Description

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" 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alt=" " />

Output

aaarticlea/jpeg;base64,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" alt=" " />
 

Sample Input

3 5
1 8 13
7 5 4 8 3

Sample Output

7
 

Data Constraint

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Hint

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g5OBEoYdBtOgJyyG6/1dHLq2UMGs0qZzjPAAYUyr2fnAPOiVHBylZtA7lOJ4wmkdwMglZCX4nGtzQCMYEWD2sy8eEXqy1BiRak/PMZ4uwyhU1QjS29cHWSQ8BWoWBuB3ngfvGHvTeMjXnmBhLDscy3yhzIddyCiHs/FzVnFkFSxILQDCD0cSGJWYPKEKXtL3yEFup6BWLmrgLnXJZPuqa43LKkTOFh/99/1zIk7AL9DmVmee1I81VKiE23S2DDAd8F2QIy6+orRSjoFGBAnXG5Mijecu/8AYx//2Q==" alt=" " />

显然有个O(n2)的暴力枚举,不过会超时。(但也有六十分呐)

时间主要花在了一个一个判断,我们设想能否一次性判断很多个。

两个数异或后有二进制中有两个一,就是说两个数二进制下有两位是不同的,即有ai xor 2k xor bj xor 2l=0(k!=l);

那么我们可以考虑枚举ai xor 2k,丢到hash表里,然后再枚举每个bj xor 2l,在hash里找是否有相等的。

为避免重复(ai xor 2k   bj xor 2l 与 ai xor 2l  bj xor 2k是相等的),我们可以令k<l。

 #include<iostream>
#include<cstdio>
#include<cstring>
#include<cstdlib>
#include<algorithm>
#include<cmath>
#define mo 9999999
#define N 100005
int n,hash[mo],m,a[N],b[N],g[mo],qwq[];
long long ans;
void init(int x){
int a=x%mo;
while ((hash[a]!=)&&(hash[a]!=x)) a=(a+)%mo;
hash[a]=x;
g[a]++;
}
int get(int x){
int a=x%mo;
while ((hash[a]!=)&&(hash[a]!=x)) a=(a+)%mo;
return g[a];
}
int main(){
scanf("%d%d",&n,&m);
for (int i=;i<=n;i++)
scanf("%d",&a[i]);
for (int j=;j<=m;j++)
scanf("%d",&b[j]);
qwq[]=;
for (int i=;i<=;i++)
qwq[i]=*qwq[i-];
for (int i=;i<=n;i++)
init(a[i]^qwq[]);
ans=;
for (int i=;i<;i++){
for (int j=;j<=m;j++)
ans+=get(b[j]^qwq[i]);
for (int j=;j<=n;j++)
init(a[j]^qwq[i]);
}
printf("%lld\n",ans);
}

神奇的代码

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