Are you back or are you new here? If you're back, why'd you even come back? If you're new, you are in for hell. People who are back, you know what's coming. People who are new, you don't know what's coming. But you will. You will. Last time, we discussed "Why Comparison-based Sorting Algorithms have $\Omega(n log n)$ Lower Bound" and this is a follow-up to that. Also, if you haven't read that, go read the previous article first, then come back here and read this. Alright, ready? Let's go.

Today, we will discuss average-case lower bounds for comparison-based sorting algorithms. Now, I don't expect your little brain to remember everything you were spoon-fed last time, so I'll give you a quick recap. As expected, our focus in this article, once again, is comparison-based sorting Algorithms. In our last article, we were able to define a comparison-based sorting algorithm.

Also, we were able to prove that any comparison-based sorting algorithm must take $\Omega(n log n)$ time in the worst case. And, we also defined a theorem for this proof. Do you remember what it was? Of course, you don't. Here's the theorem:

Alright, folks! I know I keep this weblog very personal and there's art flowing all around this website, but let's talk some mathematics today! Specifically, we are here to discuss the notion of lower bounds for sorting algorithms. Now, when I say sorting algorithms, I am talking about comparison-based sorting algorithms. There are other sorting algorithms like counting sort, radix sort, bucket sort, etc. but they are a topic for another day. Now, buckle up for a long text-based post and a vomit load of mathematics, because, by the end of this article, we are going to show that any deterministic comparison-based sorting algorithm must take $\Omega(n \log n)$ time to sort an array of n elements in the worst case.

You started reading this article, and reached this point and wondered, "Wait, we are discussing the notion of lower bounds"? "What is a lower bound"? ... "To think that, what the fuck even is a bound"? Well, if you are pondering over that question, well ponder no more! I promised you a shit-ton of information and a butt-load of theory, so here we go!