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 "the log log growth of channel capacity for nondispersive nonlinear optical fiber channel in intermediate power range extension of the model"):
  Abstract: In our previous paper [Phys. Rev. E 95, 062122 (2017)] we considered the optical channel modelled by the nonlinear Schr\"odinger equation with zero dispersion and additive Gaussian noise. We found per-sample channel capacity rof this model. In the present paper we extend per-sample model by introducing the initial signal dependence on time and the output signal detection procedure. The proposed model is a closer approximation of the realistic communication link than the per-sample model where there is no dependence of the initial signal on time. For the proposed model we found the correlators of the output signal both analytically and numerically. Using these correlators we built the conditional probability density function. Then we calculated an entropy of the output signal, a conditional entropy, and the mutual information. Maximizing the mutual information we found the optimal input signal distribution, channel capacity? and their dependence on the shape or the initial signal in the time domain for the intermediate power range.

Includes members:
  Member "autocorrelation function for dispersion free fiber channels with distributed amplification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a signal space distance measure for nondispersive optical fiber")
  Member "next to leading order corrections to capacity for nondispersive nonlinear optical fiber channel in intermediate power region":
    also connected through other hyperedges:
      (none)
  Member "calculation of mutual information for nonlinear communication channel at large signal to noise ratio":
    also connected through other hyperedges:
      (none)
  Member "capacity of a nonlinear optical channel with finite memory":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improved lower bounds on mutual information accounting for nonlinear signal noise interaction")
  Member "on the per sample capacity of nondispersive optical fibers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a signal space distance measure for nondispersive optical fiber")

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)