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 "re proving channel polarization theorems an extremality and robustness analysis"):
  Abstract: Abstract The general subject considered in this thesis is a recently discovered coding technique,polar coding, which is used to construct a class of error correction codes withunique properties. In his ground-breaking work, Arikan proved that this class ofcodes, called polar codes, achieve the symmetric capacity — the mutual informationevaluated at the uniform input distribution — of any stationary binary discretememoryless channel with low complexity encoders and decoders requiring in theorder of O(NlogN) operations in the block-length N. This discovery settledthe long standing open problem left by Shannon of ﬁnding low complexity codesachieving the channel capacity.Polar codes are not only appealing for being the ﬁrst to ‘close the deal’. Incontrast to most of the existing coding schemes, polar codes admit an explicit lowcomplexity construction. In addition, for symmetric channels, the polar code con-struction is deterministic; the theoretically beautiful but practically limited “averageperformance of an ensemble of codes is good, so there must exist one particular codein the ensemble at least as good as the average” formalism of information theory isbypassed. Simulations are thus not necessary in principle for evaluating the errorprobability which is shown in a study by Telatar and Arikan to scale exponentially inthe square root of the block-length. As such, at the time of this writing, polar codesare appealing for being the only class of codes proved, and proved with mathematicalelegance, to possess all of these properties.Polar coding settled an open problem in information theory, yet opened plentyof challenging problems that need to be addressed. This novel coding scheme is apromising method from which, in addition to data transmission, problems such asdata compression or compressed sensing, which includes all types of measurementprocesses like the MRI or ultrasound, could beneﬁt in terms of efﬁciency. To makethis technique fulﬁll its promise, the original theory has been, and should still be,extended in multiple directions. A signiﬁcant part of this thesis is dedicated toadvancing the knowledge about this technique in two directions. The ﬁrst oneprovides a better understanding of polar coding by generalizing some of the existingresults and discussing their implications, and the second one studies the robustnessof the theory over communication models introducing various forms of uncertaintyor variations into the probabilistic model of the channel.The idea behind the design of a polar code is a phenomenon called channelxi

Includes members:
  Member "universal polar codes for more capable and less noisy channels and sources":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "universal polarization for processes with memory")
  Member "the symmetric convex ordering a novel partial order for b dmcs ordering the information sets of polar codes":
    also connected through other hyperedges:
      (none)
  Member "properties of the polarization transformations for the likelihood ratios of symmetric b dmcs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a novel partial order for the information sets of polar codes over b dmcs")
  Member "extremality for gallager s reliability function e_0":
    also connected through other hyperedges:
      (none)
  Member "extremes of error exponents":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a lower bound on the interactive capacity of binary memoryless symmetric channels")
  Member "list decoding of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "on the construction of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "how to construct polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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)