Discrete Logging
| Time Limit: 5000MS | Memory Limit: 65536K | |
| Total Submissions: 1431 | Accepted: 709 |
Description
Given a prime P, 2 <= P < 231, an integer B, 2 <= B < P, and an integer N, 1 <= N < P, compute the discrete logarithm of N, base B, modulo P. That is, find an integer L such that
BL == N (mod P)
Input
Read several lines of input, each containing P,B,N separated by a space.
Output
For each line print the logarithm on a separate line. If there are several, print the smallest; if there is none, print "no solution".
Sample Input
5 2 1 5 2 2 5 2 3 5 2 4 5 3 1 5 3 2 5 3 3 5 3 4 5 4 1 5 4 2 5 4 3 5 4 4 12345701 2 1111111 1111111121 65537 1111111111
Sample Output
0 1 3 2 0 3 1 2 0 no solution no solution 1 9584351 462803587
Hint
The solution to this problem requires a well known result in number theory that is probably expected of you for Putnam but not ACM competitions. It is Fermat's theorem that states
for any prime P and some other (fairly rare) numbers known as base-B pseudoprimes. A rarer subset of the base-B pseudoprimes, known as Carmichael numbers, are pseudoprimes for every base between 2 and P-1. A corollary to Fermat's theorem is that for any m
B(P-1) == 1 (mod P)
for any prime P and some other (fairly rare) numbers known as base-B pseudoprimes. A rarer subset of the base-B pseudoprimes, known as Carmichael numbers, are pseudoprimes for every base between 2 and P-1. A corollary to Fermat's theorem is that for any m
B(-m) == B(P-1-m) (mod P) .
#include<iostream>
#include<cstdio>
#include<cmath>
#include<algorithm>
using namespace std;
struct Node
{
int index;//序号
__int64 val;//值
};
Node num[66000];
__int64 gcd(__int64 a,__int64 b)
{
return b==0?a:gcd(b,a%b);
}
__int64 _pow(__int64 a,__int64 b,__int64 m)
{
if(b==0) return 1;
if(b==1) return a%m;
__int64 t=_pow(a,b/2,m);
t=(t*t)%m;
if(b&1) t=(t*a)%m;
return t;
}
bool cmp(Node h,Node k)
{
if(h.val!=k.val) return h.val<k.val;
return h.index<k.index;
}
int _binary_search(__int64 key,__int64 len)//二分查找
{
int left = 0,right = len;
int result = - 1,mid;
while(left <= right)
{
mid = (left + right)>>1;
if(num[mid].val == key)
{
result = num[mid].index;
right = mid -1;
}
else if(num[mid].val < key) left = mid + 1;
else right = mid -1;
}
return result;
}
int Baby_step_Giant_step(__int64 a,__int64 b,__int64 n)//计算最小的x使得a^x=b(mod n) n是素数
{
__int64 m=(__int64)(sqrt(n+0.5)+1);
//计算 (j,a^j%n) (0<=j<m)
num[0].index=0,num[0].val=1;
for(int i=1;i<m;i++) num[i].index=i,num[i].val=num[i-1].val*a%n;
sort(num,num+m,cmp);
//计算 a^-m
__int64 a_m=_pow(a,n-1-m,n);//因为n是素数,所以a^(n-1)=1(mod n)
__int64 y=b;
for(int i=0;i<m;i++)
{
int res=_binary_search(y,m);
if(res!=-1) return i*m+res;
y=y*a_m%n;
}
return -1;
}
int main()
{
__int64 n,a,b;//a^x=b(mod n)
while(scanf("%I64d%I64d%I64d",&n,&a,&b)==3&&(n||a||b))
{
int r = Baby_step_Giant_step(a,b,n);
if(r == -1)
printf("no solution/n");
else
printf("%d/n",r);
}
return 0;
}
本文介绍了一种解决离散对数问题的有效算法——Baby Step Giant Step算法,并提供了详细的实现代码。该算法用于计算特定条件下基底的离散对数,通过预处理和查找表的方式减少计算复杂度。
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