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A set of stamps partitioned into bundles: No stamp is in two bundles, no bundle is empty, and every stamp is in a bundle.
The 52 partitions of a set with 5 elements. A colored region indicates a subset of X that forms a member of the enclosing partition. Uncolored dots indicate single-element subsets. The first shown partition contains five single-element subsets; the last partition contains one subset having five elements.
The traditional Japanese symbols for the 54 chapters of the Tale of Genji are based on the 52 ways of partitioning five elements (the two red symbols represent the same partition, and the green symbol is added for reaching 54).[1]

In mathematics, a partition of a set is a grouping of its elements into non-empty subsets, in such a way that every element is included in exactly one subset.

Every equivalence relation on a set defines a partition of this set, and every partition defines an equivalence relation. A set equipped with an equivalence relation or a partition is sometimes called a setoid, typically in type theory and proof theory.

Definition and notation

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A partition of a set X is a set of non-empty subsets of X such that every element x in X is in exactly one of these subsets[2] (i.e., the subsets are nonempty mutually disjoint sets).

Equivalently, a family of sets P is a partition of X if and only if all of the following conditions hold:[3]

  • The family P does not contain the empty set (that is ).
  • The union of the sets in P is equal to X (that is ). The sets in P are said to exhaust or cover X. See also collectively exhaustive events and cover (topology).
  • The intersection of any two distinct sets in P is empty (that is ). The elements of P are said to be pairwise disjoint or mutually exclusive. See also mutual exclusivity.

The sets in are called the blocks, parts, or cells, of the partition.[4] If then we represent the cell containing by . That is to say, is notation for the cell in which contains .

Every partition may be identified with an equivalence relation on , namely the relation such that for any we have if and only if (equivalently, if and only if ). The notation evokes the idea that the equivalence relation may be constructed from the partition. Conversely every equivalence relation may be identified with a partition. This is why it is sometimes said informally that "an equivalence relation is the same as a partition". If P is the partition identified with a given equivalence relation , then some authors write . This notation is suggestive of the idea that the partition is the set X divided into cells. The notation also evokes the idea that, from the equivalence relation one may construct the partition.

The rank of is , if is finite.

Examples

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  • The empty set has exactly one partition, namely . (Note: this is the partition, not a member of the partition.)
  • For any non-empty set X, P = { X } is a partition of X, called the trivial partition.
    • Particularly, every singleton set {x} has exactly one partition, namely { {x} }.
  • For any non-empty proper subset A of a set U, the set A together with its complement form a partition of U, namely, { A, UA }.
  • The set {1, 2, 3} has these five partitions (one partition per item):
    • { {1}, {2}, {3} }, sometimes written 1 | 2 | 3.
    • { {1, 2}, {3} }, or 1 2 | 3.
    • { {1, 3}, {2} }, or 1 3 | 2.
    • { {1}, {2, 3} }, or 1 | 2 3.
    • { {1, 2, 3} }, or 1 2 3.
  • The following are not partitions of {1, 2, 3}:
    • { {}, {1, 3}, {2} } is not a partition (of any set) because one of its elements is the empty set.
    • { {1, 2}, {2, 3} } is not a partition (of any set) because the element 2 is contained in more than one block.
    • { {1}, {2} } is not a partition of {1, 2, 3} because none of its blocks contains 3; however, it is a partition of {1, 2}.

Partitions and equivalence relations

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For any equivalence relation on a set X, the set of its equivalence classes is a partition of X. Conversely, from any partition P of X, we can define an equivalence relation on X by setting x ~ y precisely when x and y are in the same part in P. Thus the notions of equivalence relation and partition are essentially equivalent.[5]

The axiom of choice guarantees for any partition of a set X the existence of a subset of X containing exactly one element from each part of the partition. This implies that given an equivalence relation on a set one can select a canonical representative element from every equivalence class.

Refinement of partitions

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Partitions of a 4-element set ordered by refinement

A partition α of a set X is a refinement of a partition ρ of X—and we say that α is finer than ρ and that ρ is coarser than α—if every element of α is a subset of some element of ρ. Informally, this means that α is a further fragmentation of ρ. In that case, it is written that αρ.

This "finer-than" relation on the set of partitions of X is a partial order (so the notation "≤" is appropriate). Each set of elements has a least upper bound (their "join") and a greatest lower bound (their "meet"), so that it forms a lattice, and more specifically (for partitions of a finite set) it is a geometric and supersolvable lattice.[6][7] The partition lattice of a 4-element set has 15 elements and is depicted in the Hasse diagram on the left.

The meet and join of partitions α and ρ are defined as follows. The meet is the partition whose blocks are the intersections of a block of α and a block of ρ, except for the empty set. In other words, a block of is the intersection of a block of α and a block of ρ that are not disjoint from each other. To define the join , form a relation on the blocks A of α and the blocks B of ρ by A ~ B if A and B are not disjoint. Then is the partition in which each block C is the union of a family of blocks connected by this relation.

Based on the equivalence between geometric lattices and matroids, this lattice of partitions of a finite set corresponds to a matroid in which the base set of the matroid consists of the atoms of the lattice, namely, the partitions with singleton sets and one two-element set. These atomic partitions correspond one-for-one with the edges of a complete graph. The matroid closure of a set of atomic partitions is the finest common coarsening of them all; in graph-theoretic terms, it is the partition of the vertices of the complete graph into the connected components of the subgraph formed by the given set of edges. In this way, the lattice of partitions corresponds to the lattice of flats of the graphic matroid of the complete graph.

Another example illustrates refinement of partitions from the perspective of equivalence relations. If D is the set of cards in a standard 52-card deck, the same-color-as relation on D – which can be denoted ~C – has two equivalence classes: the sets {red cards} and {black cards}. The 2-part partition corresponding to ~C has a refinement that yields the same-suit-as relation ~S, which has the four equivalence classes {spades}, {diamonds}, {hearts}, and {clubs}.

Noncrossing partitions

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A partition of the set N = {1, 2, ..., n} with corresponding equivalence relation ~ is noncrossing if it has the following property: If four elements a, b, c and d of N having a < b < c < d satisfy a ~ c and b ~ d, then a ~ b ~ c ~ d. The name comes from the following equivalent definition: Imagine the elements 1, 2, ..., n of N drawn as the n vertices of a regular n-gon (in counterclockwise order). A partition can then be visualized by drawing each block as a polygon (whose vertices are the elements of the block). The partition is then noncrossing if and only if these polygons do not intersect.

The lattice of noncrossing partitions of a finite set forms a subset of the lattice of all partitions, but not a sublattice, since the join operations of the two lattices do not agree.

The noncrossing partition lattice has taken on importance because of its role in free probability theory.

Counting partitions

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The total number of partitions of an n-element set is the Bell number Bn. The first several Bell numbers are B0 = 1, B1 = 1, B2 = 2, B3 = 5, B4 = 15, B5 = 52, and B6 = 203 (sequence A000110 in the OEIS). Bell numbers satisfy the recursion

and have the exponential generating function

Construction of the Bell triangle

The Bell numbers may also be computed using the Bell triangle in which the first value in each row is copied from the end of the previous row, and subsequent values are computed by adding two numbers, the number to the left and the number to the above left of the position. The Bell numbers are repeated along both sides of this triangle. The numbers within the triangle count partitions in which a given element is the largest singleton.

The number of partitions of an n-element set into exactly k (non-empty) parts is the Stirling number of the second kind S(n, k).

The number of noncrossing partitions of an n-element set is the Catalan number

See also

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Notes

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References

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
In mathematics, a partition of a set $ S $ is a collection of non-empty subsets of $ S $ that are pairwise disjoint and whose union equals $ S $.[1] This means every element of $ S $ belongs to exactly one subset in the collection, ensuring a complete and non-overlapping division of the set.[2] Partitions are intimately connected to equivalence relations: every equivalence relation on a set induces a unique partition where the subsets are the equivalence classes, and conversely, every partition defines an equivalence relation by declaring elements equivalent if they lie in the same subset.[3] This correspondence underpins much of their utility in abstract algebra and set theory.[4] The enumeration of set partitions is a central topic in combinatorics. The total number of partitions of a finite set with $ n $ elements is given by the $ n $-th Bell number $ B_n $, which counts all possible ways to divide the set into non-empty subsets regardless of the number of parts.[5] More specifically, the number of partitions into exactly $ k $ non-empty subsets is the Stirling number of the second kind $ S(n, k) $, and the Bell numbers satisfy $ B_n = \sum_{k=0}^n S(n, k) $.[6] These numbers arise in diverse counting problems, such as distributing distinct objects into indistinguishable bins.[7] Set partitions find applications across mathematics and related fields, including probabilistic models and in combinatorial optimization.[8] They also play a role in the study of symmetric groups and representation theory, where partitions label irreducible representations.[9]

Basic Concepts

Definition

A partition of a set $ S $ is a collection of non-empty subsets of $ S $ that are pairwise disjoint and whose union equals $ S $. This means the subsets divide $ S $ into distinct, non-overlapping parts that together cover every element exactly once. Formally, if $ P = { A_i \mid i \in I } $ is a partition of $ S $, where $ I $ is an indexing set, then $ A_i \cap A_j = \emptyset $ for all distinct $ i, j \in I $, $ \bigcup_{i \in I} A_i = S $, and each $ A_i \neq \emptyset $. The non-emptiness condition ensures that no subset is trivial or redundant in covering $ S $, while the disjointness prevents any element from belonging to multiple subsets, and the union requirement guarantees exhaustiveness, so no element of $ S $ is omitted. The requirement for non-empty subsets arises because including the empty set would not affect the union but would violate the principle of a proper division into meaningful parts; similarly, exhaustiveness ensures the partition fully accounts for $ S $ without gaps.[10] This structure underpins the correspondence between partitions and equivalence relations, where each part corresponds to an equivalence class.

Notation and Terminology

In standard mathematical notation, the collection of all partitions of a finite set SS is often denoted by Π(S)\Pi(S) or P(S)P(S).[11] For a partition PP of SS, the cardinality P|P| represents the number of blocks in PP, while the type of PP is defined as the multiset of the sizes of its blocks, providing a way to classify partitions up to the specific elements involved.[11] The fundamental components of a partition are its blocks, which are the non-empty, pairwise disjoint subsets whose union is exactly SS. A block containing a single element is termed a singleton. Partitions are partially ordered by the refinement relation: a partition PP is finer than another partition QQ (or equivalently, QQ is coarser than PP) if every block of PP is a subset of some block of QQ; this ordering forms the partition lattice.[11] Given a partition PP of SS and a subset ASA \subseteq S, the restriction of PP to AA, denoted PAP \upharpoonright A or PAP \restriction A, is the partition of AA induced by taking the non-empty intersections of the blocks of PP with AA.[11] It is important to distinguish set partitions from integer partitions in combinatorics: while integer partitions represent ways of writing a positive integer nn as a sum of positive integers (disregarding order), set partitions divide a set into unlabeled, unordered blocks without regard to the elements' labels or the blocks' arrangement, focusing instead on the grouping structure.[12]

Examples

Simple Examples

To illustrate the concept of a set partition, consider the smallest non-trivial case: a set with two elements, such as $ S = {a, b} $. There are exactly two possible partitions of this set. The first is the trivial partition consisting of a single block containing all elements: $ {{a, b}} $. The second is the discrete partition into singletons: $ {{a}, {b}} $.[12] For a three-element set, such as $ S = {1, 2, 3} $, there are five distinct partitions, reflecting the Bell number $ B_3 = 5 $, which counts the total number of partitions of a set with three elements. These are:
  • The single-block partition: $ {{1, 2, 3}} $
  • The partitions into one doubleton and one singleton: $ {{1, 2}, {3}} $, $ {{1, 3}, {2}} $, and $ {{2, 3}, {1}} $
  • The discrete partition into three singletons: $ {{1}, {2}, {3}} $
[12] A common way to visualize these partitions for $ {1, 2, 3} $ is through set notation or simple diagrams resembling disjoint regions. For instance, the partition $ {{1, 2}, {3}} $ can be represented as two disjoint blocks:
Block 1: {1, 2}
Block 2: {3}
Similarly, the full discrete partition appears as three separate singleton blocks:
Block 1: {1}
Block 2: {2}
Block 3: {3}
Such representations emphasize the disjointness and coverage of the original set without overlap.[12] It is important to note that partitions are unordered collections of subsets; thus, the order of blocks or elements within blocks does not affect equality. For example, $ {{1, 2}, {3}} $ is identical to $ {{3}, {1, 2}} $, and $ {1, 2} $ is the same block as $ {2, 1} $. This unordered nature distinguishes partitions from ordered tuples or sequences.[13]

Partitions of Larger Sets

To illustrate the diversity of partitions for larger sets, consider the set $ S = {a, b, c, d} $. One partition consists of all singletons: $ {{a}, {b}, {c}, {d}} $, where each element forms its own block. Another type features one doubleton and two singletons, such as $ {{a, b}, {c}, {d}} $, emphasizing how elements can be paired while leaving others isolated. A further variation includes two doubletons, like $ {{a, b}, {c, d}} $, pairing all elements into equal-sized blocks.[14] Partitions of such sets exhibit patterns based on block sizes, distinguishing balanced structures—where blocks are as equal in size as possible, such as the two doubletons example above—from unbalanced ones, like a tripleton with a singleton $ {{a, b, c}, {d}} $, which creates disparity in block cardinalities. These patterns highlight the flexibility in grouping elements while maintaining disjointness and coverage.[15] For intuition, partitions resemble dividing a class of four students into study groups by skill levels: all individuals working alone (singletons), two pairing up while others remain solo (one doubleton and singletons), or two pairs forming balanced teams (two doubletons), ensuring every student is assigned without overlap. The following table enumerates all partitions of $ {a, b, c, d} $, grouped by block size compositions (in nonincreasing order), using set notation for clarity:
Block SizesPartitions
4$ {{a, b, c, d}} $
3+1$ {{a, b, c}, {d}} <br><br> {{a, b, d}, {c}} <br><br> {{a, c, d}, {b}} <br><br> {{b, c, d}, {a}} $
2+2$ {{a, b}, {c, d}} <br><br> {{a, c}, {b, d}} <br><br> {{a, d}, {b, c}} $
2+1+1$ {{a, b}, {c}, {d}} <br><br> {{a, c}, {b}, {d}} <br><br> {{a, d}, {b}, {c}} <br><br> {{b, c}, {a}, {d}} <br><br> {{b, d}, {a}, {c}} <br><br> {{c, d}, {a}, {b}} $
1+1+1+1$ {{a}, {b}, {c}, {d}} $
[15][14]

Equivalence Relations and Partitions

The Correspondence

A fundamental connection exists between equivalence relations and partitions of a set. Given a nonempty set SS and an equivalence relation \sim on SS, the equivalence classes [x]={ySyx}[x] = \{ y \in S \mid y \sim x \} for each xSx \in S form the blocks of a partition of SS. These classes are nonempty by reflexivity, disjoint by the properties of equivalence (if two classes overlapped, transitivity would merge them), and their union covers SS by totality of the relation.[16] Conversely, for any partition PP of SS, consisting of nonempty disjoint subsets whose union is SS, one can define an equivalence relation P\sim_P on SS by declaring xPyx \sim_P y if and only if xx and yy belong to the same block in PP. This relation is reflexive (each element is in its own block), symmetric (blocks are undirected), and transitive (elements in the same block stay within it).[16] These constructions establish a bijection between the set of all equivalence relations on SS and the set of all partitions of SS. The map sending an equivalence relation to its partition of equivalence classes is injective, as distinct relations yield distinct class collections (different groupings imply different relations), and surjective, as every partition arises from its induced relation. Similarly, the reverse map is bijective by construction, confirming the one-to-one correspondence. This duality underscores that equivalence relations and partitions are theoretically interchangeable representations of the same clustering structure on SS.[16] The recognition of this bijection as a core principle in set theory developed in the early 20th century, building on Georg Cantor's foundational work on set equivalence in the 1890s, with explicit terminology and formalization appearing in modern texts from the 1930s onward, such as those standardizing "equivalence relation" around that period.[17]

Constructing Partitions from Relations

Given an equivalence relation \sim on a set SS, the partition induced by \sim consists of the equivalence classes [x]={ySyx}[x] = \{ y \in S \mid y \sim x \} for each xSx \in S. To construct this partition explicitly, begin with the set SS and select an arbitrary element xSx \in S; form the equivalence class [x][x] by identifying all elements in SS that are related to xx via \sim (accounting for reflexivity, symmetry, and transitivity to ensure completeness). Remove [x][x] and all its elements from consideration, then repeat the process with a remaining element until SS is exhausted; the resulting collection of disjoint equivalence classes forms the partition. For instance, consider S={1,2,3}S = \{1, 2, 3\} with the relation specified by 121 \sim 2 and 232 \sim 3; applying the transitive closure yields 131 \sim 3, so the single equivalence class [1]=[2]=[3]={1,2,3}[1] = [2] = [3] = \{1, 2, 3\}, producing the partition {{1,2,3}}\{\{1, 2, 3\}\}. In the reverse direction, starting from the partition P={{1,2},{3}}P = \{\{1, 2\}, \{3\}\} on SS, define the relation P\sim_P by xPyx \sim_P y if and only if xx and yy belong to the same block of PP. This relation is reflexive (each xx is in its own block), symmetric (blocks are unordered), and transitive (elements in the same block remain so under chaining), confirming P\sim_P is an equivalence relation whose classes recover PP.[18] This construction establishes a bijection between equivalence relations on SS and partitions of SS, as detailed in the correspondence between the two structures. Furthermore, the lattice of all partitions of SS (ordered by refinement, where finer partitions are below coarser ones) is isomorphic to the lattice of all equivalence relations on SS (or congruences), with the meet and join operations corresponding via the blocks and transitive closures, respectively.[19]

Operations on Partitions

Refinement

In the theory of set partitions, a partition $ Q $ of a set $ S $ is a refinement of another partition $ P $ of $ S $, written $ Q \preceq P $, if every block of $ Q $ is contained as a subset in some block of $ P $. This means that $ Q $ can be obtained from $ P $ by further subdividing the blocks of $ P $, resulting in a finer grouping of the elements of $ S $. The refinement relation defines a partial order on the set of all partitions of $ S $, turning it into a partially ordered set (poset), often called the partition lattice $ \Pi_{|S|} $.[11] The partial order induced by refinement is reflexive, as every partition refines itself, since each of its blocks is contained in itself. It is also transitive: if $ Q \preceq P $ and $ P \preceq R $, then every block of $ Q $ is contained in a block of $ P $, which in turn is contained in a block of $ R $, so every block of $ Q $ is contained in a block of $ R $. Additionally, the order is antisymmetric, ensuring that if $ Q \preceq P $ and $ P \preceq Q $, then $ Q = P $. These properties make the refinement poset a lattice structure with well-defined meets and joins corresponding to common coarsenings and refinements, respectively.[11] In the refinement poset, the minimal element is the discrete partition, which consists of $ |S| $ singleton blocks $ {{x} \mid x \in S} $, as no finer partition exists. The maximal element is the indiscrete partition $ {{S}} $, the coarsest possible grouping with a single block containing all elements. For a concrete illustration, consider $ S = {1,2,3,4} $, with $ P = {{1,2}, {3,4}} $ and $ Q = {{1}, {2}, {3,4}} $. Here, $ Q \preceq P $ holds because $ {1} \subseteq {1,2} $, $ {2} \subseteq {1,2} $, and $ {3,4} = {3,4} $, but the reverse does not, since $ {1,2} $ is not contained in any single block of $ Q $. This example demonstrates how refinement captures the idea of splitting blocks to achieve greater detail in partitioning.[11]

Coarsening

In the theory of set partitions, a partition PP of a set SS is a coarsening of another partition QQ of SS (denoted PQP \geq Q) if every block of PP is a union of one or more blocks of QQ.[20] This operation merges blocks of QQ to form larger blocks in PP, reducing the number of blocks while preserving the underlying set SS.[20] Coarsening is the dual operation to refinement in the partially ordered set (poset) of all partitions of SS, ordered by refinement where QPQ \leq P if QQ refines PP (every block of QQ is contained in some block of PP). This poset is a lattice, with the meet of two partitions being their coarsest common refinement (the partition formed by taking all nonempty intersections of blocks from the two partitions) and the join being their finest common coarsening (the partition generated by the transitive closure of the union of the corresponding equivalence relations). For example, the partition {{1,2,3,4}}\{\{1,2,3,4\}\} is a coarsening of {{1,2},{3,4}}\{\{1,2\}, \{3,4\}\} because the single block {1,2,3,4}\{1,2,3,4\} is the union of the two blocks in the finer partition.[20] To obtain a coarsening of a partition QQ, select compatible groups of blocks from QQ (subsets of blocks whose elements can be merged without violating the partition structure) and replace each group with their union, ensuring the resulting collection remains a partition of SS.[20]

Special Partitions

Noncrossing Partitions

A noncrossing partition of a linearly ordered set $ S = {1 < 2 < \dots < n} $ is a partition where no two blocks cross, meaning there do not exist elements $ a < b < c < d $ such that either $ a $ and $ c $ are in one block and $ b $ and $ d $ are in another block, or $ a $ and $ d $ are in one block and $ b $ and $ c $ are in another block.[21] This condition ensures that the blocks respect the linear order without interleaving.[22] Geometrically, noncrossing partitions can be visualized by placing the elements $ 1 $ to $ n $ consecutively around a circle and connecting elements within the same block by chords; the partition is noncrossing if these chords do not intersect except possibly at the vertices.[21] This representation highlights their combinatorial significance, as the non-intersecting chords correspond to planar embeddings, linking noncrossing partitions to other Catalan structures like polygon triangulations.[22] For $ n=4 $, the partition $ {{1,2}, {3,4}} $ is noncrossing, as the blocks are contiguous and non-interleaving in the order.[21] In contrast, $ {{1,3}, {2,4}} $ is crossing, since $ 1 < 2 < 3 < 4 $ with $ 1 \sim 3 $ and $ 2 \sim 4 $, violating the noncrossing condition.[21] The number of noncrossing partitions of an $ n $-element set is given by the $ n $-th Catalan number $ C_n = \frac{1}{n+1} \binom{2n}{n} $.[22] This enumeration satisfies the recurrence relation $ C_n = \sum_{i=0}^{n-1} C_i C_{n-1-i} $, with $ C_0 = 1 $.[22]

Interval Partitions

In the context of set partitions, an interval partition of the linearly ordered set $ S = {1 < 2 < \dots < n} $ is a partition whose blocks are nonempty intervals of consecutive elements, meaning each block takes the form $ {k, k+1, \dots, m} $ for integers $ 1 \leq k \leq m \leq n $.[23] This restricts the blocks to contiguous segments, preserving the natural order of the elements.[24] For example, with $ n=5 $, the collection $ {{1,2,3}, {4}, {5}} $ forms an interval partition, as each block consists of consecutive integers.[24] Interval partitions correspond bijectively to the integer compositions of $ n $, where the sizes of the blocks match the parts of the composition; for instance, the above example corresponds to the composition $ (3,1,1) $.[23] Consequently, the total number of interval partitions of $ [n] $ is $ 2^{n-1} $, obtained by choosing whether to place a separator in each of the $ n-1 $ gaps between the elements.[24] All interval partitions are noncrossing, since their disjoint consecutive blocks cannot interleave in a way that violates the noncrossing condition (no four elements $ i < j < k < l $ with $ i \sim l $ and $ j \sim k $ in different blocks).[25] However, the reverse does not hold, as noncrossing partitions may include blocks that are non-consecutive yet non-interleaving.[24] The collection of all interval partitions forms a sublattice of the full partition lattice under the refinement order, where one partition refines another if every block of the former is contained in some block of the latter.[23] Interval partitions find applications in areas requiring segmentation of ordered data, such as time series analysis, where partitioning a sequence into consecutive segments identifies regimes or changes in behavior.[26] For instance, optimal algorithms for dividing data points on an interval into subintervals often rely on dynamic programming tailored to interval structures, enabling efficient computation for tasks like signal processing or forecasting.[26]

Enumeration

Stirling Numbers of the Second Kind

The Stirling numbers of the second kind, denoted $ S(n,k) $, count the number of ways to partition a set of $ n $ elements into exactly $ k $ nonempty unlabeled subsets.[27][28] These numbers satisfy the recurrence relation
S(n,k)=kS(n1,k)+S(n1,k1) S(n,k) = k \cdot S(n-1,k) + S(n-1,k-1)
for $ 1 \leq k \leq n $, with boundary conditions $ S(n,0) = 0 $ for $ n > 0 $, $ S(0,k) = \delta_{0k} $ (where $ \delta $ is the Kronecker delta), $ S(n,1) = 1 $, and $ S(n,n) = 1 $.[27][28] The values of $ S(n,k) $ for small $ n $ and $ k $ are given in the following table:
$ n \setminus k $12345
11
211
3131
41761
511525101
For example, $ S(4,2) = 7 $.[27][28] A generating function for fixed $ n $ is
k=0nS(n,k)xkk!=(ex1)nn!. \sum_{k=0}^{n} S(n,k) \frac{x^k}{k!} = \frac{(e^x - 1)^n}{n!}.
[27] For fixed $ k $, as $ n \to \infty $, the asymptotic approximation is $ S(n,k) \sim \frac{k^n}{k!} $.[29]

Bell Numbers

The Bell number $ B_n $ denotes the total number of partitions of a set with $ n $ elements and is defined as $ B_n = \sum_{k=0}^n S(n,k) $, where $ S(n,k) $ counts the partitions into exactly $ k $ nonempty subsets (Stirling numbers of the second kind).[30] This summation aggregates all possible block sizes, providing the overall enumeration of set partitions.[31] The sequence of Bell numbers begins 1, 1, 2, 5, 15, 52, ... and grows rapidly. The values up to $ n=10 $ are presented in the following table:
$ n $$ B_n $
01
11
22
35
415
552
6203
7877
84140
921147
10115975
These values are listed in OEIS sequence A000110.[31] Bell numbers satisfy the recurrence relation $ B_n = \sum_{k=0}^{n-1} \binom{n-1}{k} B_k $, with $ B_0 = 1 $, which arises from considering the block containing a distinguished element and partitioning the remainder.[30] Another explicit formula is Dobiński's formula: $ B_n = \frac{1}{e} \sum_{k=0}^\infty \frac{k^n}{k!} $, derived from properties of the exponential generating function for set partitions.[31] The asymptotic growth of Bell numbers is captured by $ B_n \sim \frac{n!}{(2\pi r^2 e^r)^{1/2} r^n} e^{e^r - 1} $, where $ r $ is the unique positive solution to $ r e^r = n $ (equivalent to $ r = W(n) $, with $ W $ the Lambert W-function).[31] This formula, established by Moser and Wyman, indicates super-exponential growth dominated by the term $ e^{e^r - 1} $, reflecting the explosive increase in partition counts as $ n $ grows, since $ r \sim \ln n - \ln \ln n + o(1) $.[32] For computation, the recurrence enables efficient evaluation using dynamic programming in $ O(n^2) $ time, supporting calculations for $ n $ up to several hundred on modern hardware./01%3A_Fundamentals/1.05%3A_Bell_Numbers)

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