Assuming sufficiently many terms of a n-dimensional table defined over a field are given, we aim at guessing the linear recurrence relations with either constant or polynomial coefficients they satisfy. In many applications, the table terms come along with a structure: for instance, they may be zero outside of a cone, they may be built from a Gr{\"o}bner basis of an ideal invariant under the action of a finite group. Thus, we show how to take advantage of this structure to both reduce the number of table queries and the number of operations in the base field to recover the ideal of relations of the table. In applications like in combinatorics, where all these zero terms make us guess many fake relations, this allows us to drastically reduce these wrong guesses. These algorithms have been implemented and, experimentally, they let us handle examples that we could not manage otherwise. Furthermore, we show which kind of cone and lattice structures are preserved by skew polynomial multiplication. This allows us to speed up the guessing of linear recurrence relations with polynomial coefficients by computing sparse Gr{\"o}bner bases or Gr{\"o}bner bases of an ideal invariant under the action of a finite group in a ring of skew polynomials.
翻译:假设一个字段定义的正维表的足够多的参数, 我们的目标是猜测与它们所满足的常数或多元系数的线性重复关系。 在许多应用中, 表格术语与一个结构相伴: 例如, 它们可能在锥体之外为零, 可以在一个有限组的行动下, 以理想的不变化状态为基础 建立 。 因此, 我们展示了如何利用这个结构来减少表格查询的数量和基场操作的数量, 以恢复表格关系的理想。 在组合学等应用中, 所有这些零术语都让我们猜测了许多假关系, 这使得我们能够大量减少这些错误的猜想。 这些算法已经实施, 并且实验性地, 它们让我们处理一些我们无法以其他方式管理的例子。 此外, 我们展示了哪种锥体和粘结结构由 skew 多元倍增益倍的倍增倍增倍增。 这使我们能够通过在恒定的基数基底数基底点中计算 微硬度的硬度, 以恒度为基点的基点, 来加速猜测与多诺系数的线性重复关系。