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Fast Exponentiation using Bit Manipulation

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Given two integers A and N, the task is to calculate A raised to power N (i.e. AN).

Examples: 

Input: A = 3, N = 5 
Output: 243 
Explanation: 
3 raised to power 5 = (3*3*3*3*3) = 243

Input: A = 21, N = 4
Output: 194481 
Explanation: 
21 raised to power 4 = (21*21*21*21) = 194481 
 

Naive Approach: 
The simplest approach to solve this problem is to repetitively multiply A, N times and print the product. 

C++




#include <iostream>
using namespace std;
 
// Function to calculate power using brute force approach
long long findPower(int a, int n) {
    long long result = 1;
 
    // Multiply 'a' by itself 'n' times
    for (int i = 0; i < n; ++i) {
        result *= a;
    }
 
    return result;
}
 
int main() {
    int a = 3;
    int n = 5;
 
    // Calculate and display the result
    long long result = findPower(a, n);
    cout<<result<<endl;
    return 0;
}


Java




public class Main {
    // Function to calculate power using brute force approach
    static long findPower(int a, int n) {
        long result = 1;
 
        // Multiply 'a' by itself 'n' times
        for (int i = 0; i < n; ++i) {
            result *= a;
        }
 
        return result;
    }
 
    public static void main(String[] args) {
        int a = 3;
        int n = 5;
 
        // Calculate and display the result
        long result = findPower(a, n);
        System.out.println(result);
    }
}
//This code is contributed by Aman


C#




using System;
 
public class PowerCalculation
{
    // Function to calculate power using brute force approach
    public static long FindPower(int a, int n)
    {
        long result = 1;
 
        // Multiply 'a' by itself 'n' times
        for (int i = 0; i < n; ++i)
        {
            result *= a;
        }
 
        return result;
    }
 
    public static void Main(string[] args)
    {
        int a = 3;
        int n = 5;
 
        // Calculate and display the result
        long result = FindPower(a, n);
        Console.WriteLine(result);
    }
}


Javascript




// Function to calculate power using brute force approach
function findPower(a, n) {
    let result = 1;
 
    // Multiply 'a' by itself 'n' times
    for (let i = 0; i < n; i++) {
        result *= a;
    }
 
    return result;
}
 
// Main function
const a = 3;
const n = 5;
 
// Calculate and display the result
const result = findPower(a, n);
console.log(result);
//This code is contributed by Aman.


Python3




# Function to calculate power using brute force approach
def findPower(a, n):
    result = 1
 
    # Multiply 'a' by itself 'n' times
    for i in range(n):
        result *= a
 
    return result
 
# Main function
a = 3
n = 5
 
# Calculate and display the result
result = findPower(a, n)
print(result)
 
# This code is contributed by Yash Agarwal(yashagarwal2852002)


Output

243

Time Complexity: O(N) 
Auxiliary Space: O(1)

Efficient Approach: 
To optimize the above approach, the idea is to use Bit Manipulation. Convert the integer N to its binary form and follow the steps below:  

  • Initialize ans to store the final answer of AN.
  • Traverse until N > 0 and in each iteration, perform Right Shift operation on it.
  • Also, in each iteration, multiply A with itself and update it.
  • If current LSB is set, then multiply current value of A to ans.
  • Finally, after completing the above steps, print ans.

Below is the implementation of the above approach:

C++




// C++ Program to implement
// the above approach
#include <iostream>
using namespace std;
 
// Function to return a^n
int powerOptimised(int a, int n)
{
 
    // Stores final answer
    int ans = 1;
 
    while (n > 0) {
 
        int last_bit = (n & 1);
 
        // Check if current LSB
        // is set
        if (last_bit) {
            ans = ans * a;
        }
 
        a = a * a;
 
        // Right shift
        n = n >> 1;
    }
 
    return ans;
}
 
// Driver Code
int main()
{
    int a = 3, n = 5;
 
    cout << powerOptimised(a, n);
 
    return 0;
}


Java




// Java program to implement
// the above approach
class GFG{
 
// Function to return a^n
static int powerOptimised(int a, int n)
{
 
    // Stores final answer
    int ans = 1;
 
    while (n > 0)
    {
        int last_bit = (n & 1);
 
        // Check if current LSB
        // is set
        if (last_bit > 0)
        {
            ans = ans * a;
        }
         
        a = a * a;
 
        // Right shift
        n = n >> 1;
    }
    return ans;
}
 
// Driver Code
public static void main(String[] args)
{
    int a = 3, n = 5;
 
    System.out.print(powerOptimised(a, n));
}
}
 
// This code is contributed by PrinciRaj1992


C#




// C# program to implement
// the above approach
using System;
 
class GFG{
 
// Function to return a^n
static int powerOptimised(int a, int n)
{
     
    // Stores readonly answer
    int ans = 1;
 
    while (n > 0)
    {
        int last_bit = (n & 1);
 
        // Check if current LSB
        // is set
        if (last_bit > 0)
        {
            ans = ans * a;
        }
        a = a * a;
 
        // Right shift
        n = n >> 1;
    }
    return ans;
}
 
// Driver Code
public static void Main(String[] args)
{
    int a = 3, n = 5;
 
    Console.Write(powerOptimised(a, n));
}
}
 
// This code is contributed by Princi Singh


Javascript




<script>
 
// Javascript program to implement
// the above approach
 
// Function to return a^n
function powerOptimised(a, n)
{
   
    // Stores final answer
    let ans = 1;
   
    while (n > 0)
    {
        let last_bit = (n & 1);
   
        // Check if current LSB
        // is set
        if (last_bit > 0)
        {
            ans = ans * a;
        }
           
        a = a * a;
   
        // Right shift
        n = n >> 1;
    }
    return ans;
 
    // Driver Code
         
    let a = 3, n = 5;
   
    document.write(powerOptimised(a, n));
       
</script>


Python3




# Python3 program to implement
# the above approach
 
# Function to return a^n
def powerOptimised(a, n):
     
    # Stores final answer
    ans = 1
     
    while (n > 0):
        last_bit = (n & 1)
         
        # Check if current LSB
        # is set
        if (last_bit):
            ans = ans * a
        a = a * a
         
        # Right shift
        n = n >> 1
         
    return ans
 
# Driver code
if __name__ == '__main__':
     
    a = 3
    n = 5
     
    print(powerOptimised(a,n))
 
# This code is contributed by virusbuddah_


Output

243

Time Complexity: O(logN) 
Auxiliary Space: O(1)

Another efficient approach : Recursive exponentiation

Recursive exponentiation is a method used to efficiently compute AN, where A & N are integers. It leverages recursion to break down the problem into smaller subproblems. Follow the steps below :

  • If N = 0, the result is always 1 because any non zero number raised to the power of 0 is 1.
  • If N is even, we can compute AN as (AN/2)2 . This is done by recursively computing AN/2 & squaring the result.
  • If N is odd, we compute AN as A * AN – 1 . Again, we recursively compute AN -1 & multiply the result by A.

Below is the implementation of the above approach :

Python




def recursive_exponentiation(A, N):
    if N == 0:
        return 1
    elif N % 2 == 0:
        # If N is even, recursively compute A^(N/2) and square it
        temp = recursive_exponentiation(A, N // 2)
        return temp * temp
    else:
        # If N is odd, recursively compute A^(N-1) and multiply by A
        return A * recursive_exponentiation(A, N - 1)
 
# Test cases
print(recursive_exponentiation(3, 5)) 


Output

243

Complexity Analysis :

Time Complexity: O(logN) 

Auxiliary Space: O(1)



Last Updated : 11 Mar, 2024
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