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Miller Rabin Primality Test

By appro, 7 years ago, In English

What is the time complexity for Miller Rabin Primality Test?

Here is the algorithm from wikipedia page.

write n − 1 as 2^r·d where d is odd.

WitnessLoop: repeat k times: //runs k times.

{ pick a random integer a in the range [2, n − 1]

x ← a^d mod n

if x = 1 or x = n − 1 then

      continue WitnessLoop

 repeat r − 1 times:               //r=O(logn)

 {

      x ← x^2 mod n               //TC=O(logn)

      if x = 1 then

        return composite

      if x = n − 1 then

        continue WitnessLoop

 }

return composite

}

return probably prime

According to me the worst case time complexity would be O(k*(logn)^2)? But the wikipedia page mentions it as

O(k*(logn)^3). Can anyone help me out?

https://en.wikipedia.org/wiki/Miller%E2%80%93Rabin_primality_test

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7 years ago, # |
← Rev. 3   Vote: I like it +1 Vote: I do not like it

The complexity of multiplying two big numbers in a naive way is square of the length of these numbers. So I think x ← x^2 mod n should be

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    7 years ago, # ^ |
    ← Rev. 3   Vote: I like it 0 Vote: I do not like it

    We generally multiply two big numbers numbers using the following method:-

    It assumes that 2*c is in the range of long long.

    long long mulmod(long long a,long long b,long long c)

    {

    long long x = 0,y=a%c;

while(b > 0)

{

    if(b%2 == 1)

    {

         x = (x+y)%c;

    }

    y = (y*2)%c;

    b /= 2;

}

return x%c;

    }

    I think the complexity of this will be O(logb).

    And in our case O(logx),as x=O(logn) so we can say it is O(logn).

    Are you talking about how exactly multiplication is handled by the system?

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      7 years ago, # ^ |
      ← Rev. 2   Vote: I like it 0 Vote: I do not like it

      By big numbers, I meant the numbers that can't be directly handled using native types(such as long long). According to my understand, the wiki is talking about this kind of numbers. Usually they are split into parts and saved in an array. For example if base=100, x=1234. Then the array may be a[0]=34, a[1]=12.

      Multiplying two big numbers in a naive way looks like:

      const unsigned MAXN=100;
const long long base=10000;
unsigned lena,lenb,lenc;
long long a[MAXN],b[MAXN],c[MAXN];

for(unsigned i=0;i<lena;++i) {
	for(unsigned j=0;j<lenb;++j) {
		c[i+j]+=a[i]*a[j];
		c[i+j+1]+=c[i+j]/base;
		c[i+j]%=base;
	}
}
//update lenc

      So the complexity is O(len2), which is . By using FFT, the complexity can be reduced to , result the in the wiki.

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7 years ago, # |
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Just curious, in which cases would this be better than a root N brute force check? It seems that root N is about equal to log^2 N, and the test only tells you if the number is probably prime or not.

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    7 years ago, # ^ |
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    probability of wrong answer is 4^-k there k is number of iterations, so it is very small number when, for example k = 30. and for N = 10^18, root is 10^9, but log^3 is ~ 200000

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