SearcharxivSearch

arXiv · 2404.11218

Witnessing Flows in Arithmetic

Abstract

One of the elegant achievements in the history of proof theory is the characterization of the provably total recursive functions of an arithmetical theory by its proof-theoretic ordinal as a way to measure the time complexity of the functions. Unfortunately, the machinery is not sufficiently fine-grained to be applicable on the weak theories on the one hand and to capture the bounded functions with bounded definitions of strong theories, on the other. In this paper, we develop such a machinery to address the bounded theorems of both strong and weak theories of arithmetic. In the first part, we provide a refined version of ordinal analysis to capture the feasibly definable and bounded functions that are provably total in $\mathrm{PA}+\bigcup_{\beta \prec \alpha} \mathrm{TI}(\prec_{\beta})$, the extension of Peano arithmetic by transfinite induction up to the ordinals below $\alpha$. Roughly speaking, we identify the functions as the ones that are computable by a sequence of $\mathrm{PV}$-provable polynomial time modifications on an initial polynomial time value, where the computational steps are indexed by the ordinals below $\alpha$, decreasing by the modifications. In the second part, and choosing $l \leq k$, we use similar technique to capture the functions with bounded definitions in the theory $T^k_2$ (resp. $S^k_2$) as the functions computable by exponentially (resp. polynomially) long sequence of $\mathrm{PV}_{k-l+1}$-provable reductions between $l$-turn games starting with an explicit $\mathrm{PV}_{k-l+1}$-provable winning strategy for the first game.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Amirhossein Akbar Tabatabai. 2024-04-17. Witnessing Flows in Arithmetic. https://doi.org/10.1017/s0960129524000185

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

There is no maximal $K$-degree

The Kolmogorov complexity of a string characterize how complex it is to describe the string. If every prefix of a real $x$ is more complex to describe than every prefix (of the same length) of real $y$, then it is seen as $x$ is more complex to describe than $y$. It is wondered if there is a real $x$ so that no other reals are strictly more complex (to describe) than $x$. The behavior of Kolmogorov complexity functions generated by reals (namely $n\mapsto$ the minimal description length of the real) is quite chaos. Therefore, it is widely believed that there are many reals that are maximally complex to describe. For instance, it is conjectured that all random enough reals have maximal $K$-degree. In this paper, it is shown that there is no real with maximal $K$-degree. Actually, for almost all real $x$, we can uniformly computably find another real whose $K$-degree is strictly above $x$.

math.LO

Quadruples and cubes

We prove, in $\mathsf{ZFC}$, that the $\lambda$-terraced cube relation fails whenever $\lambda$ is an uncountable cardinal. The corresponding terraced relation for quadruples fails for every $\lambda$. If $\lambda$ is $\aleph_0$ then the pretinent terraced relation has consistency strength of at least one Woodin cardinal. We prove positive polarized relations at a successor and a double successor from wondrous ideals. We show, however, that there are no such ideals over two consecutive cardinals simultaneously.

math.LO

Possibilistic Logic over a Logic of Formal Inconsistency

In this article, we have introduced a new possibilistic logic on a logic of formal inconsistency with the aim of developing a possibility theoretic framework to deal with uncertainty and inconsistency meaningfully without leading to a system collapse. We have discussed the syntax and semantics for this logic and have proved the soundness and completeness theorems. A set of new measures of consistency, contradictoriness, and triviality of a set of formulas have been defined. These have then been put to use in an example to show that this framework can provide better means of machine reasoning.

math.LO