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 "r enyi resolvability and its applications to the wiretap channel"):
  Abstract: The conventional channel resolvability problem refers to the determination of the minimum rate needed for an input process to approximate the output distribution of a channel in either the total variation distance or the relative entropy. In contrast to previous works, in this paper, we use the (normalized or unnormalized) R\'enyi divergence (with the R\'enyi parameter in [0,2]) to measure the level of approximation. We also provide asymptotic expressions for normalized R\'enyi divergence when the R\'enyi parameter is larger than or equal to $1$ as well as (lower and upper) bounds for the case when the same parameter is smaller than $1$. We characterize the minimum rate needed to ensure that the R\'enyi resolvability vanishes asymptotically. The optimal rates are the same for both the normalized and unnormalized cases. In addition, the minimum rate when the R\'enyi parameter no larger than $1$ equals the minimum mutual information over all input distributions that induce the target output distribution similarly to the traditional case. When the R\'enyi parameter is larger than $1$ the minimum rate is, in general, larger than the mutual information. The optimal R\'enyi resolvability is proven to vanish at least exponentially fast for both of these two cases, as long as the code rate is larger than the minimum admissible one. The optimal exponential rate of decay for i.i.d. random codes is also characterized exactly. We apply these results to the wiretap channel, and completely characterize the optimal tradeoff between the rates of the secret and non-secret messages when the leakage measure is given by the (unnormalized) R\'enyi divergence. This tradeoff differs from the conventional setting when the leakage is measured by the traditional mutual information.

Includes members:
  Member "corrections to wyner s common information under r enyi divergence measures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on exact and infty r enyi common informations")
  Member "exact channel synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "communication for generating correlation a unifying survey")
  Member "asymptotic coupling and its applications in information theory":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "simulation of random variables under r enyi divergence measures of all orders")
  Member "exact random coding secrecy exponents for the wiretap channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "communication for generating correlation a unifying survey")
  Member "analysis of remaining uncertainties and exponents under various conditional r e nyi entropies":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the renyi capacity and center")
  Member "strong converse theorems for classes of multimessage multicast networks a renyi divergence approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the renyi capacity and center")
  Member "secure multiplex coding with dependent and non uniform multiple messages":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exact exponent for soft covering")
  Member "distributed simulation of continuous random variables":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "constrained functional value under general convexity conditions with applications to distributed simulation")

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)