This problem is inspired by a data structure called “Sparse Table.”

Hereinafter, for integers \(l\) and \(r\) such that \(l \leq r\), let us call a set of integers between \(l\) and \(r\) (inclusive) by segment \([l, r]\). That is, \([l, r] \coloneqq \lbrace l, l+1, l+2, \ldots, r\rbrace\). Also, let us define the length of a segment \([l, r]\) by the size of the set, \(r-l+1\).

In this problem, you are asked to choose \(M\) segments beforehand so that you can represent any segment \([L, R]\) that is a subset of \([1, N]\) as a union of two of the chosen segments.

To come to the point, it is sufficient to choose all the following elements:

• Every segment of length \(1\) that is a subsets of \([1, N]\)
• Every segment of length \(2\) that is a subsets of \([1, N]\)
• Every segment of length \(4\) that is a subsets of \([1, N]\)
• \(\cdots\)
• Every segment of length $\(2^{\lfloor \log_2 N \rfloor}\)\( that is a subsets of \)[1, N]$.

For example, if \(N = 10\), we choose the following \(29\) segments:

• \(10\) segments of length \(1\): \([1, 1], [2, 2], \ldots, [10, 10]\).
• \(9\) segments of length \(2\): \([1, 2], [2, 3], \ldots, [9, 10]\).
• \(4\) segments of length \(4\): \([1, 4], [2, 5], \ldots, [7, 10]\).
• \(3\) segments of length \(8\): \([1, 8], [2, 9], \ldots, [3, 10]\).

In this choice, there are at most \(N\) segments of each length, and there are \(\lfloor \log_2 N \rfloor + 1\) kinds of distinct lengths, so \(M \leq N(\lfloor \log_2 N \rfloor + 1)\). Even in the maximum case \(N = 4000\), we have \(M \leq 4000 \times (\lfloor \log_2 4000 \rfloor + 1) = 48000\), which is below the upper bound \(50000\).

Also, given a segment \([L, R]\) as a query, we can represent it as a union of two of the chosen segments, segment \([L, L+2^K-1]\) and \([R-2^K+1, R]\), where \(K\) is the maximum integer such that \(2^K \leq R-L+1\).

Hence, by choosing the \(M\) segments as described above, you can solve this problem.

About Sparse Table

Let me briefly introduce about the original idea, sparse table.

A sparse table is a data structure that, given a fixed array \(A\) of length \(N\), enables us to find the minimum value \(\min_{i \in [L, R]} A[i]\) in a segment \([L, R]\) in an \(O(1)\) time.

We achieve it by precalculating the minimum value of \(A\) within each of the segments of \([1, N]\) whose length is \(1, 2, 4, \ldots, 2^{\lfloor \log_2 N \rfloor}\) (there are \(O(N \log N)\) such segments) as described in the editorial above.

Then, one can obtain the minimum value of \(A\) within a segment \([L, R]\) by decomposing \([L, R]\) into the union of \([L, L+2^K-1]\) and \([R-2^K+1, R]\), then finding the smaller of the minimum value within \([L, L+2^K-1]\) and within \([R-2^K+1, R]\).

Since the minimum value within the segment \([L, L+2^k-1]\) can be found as the smaller of the minimum values within the segment \([L, L+2^{k-1}-1]\) and the segment \([L+2^{k-1}, L+2^k-1]\), one can complete the precalculation by filling the table in ascending order of \(k\) in a total of \(O(N \log N)\) time.

This data structure not only supports minimum values, but also other operations like maximum value, bitwise logical sums or products, and greatest common divisor. There is a refined variant of the sparse table, which is called a disjoint sparse table. If you are interested, take a look a it.