human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a general method for finding low error rates of ldpc codes"
  Abstract: This paper outlines a three-step procedure for determining the low bit error rate performance curve of a wide class of LDPC codes of moderate length. The traditional method to estimate code performance in the higher SNR region is to use a sum of the contributions of the most dominant error events to the probability of error. These dominant error events will be both code and decoder dependent, consisting of low-weight codewords as well as non-codeword events if ML decoding is not used. For even moderate length codes, it is not feasible to find all of these dominant error events with a brute force search. The proposed method provides a convenient way to evaluate very low bit error rate performance of an LDPC code without requiring knowledge of the complete error event weight spectrum or resorting to a Monte Carlo simulation. This new method can be applied to various types of decoding such as the full belief propagation version of the message passing algorithm or the commonly used min-sum approximation to belief propagation. The proposed method allows one to efficiently see error performance at bit error rates that were previously out of reach of Monte Carlo methods. This result will provide a solid foundation for the analysis and design of LDPC codes and decoders that are required to provide a guaranteed very low bit error rate performance at certain SNRs.

Connected through hyperedge HE-1 (induced by source paper "hardness results on finding leafless elementary trapping sets and elementary absorbing sets of ldpc codes"):
  with members:
    - "characterization and efficient search of non elementary trapping sets of ldpc codes with applications to stopping sets"
    - "on the tanner graph cycle distribution of random ldpc random protograph based ldpc and random quasi cyclic ldpc code ensembles"
    - "asymptotic average number of different categories of trapping sets absorbing sets and stopping sets in random regular and irregular ldpc code ensembles"
    - "on characterization of elementary trapping sets of variable regular ldpc codes"
    - "error floor approximation for ldpc codes in the awgn channel"
    - "lowering the error floor of ldpc codes using cyclic liftings"

Connected through hyperedge HE-2 (induced by source paper "ldpc code density evolution in the error floor region"):
  with members:
    - "controlling the error floor in ldpc decoding"
    - "error floor approximation for ldpc codes in the awgn channel"
    - "on the dynamics of the error floor behavior in regular ldpc codes"
    - "the trapping redundancy of linear block codes"
    - "on the block error probability of lp decoding of ldpc codes"

Connected through hyperedge HE-3 (induced by source paper "on characterization of elementary trapping sets of variable regular ldpc codes"):
  with members:
    - "lowering the error floor of ldpc codes using cyclic liftings"
    - "on the dynamics of the error floor behavior in regular ldpc codes"
    - "trapping set enumerators for repeat multiple accumulate code ensembles"
    - "the trapping redundancy of linear block codes"
    - "pseudo codewords of cycle codes via zeta functions"

Connected through hyperedge HE-4 (induced by source paper "error floor approximation for ldpc codes in the awgn channel"):
  with members:
    - "ldpc code density evolution in the error floor region"
    - "the sum product algorithm for degree 2 check nodes and trapping sets"
    - "numerical issues affecting ldpc error floors"
    - "controlling the error floor in ldpc decoding"
    - "quantized iterative message passing decoders with low error floor for ldpc codes"
    - "on the dynamics of the error floor behavior in regular ldpc codes"
    - "the trapping redundancy of linear block codes"
    - "informed dynamic scheduling for belief propagation decoding of ldpc codes"

Connected through hyperedge HE-5 (induced by source paper "cyclic and quasi cyclic ldpc codes on row and column constrained parity check matrices and their trapping sets"):
  with members:
    - "on trapping sets and guaranteed error correction capability of ldpc codes and gldpc codes"
    - "structured ldpc codes from permutation matrices free of small trapping sets"
    - "on the hardness of approximating stopping and trapping sets in ldpc codes"
    - "instanton analysis of low density parity check codes in the error floor regime"

Connected through hyperedge HE-6 (induced by source paper "lowering the error floor of ldpc codes using cyclic liftings"):
  with members:
    - "quasi cyclic ldpc codes influence of proto and tanner graph structure on minimum hamming distance upper bounds"
    - "instanton based techniques for analysis and reduction of error floors of ldpc codes"
    - "code annealing and the suppressing effect of the cyclically lifted ldpc code ensemble"
    - "instanton analysis of low density parity check codes in the error floor regime"

Connected through hyperedge HE-7 (induced by source paper "on the hardness of approximating stopping and trapping sets in ldpc codes"):
  with members:
    - "error correction capability of column weight three ldpc codes"
    - "error correction capability of column weight three ldpc codes"
    - "instanton analysis of low density parity check codes in the error floor regime"
    - "exhausting error prone patterns in ldpc codes"

Question: Please tell me which class the center node 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)