human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "space optimal majority in population protocols"):
  Abstract: Population protocols are a model of distributed computing, in which $n$ agents with limited local state interact randomly, and cooperate to collectively compute global predicates. An extensive series of papers, across different communities, has examined the computability and complexity characteristics of this model. Majority, or consensus, is a central task, in which agents need to collectively reach a decision as to which one of two states $A$ or $B$ had a higher initial count. Two complexity metrics are important: the time that a protocol requires to stabilize to an output decision, and the state space size that each agent requires. #R##N#It is known that majority requires $\Omega(\log \log n)$ states per agent to allow for poly-logarithmic time stabilization, and that $O(\log^2 n)$ states are sufficient. Thus, there is an exponential gap between the upper and lower bounds. #R##N#We address this question. We provide a new lower bound of $\Omega(\log n)$ states for any protocol which stabilizes in $O( n^{1-c} )$ time, for any $c > 0$ constant. This result is conditional on basic monotonicity and output assumptions, satisfied by all known protocols. Technically, it represents a significant departure from previous lower bounds. Instead of relying on dense configurations, we introduce a new surgery technique to construct executions which contradict the correctness of algorithms that stabilize too fast. Subsequently, our lower bound applies to general initial configurations. #R##N#We give an algorithm for majority which uses $O(\log n)$ states, and stabilizes in $O(\log^2 n)$ time. Central to the algorithm is a new leaderless phase clock, which allows nodes to synchronize in phases of $\Theta(n \log{n})$ consecutive interactions using $O(\log n)$ states per node. We also employ our phase clock to build a leader election algorithm with $O(\log n )$ states, which stabilizes in $O(\log^2 n)$ time.

Includes members:
  Member "fast space optimal leader election in population protocols":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "robust comparison in population protocols")
  Member "population protocols for leader election and exact majority with o log 2 n states and o log 2 n convergence time":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "communication cost of consensus for nodes with limited memory")
  Member "plurality consensus via shuffling lessons learned from load balancing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "time space trade offs in molecular computation")
  Member "timing in chemical reaction networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "communication cost of consensus for nodes with limited memory")

Question: Please tell me which class the source paper 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)