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: "population protocols are fast"
  Abstract: A population protocol describes a set of state change rules for a population of $n$ indistinguishable finite-state agents (automata), undergoing random pairwise interactions. Within this very basic framework, it is possible to resolve a number of fundamental tasks in distributed computing, including: leader election, aggregate and threshold functions on the population, such as majority computation, and plurality consensus. For the first time, we show that solutions to all of these problems can be obtained \emph{quickly} using finite-state protocols. For any input, the designed finite-state protocols converge under a fair random scheduler to an output which is correct with high probability in expected $O(\mathrm{poly} \log n)$ parallel time. In the same setting, we also show protocols which always reach a valid solution, in expected parallel time $O(n^\varepsilon)$, where the number of states of the interacting automata depends only on the choice of $\varepsilon>0$. The stated time bounds hold for \emph{any} semi-linear predicate computable in the population protocol framework. #R##N#The key ingredient of our result is the decentralized design of a hierarchy of phase-clocks, which tick at different rates, with the rates of adjacent clocks separated by a factor of $\Theta(\log n)$. The construction of this clock hierarchy relies on a new protocol composition technique, combined with an adapted analysis of a self-organizing process of oscillatory dynamics. This clock hierarchy is used to provide nested synchronization primitives, which allow us to view the population in a global manner and design protocols using a high-level imperative programming language with a (limited) capacity for loops and branching instructions.

Connected through hyperedge HE-1 (induced by source paper "communication cost of consensus for nodes with limited memory"):
  with members:
    - "global majority consensus by local majority polling on graphs of a given degree sequence"
    - "population protocols for leader election and exact majority with o log 2 n states and o log 2 n convergence time"
    - "space optimal majority in population protocols"
    - "time space trade offs in population protocols"
    - "discordant voting processes on finite graphs"
    - "stable leader election in population protocols requires linear time"
    - "plurality consensus in the gossip model"
    - "determining majority in networks with local interactions and very small local memory"

Connected through hyperedge HE-2 (induced by source paper "efficient size estimation and impossibility of termination in uniform dense population protocols"):
  with members:
    - "on counting the population size"
    - "almost logarithmic time space optimal leader election in population protocols"
    - "fast space optimal leader election in population protocols"
    - "logarithmic expected time leader election in population protocol model"
    - "hardness of computing and approximating predicates and functions with leaderless population protocols"
    - "space optimal majority in population protocols"
    - "time space trade offs in population protocols"
    - "time and space optimal counting in population protocols"

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.DC(Distributed, Parallel, and Cluster Computing)