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 "hardness results on finding leafless elementary trapping sets and elementary absorbing sets of ldpc codes"):
  Abstract: Leafless elementary trapping sets (LETSs) are known to be the problematic structures in the error floor region of low-density parity-check (LDPC) codes over the additive white Gaussian (AWGN) channel under iterative decoding algorithms. While problems involving the general category of trapping sets, and the subcategory of elementary trapping sets (ETSs), have been shown to be NP-hard, similar results for LETSs, which are a subset of ETSs are not available. In this paper, we prove that, for a general LDPC code, finding a LETS of a given size a with minimum number of unsatisfied check nodes b is NP-hard to approximate with any guaranteed precision. We also prove that finding the minimum size a of a LETS with a given b is NP-hard to approximate. Similar results are proved for elementary absorbing sets, a popular subcategory of LETSs.

Includes members:
  Member "characterization and efficient search of non elementary trapping sets of ldpc codes with applications to stopping sets":
    also connected through other hyperedges:
      (none)
  Member "on the tanner graph cycle distribution of random ldpc random protograph based ldpc and random quasi cyclic ldpc code ensembles":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "perm2vec graph permutation selection for decoding of error correction codes using self attention")
  Member "asymptotic average number of different categories of trapping sets absorbing sets and stopping sets in random regular and irregular ldpc code ensembles":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the tanner graph cycle distribution of random ldpc random protograph based ldpc and random quasi cyclic ldpc code ensembles")
  Member "on characterization of elementary trapping sets of variable regular ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a combinatorial methodology for optimizing non binary graph based codes theoretical analysis and applications in data storage")
  Member "error floor approximation for ldpc codes in the awgn channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a combinatorial methodology for optimizing non binary graph based codes theoretical analysis and applications in data storage")
  Member "lowering the error floor of ldpc codes using cyclic liftings":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "integer ring sieve irs for constructing compact qc ldpc codes with large girth")
  Member "a general method for finding low error rates of ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "ldpc code density evolution in the error floor region")

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)