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: "on local equilibrium equations for clustering states"
  Abstract: In this note we show that local equilibrium equations (the generalization of the TAP equations or of the belief propagation equations) do have solutions in the colorable phase of the coloring problem. The same results extend to other optimization problems where the solutions has cost zero (e.g. K-satisfiability). On a random graph the solutions of the local equilibrium equations are associated to clusters of configurations (clustering states). On a random graph the local equilibrium equations have solutions almost everywhere in the uncolored phase; in this case we have to introduce the concept quasi-solution of the local equilibrium equations.

Connected through hyperedge HE-1 (induced by source paper "the backtracking survey propagation algorithm for solving random k sat problems"):
  with members:
    - "on the solution space geometry of random constraint satisfaction problems"
    - "a new look at survey propagation and its generalizations"
    - "some remarks on the survey decimation algorithm for k satisfiability"
    - "threshold values of random k sat from the cavity method"
    - "typical random 3 sat formulae and the satisfiability threshold"
    - "survey propagation an algorithm for satisfiability"

Connected through hyperedge HE-2 (induced by source paper "circumspect descent prevails in solving random constraint satisfaction problems"):
  with members:
    - "survey propagation revisited"
    - "threshold values of random k sat from the cavity method"

Connected through hyperedge HE-3 (induced by source paper "a new look at survey propagation and its generalizations"):
  with members:
    - "belief optimization for binary networks a stable alternative to loopy belief propagation"
    - "on the solution space geometry of random constraint satisfaction problems"
    - "low density constructions can achieve the wyner ziv and gelfand pinsker bounds"
    - "lossy source encoding via message passing and decimation over generalized codewords of ldgm codes"
    - "the threshold for random k sat is 2 k ln2 o k"
    - "typical random 3 sat formulae and the satisfiability threshold"
    - "survey propagation an algorithm for satisfiability"

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.CC(Computational Complexity)