human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "upper bound on the capacity of a cascade of nonlinear and noisy channels"
  Abstract: An upper bound on the capacity of a cascade of nonlinear and noisy channels is presented. The cascade mimics the split-step Fourier method for computing waveform propagation governed by the stochastic generalized nonlinear Schroedinger equation. It is shown that the spectral efficiency of the cascade is at most log(1+SNR), where SNR is the receiver signal-to-noise ratio. The results may be applied to optical fiber channels. However, the definition of bandwidth is subtle and leaves open interpretations of the bound. Some of these interpretations are discussed.

Connected through hyperedge HE-1 (induced by source paper "nonlinearity mitigation in wdm systems models strategies and achievable rates"):
  with members:
    - "improved lower bounds on mutual information accounting for nonlinear signal noise interaction"
    - "information rates of next generation long haul optical fiber systems using coded modulation"
    - "impact of 4d channel distribution on the achievable rates in coherent optical communication experiments"
    - "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel"
    - "on achievable rates for long haul fiber optic communications"
    - "influence of behavioral models on multiuser channel capacity"
    - "on the per sample capacity of nondispersive optical fibers"

Connected through hyperedge HE-2 (induced by source paper "improved lower bounds on mutual information accounting for nonlinear signal noise interaction"):
  with members:
    - "information rates of next generation long haul optical fiber systems using coded modulation"
    - "impact of 4d channel distribution on the achievable rates in coherent optical communication experiments"
    - "stochastic digital backpropagation with residual memory compensation"
    - "on achievable rates for long haul fiber optic communications"
    - "capacity of a nonlinear optical channel with finite memory"
    - "optimization of information rate upper and lower bounds for channels with memory"

Connected through hyperedge HE-3 (induced by source paper "non parametric estimation of mutual information with application to nonlinear optical fibers"):
  with members:
    - "improved lower bounds on mutual information accounting for nonlinear signal noise interaction"
    - "a non parametric k nearest neighbour entropy estimator"
    - "capacity of a nonlinear optical channel with finite memory"
    - "mutual information as a figure of merit for optical fiber systems"

Connected through hyperedge HE-4 (induced by source paper "information rates of next generation long haul optical fiber systems using coded modulation"):
  with members:
    - "sensitivity gains by mismatched probabilistic shaping for optical communication systems"
    - "impact of 4d channel distribution on the achievable rates in coherent optical communication experiments"
    - "replacing the soft fec limit paradigm in the design of optical communication systems"
    - "on achievable rates for long haul fiber optic communications"
    - "four dimensional coded modulation with bit wise decoders for future optical communications"
    - "capacity of a nonlinear optical channel with finite memory"
    - "staircase codes fec for 100 gb s otn"

Connected through hyperedge HE-5 (induced by source paper "autocorrelation function for dispersion free fiber channels with distributed amplification"):
  with members:
    - "capacity achieving input distributions in nondispersive optical fibers"
    - "capacity bounds for discrete time amplitude constrained additive white gaussian noise channels"
    - "optimal input signal distribution and per sample mutual information for nondispersive nonlinear optical fiber channel in large snr limit"
    - "on continuous time white phase noise channels"
    - "on the per sample capacity of nondispersive optical fibers"
    - "calculation of mutual information for partially coherent gaussian channels with applications to fiber optics"

Connected through hyperedge HE-6 (induced by source paper "capacity achieving input distributions in nondispersive optical fibers"):
  with members:
    - "on properties of the support of capacity achieving distributions for additive noise channel models with input cost constraints"
    - "on the finiteness of the capacity of continuous channels"
    - "the asymptotic capacity of the optical fiber"
    - "information theoretic proofs of entropy power inequalities"
    - "the noncoherent rician fading channel part i structure of the capacity achieving input"

Connected through hyperedge HE-7 (induced by source paper "an achievable rate for an optical channel with finite memory"):
  with members:
    - "on the capacity of a class of signal dependent noise channels"
    - "on the capacity of free space optical intensity channels"

Connected through hyperedge HE-8 (induced by source paper "information theory of molecular communication directions and challenges"):
  with members:
    - "shannon capacity of signal transduction for multiple independent receptors"
    - "capacity limits of diffusion based molecular timing channels"
    - "comprehensive reactive receiver modeling for diffusive molecular communication systems reversible binding molecule degradation and finite number of receptors"
    - "type based sign modulation for molecular communication"
    - "a comprehensive survey of recent advancements in molecular communication"
    - "information friction and its implications on minimum energy required for communication"
    - "a perspective on future research directions in information theory"
    - "information rates of ask based molecular communication in fluid media"

Question: Please tell me which class the center node 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)