codeforces 893E Counting Arrays

本文介绍一种算法,用于求解选取n个数字使其乘积等于m的所有可能方案的数量。通过质因数分解及组合数学中的插板法解决此问题,并考虑正负数的选择。

       题意:求选n个数字使得其乘积等于m的方案数。

       首先我们可以对m进行质因数分解,为p1^y1*p2^y2*p3^y3,那么显而易见我们对每一个质因数有不同的划分方式,所有质因数的划分数之积就是乘积等于x的方案数了。假设我们当前要求p1^y1的次方分成n份的答案,那么就相当于我们要将幂次y1划分为n种集合,由于幂次可为0,即可非空,由插板法可得答案为c(n+y1-1,n-1)。

       因为我们选的数字可以是负数,而且m为正数,所以我们可以选0个,2个到n/2个为负数,c(n,0)+c(n,2)+..+c(n,n/2)即为2的n-1次方。所以答案还要乘以2的n-1次方。

       下附AC代码。

#include<iostream>
#include<stdio.h>
#include<string.h>
#include<algorithm>
#define maxn 2000005
using namespace std;
typedef long long ll;
const ll mod=1e9+7;
ll tot;
ll fac[maxn],inv[maxn];
int pri[maxn],vis[maxn];
void shai()
{
	for(int i=2;i<=2000000;i++)
	{
		if(!vis[i])
			pri[++tot]=i;
		for(int j=1;j<=tot && i*pri[j]<=2000000;j++)
		{
			vis[i*pri[j]]=1;
			if(i%pri[j]==0)
			break;
		}
	}
}
ll quickpow(ll p,ll k)
{
	ll ans=1;
	while(k)
	{
		if(k&1)
			ans=(ans*p)%mod;
		p=(p*p)%mod;
		k>>=1;
	}
	return ans;
	
}
ll c(ll n,ll m)
{
	return ((fac[n]*inv[n-m])%mod*inv[m])%mod;
}
int main()
{
	
	shai();
	fac[0]=1;inv[0]=1;
	for(int i=1;i<maxn;i++)
	{
		fac[i]=(fac[i-1]*i)%mod;
		inv[i]=quickpow(fac[i],mod-2);
	}
	
	int _;
	scanf("%d",&_);
	while(_--)
	{
		ll n,m,ans=1;
		scanf("%I64d%I64d",&n,&m);
		for(int i=1;pri[i]*pri[i]<=n && n>1;i++)
		{
			ll cnt=0;
			if(n%pri[i]==0)
			{
				while(n%pri[i]==0)
					cnt++,n/=pri[i];
				ans=(ans*c(cnt+m-1,m-1))%mod;
			}
		}
		if(n>1)
			ans=(ans*c(m,m-1))%mod;
		printf("%I64d\n",(ans*quickpow(2,m-1))%mod);
	}
}


      

### Codeforces 887E Problem Solution and Discussion The problem **887E - The Great Game** on Codeforces involves a strategic game between two players who take turns to perform operations under specific rules. To tackle this challenge effectively, understanding both dynamic programming (DP) techniques and bitwise manipulation is crucial. #### Dynamic Programming Approach One effective method to approach this problem utilizes DP with memoization. By defining `dp[i][j]` as the optimal result when starting from state `(i,j)` where `i` represents current position and `j` indicates some status flag related to previous moves: ```cpp #include <bits/stdc++.h> using namespace std; const int MAXN = ...; // Define based on constraints int dp[MAXN][2]; // Function to calculate minimum steps using top-down DP int minSteps(int pos, bool prevMoveType) { if (pos >= N) return 0; if (dp[pos][prevMoveType] != -1) return dp[pos][prevMoveType]; int res = INT_MAX; // Try all possible next positions and update 'res' for (...) { /* Logic here */ } dp[pos][prevMoveType] = res; return res; } ``` This code snippet outlines how one might structure a solution involving recursive calls combined with caching results through an array named `dp`. #### Bitwise Operations Insight Another critical aspect lies within efficiently handling large integers via bitwise operators instead of arithmetic ones whenever applicable. This optimization can significantly reduce computation time especially given tight limits often found in competitive coding challenges like those hosted by platforms such as Codeforces[^1]. For detailed discussions about similar problems or more insights into solving strategies specifically tailored towards contest preparation, visiting forums dedicated to algorithmic contests would be beneficial. Websites associated directly with Codeforces offer rich resources including editorials written after each round which provide comprehensive explanations alongside alternative approaches taken by successful contestants during live events. --related questions-- 1. What are common pitfalls encountered while implementing dynamic programming solutions? 2. How does bit manipulation improve performance in algorithms dealing with integer values? 3. Can you recommend any online communities focused on discussing competitive programming tactics? 4. Are there particular patterns that frequently appear across different levels of difficulty within Codeforces contests?
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