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 "on the evaluation of the polyanskiy poor verdu converse bound for finite block length coding in awgn"):
  Abstract: A tight converse bound to the channel coding rate in the finite block-length regime and under additive white Gaussian noise conditions was recently proposed by Polyanskiy-Poor–Verdu (PPV). The bound is a generalization of a number of other classical results, and it was also claimed to be equivalent to Shannon’s 1959 cone packing bound. In this paper, we investigate methods for a reliable numerical evaluation of the bound, which is troublesome even for not too large values of the block-length    $n$   , by compactly expressing the Polyanskiy, Poor, and Verdu (PPV) converse bound in terms of non-central chi-squared distributions, and by evaluating those through an integral expression and a corresponding series expansion which exploit a method proposed by Temme. As a result, a robust evaluation method and new insights on the bound’s asymptotics, as well as new approximate expressions, are obtained.

Includes members:
  Member "the third order term in the normal approximation for the awgn channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gaussian multiple and random access in the finite blocklength regime")
  Member "finite dimensional infinite constellations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the decoding of barnes wall lattices")

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)