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: "probabilistic analysis of a differential equation for linear programming"
  Abstract: In this paper we address the complexity of solving linear programming problems with a set of differential equations that converge to a fixed point that represents the optimal solution. Assuming a probabilistic model, where the inputs are i.i.d. Gaussian variables, we compute the distribution of the convergence rate to the attracting fixed point. Using the framework of Random Matrix Theory, we derive a simple expression for this distribution in the asymptotic limit of large problem size. In this limit, we find that the distribution of the convergence rate is a scaling function, namely it is a function of one variable that is a combination of three parameters: the number of variables, the number of constraints and the convergence rate, rather than a function of these parameters separately. We also estimate numerically the distribution of computation times, namely the time required to reach a vicinity of the attracting fixed point, and find that it is also a scaling function. Using the problem size dependence of the distribution functions, we derive high probability bounds on the convergence rates and on the computation times.

Connected through hyperedge HE-1 (induced by source paper "a survey on analog models of computation"):
  with members:
    - "real time computability of real numbers by chemical reaction networks"
    - "robustness of expressivity in chemical reaction networks"
    - "efficient analog circuits for boolean satisfiability"
    - "axiomatizing analog algorithms"
    - "homonym population protocols"
    - "physical computation p poly and p log"
    - "a uniform substitution calculus for differential dynamic logic"
    - "on recurrent reachability for continuous linear dynamical systems"

Connected through hyperedge HE-2 (induced by source paper "polynomial time corresponds to solutions of polynomial ordinary differential equations of polynomial length"):
  with members:
    - "computational complexity of solving polynomial differential equations over unbounded domains"
    - "computational complexity of solving polynomial differential equations over unbounded domains with non rational coefficients"
    - "computing with polynomial ordinary differential equations"
    - "on the functions generated by the general purpose analog computer"
    - "on the complexity of solving initial value problems"
    - "lipschitz continuous ordinary differential equations are polynomial space complete"

Connected through hyperedge HE-3 (induced by source paper "polynomial time corresponds to solutions of polynomial ordinary differential equations of polynomial length journal version"):
  with members:
    - "lipschitz continuous ordinary differential equations are polynomial space complete"

Connected through hyperedge HE-4 (induced by source paper "a survey on continuous time computations"):
  with members:
    - "on probabilistic analog automata"

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)