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Transitive relation
Transitive relation
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In mathematics, a binary relation R on a set X is transitive if, for all elements a, b, c in X, whenever R relates a to b and b to c, then R also relates a to c.

Key Information

Every partial order and every equivalence relation is transitive. For example, less than and equality among real numbers are both transitive: If a < b and b < c then a < c; and if x = y and y = z then x = z.

Definition

[edit]
Transitive binary relations
Symmetric Antisymmetric Connected Well-founded Has joins Has meets Reflexive Irreflexive Asymmetric
Total,
Semiconnex
Anti-
reflexive
Equivalence relation Green tickY Green tickY
Preorder (Quasiorder) Green tickY
Partial order Green tickY Green tickY
Total preorder Green tickY Green tickY
Total order Green tickY Green tickY Green tickY
Prewellordering Green tickY Green tickY Green tickY
Well-quasi-ordering Green tickY Green tickY
Well-ordering Green tickY Green tickY Green tickY Green tickY
Lattice Green tickY Green tickY Green tickY Green tickY
Join-semilattice Green tickY Green tickY Green tickY
Meet-semilattice Green tickY Green tickY Green tickY
Strict partial order Green tickY Green tickY Green tickY
Strict weak order Green tickY Green tickY Green tickY
Strict total order Green tickY Green tickY Green tickY Green tickY
Symmetric Antisymmetric Connected Well-founded Has joins Has meets Reflexive Irreflexive Asymmetric
Definitions,
for all and
Green tickY indicates that the column's property is always true for the row's term (at the very left), while indicates that the property is not guaranteed
in general (it might, or might not, hold). For example, that every equivalence relation is symmetric, but not necessarily antisymmetric,
is indicated by Green tickY in the "Symmetric" column and in the "Antisymmetric" column, respectively.

All definitions tacitly require the homogeneous relation be transitive: for all if and then
A term's definition may require additional properties that are not listed in this table.

A homogeneous relation R on the set X is a transitive relation if,[1]

for all a, b, cX, if a R b and b R c, then a R c.

Or in terms of first-order logic:

,

where a R b is the infix notation for (a, b) ∈ R.

Examples

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As a non-mathematical example, the relation "is an ancestor of" is transitive. For example, if Amy is an ancestor of Becky, and Becky is an ancestor of Carrie, then Amy is also an ancestor of Carrie.

On the other hand, "is the birth mother of" is not a transitive relation, because if Alice is the birth mother of Brenda, and Brenda is the birth mother of Claire, then it does not follow that Alice is the birth mother of Claire. In fact, this relation is antitransitive: Alice can never be the birth mother of Claire.

Non-transitive, non-antitransitive relations include sports fixtures (playoff schedules), 'knows' and 'talks to'.

The examples "is greater than", "is at least as great as", and "is equal to" (equality) are transitive relations on various sets. As are the set of real numbers or the set of natural numbers:

whenever x > y and y > z, then also x > z
whenever xy and yz, then also xz
whenever x = y and y = z, then also x = z.

More examples of transitive relations:

Examples of non-transitive relations:

The empty relation on any set is transitive[3] because there are no elements such that and , and hence the transitivity condition is vacuously true. A relation R containing only one ordered pair is also transitive: if the ordered pair is of the form for some the only such elements are , and indeed in this case , while if the ordered pair is not of the form then there are no such elements and hence is vacuously transitive.

Vacuous transitivity is transitivity when in a relation there are no ordered pairs of the form (a,b) and (b,c).

Properties

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Closure properties

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  • The converse (inverse) of a transitive relation is always transitive. For instance, knowing that "is a subset of" is transitive and "is a superset of" is its converse, one can conclude that the latter is transitive as well.
  • The intersection of two transitive relations is always transitive.[4] For instance, knowing that "was born before" and "has the same first name as" are transitive, one can conclude that "was born before and also has the same first name as" is also transitive.
  • The union of two transitive relations need not be transitive. For instance, "was born before or has the same first name as" is not a transitive relation, since e.g. Herbert Hoover is related to Franklin D. Roosevelt, who is in turn related to Franklin Pierce, while Hoover is not related to Franklin Pierce.
  • The complement of a transitive relation need not be transitive.[5] For instance, while "equal to" is transitive, "not equal to" is only transitive on sets with at most one element.

Other properties

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A transitive relation is asymmetric if and only if it is irreflexive.[6]

A transitive relation need not be reflexive. When it is, it is called a preorder. For example, on set X = {1,2,3}:

  • R = { (1,1), (2,2), (3,3), (1,3), (3,2) } is reflexive, but not transitive, as the pair (1,2) is absent,
  • R = { (1,1), (2,2), (3,3), (1,3) } is reflexive as well as transitive, so it is a preorder,
  • R = { (1,1), (2,2), (3,3) } is reflexive as well as transitive, another preorder,
  • R = { (1,2), (2,3), (1,3) } is transitive, but not reflexive.

As a counter example, the relation on the real numbers is transitive, but not reflexive.

Transitive extensions and transitive closure

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Let R be a binary relation on set X. The transitive extension of R, denoted R1, is the smallest binary relation on X such that R1 contains R, and if (a, b) ∈ R and (b, c) ∈ R then (a, c) ∈ R1.[7] For example, suppose X is a set of towns, some of which are connected by roads. Let R be the relation on towns where (A, B) ∈ R if there is a road directly linking town A and town B. This relation need not be transitive. The transitive extension of this relation can be defined by (A, C) ∈ R1 if you can travel between towns A and C by using at most two roads.

If a relation is transitive then its transitive extension is itself, that is, if R is a transitive relation then R1 = R.

The transitive extension of R1 would be denoted by R2, and continuing in this way, in general, the transitive extension of Ri would be Ri + 1. The transitive closure of R, denoted by R* or R is the set union of R, R1, R2, ... .[8]

The transitive closure of a relation is a transitive relation.[8]

The relation "is the birth parent of" on a set of people is not a transitive relation. However, in biology the need often arises to consider birth parenthood over an arbitrary number of generations: the relation "is a birth ancestor of" is a transitive relation and it is the transitive closure of the relation "is the birth parent of".

For the example of towns and roads above, (A, C) ∈ R* provided you can travel between towns A and C using any number of roads.

Relation types that require transitivity

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Counting transitive relations

[edit]

No general formula that counts the number of transitive relations on a finite set (sequence A006905 in the OEIS) is known.[9] However, there is a formula for finding the number of relations that are simultaneously reflexive, symmetric, and transitive – in other words, equivalence relations – (sequence A000110 in the OEIS), those that are symmetric and transitive, those that are symmetric, transitive, and antisymmetric, and those that are total, transitive, and antisymmetric. Pfeiffer[10] has made some progress in this direction, expressing relations with combinations of these properties in terms of each other, but still calculating any one is difficult. See also Brinkmann and McKay (2005)[11] and Mala (2022).[12]

Since the reflexivization of any transitive relation is a preorder, the number of transitive relations an on n-element set is at most 2n time more than the number of preorders, thus it is asymptotically by results of Kleitman and Rothschild.[13]

Number of n-element binary relations of different types
Elem­ents Any Transitive Reflexive Symmetric Preorder Partial order Total preorder Total order Equivalence relation
0 1 1 1 1 1 1 1 1 1
1 2 2 1 2 1 1 1 1 1
2 16 13 4 8 4 3 3 2 2
3 512 171 64 64 29 19 13 6 5
4 65,536 3,994 4,096 1,024 355 219 75 24 15
n 2n2 2n(n−1) 2n(n+1)/2 n
k=0
k!S(n, k)
n! n
k=0
S(n, k)
OEIS A002416 A006905 A053763 A006125 A000798 A001035 A000670 A000142 A000110

Note that S(n, k) refers to Stirling numbers of the second kind.

[edit]
Cycle diagram
The Rock–paper–scissors game is based on an intransitive and antitransitive relation "x beats y".

A relation R is called intransitive if it is not transitive, that is, if xRy and yRz, but not xRz, for some x, y, z. In contrast, a relation R is called antitransitive if xRy and yRz always implies that xRz does not hold. For example, the relation defined by xRy if xy is an even number is intransitive,[14] but not antitransitive.[15] The relation defined by xRy if x is even and y is odd is both transitive and antitransitive.[16] The relation defined by xRy if x is the successor number of y is both intransitive[17] and antitransitive.[18] Unexpected examples of intransitivity arise in situations such as political questions or group preferences.[19]

Generalized to stochastic versions (stochastic transitivity), the study of transitivity finds applications of in decision theory, psychometrics and utility models.[20]

A quasitransitive relation is another generalization;[5] it is required to be transitive only on its non-symmetric part. Such relations are used in social choice theory or microeconomics.[21]

Proposition: If R is a univalent, then R;RT is transitive.

proof: Suppose Then there are a and b such that Since R is univalent, yRb and aRTy imply a=b. Therefore xRaRTz, hence xR;RTz and R;RT is transitive.

Corollary: If R is univalent, then R;RT is an equivalence relation on the domain of R.

proof: R;RT is symmetric and reflexive on its domain. With univalence of R, the transitive requirement for equivalence is fulfilled.

See also

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Notes

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References

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Further reading

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[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
In , a transitive relation is a RR on a set AA such that for all elements a,b,cAa, b, c \in A, if (a,b)R(a, b) \in R and (b,c)R(b, c) \in R, then (a,c)R(a, c) \in R. This property ensures that chains of relatedness propagate throughout the relation, capturing a form of "connectivity" in relational structures. Transitive relations play a foundational role in and , particularly in defining more complex structures like equivalence relations—which are reflexive, symmetric, and transitive—and thus partition sets into equivalence classes—and partial orders, which are reflexive, antisymmetric, and transitive, forming partially ordered sets (posets) used in areas such as lattice theory and optimization. Common examples include the "less than" relation (<<) on real numbers, where if x<yx < y and y<zy < z, then x<zx < z, and the divisibility relation on positive , where if aa divides bb and bb divides cc, then aa divides cc. A relation fails transitivity if there exists a chain aRbaRb and bRcbRc without aRcaRc, as seen in the "is the father of" relation, where grandparenthood does not imply direct parenthood. Transitivity can also be characterized equivalently: a relation RR is transitive for every positive nn, the nn-fold composition RnRR^n \subseteq R.

Fundamentals

Definition

A binary relation is a fundamental concept in set theory and mathematics, defined as a subset of the Cartesian product of two sets. Specifically, for sets AA and BB, a binary relation RR from AA to BB is any subset of A×BA \times B, where A×B={(a,b)aA,bB}A \times B = \{(a, b) \mid a \in A, b \in B\}. When A=B=XA = B = X, the relation is homogeneous, meaning it relates elements within the same set XX; in contrast, heterogeneous relations connect elements from distinct sets AA and BB. The property of transitivity applies primarily to homogeneous binary relations on a set. A binary relation RR on a set XX is transitive if, for all a,b,cXa, b, c \in X, whenever aRba \, R \, b and bRcb \, R \, c, it follows that aRca \, R \, c. This condition ensures that the relation "chains" consistently across elements. An equivalent characterization of transitivity uses relation composition, defined as RS={(a,c)bX such that (a,b)R and (b,c)S}R \circ S = \{(a, c) \mid \exists b \in X \text{ such that } (a, b) \in R \text{ and } (b, c) \in S\} for relations RR and SS on XX. A relation RR on XX is transitive if and only if RRRR \circ R \subseteq R. For heterogeneous relations, transitivity extends analogously, requiring that if (a,b)R(a, b) \in R and (b,c)R(b', c) \in R with b=bb = b' in the appropriate intersection of domains and codomains, then (a,c)R(a, c) \in R.

Examples

In everyday contexts, the relation "is an of" on the set of is transitive: if A is an of B, and B is an of C, then A must be an of C, as ancestry chains through generations without interruption. In contrast, the relation "is a of" on the same set is not transitive; for instance, if Alice is a of Bob, and Bob is a of Charlie, Alice is typically a of Charlie rather than a direct . A classic mathematical example of a transitive relation is the "less than or equal to" relation \leq on the set of real numbers: if aba \leq b and bcb \leq c, then aca \leq c, reflecting the natural ordering of the . Similarly, the relation \subseteq on the of a given set (the collection of all its subsets) is transitive: if set ABA \subseteq B and BCB \subseteq C, then every element in AA is also in CC, so ACA \subseteq C. To visualize transitivity, consider a directed graph with vertices AA, BB, and CC, where edges represent the relation: an edge from AA to BB and from BB to CC implies the relation holds between AA and CC, adding a direct edge from AA to CC to satisfy transitivity.

A ──→ B ──→ C ──→ C

A ──→ B ──→ C ──→ C

This triple forms a transitive "," as seen in graph representations of relations.

Properties

Closure Properties

Transitivity is preserved under arbitrary intersections of relations. That is, if {Ri}iI\{R_i\}_{i \in I} is a family of transitive relations on a set AA, then their R=iIRiR = \bigcap_{i \in I} R_i is transitive. To see this, suppose (a,b)R(a, b) \in R and (b,c)R(b, c) \in R. Then for every iIi \in I, (a,b)Ri(a, b) \in R_i and (b,c)Ri(b, c) \in R_i. Since each RiR_i is transitive, (a,c)Ri(a, c) \in R_i for all iIi \in I, so (a,c)R(a, c) \in R. This establishes the transitivity of the using the definition directly. In contrast, transitivity is not preserved under unions. For a , consider the set A={1,2,3}A = \{1, 2, 3\}. Let R={(1,2)}R = \{(1, 2)\} and S={(2,3)}S = \{(2, 3)\}. Both RR and SS are transitive, as neither contains a pair of consecutive elements requiring a third. However, RS={(1,2),(2,3)}R \cup S = \{(1, 2), (2, 3)\} is not transitive, since (1,2)RS(1, 2) \in R \cup S and (2,3)RS(2, 3) \in R \cup S, but (1,3)RS(1, 3) \notin R \cup S. Regarding composition, if RR and SS are transitive relations on a set AA satisfying RSSRR \circ S \subseteq S \circ R, then RSR \circ S is transitive. Note that without this condition, the composition of transitive relations need not be transitive; for instance, on A={1,2,3,4,5}A = \{1,2,3,4,5\}, let R={(1,2),(3,4)}R = \{(1,2),(3,4)\} and S={(2,3),(4,5)}S = \{(2,3),(4,5)\}, both transitive, but RS={(1,3),(3,5)}R \circ S = \{(1,3),(3,5)\} (where (x,z)RS(x,z) \in R \circ S if there exists yy with (x,y)R(x,y) \in R and (y,z)S(y,z) \in S), which contains (1,3)(1,3) and (3,5)(3,5) but not (1,5)(1,5). The reflexive-transitive closure of a relation QQ on a set AA is the smallest relation on AA that contains QQ and is both reflexive and transitive. It can be constructed as the of the reflexive closure of QQ, or equivalently as n=0Qn\bigcup_{n=0}^\infty Q^n where Q0Q^0 is the identity relation and higher powers are compositions. This closure plays a key role in generating minimal structures extending QQ with these properties, distinct from the pure detailed later.

Algebraic Properties

A transitive relation RR on a set XX becomes a when it is also reflexive, meaning that for every xXx \in X, xRxx R x holds, alongside the transitivity condition that if aRba R b and bRcb R c, then aRca R c. Preorders generalize partial orders by relaxing antisymmetry, allowing distinct elements aa and bb to satisfy both aRba R b and bRab R a without requiring a=ba = b. This structure partitions XX into equivalence classes where elements are mutually related, with a partial order defined on the quotient set of these classes. In the context of orders, a transitive relation RR interpreted as a strict partial order (irreflexive and transitive) is dense if, for any a,bXa, b \in X with aRba R b, there exists xXx \in X such that aRxa R x and xRbx R b. This density property ensures no "gaps" between comparable elements, mirroring the structure of the rational numbers under the usual order. Countable dense linear orders without endpoints are unique up to isomorphism, embedding any countable linear order. Such relations facilitate universal embedding properties in order theory, where any countable partial order can be extended to a dense linear extension. If a transitive relation RR is also symmetric—meaning aRba R b implies bRab R a—then RR forms a , which decomposes as a of on the subsets where reflexivity holds (the support of RR). Specifically, the connected components in the underlying undirected graph of RR are complete cliques, each inducing a full on its vertices, while elements outside these components relate trivially. Without symmetry, transitivity alone does not yield such a decomposition into equivalences, highlighting the role of in . Viewing a transitive relation as a G=(X,E)G = (X, E), where edges represent RR, transitivity implies that any path of length 2 (from aa to bb to cc) requires a direct edge from aa to cc, effectively closing the graph under composition of adjacent edges. In functional graphs, where each vertex has out-degree at most 1 (modeling functions or mappings), this property forces chains to collapse: if abca \to b \to c, then aca \to c must hold, but the out-degree constraint implies that non-constant functions cannot be transitive unless they are constant on cycles or fixed points, limiting such relations to simple structures like identity or constant maps. To see the component structure, consider the directed graph of a transitive relation RR; its strongly connected components (where mutual reachability holds) form equivalence classes under the symmetric part of RR, and the condensation graph—contracting each component to a single vertex—yields a strict partial order on these components, as transitivity preserves paths between them without cycles. Formally, let \sim be the relation ab    aRbbRaa \sim b \iff a R b \land b R a; then \sim is an equivalence relation on the support of RR, and RR induces a transitive relation on the quotient that is antisymmetric. This decomposition shows RR as a disjoint union of these equivalence components ordered transitively, with proof following from transitivity ensuring closure under paths within and between components.

Extensions and Constructions

Transitive Extensions

A transitive extension of a RR on a set XX is a transitive SS on XX such that RSR \subseteq S. Such extensions allow non-transitive relations to be enlarged while preserving the original connections and ensuring the transitivity property holds for the resulting relation. For any RR on a finite or infinite set XX, transitive extensions exist; the of RR provides the smallest such extension, which coincides with the minimal transitive extension (see the section on for details). This guarantees that every relation can be embedded into a transitive structure without losing its original pairs. Larger extensions are also possible, up to the full relation X×XX \times X, which is trivially transitive. When RR is a partial order (reflexive, antisymmetric, and transitive), maximal transitive extensions correspond to linear extensions of the poset, which are total orders containing RR. These are maximal in the sense that no further pairs can be added while maintaining transitivity and totality. The existence of such extensions is ensured by Szpilrajn's extension theorem, which states that every partial order on XX can be extended to a on XX. An algorithmic approach to constructing a transitive extension begins with the initial relation RR and iteratively incorporates all pairs (a,c)(a, c) for which there exists some bb such that (a,b)(a, b) and (b,c)(b, c) are in the current relation, repeating until no additional pairs can be added. This process generates the as the minimal transitive extension.

Transitive Closure

The of a RR on a set XX, denoted R+R^+, is defined as the smallest transitive relation SS on XX such that RSR \subseteq S. This means SS contains all pairs from RR and is transitive, while no proper of SS that still contains RR and remains transitive exists. One standard construction of the transitive closure is given by the infinite union of powers of the relation: R+=n=1Rn,R^+ = \bigcup_{n=1}^\infty R^n, where R1=RR^1 = R and Rn+1=RnRR^{n+1} = R^n \circ R for n1n \geq 1, with \circ denoting relational composition. This union captures all finite chains of elements connected through RR, ensuring transitivity by including pairs (x,z)(x, z) whenever there exists a sequence x=y0Ry1RRyn=zx = y_0 \, R \, y_1 \, R \, \cdots \, R \, y_n = z for some n1n \geq 1. For finite sets XX with X=n|X| = n, the construction simplifies since longer chains cannot introduce new pairs beyond length nn; thus, R+=k=1nRk.R^+ = \bigcup_{k=1}^n R^k. This finite union suffices because any chain longer than nn must repeat elements by the , and transitivity already accounts for such repetitions through shorter subchains. In , where a corresponds to the edge set of a with nn vertices, the can be computed using Warshall's . This dynamic programming approach initializes a boolean matrix with the of the graph and iteratively updates it by considering each vertex as an intermediate node, ultimately yielding the reachability matrix in O(n3)O(n^3) time. The transitive closure always exists for any binary relation on any set and is given explicitly by R+=n=1RnR^+ = \bigcup_{n=1}^\infty R^n, which is the smallest transitive relation containing RR. This construction includes all pairs connected by finite chains of length at least 1 and works for both finite and infinite sets.

Enumeration

Counting Methods

Counting transitive binary relations on a finite set of nn elements presents significant challenges due to the dependencies imposed by the transitivity condition. While the total number of binary relations is simply 2n22^{n^2}, transitivity requires that whenever (a,b)(a, b) and (b,c)(b, c) are included, (a,c)(a, c) must also be present, preventing independent selection of pairs and complicating direct combinatorial enumeration. This interdependence often leads to an exponential increase in verification steps, making naive generation inefficient for even moderate nn. The of transitive relations is intimately connected to the counting of partial orders, as the latter represent the reflexive and antisymmetric subset of transitive relations. Combinatorial techniques decompose a transitive relation into an equivalence partition of the set (capturing symmetric components) and a partial order on the , allowing the total count to be expressed through convolutions involving the number of partial orders P(k)P(k) on kk elements and partitions of the remaining elements. This reduction transforms the problem into aggregating known or computable poset counts, underscoring how transitivity enumeration builds upon poset structures. The sequence P(n)P(n), corresponding to OEIS A001035, exemplifies this linkage. These approaches highlight the methodological overlap with poset generation. For reflexive transitive relations—known as preorders or quasi-orders—the counting simplifies to a direct convolution of Stirling numbers of the second kind with P(n)P(n), further illustrating the partial order foundation. The computational difficulty of P(n)P(n) mirrors that of Dedekind numbers (OEIS A000372), which count monotone Boolean functions and require advanced recursive or generative algorithms for evaluation; both sequences grow rapidly and lack closed forms, limiting exact computations to small nn. Computational approaches, including dynamic programming over subsets, facilitate counting for small nn by maintaining states that track reachable elements or closure properties for partial relations. For example, one can define states based on subsets representing the current "layers" or connected components, updating transitions to enforce transitivity without full matrix storage. Combined with tools like GAP for algebraic computations and nauty for isomorphism handling in related structures (such as unlabelled cases up to n=12n=12), these methods contribute to enumerations, with labelled transitive relations known up to n=18n=18. Such techniques are essential given the absence of closed-form expressions.

Known Sequences and Formulas

The number of transitive relations on a set of nn labeled elements is given by the sequence A006905 in the OEIS, with values computed via recursive relations involving partial orders and of the second kind. No closed-form formula is known for this count, but an exact expression is T(n)=j=0n(nj)k=jnS(nj,kj)PkT(n) = \sum_{j=0}^{n} \binom{n}{j} \sum_{k=j}^{n} S(n-j, k-j) P_k, where S(m,l)S(m, l) is the of the second kind and PkP_k is the number of partial orders on kk labeled elements (OEIS A001035). This formula facilitates computation for small nn by incorporating the enumeration of transitive digraphs reducible to partial orders, with values verified computationally up to n=18n=18. The first few terms are presented in the following table:
nnNumber of transitive relations
01
12
213
3171
43994
5154303
69415189
7878222530
The asymptotic behavior of T(n)T(n) is T(n)2nPnT(n) \sim 2^n P_n, where Pn2n2/4+3n/2+O(logn)P_n \sim 2^{n^2/4 + 3n/2 + O(\log n)}, yielding log2T(n)n2/4+5n/2+O(logn)\log_2 T(n) \approx n^2/4 + 5n/2 + O(\log n) as the dominant growth term, reflecting the exponential increase constrained by transitivity. Special cases arise when additional properties are imposed. The number of reflexive transitive relations (preorders or quasi-orders) on nn labeled elements is given by OEIS A000798, with terms 1, 1, 4, 29, 355, 6942, 209527 for n=0n=0 to 6, computed as Q(n)=k=0nS(n,k)PkQ(n) = \sum_{k=0}^n S(n,k) P_k. For reflexive transitive antisymmetric relations (partial orders or posets), the count is OEIS A001035, with terms 1, 1, 3, 19, 219, 4231, 130023 for n=0n=0 to 6.

Applications

In Order Theory

In order theory, a preorder on a set SS is a \leq that is reflexive and transitive. This structure generalizes partial orders by omitting the antisymmetry condition, allowing elements to be equivalent without being identical. A partial order is a preorder that additionally satisfies antisymmetry: if xyx \leq y and yxy \leq x, then x=yx = y. This property ensures that distinct elements are strictly comparable only in one direction, forming a (poset) where incomparability is possible between unrelated elements. A strict partial order, in contrast, is an irreflexive and transitive relation << on SS, which is also asymmetric as a consequence. It arises naturally from a partial order by defining x<yx < y if xyx \leq y and xyx \neq y, providing a way to exclude reflexivity for applications requiring strict inequalities. Hasse diagrams visualize finite posets by representing the transitive reduction, where edges depict only the cover relation: aba \prec b if a<ba < b and no cc exists with a<c<ba < c < b. This reduction omits reflexive loops and transitive edges, yielding a that highlights the minimal structure of the partial order for intuitive comprehension. A fundamental states that every \preceq on a set XX induces a partition of XX into equivalence classes via the relation \sim defined by xyx \sim y if and only if xyx \preceq y and yxy \preceq x, which is reflexive, symmetric, and transitive. The quotient set X/X / \sim consists of these equivalence classes ={yXxy}_\sim = \{ y \in X \mid x \sim y \}. Defining a relation \leq^* on X/X / \sim by _\sim \leq^* _\sim if xyx \preceq y yields a partial order, as reflexivity follows from \sim, antisymmetry from the distinctness of classes under \sim, and transitivity from that of \preceq. This quotient poset captures the ordering up to equivalence, with the proof relying on verifying these properties directly from the definitions.

In Graph Theory and Computer Science

In directed graphs, the adjacency relation is transitive if and only if the graph is a transitive digraph, meaning that whenever there is a directed edge from vertex uu to vv and from vv to ww, there is also a direct edge from uu to ww. This property ensures the graph contains all implied edges under transitivity, forming a structure without "missing" transitive connections. In the special case of —complete directed graphs with exactly one directed edge between every pair of vertices—the adjacency relation is transitive if and only if the is a transitive , which is acyclic and corresponds to a on the vertices. The relation in a , which holds between two vertices if there exists a directed path connecting them, is always transitive by definition, as the existence of paths from uu to vv and vv to ww implies a path from uu to ww. This relation can be computed using the of the graph's , a process that identifies all pairwise reachabilities. One efficient method for this computation is a variant of the Floyd-Warshall algorithm, adapted from its original shortest-path formulation to use operations (logical OR and AND) instead of and minimization; it runs in O(n3)O(n^3) time for a graph with nn vertices, making it suitable for dense graphs where all-pairs reachability is needed. Transitive relations find practical applications in , particularly in database query optimization and type systems for programming languages. In models, transitive dependencies occur when a non-key attribute functionally depends on another non-key attribute through a key, violating (3NF) and leading to redundancy; normalization techniques eliminate these by decomposing relations to ensure dependencies are direct, as formalized in Codd's framework for relational integrity. Similarly, in programming languages, the subtype relation—where a type SS is a subtype of TT if values of SS can be used wherever TT is expected—is transitive, enabling algorithms to propagate rules across hierarchies for safe polymorphism without explicit casts. An illustrative example appears in social network analysis, where the "friend-of-a-friend" recommendation leverages the transitive closure of the friendship relation: if user AA is directly connected to BB, and BB to CC, then AA and CC are indirectly connected, suggesting potential edges to enhance network growth or user engagement models.

Comparisons with Other Binary Relation Properties

A transitive relation RR on a set AA is compared to other binary relation properties such as reflexivity, symmetry, and asymmetry, which define distinct structures when combined. Reflexivity requires that for every aAa \in A, aRaa R a holds, ensuring self-relation for all elements. When combined with transitivity, reflexivity yields a preorder, a structure that generalizes partial orders by allowing non-antisymmetric elements. Symmetry stipulates that if aRba R b, then bRab R a for all a,bAa, b \in A, promoting bidirectional relations. The combination of transitivity, , and reflexivity forms an , partitioning the set into equivalence classes where elements are indistinguishable under RR. For instance, equality on real numbers exemplifies this trio of properties. Asymmetry demands that if aRba R b, then ¬(bRa)\neg (b R a) for all a,bAa, b \in A with aba \neq b, excluding mutual relations and implying irreflexivity. Pairing with transitivity produces a strict partial order, a irreflexive and asymmetric structure suitable for modeling strict inequalities, such as the less-than relation on natural numbers. Relations violating transitivity often involve cycles, where chains fail to close appropriately. For example, consider the relation R={(1,2),(2,3),(3,1)}R = \{(1,2), (2,3), (3,1)\} on {1,2,3}\{1,2,3\}; here, 1R21 R 2 and 2R32 R 3, but ¬(1R3)\neg (1 R 3), demonstrating non-transitivity despite pairwise connections. Such cyclic configurations, like rock-paper-scissors preferences, highlight how transitivity enforces acyclic chaining. The following table summarizes key combinations of transitivity with other properties, focusing on resulting structures:
Properties Combined with TransitivityResulting StructureExample
Reflexivity\leq on real numbers (allows equivalence)
Reflexivity + Equality (== )
(implies irreflexivity)Strict Partial OrderStrict less-than (<<)

Transitivity in Broader Mathematical Structures

In , transitivity arises through the associative composition of s, which enables the construction of longer paths from successive s, analogous to chaining relations while preserving the categorical structure. This composition ensures that if there exists a f:ABf: A \to B and g:BCg: B \to C, then gf:ACg \circ f: A \to C is well-defined, reflecting a transitive-like property in the hom-sets of the category. In categories, where at most one exists between any pair of objects, this directly corresponds to the transitivity of the underlying relation. In the context of topological spaces, transitivity is prominent in group actions, where a topological group GG acts continuously and transitively on a XX if for any points x,yXx, y \in X, there exists gGg \in G such that gx=yg \cdot x = y, often implying the is homogeneous. Such actions are fundamental in studying symmetries and structures, with the stabilizer subgroups being closed in Hausdorff spaces to ensure continuity. For instance, the action is -transitive if every coincides with the entire , unifying the under the group's dynamics. Lattice theory extends transitivity via closure operations in implication lattices, where the transitive closure of a set of implications generates a deductive forming the lattice of closed sets. In formal concept analysis, implication bases define closure systems on lattices, and the transitive closure ensures all derivable implications are included, structuring the lattice as a complete algebraic framework for dependencies.

References

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