1310A · Recommendations

Problem: VK news recommendation system daily selects interesting publications of one of $n$ disjoint categories for each user. Each publication belongs to exactly one category. For each category $i$ batch algorithm selects $a_i$ publications.

The latest A/B test suggests that users are reading recommended publications more actively if each category has a different number of publications within daily recommendations. The targeted algorithm can find a single interesting publication of $i$-th category within $t_i$ seconds.

What is the minimum total time necessary to add publications to the result of batch algorithm execution, so all categories have a different number of publications? You can't remove publications recommended by the batch algorithm.

Input Format: The first line of input consists of single integer $n$ — the number of news categories ($1 \le n \le 200\,000$).

The second line of input consists of $n$ integers $a_i$ — the number of publications of $i$-th category selected by the batch algorithm ($1 \le a_i \le 10^9$).

The third line of input consists of $n$ integers $t_i$ — time it takes for targeted algorithm to find one new publication of category $i$ ($1 \le t_i \le 10^5)$.

Output Format: Print one integer — the minimal required time for the targeted algorithm to get rid of categories with the same size.

Note: In the first example, it is possible to find three publications of the second type, which will take 6 seconds.

In the second example, all news categories contain a different number of publications.