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: "capacity of continuous space electromagnetic channels with lossy transceiver"
  Abstract: In this paper, the capacity of continuous-space electromagnetic channels, where transceivers are confined in given lossy regions, is analyzed. First of all, the regions confining the transceivers are assumed to be filled with dielectric, which is either lossy or lossless. Then, for capacity analysis, we use the exact power consumption that takes into account the electromagnetic interaction between the field and the source. In addition, the exact noise model followed from the fluctuation-dissipation theorem in thermodynamics is used at the receive side. The contribution of our work is summarized as follows. First, we characterize the channel capacity as a function of the size and the physical property of the regions confining the transceivers and analytically show how the radiation efficiency affects the capacity. We also show that the outgoing channel at the transmit side and the incoming channel at the receive side are information-theoretically equivalent, and thus, the capacities of both channels are the same. Additionally, the quality factor, which is inversely proportional to the bandwidth, is theoretically derived, and the relationship between the spatial degrees of freedom of the channel and the quality factor is analyzed. Besides, we consider how the power consumption is affected by the backscattered waves and compare the recent experimental demonstration with our work by solving the gain-optimization problem with the constraint on the quality factor.

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)