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.
Throughout this article, capital letters (such as and ) will denote sets. On the left hand side of an identity, typically,
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:
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)
Assume
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:
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
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 state that for
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 properties
Intervals:
The following statements are equivalent for any [3]
The following statements are equivalent for any
The following statements are equivalent:
A set is empty if the sentence is true, where the notation is shorthand for
If is any set then the following are equivalent:
If is any set then the following are equivalent:
Given any the following are equivalent:
Moreover,
Inclusion is a partial order : Explicitly, this means that inclusion which is a binary operation, has the following three properties: [3]
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 :
The union is the join/supremum of and with respect to because:
The intersection is the join/supremum of and with respect to
The intersection is the meet/infimum of and with respect to because:
The union is the meet/infimum of and with respect to
Other inclusion properties:
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.
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.
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.
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 ).
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:
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.
Set subtraction is not associative in general: since only the following is always guaranteed:
Set subtraction on the left, and parentheses on the left
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
Set subtraction on the right, and parentheses on the left
Set subtraction on the right, and parentheses on the right
Operations of the form :
Operations of the form :
Operations of the form :
Other properties:
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:
The binary Cartesian product ⨯ distributes over unions, intersections, set subtraction, and symmetric difference:
But in general, ⨯ does not distribute over itself:
and
In general, need not be a subset nor a superset of
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.
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:
A consequence of this is the following assumption/definition:
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
Eq. 3a |
and [4]
Eq. 3b |
Eq. 4a |
and [4]
Eq. 4b |
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.
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.
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
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
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 :
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: [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 |
If is a family of sets then
Eq. 8 |
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.
The binary Cartesian product ⨯ distributes over arbitrary intersections (when the indexing set is not empty) and over arbitrary unions:
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
For unions, only the following is guaranteed in general: where is a family of sets.
However,
If and are two families of sets then: so for instance, and
Let be any function.
Let be completely arbitrary sets. Assume
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]
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
If is a family of arbitrary sets indexed by then: [5]
So of these four identities, it is onlyimages 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 |
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
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
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.
Characterizations of when equality holds for all sets:
For any function the following statements are equivalent:
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).
Characterizations of equality: The following statements are equivalent:
Sufficient conditions for equality: Equality holds if any of the following are true:
In addition, the following always hold:
Characterizations of equality: The following statements are equivalent: [proof 1]
Necessary conditions for equality (excluding characterizations): If equality holds then the following are necessarily true:
Sufficient conditions for equality: Equality holds if any of the following are true:
Characterizations of equality: The following statements are equivalent: [proof 1]
where if then this list can be extended to include:
Sufficient conditions for equality: Equality holds if any of the following are true:
Characterizations of equality: The following statements are equivalent:
Necessary conditions for equality (excluding characterizations): If equality holds then the following are necessarily true:
Sufficient conditions for equality: Equality holds if any of the following are true:
For any function and any sets and [proof 2]
Taking in the above formulas gives: where the set is equal to the image under of the largest -saturated subset of
It follows from and the above formulas for the image of a set subtraction that for any function and any sets and
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
It follows from the above formulas for the image of a set that for any function and any sets and where moreover, for any
The sets and mentioned above could, in particular, be any of the sets or for example.
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
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
Image | Preimage | Additional assumptions |
---|---|---|
None | ||
None | ||
None | ||
None | ||
None | ||
None ( and are arbitrary functions). | ||
[5] | None | |
None | ||
None |
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
| The following are equivalent:
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: Equality holds if any of the following are true:
| Equality holds if and only if the following is true:
Equality holds if any of the following are true: |
Intersection of a set and a (pre)image
The following statements are equivalent:
Thus for any [5]
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 elementwiseunion, elementwiseintersection, elementwise (set) difference, elementwisesymmetric 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:
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 | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
Semiring | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | Never |
Semialgebra(Semifield) | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | Never |
Monotone class | ![]() | ![]() | ![]() | ![]() | ![]() | only if | only if | ![]() | ![]() | ![]() |
𝜆-system(Dynkin System) | ![]() | ![]() | ![]() | only if | ![]() | ![]() | only if or they are disjoint | ![]() | ![]() | Never |
Ring (Order theory) | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
Ring (Measure theory) | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | Never |
δ-Ring | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | Never |
𝜎-Ring | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | Never |
Algebra (Field) | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | Never |
𝜎-Algebra(𝜎-Field) | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | Never |
Dual ideal | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() |
Filter | ![]() | ![]() | ![]() | Never | Never | ![]() | ![]() | ![]() | ![]() | |
Prefilter(Filter base) | ![]() | ![]() | ![]() | Never | Never | ![]() | ![]() | ![]() | ![]() | |
Filter subbase | ![]() | ![]() | ![]() | Never | Never | ![]() | ![]() | ![]() | ![]() | |
Open Topology | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() (even arbitrary ) | ![]() | ![]() | Never |
Closed Topology | ![]() | ![]() | ![]() | ![]() | ![]() | ![]() (even arbitrary ) | ![]() | ![]() | ![]() | 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 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:
A family of sets is called a/an:
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]
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.
Identity:
Domination:
If and are subsets of a vector space and if is a scalar then
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
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]
Notes
Proofs
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In topology, the closure of a subset S of points in a topological space consists of all points in S together with all limit points of S. The closure of S may equivalently be defined as the union of S and its boundary, and also as the intersection of all closed sets containing S. Intuitively, the closure can be thought of as all the points that are either in S or "very near" S. A point which is in the closure of S is a point of closure of S. The notion of closure is in many ways dual to the notion of interior.
Distributions, also known as Schwartz distributions or generalized functions, are objects that generalize the classical notion of functions in mathematical analysis. Distributions make it possible to differentiate functions whose derivatives do not exist in the classical sense. In particular, any locally integrable function has a distributional derivative.
In mathematics, a base (or basis; pl.: bases) for the topology τ of a topological space (X, τ) is a family of open subsets of X such that every open set of the topology is equal to the union of some sub-family of . For example, the set of all open intervals in the real number line is a basis for the Euclidean topology on because every open interval is an open set, and also every open subset of can be written as a union of some family of open intervals.
In mathematics, the symmetric difference of two sets, also known as the disjunctive union and set sum, is the set of elements which are in either of the sets, but not in their intersection. For example, the symmetric difference of the sets and is .
In topology and related branches of mathematics, the Kuratowski closure axioms are a set of axioms that can be used to define a topological structure on a set. They are equivalent to the more commonly used open set definition. They were first formalized by Kazimierz Kuratowski, and the idea was further studied by mathematicians such as Wacław Sierpiński and António Monteiro, among others.
In mathematics, for a function , the image of an input value is the single output value produced by when passed . The preimage of an output value is the set of input values that produce .
In mathematics, an additive set function is a function mapping sets to numbers, with the property that its value on a union of two disjoint sets equals the sum of its values on these sets, namely, If this additivity property holds for any two sets, then it also holds for any finite number of sets, namely, the function value on the union of k disjoint sets equals the sum of its values on the sets. Therefore, an additive set function is also called a finitely additive set function. However, a finitely additive set function might not have the additivity property for a union of an infinite number of sets. A σ-additive set function is a function that has the additivity property even for countably infinite many sets, that is,
Pregeometry, and in full combinatorial pregeometry, are essentially synonyms for "matroid". They were introduced by Gian-Carlo Rota with the intention of providing a less "ineffably cacophonous" alternative term. Also, the term combinatorial geometry, sometimes abbreviated to geometry, was intended to replace "simple matroid". These terms are now infrequently used in the study of matroids.
In functional and convex analysis, and related disciplines of mathematics, the polar set is a special convex set associated to any subset of a vector space lying in the dual space The bipolar of a subset is the polar of but lies in .
A Dynkin system, named after Eugene Dynkin, is a collection of subsets of another universal set satisfying a set of axioms weaker than those of 𝜎-algebra. Dynkin systems are sometimes referred to as 𝜆-systems or d-system. These set families have applications in measure theory and probability.
In mathematics, there are two different notions of a ring of sets, both referring to certain families of sets.
In mathematics, in particular in measure theory, a content is a real-valued function defined on a collection of subsets such that
In mathematics, a filter on a set is a family of subsets such that:
In mathematics, specifically set theory, the Cartesian product of two sets A and B, denoted A × B, is the set of all ordered pairs (a, b) where a is in A and b is in B. In terms of set-builder notation, that is
In mathematics, especially measure theory, a set function is a function whose domain is a family of subsets of some given set and that (usually) takes its values in the extended real number line which consists of the real numbers and
Filters in topology, a subfield of mathematics, can be used to study topological spaces and define all basic topological notions such as convergence, continuity, compactness, and more. Filters, which are special families of subsets of some given set, also provide a common framework for defining various types of limits of functions such as limits from the left/right, to infinity, to a point or a set, and many others. Special types of filters called ultrafilters have many useful technical properties and they may often be used in place of arbitrary filters.
In functional analysis and related areas of mathematics, a complete topological vector space is a topological vector space (TVS) with the property that whenever points get progressively closer to each other, then there exists some point towards which they all get closer. The notion of "points that get progressively closer" is made rigorous by Cauchy nets or Cauchy filters, which are generalizations of Cauchy sequences, while "point towards which they all get closer" means that this Cauchy net or filter converges to The notion of completeness for TVSs uses the theory of uniform spaces as a framework to generalize the notion of completeness for metric spaces. But unlike metric-completeness, TVS-completeness does not depend on any metric and is defined for all TVSs, including those that are not metrizable or Hausdorff.
In the mathematical field of set theory, an ultrafilter on a set is a maximal filter on the set In other words, it is a collection of subsets of that satisfies the definition of a filter on and that is maximal with respect to inclusion, in the sense that there does not exist a strictly larger collection of subsets of that is also a filter. Equivalently, an ultrafilter on the set can also be characterized as a filter on with the property that for every subset of either or its complement belongs to the ultrafilter.