In combinatorics, the rencontres numbers are a triangular array of integers that enumerate permutations of the set { 1, ..., n } with specified numbers of fixed points: in other words, partial derangements. (Rencontre is French for encounter. By some accounts, the problem is named after a solitaire game.) For n ≥ 0 and 0 ≤ k ≤ n, the rencontres number Dn, k is the number of permutations of { 1, ..., n } that have exactly k fixed points.
For example, if seven presents are given to seven different people, but only two are destined to get the right present, there are D7, 2 = 924 ways this could happen. Another often cited example is that of a dance school with 7 opposite-sex couples, where, after tea-break the participants are told to randomly find an opposite-sex partner to continue, then once more there are D7, 2 = 924 possibilities that exactly 2 previous couples meet again by chance.
Numerical values
Here is the beginning of this array (sequence A008290 in the OEIS):
k
n
0
1
2
3
4
5
6
7
8
0
1
1
0
1
2
1
0
1
3
2
3
0
1
4
9
8
6
0
1
5
44
45
20
10
0
1
6
265
264
135
40
15
0
1
7
1854
1855
924
315
70
21
0
1
8
14833
14832
7420
2464
630
112
28
0
1
ordered by number of moved elements
The usual way (table above) to show the rencontres numbers is in columns corresponding to the number of fixed points .
But one can also order them in columns corresponding to the number of moved elements (sequence A098825 in the OEIS).
Each entry in the table below on the left can be factored into two terms given in the table below on the right: the product of a binomial coefficient (given first in red) and a subfactorial (given second in blue).
In this order each column corresponds to one subfactorial:
i
n
0
1
2
3
4
5
6
7
8
0
1
1
1
0
2
1
0
1
3
1
0
3
2
4
1
0
6
8
9
5
1
0
10
20
45
44
6
1
0
15
40
135
264
265
7
1
0
21
70
315
924
1855
1854
8
1
0
28
112
630
2464
7420
14832
14833
i
n
0
1
2
3
4
5
6
7
8
0
1⋅1
1
1⋅1
1⋅0
2
1⋅1
2⋅0
1⋅1
3
1⋅1
3⋅0
3⋅1
1⋅2
4
1⋅1
4⋅0
6⋅1
4⋅2
1⋅9
5
1⋅1
5⋅0
10⋅1
10⋅2
5⋅9
1⋅44
6
1⋅1
6⋅0
15⋅1
20⋅2
15⋅9
6⋅44
1⋅265
7
1⋅1
7⋅0
21⋅1
35⋅2
35⋅9
21⋅44
7⋅265
1⋅1854
8
1⋅1
8⋅0
28⋅1
56⋅2
70⋅9
56⋅44
28⋅265
8⋅1854
1⋅14833
Formulas
The numbers in the k = 0 column enumerate derangements. Thus
for non-negative n. It turns out that
where the ratio is rounded up for even n and rounded down for odd n. For n ≥ 1, this gives the nearest integer.
More generally, for any , we have
The proof is easy after one knows how to enumerate derangements: choose the k fixed points out of n; then choose the derangement of the other n − k points.
The numbers Dn,0/(n!) are generated by the power seriese−z/(1 − z); accordingly,
an explicit formula for Dn, m can be derived as follows:
This immediately implies that
for n large, m fixed.
Probability distribution
The sum of the entries in each row for the table in "Numerical Values" is the total number of permutations of { 1, ..., n }, and is therefore n!. If one divides all the entries in the nth row by n!, one gets the probability distribution of the number of fixed points of a uniformly distributed random permutation of { 1, ..., n }. The probability that the number of fixed points is k is
For n ≥ 1, the expected number of fixed points is 1 (a fact that follows from linearity of expectation).
More generally, for i ≤ n, the ith moment of this probability distribution is the ith moment of the Poisson distribution with expected value 1.[1] For i > n, the ith moment is smaller than that of that Poisson distribution. Specifically, for i ≤ n, the ith moment is the ith Bell number, i.e. the number of partitions of a set of size i.
Limiting probability distribution
As the size of the permuted set grows, we get
This is just the probability that a Poisson-distributed random variable with expected value 1 is equal to k. In other words, as n grows, the probability distribution of the number of fixed points of a random permutation of a set of size n approaches the Poisson distribution with expected value 1.
See also
Oberwolfach problem, a different mathematical problem involving the arrangement of diners at tables