\(\mathcal {L}\)-reduction computation revisited

IF 0.4 4区 计算机科学 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Acta Informatica Pub Date : 2022-03-24 DOI:10.1007/s00236-022-00418-0
Kaoru Fujioka, Fumiya Okubo, Takashi Yokomori
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Abstract

Let K and L be two languages over \(\Sigma \) and \(\Gamma \) (with \(\Gamma \subset \Sigma \)), respectively. Then, the L-reduction of K, denoted by \(K\%\,L\), is defined by \(\{ u_0u_1\cdots u_n \in (\Sigma - \Gamma )^* \mid u_0v_1u_1 \cdots v_nu_n \in K, \ v_i \in L \ (1\le i \le n) \}\). This is extended to language classes as follows: \({\mathcal {K}}\% {\mathcal {L}}=\{K\%L \mid K \in {\mathcal {K}}, \, L \in {\mathcal {L}} \}\). In this paper, we investigate the computing powers of \(\mathcal {K}\%\,\mathcal {L}\) in which \(\mathcal {K}\) ranges among various classes of \(\mathcal {INS}^i_{\!\!j}\) and min-\(\mathcal {LIN}\), while \(\mathcal {L}\) is taken as \(\mathcal {DYCK}\) and \(\mathcal {F}\), where \(\mathcal {INS}^i_{\!\!j}\): the class of insertion languages of weight (ji), min-\(\mathcal {LIN}\): the class of minimal linear languages, \(\mathcal {DYCK}\): the class of Dyck languages, and \(\mathcal {F}\): the class of finite languages. The obtained results include:

  • \(\mathcal {INS}^1_1\,\%\,\mathcal {DYCK}=\mathcal {RE}\)

  • \(\mathcal {INS}^0_i\,\%\,\mathcal {F}= \mathcal {INS}^1_j\,\%\,\mathcal {F}=\mathcal {CF}\) (for \(i\ge 3\) and \(j\ge 1\))

  • \(\mathcal {INS}^0_2\,\%\,\mathcal {DYCK}=\mathcal {INS}^0_2\)

  • min-\(\mathcal {LIN}\,\%\,\mathcal {F}_1=\mathcal {LIN}\)

where \(\mathcal {RE}\), \(\mathcal {CF}\), \(\mathcal {LIN}\), \(\mathcal {F}_1\) are classes of recursively enumerable, of context-free, of linear languages, and of singleton languages over unary alphabet, respectively. Further, we provide a very simple alternative proof for the known result min-\(\mathcal {LIN}\,\%\,\mathcal {DYCK}_2=\mathcal {RE}\). We also show that with a certain condition, for the class of context-sensitive languages \(\mathcal {CS}\), there exists no \(\mathcal {K}\) such that \(\mathcal {K}\%\,\mathcal {DYCK}=\mathcal {CS}\), which is in marked contrast to the characterization results mentioned above for other classes in Chomsky hierarchy. It should be remarked from the viewpoint of molecular computing theory that the notion of L-reduction is naturally motivated by a molecular biological functioning well-known as RNA splicing occurring in most eukaryotic genes.

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\重新讨论(\mathcal{L}\)-归约计算
设K和L分别是在\(\ Sigma \)和\(\ Gamma \)上的两种语言(带有\(\伽玛\子集\西格玛\))。然后,用\(K\%\,L\)表示的K的L-归约由\(\{u_0u1\cdots u_n\ in(\ Sigma-\Gamma)^*\ mid u_0v_1\cdots v_n\ in K,\ v_i\ in L\(1\le i\le n)\}\)定义。这被扩展到如下的语言类:\({\mathcal{K}}\%{\math cal{L})=\{K \%L\mid K\in{\matical{K}},\,L\in}\mathical{L}}\}\)。在本文中,我们研究了\(\mathcal{K}\%\,\mathcal{L}\)的计算能力,其中\(\matchal{K}\)范围在\(\mathical{INS}^i_{!\!j})和min-\(\mathical{LIN}\,i),min-\(\mathcal{LIN}\):极小线性语言的类,\(\mathical{DYCK}\。所获得的结果包括:\(\mathcal{INS}^1_1\,\%\,\mathcal{DYCK}=\mathical{RE}\)\(\math cal{INS}^0_i\,\%\,\math cal{F}=\ mathcal{INS}^1_j\,\%\,\mathal{F}=\ mathccal{CF}\^0_2\)最小-\(\mathcal{LIN}\,\%\,\mathcal{F}_1=\mathcal{LIN}\),其中\(\mathcal{RE}\{F}_1\)分别是递归可枚举类、上下文无关类、线性语言类和一元字母表上的单例语言类。此外,我们为已知结果min-\(\mathcal{LIN}\,\%\,\mathcal{DYCK}_2=\mathcal{RE}\)。我们还证明,在一定条件下,对于上下文敏感语言类\(\mathcal{CS}\),不存在\(\math cal{K}\,\mathcal{DYCK}=\mathcal}CS}\),这与上述Chomsky层次结构中其他类的特征化结果形成了鲜明对比。从分子计算理论的角度来看,L-还原的概念是由大多数真核生物基因中发生的众所周知的RNA剪接的分子生物学功能自然驱动的。
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来源期刊
Acta Informatica
Acta Informatica 工程技术-计算机:信息系统
CiteScore
2.40
自引率
16.70%
发文量
24
审稿时长
>12 weeks
期刊介绍: Acta Informatica provides international dissemination of articles on formal methods for the design and analysis of programs, computing systems and information structures, as well as related fields of Theoretical Computer Science such as Automata Theory, Logic in Computer Science, and Algorithmics. Topics of interest include: • semantics of programming languages • models and modeling languages for concurrent, distributed, reactive and mobile systems • models and modeling languages for timed, hybrid and probabilistic systems • specification, program analysis and verification • model checking and theorem proving • modal, temporal, first- and higher-order logics, and their variants • constraint logic, SAT/SMT-solving techniques • theoretical aspects of databases, semi-structured data and finite model theory • theoretical aspects of artificial intelligence, knowledge representation, description logic • automata theory, formal languages, term and graph rewriting • game-based models, synthesis • type theory, typed calculi • algebraic, coalgebraic and categorical methods • formal aspects of performance, dependability and reliability analysis • foundations of information and network security • parallel, distributed and randomized algorithms • design and analysis of algorithms • foundations of network and communication protocols.
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