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- From: jmount+@CS.CMU.EDU (John Mount)
- Subject: Re: Cryptography and P=NP
- Message-ID: <By2v5F.DCM.2@cs.cmu.edu>
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- Organization: Carnegie Mellon University
- References: <1992Nov15.110945.19939@ringer.cs.utsa.edu> <1992Nov18.193900.20199@rchland.ibm.com> <BxzD1t.3xA.2@cs.cmu.edu> <722273103@pike.cs.duke.edu>
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- Date: Sat, 21 Nov 1992 17:56:03 GMT
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-
- In article <722273103@pike.cs.duke.edu>, srt@duke.cs.duke.edu (Stephen R. Tate) writes:
- >In article <BxzD1t.3xA.2@cs.cmu.edu> sgall+@CS.CMU.EDU (Jiri Sgall) writes:
- >>So if you know that P=NP, you also have a polynomial algorithm for SAT that
- >>either answers NO or gives you an satisfying assignment. You can do the same
- >>for anything in NP.
- >
- >No, this is not true. There are two *different* problems here: knowing
- >that P=NP, and having an algorithm for SAT (or any previously proved
- >NP-complete problem, for that matter). Don't forget the perfectly valid
- >possibility that someone comes up with a non-constructive proof of P=NP ---
- >this would be amazingly frustrating though. Imagine knowing that P=NP, so you
- >know that polynomial time algorithms exist for all problems in NP,
- >but you don't know a polynomial time algorithm for any problem previously
- >shown to be NP-complete! I think that's what the original poster probably
- >meant.
-
- No- you are wrong. Here is, roughly what Jiri was saying.
-
- Assume an enumeration of all Turing machines. Suppose we want to
- solve SAT. Let ALG be the Turing machine that simulates one step of
- machine i every 2^i steps (so it runs machine 1 every other step, 2
- every 4th , 4 every 8th). If a machine being simulated ever halts ALG
- checks if the output on the simulated tape is a satisfying assignment
- for ALG's input formula- if so it halts in the accepting state.
-
- Jiri's claim is that if P=NP then ALG accepts every satisfiable
- formula in time polynomial in the input size (though it will not halt
- on unsatisfiable formulae).
-
- Why is this true? Because if P=NP then by definition is a polynomial
- p and a Turing machine j such that for every SAT formula x, j accepts
- within x in time p(|x|) iff x is satisfiable (|x| = size of x in
- bits). (Even though the proof that P=NP may be nonconstructive and
- not give an algorithm or even the polynomial p.) In fact by the self
- reducibility of problems in NP there must be a machine j' and a
- polynomial p' such that for every SAT formula x, j' always halts
- within time p'(|x|) and leaves a satisfying assignment on it's tape if
- the formula was satisfiable. Then it is not hard to see that ALG
- accepts every satisfiable boolean formula in <= 2^j' p'(|x|) |x|
- simulation steps. (it is sufficient for the machine to run algorithm
- j' for p'(|x|) steps- but it only runs alg j' once every 2^j' steps of
- overall simulation- and may have to check an output from other
- simulated Turing machines every step). Now all this is true even if
- you don't know j,j' or even p or p'! Thus if P=NP the ALG is a Ptime
- acceptor of satisfiable boolean formula- but you won't know why or how
- long it is going to take.
-
- The main weakness is the ALG can not deal with unsatisfiable assignment
- (because you can not tell if it has run too long unless you know both
- j and p).
-
- --
- --- It is kind of strange being in CS theory, given computers really do exist.
- John Mount: jmount+@cs.cmu.edu (412)268-6247
- School of Computer Science, Carnegie Mellon University,
- 5000 Forbes Ave., Pittsburgh PA 15213-3891
-