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: "global majority consensus by local majority polling on graphs of a given degree sequence"
  Abstract: Suppose in a graph $G$ vertices can be either red or blue. Let $k$ be odd. At each time step, each vertex $v$ in $G$ polls $k$ random neighbours and takes the majority colour. If it doesn't have $k$ neighbours, it simply polls all of them, or all less one if the degree of $v$ is even. We study this protocol on graphs of a given degree sequence, in the following setting: initially each vertex of $G$ is red independently with probability $\alpha   d$. Here, $d\geq 5$ is the effective minimum degree, the smallest integer which occurs $\Theta(n)$ times in the degree sequence. We further show that on such graphs, any local protocol in which a vertex does not change colour if all its neighbours have that same colour, takes time at least $\Omega(\log_d \log_d n)$, with high probability. Additionally, we demonstrate how the technique for the above sparse graphs can be applied in a straightforward manner to get bounds for the Erd\H{o}s-R\'enyi random graphs in the connected regime.

Connected through hyperedge HE-1 (induced by source paper "communication cost of consensus for nodes with limited memory"):
  with members:
    - "population protocols are fast"
    - "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 "barracuda the power of ell polling in proof of stake blockchains"):
  with members:
    - "deconstructing the blockchain to approach physical limits"
    - "scaling nakamoto consensus to thousands of transactions per second"
    - "casper the friendly finality gadget"
    - "enhancing bitcoin security and performance with strong consistency via collective signing"
    - "bitcoin ng a scalable blockchain protocol"
    - "deanonymisation of clients in bitcoin p2p network"
    - "majority is not enough bitcoin mining is vulnerable"

Connected through hyperedge HE-3 (induced by source paper "best of three voting on dense graphs"):
  with members:
    - "better bounds for coalescing branching random walks"
    - "fast plurality consensus in regular expanders"
    - "the power of two choices in distributed voting"
    - "simple dynamics for plurality consensus"

Connected through hyperedge HE-4 (induced by source paper "robustness and efficiency of leaderless probabilistic consensus protocols within byzantine infrastructures"):
  with members:
    - "scalable byzantine consensus via hardware assisted secret sharing"
    - "majority model on random regular graphs"
    - "fast deterministic consensus in a noisy environment"

Connected through hyperedge HE-5 (induced by source paper "bounds on the voter model in dynamic networks"):
  with members:
    - "efficient k party voting with two choices"
    - "the power of two choices in distributed voting"
    - "absorption time of the moran process"
    - "coalescing random walks and voting on connected graphs"
    - "approximating fixation probabilities in the generalized moran process"

Connected through hyperedge HE-6 (induced by source paper "noisy rumor spreading and plurality consensus"):
  with members:
    - "limits for rumor spreading in stochastic populations"
    - "space optimal majority in population protocols"
    - "minimizing message size in stochastic communication patterns fast self stabilizing protocols with 3 bits"
    - "noisy information spreading and plurality consensus"
    - "the power of two choices in distributed voting"
    - "plurality consensus in the gossip model"
    - "breathe before speaking efficient information dissemination despite noisy limited and anonymous communication"
    - "determining majority in networks with local interactions and very small local memory"

Connected through hyperedge HE-7 (induced by source paper "noisy information spreading and plurality consensus"):
  with members:
    - "the power of two choices in distributed voting"
    - "plurality consensus in the gossip model"
    - "breathe before speaking efficient information dissemination despite noisy limited and anonymous communication"
    - "simple dynamics for plurality consensus"
    - "the computational power of population protocols"

Connected through hyperedge HE-8 (induced by source paper "on convergence and threshold properties of discrete lotka volterra population protocols"):
  with members:
    - "the power of two choices in distributed voting"
    - "determining majority in networks with local interactions and very small local memory"
    - "simple dynamics for plurality consensus"
    - "the dynamics of probabilistic population protocols"
    - "the computational power of 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)