Polynomial Time Code For 3-SAT Released, P==NP

An anonymous reader writes "Vladimir Romanov has released what he claims is a polynomial-time algorithm for solving 3-SAT. Because 3-SAT is NP-complete, this would imply that P==NP. While there's still good reason to be skeptical that this is, in fact, true, he's made source code available and appears decidedly more serious than most of the people attempting to prove that P==NP or P!=NP. Even though this is probably wrong, just based on the sheer number of prior failures, it seems more likely to lead to new discoveries than most. Note that there are already algorithms to solve 3-SAT, including one that runs in time (4/3)^n and succeeds with high probability. Incidentally, this wouldn't necessarily imply that encryption is worthless: it may still be too slow to be practical."

Comments

Re:I'll be first to say WTF

[deapbluesea]

Absolutely untrue. All experts in the field that I've spoken to think that P is probably not equal to NP, but that a proof either way is going to be very hard.

Absolutely correct. The difference between say, computer science and sociology, is that computer scientists require absolute proofs. In other words, if you claim that P==NP, as this paper does, then I require you to show that it is so for all possible inputs.

The paper, in fact, does not show such a thing. To the contrary, it fails to show a sound and complete reduction of 3-SAT to hyperstructures, or CTF or CTS or whatever other acronyms were made up by the author. I'm not saying that he's wrong, simply that this is not a proof - it is only a claim. The author claims to have "proven" his algorithm is polynomial time by giving it a smattering of inputs and noting that the time the algorithm took to complete increased by a polynomial factor of the input size.

Clearly the author has not studied his algorithmic complexity texts well enough to understand the definition of Big-O. Big-O only claims that algorithmic growth is asymptotic to a given curve as the input size goes to infinity from some value n0. In other words, many algorithms may display linear growth to a point, and then become exponential after input size greater than n0. A statistical analysis will not prove anything. The author needs to do a full algorithmic analysis instead.

I predict this paper will be rapidly debunked and we will still not know if P==NP.