Executable Multivariate Polynomials. We define multivariate polynomials over arbitrary (ordered) semirings in combination with (executable) operations like addition, multiplication, and substitution. We also define (weak) monotonicity of polynomials and comparison of polynomials where we provide standard estimations like absolute positiveness or the more recent approach of Neurauter, Zankl, and Middeldorp. Moreover, it is proven that strongly normalizing (monotone) orders can be lifted to strongly normalizing (monotone) orders over polynomials. Our formalization was performed as part of the IsaFoR/CeTA-system which contains several termination techniques. The provided theories have been essential to formalize polynomial interpretations. This formalization also contains an abstract representation as coefficient functions with finite support and a type of power-products. If this type is ordered by a linear (term) ordering, various additional notions, such as leading power-product, leading coefficient etc., are introduced as well. Furthermore, a lot of generic properties of, and functions on, multivariate polynomials are formalized, including the substitution and evaluation homomorphisms, embeddings of polynomial rings into larger rings (i.e. with one additional indeterminate), homogenization and dehomogenization of polynomials, and the canonical isomorphism between R[X,Y] and R[X][Y].
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References in zbMATH (referenced in 4 articles )
Showing results 1 to 4 of 4.
- Bentkamp, Alexander; Blanchette, Jasmin Christian; Klakow, Dietrich: A formal proof of the expressiveness of deep learning (2019)
- Maletzky, Alexander: Formalization of Dubé’s degree bounds for Gröbner bases in Isabelle/HOL (2019)
- Maletzky, Alexander; Immler, Fabian: Gröbner bases of modules and Faugère’s (F_4) algorithm in Isabelle/HOL (2018)
- Bentkamp, Alexander; Blanchette, Jasmin Christian; Klakow, Dietrich: A formal proof of the expressiveness of deep learning (2017)