DeepAI AI Chat
Log In Sign Up

An effective method for computing Grothendieck point residue mappings

by   Shinichi Tajima, et al.

Grothendieck point residue is considered in the context of computational complex analysis. A new effective method is proposed for computing Grothendieck point residues mappings and residues. Basic ideas of our approach are the use of Grothendieck local duality and a transformation law for local cohomology classes. A new tool is devised for efficiency to solve the extended ideal membership problems in local rings. The resulting algorithms are described with an example to illustrate them. An extension of the proposed method to parametric cases is also discussed as an application.


page 1

page 2

page 3

page 4


Two-to-one mappings and involutions without fixed points over _2^n

In this paper, two-to-one mappings and involutions without any fixed poi...

Testing zero-dimensionality of varieties at a point

Effective methods are introduced for testing zero-dimensionality of vari...

Linear Algebra and Duality of Neural Networks

Natural for Neural networks bases, mappings, projections and metrics are...

Millions of 5-State n^3 Sequence Generators via Local Mappings

In this paper, we come back on the notion of local simulation allowing t...

Topology-induced Enhancement of Mappings

In this paper we propose a new method to enhance a mapping μ(·) of a par...

Rao distances and Conformal Mapping

In this article, we have described the Rao distance (due to C.R. Rao) an...

Methods for computing b-functions associated with μ-constant deformations – Case of inner modality 2 –

New methods for computing parametric local b-functions are introduced fo...