def solve() -> None: data = sys.stdin.buffer.read().split() it = iter(data) t = int(next(it)) out_lines = [] for _ in range(t): n = int(next(it)) love = [0] + [int(next(it)) for _ in range(n)] # 1‑based list ans = 0 for i in range(1, n + 1): j = love[i] if i < j and love[j] == i: ans += 1 out_lines.append(str(ans)) sys.stdout.write("\n".join(out_lines))
If i, j is not mutual, at least one of the equalities love[i]=j or love[j]=i is false. Consider the iteration where i is the smaller index of the two. If love[i] ≠ j → the algorithm’s first condition ( j = love[i] ) fails. If love[i] = j but love[j] ≠ i → the second condition fails. Thus the counter is never increased for this unordered pair. ∎ Theorem After processing a test case, mutualPairs equals the total number of mutual‑love pairs in the group. 412. Sislovesme
long long ans = 0; // up to N/2 fits in int, but long long is safe for (int i = 1; i <= N; ++i) int j = love[i]; if (i < j && love[j] == i) ++ans; // count each 2‑cycle once cout << ans << '\n'; return 0; def solve() -> None: data = sys
Memory – The array love[1…N] is stored: . If love[i] = j but love[j] ≠ i
love[1 … N] // 1‑based indexing where love[i] = j means person i loves person j .
From Lemma 1 every increment corresponds to a genuine mutual‑love pair. From Lemma 2 every genuine pair contributes exactly one increment. From Lemma 3 no non‑mutual pair contributes any increment. Therefore the total number of increments equals precisely the number of mutual‑love pairs. ∎ 5️⃣ Complexity analysis Time – The loop visits each of the N people once, performing O(1) work per iteration: O(N) per test case.
import sys