On the complexity of computing Gröbner bases for weighted homogeneous systems

الأصل · EN

Solving polynomial systems arising from applications is frequently made easier by the structure of the systems. Weighted homogeneity (or quasi-homogeneity) is one example of such a structure: given a system of weights W=(w_1,,w_n), W-homogeneous polynomials are polynomials which are homogeneous w.r.t the weighted degree °_W(X_1α_1,,X_nα_n) = ∑ w_iα_i. Gröbner bases for weighted homogeneous systems can be computed by adapting existing algorithms for homogeneous systems to the weighted homogeneous case. We show that in this case, the complexity estimate for Algorithm 5 (n+-1ω) can be divided by a factor (∏ w_i)ω. For zero-dimensional systems, the complexity of Algorithm nDω (where D is the number of solutions of the system) can be divided by the same factor (∏ w_i)ω. Under genericity assumptions, for zero-dimensional weighted homogeneous systems of W-degree (d_1,,d_n), these complexity estimates are polynomial in the weighted Bézout bound ∏_i=1ⁿd_i / ∏_i=1ⁿw_i. Furthermore, the maximum degree reached in a run of Algorithm 5 is bounded by the weighted Macaulay bound ∑ (d_i-w_i) + w_n, and this bound is sharp if we can order the weights so that w_n=1. For overdetermined semi-regular systems, estimates from the homogeneous case can be adapted to the weighted case. We provide some experimental results based on systems arising from a cryptography problem and from polynomial inversion problems. They show that taking advantage of the weighted homogeneous structure yields substantial speed-ups, and allows us to solve systems which were otherwise out of reach.