Slide 46
With fixed m, the algorith checks if
If it is, the algorith calculates
Input: f of degree n; prime p; natural k; h such that lc(h)=1 and
, also h(mod p)is irreducible and f(mod p) is not divided by ;
natural such that
Slide 47
Auxiliary algorith
With fixed m, the algorith checks if
If it is, the algorith calculates
Input: f of degree n; prime p; natural k; h such that lc(h)=1 and
, also h(mod p)is irreducible and f(mod p) is not divided by ;
natural such that
Work: For the lattice with basis
find reduced basis
If then and the algorith stops
Otherwise, and
Slide 48
Calculation of .
l=deg h < deg f=n.
Work:
Calculate the least k for which is held with m=n-1.
For the factorization calculate its Hensel lifting
,
Let u be the greatest integer:
Run the auxiliary algorith for
until we get
And if we don’t get it, deg > n-1 and is equal to f.
Slide 49
The reductions and simplifications, which were used in the case of univariate polynomials, are not proper when dealing with multivariate ones.
Performing this type of square free decomposition before factoring F leads to exponential intermediate expression swell.
Slide 50
Multivariate factorization: idea
The basic approach used to factor multivariate polynomials is much the same as the exponential time algorith for u.p.
Rouphly speaking, we reduce the problem of factoring a polynomial of n variables to the case of polynomial of n-1 variables, pointing at one (or two) variables at the end.
Slide 51
Let be an irreducible polynomial over Q and let R(N) denote the number of n-tuples over Z with |xi|<N such that is reducible. Then
, where c depends only on the degree of F.
Slide 52
Hilbert theorem: disadvantages
There is no upper bound on the number of random points needed.
The approach can not be applied when working over finite field.
Slide 53
Let be an irreducible polynomial of R[Z], where
and is an intergal domain. Let the degree of in be d,