# Understanding the iterative version of Binary Exponentiation

Honestly, for me, understanding the recursive version of Binary Exponentiation was way easier than understanding its iterative version. And since you are here, I guess it might be the same for you. Anyway, let’s get straight to the point.

You may have noticed it already, as it’s pretty obvious.
Every decimal number can be expressed as the sum of some powers of 2. For instance, 13 = 1 + 4 + 8 = 2⁰ + 2² + 2³; which indeed is how we convert any binary number to its decimal equivalent at the first place.
Like, 1101(binary) = 2⁰ * 1 + 2¹ * 0 + 2² * 1 + 2³ * 1 = 2⁰ + 2² + 2³ = 13

Also, every number N can be represented in ceil(log₂N) + 1 bits.
For instance, 8 = 1000(binary) i.e in 4 bits, 17 = 10001(binary) i.e in 5 bits and so on.

Keep the above two points in mind. They will be used soon.

Let's understand the following approaches with the example of calculating 3¹¹.

# Naive approach

Calculates 3¹¹ as:
We run a loop 11 times. Each time the result is multiplied by 3.
3¹¹ = 3 . 3 . 3 . 3 . 3 . 3 . 3 . 3 . 3 . 3 . 3

So the loop run 11 times. Had the power been 10⁶, it would have run 10⁶ times. Thus its time complexity is O(N).

# Binary Exponentiation approach

The naive approach looks at 3¹¹ as 3 . 3 . 3 . 3 . 3 . 3 . 3 . 3 . 3 . 3 . 3
Whereas the binary exponentiation approach looks at 3¹¹ as 3¹. 3² . 3⁸;

Where did we get this 1, 2, 8 power from?
Well, 11 = 1011₂ (binary equivalent of 11)
1011₂ = 2⁰ + 2¹ + 2³ = 1 + 2 + 8

3¹¹ = 3¹⁺²⁺⁸ = 3¹. 3² . 3⁸

Our aim here is to calculate 3¹¹ in fewer steps, to be precise in ceil(log₂11) steps.

Let a be the base and b be the power.
In the naive approach, with each iteration, we are multiplying the result with a, i.e by the same number every time. Can we do better?

Guess what, we can!
After each iteration, we can replace a by . So in the case of 3¹¹, we will have 3¹¹ = 3¹ * 3² * 3⁴ …

Well, we have already discussed how 11 can be written as the sum of some powers of 2. Thus we know how 3¹¹ can be written as the product of 3 raised to some powers of 2.

Here’s the code —

`/* a is the base, b is the power. */long long binpow(long long a, long long b) {        long long result = 1;   while (b > 0) {       /*        The below condition is true when b is odd, i.e when the       leftmost bit of b is 1. Since with each iteration a is       replaced by a², the set bit of b indicates that the current       value of a is required to build up the result.       */       if (b % 2 == 1)           result = result * a;       /*        a maintains the value which needs to be multiplied when b       becomes odd i.e when the last bit of b is 1.       */       a = a * a;       /*        This is equivalent to right shift. 1011₂ first becomes         101₂, then 10₂, then 1₂, and at last 0₂.        */       b /= 2;   }   return result;}`

I hope this makes sense.

Reference —

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