Nicola Galesi, Joshua A. Grochow, T. Pitassi, Adrian She
{"title":"On the algebraic proof complexity of Tensor Isomorphism","authors":"Nicola Galesi, Joshua A. Grochow, T. Pitassi, Adrian She","doi":"10.48550/arXiv.2305.19320","DOIUrl":null,"url":null,"abstract":"The Tensor Isomorphism problem (TI) has recently emerged as having connections to multiple areas of research within complexity and beyond, but the current best upper bound is essentially the brute force algorithm. Being an algebraic problem, TI (or rather, proving that two tensors are non-isomorphic) lends itself very naturally to algebraic and semi-algebraic proof systems, such as the Polynomial Calculus (PC) and Sum of Squares (SoS). For its combinatorial cousin Graph Isomorphism, essentially optimal lower bounds are known for approaches based on PC and SoS (Berkholz&Grohe, SODA '17). Our main results are an $\\Omega(n)$ lower bound on PC degree or SoS degree for Tensor Isomorphism, and a nontrivial upper bound for testing isomorphism of tensors of bounded rank. We also show that PC cannot perform basic linear algebra in sub-linear degree, such as comparing the rank of two matrices, or deriving $BA=I$ from $AB=I$. As linear algebra is a key tool for understanding tensors, we introduce a strictly stronger proof system, PC+Inv, which allows as derivation rules all substitution instances of the implication $AB=I \\rightarrow BA=I$. We conjecture that even PC+Inv cannot solve TI in polynomial time either, but leave open getting lower bounds on PC+Inv for any system of equations, let alone those for TI. We also highlight many other open questions about proof complexity approaches to TI.","PeriodicalId":246506,"journal":{"name":"Cybersecurity and Cyberforensics Conference","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cybersecurity and Cyberforensics Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48550/arXiv.2305.19320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
The Tensor Isomorphism problem (TI) has recently emerged as having connections to multiple areas of research within complexity and beyond, but the current best upper bound is essentially the brute force algorithm. Being an algebraic problem, TI (or rather, proving that two tensors are non-isomorphic) lends itself very naturally to algebraic and semi-algebraic proof systems, such as the Polynomial Calculus (PC) and Sum of Squares (SoS). For its combinatorial cousin Graph Isomorphism, essentially optimal lower bounds are known for approaches based on PC and SoS (Berkholz&Grohe, SODA '17). Our main results are an $\Omega(n)$ lower bound on PC degree or SoS degree for Tensor Isomorphism, and a nontrivial upper bound for testing isomorphism of tensors of bounded rank. We also show that PC cannot perform basic linear algebra in sub-linear degree, such as comparing the rank of two matrices, or deriving $BA=I$ from $AB=I$. As linear algebra is a key tool for understanding tensors, we introduce a strictly stronger proof system, PC+Inv, which allows as derivation rules all substitution instances of the implication $AB=I \rightarrow BA=I$. We conjecture that even PC+Inv cannot solve TI in polynomial time either, but leave open getting lower bounds on PC+Inv for any system of equations, let alone those for TI. We also highlight many other open questions about proof complexity approaches to TI.
张量同构问题(TI)最近出现了,它与复杂性内外的多个研究领域有联系,但目前最好的上限本质上是蛮力算法。作为一个代数问题,TI(或者更确切地说,证明两个张量是非同构的)非常自然地适用于代数和半代数证明系统,例如多项式微积分(PC)和平方和(so)。对于其组合表兄弟图同构,本质上最优下界是基于PC和so的方法(Berkholz&Grohe, SODA '17)。我们的主要结果是张量同构的PC度或SoS度的$\Omega(n)$下界,以及检验有界秩张量同构的非平凡上界。我们还表明,PC不能在亚线性度上执行基本线性代数,例如比较两个矩阵的秩,或从$AB=I$推导$BA=I$。由于线性代数是理解张量的关键工具,我们引入了一个严格更强的证明系统,PC+Inv,它允许作为推导规则的所有代换实例的含义$AB=I \rightarrow BA=I$。我们推测即使PC+Inv也不能在多项式时间内解出TI,但对于任何方程组,PC+Inv的下界都是开放的,更不用说TI的下界了。我们还强调了关于TI证明复杂性方法的许多其他开放问题。