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: "thresholds of absorbing sets in low density parity check codes"
  Abstract: In this paper, we investigate absorbing sets, responsible of error floors in Low Density Parity Check codes. We look for a concise, quantitative way to rate the absorbing sets' dangerousness. Based on a simplified model for iterative decoding evolution, we show that absorbing sets exhibit a threshold behavior. An absorbing set with at least one channel log-likelihood-ratio below the threshold can stop the convergence towards the right codeword. Otherwise convergence is guaranteed. We show that absorbing sets with negative thresholds can be deactivated simply using proper saturation levels. We propose an efficient algorithm to compute thresholds.

Connected through hyperedge HE-1 (induced by source paper "a combinatorial methodology for optimizing non binary graph based codes theoretical analysis and applications in data storage"):
  with members:
    - "finite length construction of high performance spatially coupled codes via optimized partitioning and lifting"
    - "spatially coupled code design for partial response channels optimal object minimization approach"
    - "a generalized algebraic approach to optimizing sc ldpc codes"
    - "high performance non binary spatially coupled codes for flash memories"
    - "threshold saturation for nonbinary sc ldpc codes on the binary erasure channel"
    - "spatially coupled ldpc codes constructed from protographs"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "iterative decoding of ldpc codes over the q ary partial erasure channel"

Connected through hyperedge HE-2 (induced by source paper "construction of qc ldpc codes with low error floor by efficient systematic search and elimination of trapping sets"):
  with members:
    - "edge coloring technique to remove small elementary trapping sets from tanner graph of qc ldpc codes with column weight 4"
    - "efficient search of qc ldpc codes with girths 6 and 8 and free of elementary trapping sets with small size"
    - "the cycle consistency matrix approach to absorbing sets in separable circulant based ldpc codes"
    - "design of finite length irregular protograph codes with low error floors over the binary input awgn channel using cyclic liftings"
    - "lowering the error floor of ldpc codes using cyclic liftings"
    - "on the dynamics of the error floor behavior in regular ldpc codes"

Connected through hyperedge HE-3 (induced by source paper "performance bounds and estimates for quantized ldpc decoders"):
  with members:
    - "on characterization of elementary trapping sets of variable regular ldpc codes"
    - "controlling the error floor in ldpc decoding"
    - "error floor approximation for ldpc codes in the awgn channel"
    - "quantized iterative message passing decoders with low error floor for ldpc codes"
    - "the trapping redundancy of linear block codes"

Connected through hyperedge HE-4 (induced by source paper "asymptotic average multiplicity of structures within different categories of trapping sets absorbing sets and stopping sets in random regular and irregular ldpc code ensembles"):
  with members:
    - "on the tanner graph cycle distribution of random ldpc random protograph based ldpc and random quasi cyclic ldpc code ensembles"
    - "hardness results on finding leafless elementary trapping sets and elementary absorbing sets of ldpc codes"
    - "on the minimum stopping distance of array low density parity check codes"
    - "on characterization of elementary trapping sets of variable regular ldpc codes"
    - "error floor approximation for ldpc codes in the awgn channel"

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)