You are given an array of integers citations, where each element citations[i] represents the number of citations received for the $i^{th}$ publication of a researcher.

Your task is to find the researcher’s h-index and return the value of $h$.

Note: The h-index is defined as the highest number $h$ such that the given researcher has published at least $h$ papers, each of which has been cited at least $h$ times.

Constraints:

• $n ==$ citations.length

• $1 \leq n \leq 1000$

• $0 \leq$ citations[i] $\leq 1000$

The core idea of this solution is to calculate the h-index of a researcher by using a counting sort-based strategy rather than sorting the citation array directly. Since the h-index is defined as the maximum value $h$ such that the researcher has at least $h$ papers with at least $h$ citations, we can reframe the problem into counting how many papers have a certain number of citations. The observation is that citations above $n$ (the total number of papers) don’t increase the h-index beyond $n$. So, all citation counts are capped at $n$, allowing us to operate within a fixed-size frequency array.

The algorithm builds a bucket array to count how many papers have exactly $0, 1, ..., n$ citations, where any citation value above $n$ is counted in the last bucket. Then, starting from the highest possible h-index candidate ($n$), the algorithm accumulates the number of papers that have at least $k$ citations. The first point where this count meets or exceeds $k$ gives us the correct h-index.

This approach avoids the overhead of full sorting and leverages counting sort principles along with a reverse accumulation search.

Now, let’s look at the solution steps below:

1. We initialize the following:

   1. n to represent the number of papers (length of the citations list).

   2. A list papers of size n + 1 to count how many papers have a specific number of citations, with papers[i] representing the count of papers cited exactly i times.

   3. All citation values greater than n are capped and grouped into papers[n], since the h-index cannot exceed n.

2. Next, we iterate through the citations list:

   1. For each citation count, c, we increment papers[min(n, c)].

3. We also initialize k = n as our candidate h-index, and s = papers[n], the number of papers with at least n citations.

4. We then iterate through the papers array, while k > s, and search for the h-index by:

   1. We decrement k and add papers[k] to s, computing the total number of papers with at least k citations.

5. The iteration continues until we find the highest k such that there are at least k papers with k or more citations.

6. After iterating, the current k is returned as the h-index.

Let’s look at the following illustration to get a better understanding of the solution: