Fermat’s Little Theorem Proof & Algorithm

Fermat’s Little Theorem states that for a prime number p , the following statement holds true –

ap ≡ a (mod p)
(~ which can be read as ap mod p = a)
ap-1 ≡ 1 (mod p)

Here is any number less than p.


There are tons of proofs for Fermat’s Little Theorem on Wikipedia . I am discussing an easy one based on binomial expansion – Proof by Induction.

Consider a binomial expression – (1+a)p

On expanding it , we get –
(1+a)p = ap + pC1 ap-1 + pC2 ap-2 + pC3 ap-3 …… + 1

If we take modulo p both sides, All the terms except the first and the last term becomes 0.

How? Let’s See.

Consider a binomial coefficient – pC = p!(p-k)! (k)!

Since is prime (no divisors) ,pCk   will have p as it’s divisor .Thus modulo p will yield 0 as result.

we get –
(1+a)p ≡ ap + 1 mod p

Considering the Fermat’s Little theorem true , we can replace ap mod p by
We get the following result – (1+a)p ≡ (1+a) mod p

Thus Fermat’s Little Theorem is proved by Induction.

Now that we’ve proved the theorem , let’s see how we can use it to check the probabilistic primality of a number.

PRIME Algorithm

To check whether a number p is prime or not, just take a random a less than p and verify the theorem.

if  (ap-1 mod p)  yields 1 as result , then the number may be prime.

To increase the accuracy of the algorithm,perform the check for a certain number of iterations.

Here’s the python Code for the Algorithm

import random

def exp(a,p,m):
	if (p==0):
		return 1
	elif (p%2==1):
		return (a*exp(a,p-1,m))%m
	return (x*x)%m

def fermat_primality(p):
	if (p==2 or p==3):return 1 
	if (p<=3):return 0

	#number of iterations = 10

	for i in range(10):	
		#Generating a random number a lesser than p
		a = random.randrange(2,p-1)	
		if (exp(a,p-1,p)!=1):
			return 0

	return 1


The time complexity of the Algorithm is O(iterations*log(n)) which is pretty fast. But the algorithm is not always accurate as there may be many composite numbers p which may yield the result for some value of a. Therefore it is advised to perform the check for certain number of iterations.

Also there are certain composite numbers n which satisfies the Fermat’s Little congruence relation for all values 1<a<n (a is relatively prime to n). Such numbers are called Carmichael numbers.

But they are very less in number – around 2000 under 25,000,0000,000.

Here’s a problem to try – SPOJ/PON


The Fermat’s result proved above ap-1 ≡ 1 (mod p)  can be rewritten as  a.ap-2 ≡ 1 (mod p).

In the expression a.x ≡ 1 (mod p) , x is the inverse of a.

Thus, when p is prime , (1a) mod p , is given by ap-2 mod p .

def exp(a,p,m):
	if (p==0):
		return 1
	elif (p%2==1):
		return (a*exp(a,p-1,m))%m
	return (x*x)%m

def mod_inverse(a,p):
	return exp(a,p-2,p)


For any queries related to the article , feel free to drop a comment below 🙂

EDIT – If you’re trying to implement the above algorithm on C/C++, take care of overflows while multiplying two long long int numbers.


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