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 "construction of polar codes for arbitrary discrete memoryless channels"):
  Abstract: It is known that polar codes can be efficiently constructed for binary-input channels. At the same time, existing algorithms for general input alphabets are less practical because of high complexity. We address the construction problem for the general case, and analyze an algorithm that is based on successive reduction of the output alphabet size of the subchannels in each recursion step. For this procedure we estimate the approximation error as $O(\mu^{-1/(q-1)}),$ where $\mu$ is the "quantization parameter," i.e., the maximum size of the subchannel output alphabet allowed by the algorithm. The complexity of the code construction scales as $O(N\mu^4),$ where $N$ is the length of the code. #R##N#We also show that if the polarizing operation relies on modulo-$q$ addition, it is possible to merge subsets of output symbols without any loss in subchannel capacity. Performing this procedure before each approximation step results in a further speed-up of the code construction, and the resulting codes have smaller gap to capacity. We show that a similar acceleration can be attained for polar codes over finite field alphabets. #R##N#Experimentation shows that the suggested construction algorithms can be used to construct long polar codes for alphabets of size $q=16$ and more with acceptable loss of the code rate for a variety of polarizing transforms.

Includes members:
  Member "a comparative study of polar code constructions for the awgn channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "on the construction of polar codes for channels with moderate input alphabet sizes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "universal polarization for processes with memory")
  Member "ergodic theory meets polarization ii a foundation of polarization theory":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the fractality of polar and reed muller codes")
  Member "practical polar code construction using generalised generator matrices":
    also connected through other hyperedges:
      (none)
  Member "upgraded approximation of non binary alphabets for polar code construction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the construction of polar codes for channels with moderate input alphabet sizes")
  Member "channel upgradation for non binary input alphabets and macs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "universal polarization for processes with memory")
  Member "on the construction and decoding of concatenated polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "rate matching for polar codes based on binary domination")
  Member "universal polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "polar codes and their quantum domain counterparts")

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)