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Supreme Successive Shuffle (Posted on 2009-12-15) |
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A deck of M cards is numbered 1 to M and shuffled, and dealt from top to bottom.
Denoting the probability of dealing at least one pair of successive cards in their proper order (that is, a 1 followed by a 2 or, a 2 followed by a 3, and so on) at any position in the deck by s(M), determine s(M) as M → ∞ (The pairs may overlap. For example, for M=5, we have two successive pairs corresponding to 73452.)
As a bonus, what is the expected number of such successive pairs in an M card deck as a function of M?
Some thoughts (Spoiler)
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| Comment 6 of 9 |
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Some thoughts. All m! permutations of m cards can be produced by inserting the card marked ‘m’ into each of the m possible places in each of the (m – 1)! permutations of m – 1 cards. If a(m – 1, k) is the number of permutations of m – 1 cards that contain k successive pairs (s-pairs), then the insertion of card ‘m’ will have one of the following effects. (A) An Insertion just after card ‘m – 1’ will increase the number of s-pairs by 1. (B) An insertion that splits an s-pair will decrease the number of s-pairs by 1. (C) An Insertion in any other place will not change the number of s-pairs. A, B and C can happen in 1, k and m – 1 – k ways respectively, and the resulting permutation will contain r s-pairs only if A, B and C are applied to permutations initially containing (k =) r – 1, r and r + 1 s-pairs respectively. This gives:
a(m, r) = a(m – 1, r – 1) + (r + 1) a(m – 1, r + 1) + (m – 1 – r) a(m – 1, r) (1)
Using a(1, 0) = 1 and a(2, 0) = 1 allows evaluation for 0 <= r <= m – 1.
a(m, r) r = 0 1 2 3 4 m = 1 1 2 1 1 3 3 2 1 4 11 9 3 1 5 53 44 18 4 1 etc..
Using r = 0 in (1) gives: a(m, 0) = a(m – 1, 1) + (m – 1) a(m – 1, 0) and the using the fact that a(m - 1, 1) = (m – 2) a(m – 2, 0) gives: a(m, 0) = (m – 2) a(m – 2, 0) + (m – 1) a(m – 1, 0)
Abbreviating a(m, 0) to A(m) we can then write: A(m) = (m – 1) A(m – 1) + (m – 2) A(m – 2) with A(1) = A(2) = 1 (2) where A(m) is the number of permutations of m cards that contain no s-pairs. [The number of perms with at least 1 s-pair will be m! – A(m)].
(2) allows easier evaluation of A(m) values, which are shown below together with A(m)/m! , the probability of no s-pairs.
m A(m) P(no s-pairs) = 1 1 1/1 1 2 1 1/2 0.5 3 3 3/6 0.5 4 11 11/24 0.4583333333.. 5 53 53/120 0.4416666667.. 6 309 309/720 0.4291666667.. 10 1468457 long 0.4046673832.. 100 big long 0.3715582356.. 1000 big 0.3682473206.. 10000 big 0.3679162291..
It appears that the probability of having no s-pairs tends to a limit which could well be 1/e (whose value is 0.36787944117..). The probability of at least one s-pair would then be 1 – 1/e, as Charlie conjectured.
However, I’ve not yet proved that this is the limit, though (2) should be sufficient information to complete a proof. I’ll keep trying.
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Posted by Harry
on 2009-12-18 00:18:57 |
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