Welcome back with another problem to solve!
Today’s problem will focus on calculating big exponentials from scratch. This problem is similar to the problem seen in the
This problem is provided by the wonderful website
We’ll be using Go for this program: headache time! :D
Let’s take a look at the problem:
2¹⁵ = 32768, and the sum of its digits is 3+2+7+6+8=26.
What is the sum of the digits of the number 2¹⁰⁰⁰?
The problem is really simple: we need to calculate 2¹⁰⁰⁰ and sum its digits to give it a result. Simple, isn’t it? Well…
To give out some simple basics, an exponential number is simply the repetition of that same number a certain number of times. For example, writing 4³ means calculating 4*4*4. What’s really cool about powers (which is also what causes us this problem) is how fast they grow: not the fastest, but still pretty fast.
The function we are interested in is the green one: you can easily see how fast it grows. Even if the power function x³ grows faster initially, the exponentiation of 2 catches up pretty quickly. As in the previous article, try with your calculator: you should not be able to calculate over 2³³², which is 8.749002899x10⁹⁹.
And yet, with a little bit of reasoning and a simple program, we can calculate that 2³³³ is
17498005798264095394980017816940970922825355447145699491406164851279623993595007385788105416184430592
And with the same approach, 2⁵⁰⁰ is
3273390607896141870013189696827599152216642046043064789483291368096133796404674554883270092325904157150886684127560071009217256545885393053328527589376
Cool right? Let’s see how it’s done then!
If there’s one thing computers are good at, it’s repeating the same job multiple times really fast. We’ll exploit this ability to repeat a simple task many, many times to iterate over all the exponents from 1 to the desired one and print out the result. The simple operation we are doing is the multiplication of a certain number with the number 2 to increase the exponent. However, we are doing this by multiplying each digit of the starting number by 2: this way, we can manage increasingly big numbers simply by multiplying their digits. Let’s write a multiplication function.
As always, let’s explain a bit what’s happening here. We create the multiply
function, which takes in two parameters: stringedInt
, the integer we want to multiply, and factor
, the factor we are multiplying it for. After that, we define the variable carryover
, which we’ll explain in a moment.
Now we start looping: we loop over the length of stringedInt
and multiply each digit by factor
.
We have some type of conversion to do, however:
integer
to save our converted digit from the string (with stringedInt[n]-'0'
we convert the rune value to its UNICODE counterpart and then convert it to int
)fmt.Sprintf
function, we convert the result back to a string and add it to the front of the out
variable, which will be our result.
Let’s take a moment at the math done here: the possible digits we are multiplying are 0,1,2,3,4,5,6,7,8,9, but the results somehow repeat in a certain manner. For example, 2*2 is 4, and 2*7 is 14, so a 4 with a 1 in front of it. The 1 will be our carryover, which will be added to the next multiplication, so to keep just the unit digit we calculate integer % 5 * 2
. If you’re not versed with modulo operations, integer % 5 * 2 + carryover
.
We must store the carry though; that is done in the next block of code, which evaluates if integer > 4
. This is because, for values from 5 to 9, our mudulo will bring us back to the values from 0 to 4, but we need to deal with the carry. We know that the carry can only be 1 at most, so we simply check if integer > 4
: if it is, we have a 1 to carryover and we store it in its variable carryover
.
The final block, from lines 12 to 14, simply adds the last carry possibly left from the last multiplication: for example, if the last number multiplied was an 8, out
will now start with a 6, but we have a 1 stored in carryover
. We must add it to the front of out
to have the correct result.
It’s really basic math, to be honest, but describing it textually could make it worse than it is. So here’s a drawn example of the process:
Now we just need to apply that process 1,000 times to calculate the wall of text corresponding to 2¹⁰⁰⁰! Let’s write the simple code:
In our main
function, we define the final
variable, initially equal to "1"
. Then we loop over for 1000 times to update the result. Now, since the problem wants the sum of the digits of 2¹⁰⁰⁰, we simply create the variable sum
and loop over final
summing up all the digits.
Also, this same algorithm can be used to calculate every exponential of every number: just change the value in the multiply
call or the n
upper limit in the loop, and you’ll get whatever result you want. For example, running
...
for n := 0; n < 500; n++ {
final = multiply(final, 5)
}
...
Will calculate 5⁵⁰⁰.
As in
Have a nice coding, guys! 😎
As always, let’s take a brief moment to discuss the time complexity of this algorithm. The first part of the code runs a number of times equal to the length of the stringedInt
, which, unfortunately, will increase at each loop. Then, we run the multiplier n
times to reach the nth exponent. So, technically speaking, we’ll have a complexity of O[len(stringedInt)*n]
, which we can generalize with some approximation to O(n²).
Here it is: that’s my solution! I hope you enjoyed following along and reading about this problem. If so, please leave a clap or two: that would make my day!
Also, if you are willing and can contribute to the channel, share a Ko-fi.
As always, thank you so much for reading.
Nicola
Also published here.