Ajith G Nayak ajithor

## PvsNP.txt
Before addressing the big questions, we'll get into what it is based on, so everyone can justify the address.
So let us just look at the world for an instance. The world is filled with questions.

Now, consider a class of problems, that computers can easily solve, call it 'P'. But 'easy' is not an appreciably quantifiable metric. That's when the study of Algorithmic complexities comes in. We can use the big-Oh 'O' notation to quantify 'easy'.
Redifining P, it is the class of algorithms(solutions of a problem) which can be solved in polynomial time.
or P = { solvable problem in polynomial time } (O being quite generous, like O(n^10000) os so)
eg: finding product of 2 numbers, finding gcd, etc. the essence being, that it is just simpler to work the algorithm.

Now, consider a set of problems, whose solution has vast parametric dependability, ergo cannot be solved easily. Which means the complexity of the algorithms is so high, that computers might take ages, arriving at optimal solutions.
Although, provided the
	Before addressing the big questions, we'll get into what it is based on, so everyone can justify the address.
	So let us just look at the world for an instance. The world is filled with questions.

	Now, consider a class of problems, that computers can easily solve, call it 'P'. But 'easy' is not an appreciably quantifiable metric. That's when the study of Algorithmic complexities comes in. We can use the big-Oh 'O' notation to quantify 'easy'.
	Redifining P, it is the class of algorithms(solutions of a problem) which can be solved in polynomial time.
	or P = { solvable problem in polynomial time } (O being quite generous, like O(n^10000) os so)
	eg: finding product of 2 numbers, finding gcd, etc. the essence being, that it is just simpler to work the algorithm.

	Now, consider a set of problems, whose solution has vast parametric dependability, ergo cannot be solved easily. Which means the complexity of the algorithms is so high, that computers might take ages, arriving at optimal solutions.
	Although, provided the