codeforces1323D Present

本文介绍了一种处理大规模二进制数据的算法,通过逐位分析和优化,实现快速计算二进制位上特定模式出现的次数。该算法采用二分查找技术,复杂度为O(26nlogn),适用于处理大量数据的二进制位运算问题。

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题意

( a 1 + a 2 ) ⊕ ( a 1 + a 3 ) ⊕ … ⊕ ( a 1 + a n ) ⊕ ( a 2 + a 3 ) ⊕ … ⊕ ( a 2 + a n ) … ⊕ ( a n − 1 + a n ) (a_1 + a_2) \oplus (a_1 + a_3) \oplus \ldots \oplus (a_1 + a_n) \\ \oplus (a_2 + a_3) \oplus \ldots \oplus (a_2 + a_n) \\ \ldots \\ \oplus (a_{n-1} + a_n) (a1+a2)(a1+a3)(a1+an)(a2+a3)(a2+an)(an1+an)

其中 n ≤ 400000 n\leq 400000 n400000 a i ≤ 1 0 7 a_i\leq10^7 ai107

分析

这场用手速上了紫嘿嘿嘿,不过 D D D 没做出来还是太菜了。
对于这种二进制的题,都是一位一位考虑。这里考虑答案的第 k k k 位。
我们将每个数取前 k k k 位。现在就是考虑 a i + a j a_i+a_j ai+aj k k k 位为 1 1 1 的对数。
k k k 位为 1 1 1 只有两种情况:

  • k k k 位为 1 1 1,第 k + 1 k+1 k+1 位为 0 0 0
    这种情况就是大于 2 k − a i 2^k-a_i 2kai 的个数减去大于 2 k + 1 − a i 2^{k+1}-a_i 2k+1ai 的个数
  • k k k 位和第 k + 1 k+1 k+1 位都为 1 1 1
    这种情况就是大于 2 k + 2 k + 1 − a i 2^k+2^{k+1}-a_i 2k+2k+1ai a j a_j aj 个数

加起来就是第 k k k 位为 1 1 1 的对数了。
二分找个数复杂度 O ( l o g n ) O(logn) O(logn)
总共 26 位
复杂度 O ( 26 n l o g n ) O(26nlogn) O(26nlogn)

代码如下

#include <bits/stdc++.h>
#define N 400005
using namespace std;
int a[N], b[N], n;
int get(int l, int x){
	if(b[n] < x) return 0;
	int r = n, mid;
	while(l < r){
		mid = l + r >> 1;
		if(b[mid] >= x) r = mid;
		else l = mid + 1;
	}
	return n - l + 1;
}
int main(){
	int i, j, m, sum, ans = 0;
	scanf("%d", &n);
	for(i = 1; i <= n; i++) scanf("%d", &a[i]);
	for(j = 0; j <= 26; j++){
		for(i = 1; i <= n; i++) b[i] = a[i] & ((1 << j + 1) - 1);
		//printf("%d======\n", j);
		//for(i = 1; i <= n; i++) printf("%d ", b[i]);
		//printf("\n");
		sort(b + 1, b + i);
		sum = 0;
		for(i = 1; i < n; i++){
			sum = (sum + get(i + 1, (1 << j) - b[i])) % 2;
			sum = (sum - get(i + 1, (1 << j + 1) - b[i])) % 2;
			sum = (sum + get(i + 1, (1 << j) + (1 << j + 1) - b[i])) % 2;
		}
		//printf("sum === %d\n", sum);
		if(sum % 2) ans |= (1 << j);
	}
	printf("%d", ans);
	return 0;
}
### Codeforces 1487D Problem Solution The problem described involves determining the maximum amount of a product that can be created from given quantities of ingredients under an idealized production process. For this specific case on Codeforces with problem number 1487D, while direct details about this exact question are not provided here, similar problems often involve resource allocation or limiting reagent type calculations. For instance, when faced with such constraints-based questions where multiple resources contribute to producing one unit of output but at different ratios, finding the bottleneck becomes crucial. In another context related to crafting items using various materials, it was determined that the formula `min(a[0],a[1],a[2]/2,a[3]/7,a[4]/4)` could represent how these limits interact[^1]. However, applying this directly without knowing specifics like what each array element represents in relation to the actual requirements for creating "philosophical stones" as mentioned would require adjustments based upon the precise conditions outlined within 1487D itself. To solve or discuss solutions effectively regarding Codeforces' challenge numbered 1487D: - Carefully read through all aspects presented by the contest organizers. - Identify which ingredient or component acts as the primary constraint towards achieving full capacity utilization. - Implement logic reflecting those relationships accurately; typically involving loops, conditionals, and possibly dynamic programming depending on complexity level required beyond simple minimum value determination across adjusted inputs. ```cpp #include <iostream> #include <vector> using namespace std; int main() { int n; cin >> n; vector<long long> a(n); for(int i=0;i<n;++i){ cin>>a[i]; } // Assuming indices correspond appropriately per problem statement's ratio requirement cout << min({a[0], a[1], a[2]/2LL, a[3]/7LL, a[4]/4LL}) << endl; } ``` --related questions-- 1. How does identifying bottlenecks help optimize algorithms solving constrained optimization problems? 2. What strategies should contestants adopt when translating mathematical formulas into code during competitive coding events? 3. Can you explain why understanding input-output relations is critical before implementing any algorithmic approach? 4. In what ways do prefix-suffix-middle frameworks enhance model training efficiency outside of just tokenization improvements? 5. Why might adjusting sample proportions specifically benefit models designed for tasks requiring both strong linguistic comprehension alongside logical reasoning skills?
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