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Real life motivation. In my younger son's class, there are $18$ students. His teacher provided $18$ time slots for the parents of each child to have a 30-minute conversation of their kid's progress in school and asked the parents to provide $4$ possible time slots that would be convenient for them. I wondered how probable it is that given all the choices, the teacher can select a convenient time slot for the parents of every child so that everyone can have the "progress conversation."

Formal version. We say that an $n$-tuple $(S_1,\ldots,S_n)$ of $k$-element subsets of $\{1,\ldots,n\}$ has the satisfiability property if there is a permutation $\sigma \in \mathfrak{S}_n$ with $\sigma(i)\in S_i$ for all $i=1,\ldots,n$.

Given an integer $n>1$, what is the smallest $k$ (in terms of $n$) such that at least half of the $n$-tuples $(S_1,\ldots,S_n)$ of $k$-element subsets of $\{1,\ldots,n\}$ have the satisfiability property? If no exact formula can be given, is there an approximation for when $n\to\infty$?

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    $\begingroup$ To check if a collection has the "satisfiability property" there is of course the famous "Hall's marriage theorem": en.wikipedia.org/wiki/Hall%27s_marriage_theorem. Presumably the condition in Hall's theorem will also be useful for answering your probabilistic question. $\endgroup$ Commented Jan 8, 2023 at 19:56
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    $\begingroup$ Another statement: Given an $n\times n$ matrix of zeroes and ones with $k$ ones in each row, what is the probability that some rearrangement of rows produces ones all along the main diagonal? Or what is the least value of $k$ making that probability at least $\frac12$? $\endgroup$
    – user44143
    Commented Jan 8, 2023 at 23:30
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    $\begingroup$ Not a full answer, but using Hall's theorem we can get a lower bound of $\log n$: by the coupon collector's problem we see that if $k < \log n$ with high probability at least one element of $\{1, \dots, n\}$ does not appear in any of the tuples, so we get a contradiction to Hall's theorem when taking the set of all parents. $\endgroup$
    – Random
    Commented Jan 9, 2023 at 7:19
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    $\begingroup$ My guess is that the threshold is about $\log n$, that is for $k > (1 + \varepsilon) \log n$ there should be a bijection. Here is a heuristic: in Hall's theorem the only obstruction should come from very large sets of parents, and in very large sets of parents the obstruction comes from a certain set of times that only few parents accept (then, removing the parents that accept those times we get the obstruction in Hall's theorem). However looking at the Wikipedia page on the coupon collector's problem, it seems that for $k > (1 + \varepsilon) \log n$ every time is accepted by many parents. $\endgroup$
    – Random
    Commented Jan 9, 2023 at 7:43
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    $\begingroup$ Let $p(n,k)$ be the sought probability. For $n\geq 1$ obviously $p(n,0)=0$, $p(n,1)=n!/n^n$ and $p(n,n)=1$. Moreover $p(n,n-1)=1-n^{-(n-1)}$. For $n\leq 5$ the computer says that $p(n,2)=\text{A174586}(n)/\binom{n}{2}^n$. OEIS reference is A174586 $\endgroup$ Commented Jan 9, 2023 at 16:24

1 Answer 1

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To restate the question in probabilistic language, each of the $n$ chldren's parents independently and with uniform probabilities chooses a $k$-element subset of $[n]$; say $X_i$ is the choice of child $i$'s parents. You want the probability that there is a successful assignment of parents to slots, corresponding to a permutation $\pi$ of $[n]$, such that $\pi(i) \in X_i$ for all $i$.

I don't know how to answer this question, but here's a related one that gives a bound. Consider a given permutation $\pi$. The probability that $\pi(i) \in X_i$ for all $i$ is $(k/n)^n$. Since there are $n!$ permutations, the expected number of successful permutations is $n! (k/n)^n$. As $n \to \infty$, by Stirling's approximation $n! \sim \sqrt{2\pi} n^{n+1/2} e^{-n}$. Of course the expected number of successful permutations is an upper bound on the probability of existence of at least one of them. Thus as long as $k \ge 3 > e$, the expected number of successful permutations should be greater than $1$ if $n$ is large enough, but if $k \le 2$ it will be less than $1$ (and go to $0$ as $n \to \infty$). For the example given with $k=4$ and $n=18$, $18! (4/18)^n \approx 11182$, while with $k=3$ and $n=18$, $18! (3/18)^n \approx 63$ .

I tried simulations to find the actual probabilities for $k = 3$ and $k=4$ with $n=18$. For $k=4$ I found success in $817$ cases out of $1000$, while for $k=3$ I found success in only $388$ out of $1000$.

Of course, in real life the probabilities are not likely to be uniform: there will be some very popular slots and others that nobody wants.

EDIT: I am not suggesting that with $k = O(1)$ we have a solution with high probability. The probability that a given day is not chosen by anyone (which obviously implies there is no successful permutation) is $(1 - k/n)^n \to e^{-k}$ as $n \to \infty$, and thus the expected number of days not chosen is $n e^{-k}$. If we want high probability of a successful permutation it seems reasonable to require this to go to $0$ as $n \to \infty$, and thus $k - \log(n) \to \infty$.

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  • $\begingroup$ Thanks Robert for reformulating my question in a better way! I agree that in real life, the "convenient" slots to be selected will not be uniform - but I tried to simplify things a little. Even in the original setting (18 students, 4 "convenient" slots for every student), I had no intuition whether the probability of succeeding in making things convenient for everybody was much lower than $50\%$, much higher, or about equal. So, thanks for your simulations! $\endgroup$ Commented Jan 9, 2023 at 10:10
  • $\begingroup$ I decided not to accept your answer yet - but of course I upvoted. I will accept your answer after a while, because the problem you mention and solve is related. I hope this is ok with you, Robert? $\endgroup$ Commented Jan 9, 2023 at 10:13
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    $\begingroup$ Are you suggesting that with $k=O(1)$ we will have a solution with high probability? That seems very implausible: see the comments of Random under the question... $\endgroup$ Commented Jan 9, 2023 at 14:35

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