As you have undoubtedly heard by now, there is a paper that claims to prove P!=NP, and there is a serious effort to understand the proof.
It has been fun to watch the experts set to work on this, and it has brought a lot of attention to random k-SAT, a problem that was near and dear to me when I was a grad student. And I get to learn interesting things from them without having to struggle through Deolalikar’s opus myself.
One interesting thing is the way Scott Aaronson reacted, saying:
If Vinay Deolalikar is awarded the $1,000,000 Clay Millennium Prize for his proof of P≠NP, then I, Scott Aaronson, will personally supplement his prize by the amount of $200,000.
When I first read about Aaronson’s offer to add $200K to the prize money, reported 2nd hand in a roundup of what the #pnp blogs were saying, it came off like the young professor is really hoping to have people work on this thing. But once my trusty rss feeder fed me his post, I realized his offer is not about how profs at private universities have disposable income that public schools don’t provide. It’s his way of quantifing his confidence in the accuracy of the proof.
If Aaronson had framed this in terms of a bet, it would be a textbook example of his level of certainty that the proof will have a flaw (a textbook in decision theory, anyway). But offering the sum without any possibility of receiving a return in the alternative scenario breaks expected utility theory. How certain is Scott? It all depends on what amount of money means nothing to him.
Filed under probability, TCS
There was a lot of buzz this weekend about a paper claiming to resolve the “P vs NP” conjecture. I’ve seen plenty of papers claiming to do this over the years, so I didn’t rush to track it down. But as the tweeting continued, I decided to have a quick look for myself, if only to produce a crotchety blog post on the matter.
Part of the drama around this paper comes from the way it appeared. Author Vinay Deolalikar‘s web page explains:
Manuscript sent on 6th August to several leading researchers in various areas. Confirmations began arriving 8th August early morning. The preliminary version made it to the web without my knowledge. I have made minor updates, here. Please note that the final version of the paper is under preparation, and is to be posted here very shortly.
I’m a global health researcher now, so I’m not going to be the one who tries to verify this 104 page paper, but I would love to learn from a careful review that it is true. The result seems to go further than separating P and NP, since it is a statement about a natural distribution of instances being hard (from p. 78):
If LFP were able to compute solutions to the d1RSB phase of random k-SAT, then the distribution of the entire space of solutions would have a substantially simpler parametrization than we know it does.
Ryan Williams thinks this is suspicious, and expressed his concern in a series of tweets:
- This P vs NP claim is getting tons of press. I am really doubtful that it works. Hard to convey my skepticism in a tweet, but here goes…
- The author tries to use the fact that for certain distributions of random k-SAT, the solution space has a “hard structure”. Two problems:
(1) Polytime solvable problems (such as perfect matching on random graphs) can also have complicated solution distributions.
(2) There is a randomized reduction from SAT to formulas with at most ONE satisfying assignment (Valiant-Vazirani). A simple solution space
So either Valiant-Vazirani can’t be derandomized or RP=NP (seems very unlikely!) or the proof must break. That’s my intuition.
Time will tell. I find proof of the existence of hard-on-average distributions much more exciting than plain old P vs NP, and Deolalikar’s paper might have something for everybody.