human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "asymptotically optimal codes correcting fixed length duplication errors in dna storage systems"):
  Abstract: A (tandem) duplication of length    ${k} $    is an insertion of an exact copy of a substring of length    ${k} $    next to its original position. This and related types of impairments are of relevance in modeling communication in the presence of synchronization errors, as well as in several information storage applications. We demonstrate that Levenshtein’s construction of binary codes correcting insertions of zeros is, with minor modifications, applicable also to channels with arbitrary alphabets and with  duplication  errors of arbitrary (but fixed) length    ${k} $   . Furthermore, we derive bounds on the cardinality of optimal    ${q} $   -ary codes correcting up to    ${t} $    duplications of length    ${k} $    and establish the following corollaries in the asymptotic regime of growing block length: 1) the presented family of codes is optimal for every    ${q, t, k} $   , in the sense of the asymptotic scaling of code redundancy; 2) the upper bound, when specialized to    ${q=2} $   ,    ${k=1} $   , improves upon Levenshtein’s bound for every    ${t\geq 3} $   ; and 3) the bounds coincide for    ${t=1} $   , thus yielding the exact asymptotic behavior of the size of optimal single-duplication-correcting codes.

Includes members:
  Member "runlength limited sequences and shift correcting codes asymptotic analysis":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "zero error capacity of duplication channels")
  Member "reconstruction codes for dna sequences with uniform tandem duplication errors":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimal constant weight codes under l_1 metric")
  Member "bounds and constructions for multi symbol duplication error correcting codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal constant weight codes under l_1 metric")
  Member "codes in the space of multisets coding for permutation channels with impairments":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "optimal constant weight codes under l_1 metric")
  Member "duplication correcting codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "uncertainty of reconstruction with list decoding from uniform tandem duplication noise")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)