set equality does not hold).

Conditions for f(L⋂R) = f(L)⋂f(R)

Characterizations of equality: The following statements are equivalent:

    • The left hand side is always equal to (because always holds).
  1. If satisfies then
  2. If but then
  3. Any of the above three conditions (i) - (k) but with the subset symbol replaced with an equals sign

Sufficient conditions for equality: Equality holds if any of the following are true:

  1. is injective.[7]
  2. The restriction is injective.
  3. [note 6]
  4. is -saturated; that is, [note 6]
  5. is -saturated; that is,
  6. or equivalently,
  7. or equivalently,
  8. or equivalently,

In addition, the following always hold:

Conditions for f(L\R) = f(L)\f(R)

Characterizations of equality: The following statements are equivalent:[proof 1]

  1. Whenever then
    • The set on the right hand side is always equal to
    • This is the above condition (f) but with the subset symbol replaced with an equals sign

Necessary conditions for equality (excluding characterizations): If equality holds then the following are necessarily true:

  1. or equivalently
  2. or equivalently,

Sufficient conditions for equality: Equality holds if any of the following are true:

  1. is injective.
  2. The restriction is injective.
  3. [note 6] or equivalently,
  4. is -saturated; that is, [note 6]
  5. or equivalently,
Conditions for f(X\R) = f(X)\f(R)

Characterizations of equality: The following statements are equivalent:[proof 1]

  1. is -saturated.
  2. Whenever then

   where if then this list can be extended to include:

  1. is -saturated; that is,

Sufficient conditions for equality: Equality holds if any of the following are true:

  1. is injective.
  2. is -saturated; that is,
Conditions for f(L∆R) = f(L)∆f(R)

Characterizations of equality: The following statements are equivalent:

  1.  and 
  2.  and 
  3.  and 
    • The inclusions and always hold.
    • If this above set equality holds, then this set will also be equal to both and
  4.  and 

Necessary conditions for equality (excluding characterizations): If equality holds then the following are necessarily true:

  1. or equivalently

Sufficient conditions for equality: Equality holds if any of the following are true:

  1. is injective.
  2. The restriction is injective.

Exact formulas/equalities for images of set operations

Formulas for f(L\R) =

For any function and any sets and [proof 2]

Formulas for f(X\R) =

Taking in the above formulas gives: where the set is equal to the image under of the largest -saturated subset of

  • In general, only always holds and equality is not guaranteed; but replacing "" with its subset "" results in a formula in which equality is always guaranteed: From this it follows that:[proof 1]
  • If then which can be written more symmetrically as (since ).
Formulas for f(L∆R) =

It follows from and the above formulas for the image of a set subtraction that for any function and any sets and

Formulas for f(L) =

It follows from the above formulas for the image of a set subtraction that for any function and any set

This is more easily seen as being a consequence of the fact that for any if and only if

Formulas for f(L⋂R) =

It follows from the above formulas for the image of a set that for any function and any sets and where moreover, for any

if and only if if and only if if and only if

The sets and mentioned above could, in particular, be any of the sets or for example.

(Pre)Images of set operations on (pre)images

Let and be arbitrary sets, be any map, and let and

Image of preimage Preimage of image Additional assumptions on sets
[5] None
[8]

Equality holds if any of the following are true:

(Pre)Images of operations on images

Since

Since

Using this becomes and and so

(Pre)Images and Cartesian products Π

Let and for every let denote the canonical projection onto

Definitions

Given a collection of maps indexed by define the map which is also denoted by This is the unique map satisfying

Conversely, if given a map then Explicitly, what this means is that if is defined for every then the unique map satisfying: for all or said more briefly,

The map should not be confused with the Cartesian product of these maps, which is by definition is the map with domain rather than

Preimage and images of a Cartesian product

Suppose

If then

If then where equality will hold if in which case and

(Eq. 11a)

For equality to hold, it suffices for there to exist a family of subsets such that in which case:

(Eq. 11b)

and for all

(Pre)Image of a single set

Image Preimage Additional assumptions
None
None
None
None
None
None ( and are arbitrary functions).

[5] None
None
None

Containments ⊆ and intersections ⋂ of images and preimages

Equivalences and implications of images and preimages

Image Preimage Additional assumptions on sets
if and only if None
if and only if if and only if None
if and only if if and only if and
implies [5] implies [5] None
The following are equivalent:
The following are equivalent:

If then if and only if

The following are equivalent when
  1. for some
  2. for some
The following are equivalent:
  1. and

The following are equivalent when

and
The following are equivalent:
The following are equivalent:
and
[5]

Equality holds if and only if the following is true:

  1. [9][10]

Equality holds if any of the following are true:

  1. and is surjective.

Equality holds if and only if the following is true:

  1. is -saturated.

Equality holds if any of the following are true:

  1. is injective.[9][10]

Intersection of a set and a (pre)image

The following statements are equivalent:

  1. [5]

Thus for any [5]

Sequences and collections of families of sets

Definitions

A family of sets or simply a family is a set whose elements are sets. A family over is a family of subsets of

The power set of a set is the set of all subsets of :

Notation for sequences of sets

Throughout, will be arbitrary sets and and will denote a net or a sequence of sets where if it is a sequence then this will be indicated by either of the notations where denotes the natural numbers. A notation indicates that is a net directed by which (by definition) is a sequence if the set which is called the net's indexing set, is the natural numbers (that is, if ) and is the natural order on

Disjoint and monotone sequences of sets

If for all distinct indices then is called a pairwise disjoint or simply a disjoint. A sequence or net of set is called increasing or non-decreasing if (resp. decreasing or non-increasing) if for all indices (resp. ). A sequence or net of set is called strictly increasing (resp. strictly decreasing) if it is non-decreasing (resp. is non-increasing) and also for all distinct indices It is called monotone if it is non-decreasing or non-increasing and it is called strictly monotone if it is strictly increasing or strictly decreasing.

A sequences or net is said to increase to denoted by [11] or if is increasing and the union of all is that is, if It is said to decrease to denoted by [11] or if is increasing and the intersection of all is that is, if

Definitions of elementwise operations on families

If are families of sets and if is any set then define:[12] which are respectively called elementwise union, elementwise intersection, elementwise (set) difference, elementwise symmetric difference, and the trace/restriction of to The regular union, intersection, and set difference are all defined as usual and are denoted with their usual notation: and respectively. These elementwise operations on families of sets play an important role in, among other subjects, the theory of filters and prefilters on sets.

The upward closure in of a family is the family: and the downward closure of is the family:

Definitions of categories of families of sets

The following table lists some well-known categories of families of sets having applications in general topology and measure theory.

Families of sets over
Is necessarily true of
or, is closed under:
Directed
by
F.I.P.
π-system Yes Yes No No No No No No No No
Semiring Yes Yes No No No No No No Yes Never
Semialgebra (Semifield) Yes Yes No No No No No No Yes Never
Monotone class No No No No No only if only if No No No
𝜆-system (Dynkin System) Yes No No only if
Yes No only if or
they are disjoint
Yes Yes Never
Ring (Order theory) Yes Yes Yes No No No No No No No
Ring (Measure theory) Yes Yes Yes Yes No No No No Yes Never
δ-Ring Yes Yes Yes Yes No Yes No No Yes Never
𝜎-Ring Yes Yes Yes Yes No Yes Yes No Yes Never
Algebra (Field) Yes Yes Yes Yes Yes No No Yes Yes Never
𝜎-Algebra (𝜎-Field) Yes Yes Yes Yes Yes Yes Yes Yes Yes Never
Dual ideal Yes Yes Yes No No No Yes Yes No No
Filter Yes Yes Yes Never Never No Yes Yes Yes
Prefilter (Filter base) Yes No No Never Never No No No Yes
Filter subbase No No No Never Never No No No Yes
Open Topology Yes Yes Yes No No No
(even arbitrary )
Yes Yes Never
Closed Topology Yes Yes Yes No No
(even arbitrary )
No Yes Yes Never
Is necessarily true of
or, is closed under:
directed
downward
finite
intersections
finite
unions
relative
complements
complements
in
countable
intersections
countable
unions
contains contains Finite
Intersection
Property

Additionally, a semiring is a π-system where every complement is equal to a finite disjoint union of sets in
A semialgebra is a semiring where every complement is equal to a finite disjoint union of sets in
are arbitrary elements of and it is assumed that

A family is called isotone, ascending, or upward closed in if and [12] A family is called downward closed if

A family is said to be:

  • closed under finite intersections (resp. closed under finite unions) if whenever then (respectively, ).
  • closed under countable intersections (resp. closed under countable unions) if whenever are elements of then so is their intersections (resp. so is their union ).
  • closed under complementation in (or with respect to) if whenever then

A family of sets is called a/an:

  • π−system if and is closed under finite-intersections.
    • Every non-empty family is contained in a unique smallest (with respect to ) π−system that is denoted by and called the π−system generated by
  • filter subbase and is said to have the finite intersection property if and
  • filter on if is a family of subsets of that is a π−system, is upward closed in and is also proper, which by definition means that it does not contain the empty set as an element.
  • prefilter or filter base if it is a non-empty family of subsets of some set whose upward closure in is a filter on
  • algebra on is a non-empty family of subsets of that contains the empty set, forms a π−system, and is also closed under complementation with respect to
  • σ-algebra on is an algebra on that is closed under countable unions (or equivalently, closed under countable intersections).

Sequences of sets often arise in measure theory.

Algebra of sets

A family of subsets of a set is said to be an algebra of sets if and for all all three of the sets and are elements of [13] The article on this topic lists set identities and other relationships these three operations.

Every algebra of sets is also a ring of sets[13] and a π-system.

Algebra generated by a family of sets

Given any family of subsets of there is a unique smallest[note 7] algebra of sets in containing [13] It is called the algebra generated by and it will be denote it by This algebra can be constructed as follows:[13]

  1. If then and we are done. Alternatively, if is empty then may be replaced with and continue with the construction.
  2. Let be the family of all sets in together with their complements (taken in ).
  3. Let be the family of all possible finite intersections of sets in [note 8]
  4. Then the algebra generated by is the set consisting of all possible finite unions of sets in

Elementwise operations on families

Let and be families of sets over On the left hand sides of the following identities, is the L eft most family, is in the M iddle, and is the R ight most set.

Commutativity:[12]

Associativity:[12]

Identity:

Domination:

Power set

If and are subsets of a vector space and if is a scalar then

Sequences of sets

Suppose that is any set such that for every index If decreases to then increases to [11] whereas if instead increases to then decreases to

If are arbitrary sets and if increases (resp. decreases) to then increase (resp. decreases) to

Partitions

Suppose that is any sequence of sets, that is any subset, and for every index let Then and is a sequence of pairwise disjoint sets.[11]

Suppose that is non-decreasing, let and let for every Then and is a sequence of pairwise disjoint sets.[11]

See also

Notes

Notes

  1. ^ For example, the expression uses two of the same symbols ( and ) that appear in the identity but they refer to different sets in each expression. To apply this identity to substitute and (since these are the left, middle, and right sets in ) to obtain: For a second example, this time applying the identity to is now given. The identity can be applied to by reading and as and and then substituting and to obtain:
  2. ^ a b To deduce Eq. 2c from Eq. 2a, it must still be shown that so Eq. 2c is not a completely immediate consequence of Eq. 2a. (Compare this to the commentary about Eq. 3b).
  3. ^ So for instance, it's even possible that or that and (which happens, for instance, if ), etc.
  4. ^ The conclusion can also be written as:
  5. ^ Whether or not it is even feasible for the function to be constant and the sets and to be non-empty and disjoint is irrelevant for reaching the correct conclusion about whether to use
  6. ^ a b c d Note that this condition depends entirely on and not on
  7. ^ Here "smallest" means relative to subset containment. So if is any algebra of sets containing then
  8. ^ Since there is some such that its complement also belongs to The intersection of these two sets implies that The union of these two sets is equal to which implies that

Proofs

  1. ^ a b c Let where because is also equal to As proved above, so that if and only if Since this happens if and only if Because are both subsets of the condition on the right hand side happens if and only if Because the equality holds if and only if If (such as when or ) then if and only if In particular, taking proves: if and only if where
  2. ^ Let and let denote the set equality which will now be proven. If then so there exists some now implies so that To prove the reverse inclusion let so that there exists some such that Then so that and thus which proves that as desired. Defining the identity follows from and the inclusions

Citations

  1. ^ Taylor, Courtney (March 31, 2019). "What Is Symmetric Difference in Math?". ThoughtCo. Retrieved 2020-09-05.
  2. ^ Weisstein, Eric W. "Symmetric Difference". mathworld.wolfram.com. Retrieved 2020-09-05.
  3. ^ a b c d e f g h i j k l m n o p q r s t u v w x y Monk 1969, pp. 24–54.
  4. ^ a b c d e f g Császár 1978, pp. 15–26.
  5. ^ a b c d e f g h i Császár 1978, pp. 102–120.
  6. ^ Kelley 1985, p. 85
  7. ^ See Munkres 2000, p. 21
  8. ^ Lee p.388 of Lee, John M. (2010). Introduction to Topological Manifolds, 2nd Ed.
  9. ^ a b Lee Halmos 1960, p. 39
  10. ^ a b Lee Munkres 2000, p. 19
  11. ^ a b c d e Durrett 2019, pp. 1–8.
  12. ^ a b c d Császár 1978, pp. 53–65.
  13. ^ a b c d "Algebra of sets". Encyclopediaofmath.org. 16 August 2013. Retrieved 8 November 2020.

References

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