Coin-weighting problem Let n coins of weights 0 and 1 be given. We are also given a scale with whic

Callum Dudley

Callum Dudley

Answered question

2022-07-01

Coin-weighting problem
Let n coins of weights 0 and 1 be given. We are also given a scale with which we may weigh any subset of the coins. The information from previous weighting may be used. The object is to determine the weights of the coins with the minimal number of weightings. Formally, a collection S 1 , , S m subsets of { 1 , , n } is called determing if any T { 1 , , n } can be uniquely determined by the cardinalities | S i T | for 1 i m .. Let D(n) be the minimum m for which such a determing collection exists. Show that D ( n ) n log 2 ( n + 1 ) .
Let S 1 , , S m be an arbitrary determining collection. Also, assume that T be an arbitrary subset of { 1 , , n }. Then there are 2 n possibilities to choose T from { 1 , , n }. On the other hand, for each 1 i m, there are only n + 1 possible | S i T | because 0 | S i T | | S i | n. But now I don't know how to apply the pigeonhole principle. This principle says that: if a set A consisting of at least r s + 1 objects is partitioned into r classes, then some class receives at least s + 1 objects. Equivalently, if A = i = 1 r B i (disjoint union) and | B i | s for every 1 i r, then | A | r s. I can't use this principle in my answer. How can I introduce A and B i s here? I was wondering if someone could help me about it.

Answer & Explanation

treccinair

treccinair

Beginner2022-07-02Added 18 answers

Step 1
We see that a collection of m subsets S 1 , S 2 , , S m is determining if there exists a function f such that f ( | S 1 T | , | S 2 T | , , | S m T | ) = T for every T { 1 , 2 , , n }.
Step 2
The number of 'inputs' of f above is ( n + 1 ) m , because | S i T | has at most n + 1 possible values (ranging from 0 to n). On the other hand, notice that there are 2 n possible subsets of { 1 , 2 , , n }. Hence, f must have at least 2 n possible 'inputs'. Therefore, ( n + 1 ) m 2 n , which is equivalent to m n log 2 ( n + 1 ) .

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