Why should I bother?
This chapter gives an introduction to complexity theory.
We'll cover the following
In the previous sections, we studied problems which didn't require brute force search to find solutions. However, there are problems whose solutions can't be found without examining the entire possible search space. Take the case of prime factorization, for example. Below are the prime factors for 21:
It is easy to verify the solution; we just multiply 7 and 3, and check if the product equals 21. However, when we want to do the reverse, i.e. find the prime factors for 21, we need to go through trial division starting from 1, till we finally find the prime factors.
For smaller numbers like 21 a brute force algorithm would finish in reasonable time, but what about really large numbers like the one below?
A brute force algorithm would not be able to come up with prime factors for the above number in a reasonable amount of time, especially with today’s computer technology. You may wonder why this matters or is even important. Well, enter cryptography! Encryption algorithms make use of the fact that it is easy to multiply two very large prime numbers, but un-assembling the resulting product back into its constituent prime numbers isn’t easy. If an easy solution was found for prime factorization, then a lot of the heavily relied upon encryption algorithms used in the industry would fall apart.
The consequences aren't just limited to cryptography. Thus far, even while using existing algorithm design techniques, humans have been unable to find efficient solutions to many problems. If efficient solutions to these problems were found, it would result in major advancements in fields as far apart as medical science and AI.
Complexity theorists define various classes of complexity depending on how hard a problem is to solve. We'll briefly describe the important classes in the upcoming sections. However, before we embark upon our study of complexity classes, we'll discuss decision problems which help us in defining some of the complexity classes.
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