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I think what is being suggested here is that instead of creating all possible pairs of numbers (x,y) from the digits of a number p and testing if x*y == p, it is more efficient to factor the number p first and and then test all possible factorizations to see if they are just a permuation of the digits of p.

Finidng a quadratic residue x^2=y^2 (mod p) is useful, because then x^2 - y^2 = (x+y)*(x-y) = 0 (mod p) and so (x+y) or (x-y) may be factors of p.

In practice, one starts with an x that has the smallest square larger than p, then computes x^2-p to see if it is a perfect square. If not, increment x and repeat.

This is pretty fast relative to testing by division from 2 to sqrt(p), but there exist even faster methods based on the quadratic residue. The Quadratic Sieve, invented by Pomerance in 1981 is a direct derivative and the Number Field Sieve is a related method.

Getting back to Vampire numbers, what are the relative efficiencies for a number p with 2d digits? For the first method, a naive approach generates all permutations of 2*d digits and splits each into two d-digit numbers to test. Thus each 2d digit number requires about (2*d)! == (2*log(p))! tests, or (2*log p)^(2*log p) by Stirling's approximation. For the second method, a quadratic sieve has running time of order exp(sqrt(log(p)*log(log(p)))) to find a single factor of p. So finding a single factor using QS is more efficient that testing all factors using the first method. But I don't know the running time for finding all the factors using the QS and I don't know the typical multiplier for the scaling result of the QS method.

Anyone?

-Mark

In reply to Re: Factors by kvale
in thread Vampire Numbers by YuckFoo

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