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: "the computational power of beeps"
  Abstract: In this paper, we study the quantity of computational resources (state machine states and/or probabilistic transition precision) needed to solve specific problems in a single hop network where nodes communicate using only beeps. We begin by focusing on randomized leader election. We prove a lower bound on the states required to solve this problem with a given error bound, probability precision, and (when relevant) network size lower bound. We then show the bound tight with a matching upper bound. Noting that our optimal upper bound is slow, we describe two faster algorithms that trade some state optimality to gain efficiency. We then turn our attention to more general classes of problems by proving that once you have enough states to solve leader election with a given error bound, you have (within constant factors) enough states to simulate correctly, with this same error bound, a logspace TM with a constant number of unary input tapes: allowing you to solve a large and expressive set of problems. These results identify a key simplicity threshold beyond which useful distributed computation is possible in the beeping model.

Connected through hyperedge HE-1 (induced by source paper "distributed voting in beep model"):
  with members:
    - "distributed voting ranking with optimal number of states per node"
    - "beeping a maximal independent set fast"
    - "deterministic rendezvous with detection using beeps"
    - "counting in one hop beeping networks"
    - "naming a channel with beeps"
    - "asynchronous broadcasting with bivalent beeps"
    - "feedback from nature simple randomised distributed algorithms for maximal independent set selection and greedy colouring"
    - "design patterns in beeping algorithms examples emulation and analysis"

Connected through hyperedge HE-2 (induced by source paper "some problems in compact message passing"):
  with members:
    - "linear size hopsets with small hopbound and distributed routing with low memory"
    - "a self stabilizing general de bruijn graph"
    - "fast partial distance estimation and applications"
    - "dex self healing expanders"
    - "algorithms for self healing networks"
    - "the forgiving graph a distributed data structure for low stretch under adversarial attack"
    - "the forgiving tree a self healing distributed data structure"
    - "general compact labeling schemes for dynamic trees"

Connected through hyperedge HE-3 (induced by source paper "deterministic rendezvous with detection using beeps"):
  with members:
    - "time versus cost tradeoffs for deterministic rendezvous in networks"
    - "rendezvous of two robots with constant memory"
    - "how to meet asynchronously at polynomial cost"
    - "beeping a maximal independent set"
    - "delays induce an exponential memory gap for rendezvous in trees"
    - "deploying wireless networks with beeps"

Connected through hyperedge HE-4 (induced by source paper "naming a channel with beeps"):
  with members:
    - "randomized communication in radio networks"
    - "asynchronous broadcasting with bivalent beeps"
    - "scalable wake up of multi channel single hop radio networks"
    - "feedback from nature simple randomised distributed algorithms for maximal independent set selection and greedy colouring"
    - "anonymous processors with synchronous shared memory"
    - "communicating with beeps"
    - "randomized broadcast in radio networks with collision detection"
    - "beeping a maximal independent set"

Connected through hyperedge HE-5 (induced by source paper "counting in one hop beeping networks"):
  with members:
    - "randomized communication in radio networks"
    - "design patterns in beeping algorithms"
    - "scalable wake up of multi channel single hop radio networks"
    - "design patterns in beeping algorithms examples emulation and analysis"
    - "naming and counting in anonymous unknown dynamic networks"
    - "beeping a maximal independent set"
    - "feedback from nature an optimal distributed algorithm for maximal independent set selection"
    - "deploying wireless networks with beeps"

Connected through hyperedge HE-6 (induced by source paper "design patterns in beeping algorithms examples emulation and analysis"):
  with members:
    - "randomized communication in radio networks"
    - "counting in one hop beeping networks"
    - "feedback from nature simple randomised distributed algorithms for maximal independent set selection and greedy colouring"
    - "randomized broadcast in radio networks with collision detection"
    - "the locality of distributed symmetry breaking"
    - "beeping a maximal independent set"
    - "feedback from nature an optimal distributed algorithm for maximal independent set selection"
    - "deploying wireless networks with beeps"

Connected through hyperedge HE-7 (induced by source paper "exponential separations in the energy complexity of leader election"):
  with members:
    - "the energy complexity of broadcast"
    - "broadcasting in noisy radio networks"
    - "exploiting spontaneous transmissions for broadcasting and leader election in radio networks"
    - "optimal leader election in multi hop radio networks"
    - "radio network lower bounds made easy"
    - "near optimal leader election in multi hop radio networks"
    - "deploying wireless networks with beeps"

Connected through hyperedge HE-8 (induced by source paper "asynchronous broadcasting with bivalent beeps"):
  with members:
    - "deterministic rendezvous with detection using beeps"
    - "global synchronization and consensus using beeps in a fault prone mac"
    - "on distributed computing with beeps"
    - "communicating with beeps"
    - "beeping a maximal independent set"
    - "near optimal leader election in multi hop radio networks"
    - "deploying wireless networks with beeps"

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)