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 asymptotic capacity of the optical fiber"):
  Abstract: It is shown that signal energy is the only available degree-of-freedom (DOF) for fiber-optic transmission as the input power tends to infinity. With $n$ signal DOFs at the input, $n-1$ DOFs are asymptotically lost to signal-noise interactions. The main observation is that, nonlinearity introduces a multiplicative noise in the channel, similar to fading in wireless channels. The channel is viewed in the spherical coordinate system, where signal vector $\underline{X}\in\mathbb{C}^n$ is represented in terms of its norm $|\underline{X}|$ and direction $\underline{\hat{X}}$. The multiplicative noise causes signal direction $\underline{\hat{X}}$ to vary randomly on the surface of the unit $(2n-1)$-sphere in $\mathbb{C}^{n}$, in such a way that the effective area of the support of $\underline{\hat{X}}$ does not vanish as $|\underline{X}|\rightarrow\infty$. On the other hand, the surface area of the sphere is finite, so that $\underline{\hat{X}}$ carries finite information. This observation is used to show several results. Firstly, let $\mathcal C(\mathcal P)$ be the capacity of a discrete-time periodic model of the optical fiber with distributed noise and frequency-dependent loss, as a function of the average input power $\mathcal P$. It is shown that asymptotically as $\mathcal P\rightarrow\infty$, $\mathcal C=\frac{1}{n}\log\bigl(\log\mathcal P\bigr)+c$, where $n$ is the dimension of the input signal space and $c$ is a bounded number. In particular, $\lim_{\mathcal P\rightarrow\infty}\mathcal C(\mathcal P)=\infty$ in finite-dimensional periodic models. Secondly, it is shown that capacity saturates to a constant in infinite-dimensional models where $n=\infty$.

Includes members:
  Member "nonlinear frequency division multiplexing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "nonlinear fourier transform of truncated multi soliton pulses")
  Member "models and information rates for multiuser optical fiber channels with nonlinearity and dispersion":
    also connected through other hyperedges:
      (none)
  Member "conditions for a monotonic channel capacity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "linear and nonlinear frequency division multiplexing")
  Member "upper bound on the capacity of a cascade of nonlinear and noisy channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "nonlinearity mitigation in wdm systems models strategies and achievable rates")
  Member "upper bound on the capacity of the nonlinear schr odinger channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a signal space distance measure for nondispersive optical fiber")
  Member "information transmission using the nonlinear fourier transform part ii numerical methods":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polarization division multiplexing based on the nonlinear fourier transform")
  Member "information transmission using the nonlinear fourier transform part i mathematical tools":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient nonlinear fourier transform algorithms of order four on equispaced grid")
  Member "information transmission using the nonlinear fourier transform part iii spectrum modulation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (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)