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: "divergence optimal fixed to fixed length distribution matching with shell mapping"
  Abstract: Distribution matching (DM) transforms independent and Bernoulli(1/2) distributed bits into a sequence of output symbols with a desired distribution. A fixed-to-fixed length, invertible DM architecture based on shell mapping is presented. It is shown that shell mapping for distribution matching (SMDM) is the optimum DM for the informational divergence metric and that finding energy optimal sequences is a special case of divergence minimization. Additionally, it is shown how to find the required shell mapping weight function to approximate arbitrary output distributions. SMDM is combined with probabilistic amplitude shaping (PAS) to operate close to the Shannon limit. SMDM exhibits excellent performance for short blocklengths as required by ultra-reliable low-latency (URLLC) applications. SMDM outperforms constant composition DM (CCDM) by 0.6 dB when used with 64-QAM at a spectral efficiency of 3 bits/channel use and a 5G low-density parity-check code with a short blocklength of 192 bits

Connected through hyperedge HE-1 (induced by source paper "rate constrained shaping codes for structured sources"):
  with members:
    - "performance of optimal data shaping codes"
    - "constant composition distribution matching"
    - "arithmetic distribution matching"
    - "how to achieve the capacity of asymmetric channels"
    - "fixed to variable length distribution matching"
    - "informational divergence and entropy rate on rooted trees with probabilities"
    - "matching dyadic distributions to channels"

Connected through hyperedge HE-2 (induced by source paper "introducing enumerative sphere shaping for optical communication systems with short blocklengths"):
  with members:
    - "exploring and experimenting with shaping designs for next generation optical communications"
    - "experimental verification of rate flexibility and probabilistic shaping by 4d signaling"
    - "increasing achievable information rates via geometric shaping"
    - "experimental comparison of probabilistic shaping methods for unrepeated fiber transmission"
    - "a survey on fiber nonlinearity compensation for 400 gb s and beyond optical communication systems"
    - "comparison of geometric and probabilistic shaping with application to atsc 3 0"
    - "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel"
    - "constellation shaping for wdm systems using 256qam 1024qam with probabilistic optimization"

Connected through hyperedge HE-3 (induced by source paper "prefix free code distribution matching for probabilistic constellation shaping"):
  with members:
    - "shell mapping for distribution matching"
    - "divergence scaling of fixed length binary output one to one distribution matching"
    - "fixed to variable length resolution coding for target distributions"
    - "constellation shaping for bit interleaved ldpc coded apsk"
    - "matching dyadic distributions to channels"
    - "prefix codes equiprobable words unequal letter costs"

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)