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 "non asymptotic and asymptotic analyses of information processing on markov chains"):
  Abstract: In this paper, we derive non-asymptotic achievability and converse bounds on the source coding with/without side-information, the random number generation with/without side-information, and the channel coding for the regular channel. Our bounds are efficiently computable in the sense that the computational complexity does not depend on the block length. We also characterize the asymptotic behaviors of the large deviation regime and the moderate deviation regime by using our bounds, which implies that our bounds are asymptotically tight in those regimes. We also show the second order rates of those problems, and derive single letter forms of the variances characterizing the second order rates.

Includes members:
  Member "security analysis of varepsilon almost dual universal 2 hash functions smoothing of min entropy versus smoothing of renyi entropy of order 2":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "finite blocklength bounds for wiretap channels")
  Member "second order coding rates for channels with state":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "second order and moderate deviation analysis of a block fading channel with deterministic and energy harvesting power constraints")
  Member "the saddlepoint approximation unified random coding asymptotics for fixed and varying rates":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on exact asymptotics of the error probability in channel coding symmetric channels")
  Member "mismatched decoding error exponents second order rates and saddlepoint approximations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "saddlepoint approximations for short packet wireless communications")
  Member "non asymptotic analysis of privacy amplification via renyi entropy and inf spectral entropy":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "two way physical layer security protocol for gaussian channels")
  Member "exponential decreasing rate of leaked information in universal random privacy amplification":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "communication for generating correlation a unifying survey")
  Member "moderate deviations of lossy source coding for discrete and gaussian sources":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exponential strong converse for content identification with lossy recovery")
  Member "information spectrum approach to second order coding rate in channel coding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "finite sample analysis of image registration")

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)