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: "on the finite length scaling of ternary polar codes"
  Abstract: The polarization process of polar codes over a ternary alphabet is studied. Recently it has been shown that the scaling of the blocklength of polar codes with prime alphabet size scales polynomially with respect to the inverse of the gap between code rate and channel capacity. However, except for the binary case, the degree of the polynomial in the bound is extremely large. In this work, it is shown that a much lower degree polynomial can be computed numerically for the ternary case. Similar results are conjectured for the general case of prime alphabet size.

Connected through hyperedge HE-1 (induced by source paper "adaptive linear programming decoding of nonbinary linear codes over prime fields"):
  with members:
    - "hardware based linear program decoding with the alternating direction method of multipliers"
    - "low complexity lp decoding of nonbinary linear codes"
    - "mathematical programming decoding of binary linear codes theory and algorithms"
    - "adaptive cut generation algorithm for improved linear programming decoding of binary linear codes"
    - "decomposition methods for large scale lp decoding"
    - "efficient implementation of linear programming decoding"
    - "linear programming decoding of nonbinary linear codes"
    - "a separation algorithm for improved lp decoding of linear block codes"

Connected through hyperedge HE-2 (induced by source paper "near optimal finite length scaling for polar codes over large alphabets"):
  with members:
    - "binary linear codes with optimal scaling and quasi linear complexity"
    - "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors"
    - "finite length scaling for polar codes"
    - "binary polarization kernels from code decompositions"
    - "an entropy sumset inequality and polynomially fast convergence to shannon capacity over all alphabets"
    - "polar codes speed of polarization and polynomial gap to capacity"
    - "improved bounds on the finite length scaling of polar codes"
    - "rate dependent analysis of the asymptotic behavior of channel polarization"

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)