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Union (set theory)
Union (set theory)
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Union of two sets:
Union of three sets:
The union of A, B, C, D, and E is everything except the white area.

In set theory, the union (denoted by ∪) of a collection of sets is the set of all elements in the collection.[1] It is one of the fundamental operations through which sets can be combined and related to each other. A nullary union refers to a union of zero () sets and it is by definition equal to the empty set.

For explanation of the symbols used in this article, refer to the table of mathematical symbols.

Union of two sets

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The union of two sets A and B is the set of elements which are in A, in B, or in both A and B.[2] In set-builder notation,

.[3]

For example, if A = {1, 3, 5, 7} and B = {1, 2, 4, 6, 7} then AB = {1, 2, 3, 4, 5, 6, 7}. A more elaborate example (involving two infinite sets) is:

A = {x is an even integer greater than 1}
B = {x is an odd integer greater than 1}

As another example, the number 9 is not contained in the union of the set of prime numbers {2, 3, 5, 7, 11, ...} and the set of even numbers {2, 4, 6, 8, 10, ...}, because 9 is neither prime nor even.

Sets cannot have duplicate elements,[3][4] so the union of the sets {1, 2, 3} and {2, 3, 4} is {1, 2, 3, 4}.

Finite unions

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One can take the union of several sets simultaneously. For example, the union of three sets A, B, and C contains all elements of A, all elements of B, and all elements of C, and nothing else. Thus, x is an element of ABC if and only if x is in at least one of A, B, and C.

A finite union is the union of a finite number of sets; the phrase does not imply that the union set is a finite set.[5][6]

Notation

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The notation for the general concept can vary considerably. For a finite union of sets one often writes or . Various common notations for arbitrary unions include , , and . The last of these notations refers to the union of the collection , where I is an index set and is a set for every . In the case that the index set I is the set of natural numbers, one uses the notation , which is analogous to that of the infinite sums in series.[7]

When the symbol "∪" is placed before other symbols (instead of between them), it is usually rendered as a larger size.

Notation encoding

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In Unicode, union is represented by the character U+222A UNION.[8] In TeX, is rendered from \cup and is rendered from \bigcup.

Arbitrary union

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The most general notion is the union of an arbitrary collection of sets, sometimes called an infinitary union. If M is a set or class whose elements are sets, then x is an element of the union of M if and only if there is at least one element A of M such that x is an element of A.[7] In symbols:

This idea subsumes the preceding sections—for example, ABC is the union of the collection {A, B, C}. Also, if M is the empty collection, then the union of M is the empty set.

Formal derivation

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In Zermelo–Fraenkel set theory (ZFC) and other set theories, the ability to take the arbitrary union of any sets is granted by the axiom of union, which states that, given any set of sets , there exists a set , whose elements are exactly those of the elements of . Sometimes this axiom is less specific, where there exists a which contains the elements of the elements of , but may be larger. For example if then it may be that since contains 1 and 2. This can be fixed by using the axiom of specification to get the subset of whose elements are exactly those of the elements of . Then one can use the axiom of extensionality to show that this set is unique. For readability, define the binary predicate meaning " is the union of " or "" as:

Then, one can prove the statement "for all , there is a unique , such that is the union of ":

Then, one can use an extension by definition to add the union operator to the language of ZFC as:

or equivalently:

After the union operator has been defined, the binary union can be defined by showing there exists a unique set using the axiom of pairing, and defining . Then, finite unions can be defined inductively as:

Algebraic properties

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Binary union is an associative operation; that is, for any sets , Thus, the parentheses may be omitted without ambiguity: either of the above can be written as . Also, union is commutative, so the sets can be written in any order.[9] The empty set is an identity element for the operation of union. That is, , for any set . Also, the union operation is idempotent: . All these properties follow from analogous facts about logical disjunction.

Intersection distributes over union and union distributes over intersection[2] The power set of a set , together with the operations given by union, intersection, and complementation, is a Boolean algebra. In this Boolean algebra, union can be expressed in terms of intersection and complementation by the formula where the superscript denotes the complement in the universal set . Alternatively, intersection can be expressed in terms of union and complementation in a similar way: . These two expressions together are called De Morgan's laws.[10][11][12]

History and etymology

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The english word union comes from the term in middle French meaning "coming together", which comes from the post-classical Latin unionem, "oneness".[13] The original term for union in set theory was Vereinigung (in german), which was introduced in 1895 by Georg Cantor.[14] The english use of union of two sets in mathematics began to be used by at least 1912, used by James Pierpont.[15][16] The symbol used for union in mathematics was introduced by Giuseppe Peano in his Arithmetices principia in 1889, along with the notations for intersection , set membership , and subsets .[17]

See also

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Notes

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
In set theory, the union of a collection of sets is the set comprising all elements that belong to at least one of the sets in the collection, providing a fundamental operation for combining sets without duplication. For two sets AA and BB, the union is denoted AB={xxAxB}A \cup B = \{ x \mid x \in A \lor x \in B \}, meaning it includes every element from either set. This binary operation extends naturally to finite collections, such as (AB)C(A \cup B) \cup C, and to arbitrary families of sets, where the union iIAi\bigcup_{i \in I} A_i consists of all elements in any AiA_i for index set II. In axiomatic set theory, particularly Zermelo-Fraenkel set theory (ZF), the existence of the union for any set AA—whose elements are themselves sets—is ensured by the axiom of union, which states that for every set AA, there exists a set A\bigcup A such that zAz \in \bigcup A if and only if there is some wAw \in A with zwz \in w. This axiom, introduced in Ernst Zermelo's 1908 axiomatization to resolve foundational paradoxes, allows the construction of complex sets from simpler ones and supports transfinite processes like ordinal arithmetic. Without it, basic set-building would be limited, as unions enable the aggregation of elements across multiple levels of membership. The union operation exhibits several key properties that underpin its utility in . It is commutative (AB=BAA \cup B = B \cup A) and associative ((AB)C=A(BC)(A \cup B) \cup C = A \cup (B \cup C)), permitting unions of multiple sets without regard to order or grouping. Additionally, it is idempotent (AA=AA \cup A = A), distributive over (A(BC)=(AB)(AC)A \cup (B \cap C) = (A \cup B) \cap (A \cup C)), and absorbs the (A=AA \cup \emptyset = A). These algebraic properties make union essential in fields like probability, where the union of events represents their combined occurrence, and in , where arbitrary unions of open sets form the basis for open sets in a topology. In infinite cases, unions can yield uncountable sets, highlighting set theory's power in handling .

Fundamentals

Binary Union

The binary union of two sets AA and BB, denoted ABA \cup B, is the set containing all elements that belong to AA, to BB, or to both. This operation collects the distinct elements from the two sets into a single set, ensuring no duplicates. Intuitively, the union merges the contents of the two sets like combining separate lists while eliminating any repeated items, resulting in a comprehensive collection of unique elements. Formally, it is defined in as AB={xxAxB}.A \cup B = \{ x \mid x \in A \lor x \in B \}. This notation specifies that membership in the union depends on the of membership in either set. A simple example illustrates this: the union of {1,2}\{1, 2\} and {2,3}\{2, 3\} is {1,2,3}\{1, 2, 3\}, as the element 2 appears in both but is included only once. Another basic case involves the \emptyset, which contains no elements; the union of any set AA with \emptyset yields AA itself, since no new elements are added. To verify A=AA \cup \emptyset = A, consider an arbitrary element yy. By , yAy \in A \cup \emptyset yAy \in A or yy \in \emptyset. However, no yy satisfies yy \in \emptyset, so the condition reduces to yAy \in A. Thus, the sets AA \cup \emptyset and AA have exactly the same elements, confirming equality.

Finite Unions

The finite union of a collection of sets extends the binary union operation to any finite number of sets through recursive application. Specifically, for sets A1,A2,,AnA_1, A_2, \dots, A_n where n2n \geq 2, the union i=1nAi\bigcup_{i=1}^n A_i is defined as (A1A2)An(A_1 \cup A_2) \cup \cdots \cup A_n, with the base case for n=1n=1 being the set itself and for n=0n=0 the empty set. This recursive definition ensures that the operation builds upon the binary union, collecting all elements that belong to at least one of the sets. The order and parenthesization of the unions do not affect the result due to the associativity of the union operation. To see this, consider three sets AA, BB, and CC. An element xx belongs to A(BC)A \cup (B \cup C) if and only if xAx \in A or xBCx \in B \cup C, which means xAx \in A or (xBx \in B or xCx \in C). By the of logical disjunction, this is equivalent to (xA(x \in A or xB)x \in B) or xCx \in C, so x(AB)Cx \in (A \cup B) \cup C. Thus, A(BC)=(AB)CA \cup (B \cup C) = (A \cup B) \cup C. This property extends inductively to any finite number of sets, justifying that the recursive definition yields a unique result independent of grouping. For notation, the finite union of sets A1,A2,,AnA_1, A_2, \dots, A_n is commonly written as A1[](/page/Cup)A2[](/page/Cup)[](/page/Cup)AnA_1 [\cup](/page/Cup) A_2 [\cup](/page/Cup) \cdots [\cup](/page/Cup) A_n or, for greater clarity in indexed collections, i=1nAi={xi{1,2,,n}:xAi}\bigcup_{i=1}^n A_i = \{ x \mid \exists i \in \{1, 2, \dots, n\} : x \in A_i \}. This indexed form emphasizes the collection over a finite {1,2,,n}\{1, 2, \dots, n\}. Consider the example of three sets: A1={1}A_1 = \{1\}, A2={2,3}A_2 = \{2, 3\}, and A3={3,4}A_3 = \{3, 4\}. Their finite union is {1}{2,3}{3,4}={1,2,3,4}\{1\} \cup \{2, 3\} \cup \{3, 4\} = \{1, 2, 3, 4\}, as it includes all distinct elements from the sets. If the sets are pairwise disjoint, such as A1={1,2}A_1 = \{1, 2\}, A2={3}A_2 = \{3\}, and A3={4,5}A_3 = \{4, 5\}, the union {1,2}{3}{4,5}={1,2,3,4,5}\{1, 2\} \cup \{3\} \cup \{4, 5\} = \{1, 2, 3, 4, 5\} simply combines them without overlap. If each AiA_i is a subset of some SS (i.e., AiSA_i \subseteq S for i=1,,ni = 1, \dots, n), then the finite union i=1nAiS\bigcup_{i=1}^n A_i \subseteq S, meaning the result is also a subset of SS and thus an element of the power set P(S)\mathcal{P}(S). This closure property ensures that finite unions preserve membership within the collection of subsets of SS.

Generalizations

Infinite Unions

In set theory, an infinite union over a countable , such as the natural numbers N\mathbb{N}, is defined as the set n=1An={xnN such that xAn}\bigcup_{n=1}^\infty A_n = \{ x \mid \exists n \in \mathbb{N} \ \text{such that} \ x \in A_n \}, where each AnA_n is a set in the collection. This construction extends the notion of finite unions, which can be viewed as a special case where the index set is finite. A concrete example from real analysis illustrates this: consider the collection of open intervals An=(0,1/n)A_n = (0, 1/n) for n=1,2,n = 1, 2, \dots; their infinite union is n=1(0,1/n)=(0,1)\bigcup_{n=1}^\infty (0, 1/n) = (0, 1), as any x(0,1)x \in (0,1) belongs to some interval (0,1/n)(0, 1/n) for sufficiently large n>1/xn > 1/x. Another illustrative case arises in generating dense sets: the rational numbers Q\mathbb{Q} can be expressed as the countable union of singleton sets {qi}\{q_i\}, where {qi}i=1\{q_i\}_{i=1}^\infty enumerates Q\mathbb{Q}, since Q\mathbb{Q} is countable and each singleton is a set. This demonstrates how infinite unions can construct familiar sets from simpler components in analysis. One challenge with infinite unions is that they may fail to preserve topological properties like compactness, even when each individual set is compact. For instance, in R\mathbb{R} with the standard topology, the closed intervals [n,n][-n, n] for nNn \in \mathbb{N} are each compact (closed and bounded), but their union n=1[n,n]=R\bigcup_{n=1}^\infty [-n, n] = \mathbb{R} is not compact, as it is unbounded and admits the open cover {(k1,k+1)kN}\{( -k-1, k+1 ) \mid k \in \mathbb{N} \} with no finite subcover. While countable infinite unions behave predictably in many contexts due to the well-ordering of N\mathbb{N}, uncountable infinite unions—over index sets of cardinality greater than 0\aleph_0—introduce subtler issues; for example, using the , one can construct an uncountable union of null sets that is neither null nor measurable.

Arbitrary Unions

The arbitrary union extends the union operation to any collection of sets indexed by an arbitrary , providing the foundational construct in for combining elements across potentially uncountable families. Given an II and a {AiiI}\{ A_i \mid i \in I \}, the arbitrary union is defined as iIAi={xiI(xAi)}.\bigcup_{i \in I} A_i = \{ x \mid \exists i \in I \, (x \in A_i) \}. This set comprises all elements belonging to at least one set in the family, independent of the structure or cardinality of II. In Zermelo-Fraenkel (ZF), the existence of arbitrary unions derives from core axioms, ensuring such sets are well-defined within the theory. The Union Axiom asserts that for any set XX, there exists a set Y=XY = \bigcup X such that u(uYzX(uz)).\forall u \, (u \in Y \leftrightarrow \exists z \in X \, (u \in z)). This primitive operation guarantees the union of the elements of any given set of sets. To construct the union over an , first form the family as a set: assuming II is a set and the iAii \mapsto A_i is a definable function, the Axiom Schema of Replacement produces the set of pairs {(i,Ai)iI}\{ (i, A_i) \mid i \in I \}, from which the image F={AiiI}F = \{ A_i \mid i \in I \} is obtained via the Axiom Schema of Separation. Applying the Union Axiom to FF yields F\bigcup F, the desired union. The explicit definition via is then isolated using Separation on F\bigcup F, confirming the set's membership criterion without invoking additional primitives. This step-by-step derivation anchors arbitrary unions in ZF's foundational structure, distinguishing them from more restrictive cases like countable unions. For example, taking I=RI = \mathbb{R} and Ar={r}A_r = \{ r \} for each rRr \in \mathbb{R}, the arbitrary union is rR{r}=R,\bigcup_{r \in \mathbb{R}} \{ r \} = \mathbb{R}, demonstrating how an uncountable indexed family reconstructs the continuum from singleton sets. Arbitrary unions over non-well-ordered index sets play a key role in advanced applications, such as topology, where the index set lacks a natural ordering. A prominent example is the disjoint union topology on an uncountable family {XααA}\{ X_\alpha \mid \alpha \in A \} with AA uncountable and each XαX_\alpha a topological space (e.g., copies of R\mathbb{R}): the topology consists of unions αAUα\bigsqcup_{\alpha \in A} U_\alpha where each UαU_\alpha is open in XαX_\alpha, yielding a space that inherits openness from components while accommodating uncountable disjointness, useful for constructing non-second-countable spaces. The defining property holds by : xiIAix \in \bigcup_{i \in I} A_i iI\exists i \in I such that xAix \in A_i, a direct consequence of the comprehension used in the derivation, ensuring every element in some AiA_i is included and no extraneous elements are added.

Notation and Representation

Symbolic Notation

In , the union of two sets AA and BB is denoted by the symbol \cup, written as ABA \cup B, which was introduced by in his 1888 work Calcolo geometrico secondo l'Ausdehnungslehre di H. Grassmann. This symbol, resembling a , has become the standard for binary unions and extends to general unions of multiple sets. For the union of an indexed family of sets {AiiI}\{A_i \mid i \in I\}, where II is an index set, the notation iIAi\bigcup_{i \in I} A_i is employed, using the enlarged symbol \bigcup (n-ary union) with the subscript indicating the range of indices. Peano introduced this large union symbol in 1908 in Formulario mathematico, tomo V, to represent unions over more than two sets. Prior to the widespread adoption of \cup, alternative notations appeared in early logical and set-theoretic texts; for instance, Ernst Schröder used the plus sign ++ to denote the union (or logical sum) of classes in his 1890 Vorlesungen über die Algebra der Logik, volume 1. Simple juxtaposition of set names, such as ABAB, occasionally served as an informal notation for union in preliminary writings by pioneers like before standardized symbols emerged. To ensure clarity in compound expressions, parentheses are conventionally used despite the associativity of union; for example, (AB)C(A \cup B) \cup C explicitly groups the operations. In mathematical typesetting with LaTeX, the binary union is produced via the command \cup, yielding \cup, while the n-ary union uses \bigcup, yielding \bigcup. These symbols correspond to Unicode code points U+222A for \cup (UNION) and U+22C3 for \bigcup (N-ARY UNION), facilitating digital representation in mathematical software and documents. As an illustrative example, consider sets A={1,2}A = \{1, 2\} and B={2,3}B = \{2, 3\}; their union is AB={1,2,3}A \cup B = \{1, 2, 3\}.

Visual Representations

Visual representations play a crucial role in by providing intuitive graphical depictions of unions, helping to convey abstract concepts through spatial relationships. These diagrams illustrate how the union of sets encompasses all elements from the participating sets, often by shading or enclosing regions to highlight the combined area. Venn diagrams, introduced by John Venn in 1880, are among the most common tools for visualizing binary unions, where the union of two sets A and B is represented by the shaded region covering the entire area occupied by both circles, including their overlap. For instance, in a Venn diagram of sets A = {1, 2} and B = {2, 3}, the union A ∪ B = {1, 2, 3} is shown as the full extent of both circles, with the point labeled 2 in the intersection to demonstrate shared elements. However, traditional Venn diagrams are limited to three sets due to the increasing complexity of drawing simple closed curves that intersect in all possible ways for higher cardinalities; for more than three sets, modifications proposed by A. W. F. Edwards in 2004 use rotated ellipses or other shapes to approximate these intersections while maintaining readability. Euler diagrams offer a more general alternative, employing enclosed curves to represent sets where regions exist only if the corresponding intersections are non-empty, thus avoiding the exhaustive overlap requirements of Venn diagrams and better suiting unions of sets with empty intersections. In practice, these diagrams reveal key insights into unions, such as how A ∪ B equals A unioned with the elements of B excluding A (B \ A), visually depicted as the non-overlapping part of B added to A. For arbitrary or infinite unions, modern digital tools like SetViz enable interactive visualizations using techniques such as UpSet plots or chord diagrams to handle complex intersections beyond what static hand-drawn diagrams can achieve.

Properties

Algebraic Properties

The union operation in forms the join in the power set lattice and corresponds to in , endowing it with a rich structure of identities. Commutativity states that for any sets AA and BB, AB=BAA \cup B = B \cup A. To prove this, consider an arbitrary element xx. If xABx \in A \cup B, then xAx \in A or xBx \in B; by of the disjunction, this implies xBx \in B or xAx \in A, so xBAx \in B \cup A. Conversely, if xBAx \in B \cup A, the same yields xABx \in A \cup B. Thus, the sets are equal. Associativity holds: for sets AA, BB, and CC, (AB)C=A(BC)(A \cup B) \cup C = A \cup (B \cup C). The proof proceeds by double inclusion. First, show (AB)CA(BC)(A \cup B) \cup C \subseteq A \cup (B \cup C): if x(AB)Cx \in (A \cup B) \cup C, then either xABx \in A \cup B (so xAx \in A or xBx \in B, hence xA(BC)x \in A \cup (B \cup C)) or xCx \in C (so xA(BC)x \in A \cup (B \cup C)). Conversely, if xA(BC)x \in A \cup (B \cup C), then xAx \in A (so xABx \in A \cup B, hence x(AB)Cx \in (A \cup B) \cup C), or xBCx \in B \cup C (so xBx \in B or xCx \in C; if xBx \in B then xABx \in A \cup B, hence x(AB)Cx \in (A \cup B) \cup C; if xCx \in C then directly x(AB)Cx \in (A \cup B) \cup C). Idempotence is given by AA=AA \cup A = A for any set AA. To verify, if xAAx \in A \cup A, then xAx \in A or xAx \in A, which simplifies to xAx \in A by the of disjunction. Thus, AAAA \cup A \subseteq A. The reverse inclusion holds since AAAA \subseteq A \cup A by definition of union. The absorption law asserts A(AB)=AA \cup (A \cap B) = A. For the inclusion A(AB)AA \cup (A \cap B) \subseteq A, note that AAA \subseteq A and ABAA \cap B \subseteq A, so their union is contained in AA. For the reverse, AA(AB)A \subseteq A \cup (A \cap B) follows directly from the definition of union. Distributivity of union over intersection is A(BC)=(AB)(AC)A \cup (B \cap C) = (A \cup B) \cap (A \cup C). To verify, first show the left side is contained in the right: if xA(BC)x \in A \cup (B \cap C), then either xAx \in A (so xABx \in A \cup B and xACx \in A \cup C, hence x(AB)(AC)x \in (A \cup B) \cap (A \cup C)) or xBCx \in B \cap C (so xBx \in B and xCx \in C, implying xABx \in A \cup B and xACx \in A \cup C). Conversely, if x(AB)(AC)x \in (A \cup B) \cap (A \cup C), then xABx \in A \cup B and xACx \in A \cup C; if xAx \in A, then xA(BC)x \in A \cup (B \cap C); otherwise, xBx \in B and xCx \in C, so xBCx \in B \cap C and thus xA(BC)x \in A \cup (B \cap C). These properties parallel those of intersection, which serves as the meet in the lattice structure (detailed elsewhere). A related identity from Boolean algebra is De Morgan's law, which connects union to complements: AB=(AcBc)cA \cup B = (A^c \cap B^c)^c, where c^c denotes complement relative to a universal set.

Cardinality and Measure

In set theory, the cardinality of the union of two finite sets AA and BB is given by the formula AB=A+BAB|A \cup B| = |A| + |B| - |A \cap B|, which accounts for the overlap to avoid double-counting elements. This relation derives from the principle of inclusion-exclusion applied to the first two terms, where the total elements in the union equal the sum of individual cardinalities minus the shared intersection. For a proof sketch in the finite case, partition BB into BAB \cap A and BAB \setminus A; since AA and BAB \setminus A are disjoint, AB=A+BA|A \cup B| = |A| + |B \setminus A|, and BA=BAB|B \setminus A| = |B| - |A \cap B| holds for finite cardinals, yielding the formula. For a finite or infinite family of pairwise disjoint sets {Ai}iI\{A_i\}_{i \in I}, the cardinality of their union is the sum of the individual cardinalities: iIAi=iIAi|\bigcup_{i \in I} A_i| = \sum_{i \in I} |A_i|, where the sum is interpreted in cardinal arithmetic. In the infinite case, cardinal addition is idempotent, so for infinite cardinals κ\kappa and λ\lambda with at least one infinite, the union cardinality simplifies to κ+λ=max(κ,λ)|\kappa + \lambda| = \max(\kappa, \lambda) when sets are not necessarily disjoint, assuming the axiom of choice. For example, the infinite union of singleton sets xS{x}\bigcup_{x \in S} \{x\} over an index set SS has cardinality S|S|, as it reconstructs SS without overlaps. In measure theory, for Lebesgue measurable sets AA and BB in Rn\mathbb{R}^n, the measure of their union follows an analogous subadditive relation: μ(AB)=μ(A)+μ(B)μ(AB)\mu(A \cup B) = \mu(A) + \mu(B) - \mu(A \cap B), extending finite additivity to account for overlap. For countable unions of measurable sets, is only subadditive: μ(i=1Ai)i=1μ(Ai)\mu\left(\bigcup_{i=1}^\infty A_i\right) \leq \sum_{i=1}^\infty \mu(A_i), with equality if the sets are pairwise disjoint. Strict inequality arises in overlapping cases; for instance, if A=B=[0,1]A = B = [0,1], then μ(AB)=1<2=μ(A)+μ(B)\mu(A \cup B) = 1 < 2 = \mu(A) + \mu(B).

Historical Development

Origins in Mathematics

The concept of union in set theory has early roots implicit in Aristotelian logic, where syllogisms combined categories—such as substances, quantities, and relations—to reason about classes of entities around 350 BCE. In the , advanced this idea through his algebraic treatment of logical classes in An Investigation of the Laws of Thought (), defining "addition" as a partial operation representing the union of disjoint classes, thus laying groundwork for set-theoretic operations. This proto-union allowed symbolic manipulation of classes, bridging logic and mathematics. Georg Cantor formalized the union explicitly in his Grundlagen einer allgemeinen Mannigfaltigkeitslehre (1883), defining Vereinigung (union) as the aggregate formed by combining elements from multiple sets, foundational to his of infinite aggregates. contributed overlooked notation in his 1888 work Calcolo geometrico and 1889 Arithmetices principia, introducing symbols like ∪ for union, which influenced modern symbolic conventions in . The discovery of Bertrand Russell's paradox in 1901 exposed contradictions in naive set theory, such as the set of all sets not containing themselves, prompting a shift from descriptive to axiomatic foundations. Ernst Zermelo addressed this in his 1908 axiomatization, introducing the union axiom, which guarantees the existence of the union of any set's elements as a set itself, stabilizing set theory against paradoxes. This evolution marked the transition to rigorous, paradox-free frameworks like Zermelo-Fraenkel set theory.

Etymology and Terminology

The English term "union" originates from the Latin ūniō (nominative ūnio), meaning "oneness" or "unity," derived from ūnus ("one"), and entered the in the early via Anglo-French and union, initially denoting the act of joining or a state of agreement. In mathematical contexts, particularly , it was adopted through 19th-century translations of continental European works, reflecting the concept of combining elements into a single whole. In German, the equivalent term "Vereinigung," meaning "joining together" or "combination," was introduced by in 1880 in his foundational paper "Über unendliche, lineare Punktmannigfaltigkeiten" (On Infinite Linear Point Manifolds), where it described the operation of merging sets. Cantor's use of "Vereinigung" played a key in formalizing set-theoretic , influencing subsequent across languages. The French "union" similarly emerged in mathematical usage, directly influenced by Giuseppe Peano's 1888 work Calcolo geometrico secondo l'Ausdehnungslehre di H. Grassmann, where Peano introduced the symbol ∪ for the operation of logical sum (summa logica). Synonyms for the operation include "join" in lattice theory, where it denotes the least upper bound of elements, corresponding to set union in the power set lattice. In older logical and probabilistic texts, it was sometimes called "sum," evolving from George Boole's "" of classes in (1854), later termed "logical sum" by Peano to distinguish disjunction from arithmetic operations. This terminology shifted to the standardized "union" around 1900, as matured beyond logic. The term's adoption in mathematics mirrors its broader cultural analogy to physical or social merging, as in "labor unions" formed by workers combining for collective strength, emphasizing unity from multiplicity—a parallel that underscores the intuitive appeal of the concept in set theory.

References

  1. https://proofwiki.org/wiki/Definition:Set_Union/Finite_Union
  2. https://proofwiki.org/wiki/Union_is_Associative
  3. https://proofwiki.org/wiki/Set_Union_is_Idempotent
  4. https://proofwiki.org/wiki/Union_Distributes_over_Intersection
  5. https://proofwiki.org/wiki/De_Morgan%27s_Laws_(Set_Theory)
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