English

Degrees of Second and Higher-Order Polynomials

Logic in Computer Science 2023-05-23 v2 Computational Complexity Logic

Abstract

Second-order polynomials generalize classical first-order ones in allowing for additional variables that range over functions rather than values. We are motivated by their applications in higher-order computational complexity theory, extending for example classical classes like P or PSPACE to operators in Analysis [doi:10.1137/S0097539794263452, doi:10.1145/2189778.2189780]. The degree subclassifies ordinary polynomial growth into linear, quadratic, cubic etc. In order to similarly classify second-order polynomials, define their degree to be an 'arctic' first-order polynomial (namely a term/expression over variable DD and operations ++ and \cdot and max\max). This degree turns out to transform as nicely under (now two kinds of) polynomial composition as the ordinary one. We also establish a normal form and semantic uniqueness for second-order polynomials. Then we define the degree of a third-order polynomial to be an arctic second-order polynomial, and establish its transformation under three kinds of composition.

Keywords

Cite

@article{arxiv.2305.03439,
  title  = {Degrees of Second and Higher-Order Polynomials},
  author = {Donghyun Lim and Martin Ziegler},
  journal= {arXiv preprint arXiv:2305.03439},
  year   = {2023}
}
R2 v1 2026-06-28T10:26:44.770Z