Stefan Dantchev, Nicola Galesi, Abdul Ghani, Barnaby Martin
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For the unary encoding of the Pigeonhole Principle and the Ordering Principle, it is known that linear rank is required for refutations in SA, although both admit refutations of polynomial size. We prove that the binary encoding of the (weak) Pigeonhole Principle [math] requires exponentially sized (in [math]) SA refutations, whereas the binary encoding of the Ordering Principle admits logarithmic rank, polynomially sized SA refutations. We continue by considering a natural refutation system we call “SA+Squares,” which is intermediate between SA and Lasserre (Sum-of-Squares). This has been studied under the name static-[math] by Grigoriev et al. In this system, the unary encoding of the Linear Ordering Principle [math] requires [math] rank while the unary encoding of the Pigeonhole Principle becomes constant rank. Since Potechin has shown that the rank of [math] in Lasserre is [math], we uncover an almost quadratic separation between SA+Squares and Lasserre in terms of rank. 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We contrast this proof complexity with the normal unary encoding in several refutation systems, based on Resolution and Sherali–Adams. We first consider [math], which is an extension of Resolution working on [math]-DNFs (Disjunctive Normal Form formulas). We prove an exponential lower bound of [math] for the size of refutations of the binary version of the [math]-Clique Principle in [math], where [math] and [math] is a doubly exponential function. Our result improves that of Lauria et al., who proved a similar lower bound for [math], i.e., Resolution. For the [math]-Clique and other principles we study, we show how lower bounds in Resolution for the unary version follow from lower bounds in [math] for the binary version, so we start a systematic study of the complexity of proofs in Resolution-based systems for families of contradictions given in the binary encoding. We go on to consider the binary version of the (weak) Pigeonhole Principle [math]. 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引用次数: 0
摘要
SIAM 计算期刊》,第 53 卷第 3 期,第 764-802 页,2024 年 6 月。 摘要。我们根据某些组合原理的不寻常二进制编码来考虑证明复杂性。我们将这种证明复杂性与基于解析(Resolution)和谢拉利-亚当斯(Sherali-Adams)的几个驳斥系统中的正常一元编码进行对比。我们首先考虑[math],它是在[math]-DNFs(Disjunctive Normal Form form 公式)上运行的 Resolution 的扩展。我们证明了[math]中二元版[math]-Clique 原则的反驳大小的指数下限,其中[math]和[math]是双指数函数。我们的结果改进了劳里亚等人的结果,他们证明了[math]的类似下界,即分辨率。对于我们研究的[math]-Clique 和其他原理,我们展示了一元版本的解析下界是如何与二元版本的[math]下界相一致的,因此我们开始系统地研究基于解析的系统对二元编码给出的矛盾族进行证明的复杂性。我们接着考虑二进制版本的(弱)鸽洞原理[math]。我们证明,对于任何 [math],[math] 都需要在 [math] 中对 [math] 进行大小为 [math] 的反驳。我们的下界无法用同样的方法大幅提高,因为对于[math],我们可以证明在[math]中存在[math]大小的[math]反驳。这是布斯和皮塔西的一元弱鸽子洞原理的同一上界的结果。我们对比了谢拉利-亚当斯(Sherali-Adams,SA)反驳系统中的一元编码和二元编码,证明了秩和大小的下界。对于鸽子洞原理和排序原理的一元编码,众所周知,SA 中的驳斥需要线性秩,尽管两者都允许多项式大小的驳斥。我们证明,(弱)鸽洞原理[math]的二进制编码需要指数大小(在[math]中)的 SA 反驳,而排序原理的二进制编码允许对数等级、多项式大小的 SA 反驳。我们将继续考虑一种我们称之为 "SA+Squares "的自然驳斥系统,它介于 SA 和 Lasserre(Sum-of-Squares)之间。在这个系统中,线性排序原理[math]的一元编码需要[math]秩,而鸽子洞原理的一元编码则需要恒定秩。由于波钦(Potechin)已经证明拉塞尔方程中[math]的秩为[math],因此我们发现 SA+Squares 与拉塞尔方程在秩方面几乎存在二次分隔。格里戈里耶夫等人指出,一元鸽洞原理在 SA+Squares 中的秩为 2,因此大小为多项式。由于我们证明二元[math]也是如此,因此我们推导出 SA 和 SA+Squares 的大小呈指数级分离。
Proof Complexity and the Binary Encoding of Combinatorial Principles
SIAM Journal on Computing, Volume 53, Issue 3, Page 764-802, June 2024. Abstract. We consider proof complexity in light of the unusual binary encoding of certain combinatorial principles. We contrast this proof complexity with the normal unary encoding in several refutation systems, based on Resolution and Sherali–Adams. We first consider [math], which is an extension of Resolution working on [math]-DNFs (Disjunctive Normal Form formulas). We prove an exponential lower bound of [math] for the size of refutations of the binary version of the [math]-Clique Principle in [math], where [math] and [math] is a doubly exponential function. Our result improves that of Lauria et al., who proved a similar lower bound for [math], i.e., Resolution. For the [math]-Clique and other principles we study, we show how lower bounds in Resolution for the unary version follow from lower bounds in [math] for the binary version, so we start a systematic study of the complexity of proofs in Resolution-based systems for families of contradictions given in the binary encoding. We go on to consider the binary version of the (weak) Pigeonhole Principle [math]. We prove that for any [math], [math] requires refutations of size [math] in [math] for [math]. Our lower bound cannot be improved substantially with the same method since for [math] we can prove there are [math] size refutations of [math] in [math]. This is a consequence of the same upper bound for the unary weak Pigeonhole Principle of Buss and Pitassi. We contrast unary versus binary encoding in the Sherali–Adams (SA) refutation system where we prove lower bounds for both rank and size. For the unary encoding of the Pigeonhole Principle and the Ordering Principle, it is known that linear rank is required for refutations in SA, although both admit refutations of polynomial size. We prove that the binary encoding of the (weak) Pigeonhole Principle [math] requires exponentially sized (in [math]) SA refutations, whereas the binary encoding of the Ordering Principle admits logarithmic rank, polynomially sized SA refutations. We continue by considering a natural refutation system we call “SA+Squares,” which is intermediate between SA and Lasserre (Sum-of-Squares). This has been studied under the name static-[math] by Grigoriev et al. In this system, the unary encoding of the Linear Ordering Principle [math] requires [math] rank while the unary encoding of the Pigeonhole Principle becomes constant rank. Since Potechin has shown that the rank of [math] in Lasserre is [math], we uncover an almost quadratic separation between SA+Squares and Lasserre in terms of rank. Grigoriev et al. noted that the unary Pigeonhole Principle has rank 2 in SA+Squares and therefore polynomial size. Since we show the same applies to the binary [math], we deduce an exponential separation for size between SA and SA+Squares.
期刊介绍:
The SIAM Journal on Computing aims to provide coverage of the most significant work going on in the mathematical and formal aspects of computer science and nonnumerical computing. Submissions must be clearly written and make a significant technical contribution. Topics include but are not limited to analysis and design of algorithms, algorithmic game theory, data structures, computational complexity, computational algebra, computational aspects of combinatorics and graph theory, computational biology, computational geometry, computational robotics, the mathematical aspects of programming languages, artificial intelligence, computational learning, databases, information retrieval, cryptography, networks, distributed computing, parallel algorithms, and computer architecture.