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 "polar code moderate deviation recovering the scaling exponent"):
  Abstract: In 2008 Arikan proposed polar coding [arXiv:0807.3917] which we summarize as follows: (a) From the root channel $W$ synthesize recursively a series of channels $W_N^{(1)},\dotsc,W_N^{(N)}$. (b) Select sophisticatedly a subset $A$ of synthetic channels. (c) Transmit information using synthetic channels indexed by $A$ and freeze the remaining synthetic channels. #R##N#Arikan gives each synthetic channel a score (called the Bhattacharyya parameter) that determines whether it should be selected or frozen. As $N$ grows, a majority of the scores are either very high or very low, i.e., they polarize. By characterizing how fast they polarize, Arikan showed that polar coding is able to produce a series of codes that achieve capacity on symmetric binary-input memoryless channels. #R##N#In measuring how the scores polarize the relation among block length, gap to capacity, and block error probability are studied. In particular, the error exponent regime fixes the gap to capacity and varies the other two. The scaling exponent regime fixes the block error probability and varies the other two. The moderate deviation regime varies all three factors at once. #R##N#The latest result [arxiv:1501.02444, Theorem 7] in the moderate deviation regime does not imply the scaling exponent regime as a special case. We give a result that does. (See Corollary 8.)

Includes members:
  Member "general strong polarization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "reed muller codes theory and algorithms")
  Member "near optimal finite length scaling for polar codes over large alphabets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "polar codes simplicity random codes durability")
  Member "finite length scaling for polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "reed muller codes theory and algorithms")
  Member "polar codes speed of polarization and polynomial gap to capacity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "polar codes simplicity random codes durability")
  Member "improved bounds on the finite length scaling of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polar codes simplicity random codes durability")
  Member "on the correlation between polarized becs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "faulty successive cancellation decoding of polar codes for the binary erasure channel")
  Member "scaling exponent of list decoders with applications to polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "rate dependent analysis of the asymptotic behavior of channel polarization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "polar codes simplicity random codes durability")

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)