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arXiv 2109.04438math.LO
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Keisler 定理与基数不变量

Keisler's Theorem and Cardinal Invariants

Nagoya University(名古屋大学)

Tatsuya Goto

AI总结:

本文研究了Keisler定理的不同变体及其与基数不变量的关系,证明了在特定条件下该定理的成立与某些基数的等价性有关。

摘要:

我们考虑了Keisler定理的几个变体。通过展示它们之间的蕴含关系以及基数不变量假设,我们将这些变体区分开来。我们通过CH和cov(meager)=c ∧ 2< c=c分别表征比Keisler定理在大小为ℵ₁和ℵ₀的模型中更强的饱和假设。我们证明Keisler定理对于大小为ℵ₁和ℵ₀的模型分别蕴含b=ℵ₁和cov(null)≤d。作为结果,Keisler定理对于大小为ℵ₀的模型在随机模型中失效。我们还表明,对于Keisler定理在大小为ℵ₁的模型中成立,不必要求cov(meager)等于c。

英文摘要:

We consider several variants of Keisler's isomorphism theorem. We separate these variants by showing implications between them and cardinal invariants hypotheses. We characterize saturation hypotheses that are stronger than Keisler's theorem with respect to models of size $\aleph_1$ and $\aleph_0$ by $\mathrm{CH}$ and $\operatorname{cov}(\mathsf{meager}) = \mathfrak{c} \land 2^{<\mathfrak{c}} = \mathfrak{c}$ respectively. We prove that Keisler's theorem for models of size $\aleph_1$ and $\aleph_0$ implies $\mathfrak{b} = \aleph_1$ and $\operatorname{cov}(\mathsf{null}) \le \mathfrak{d}$ respectively. As a consequence, Keisler's theorem for models of size $\aleph_0$ fails in the random model. We also show that for Keisler's theorem for models of size $\aleph_1$ to hold it is not necessary that $\operatorname{cov}(\mathsf{meager})$ equals $\mathfrak{c}$.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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