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 "can quantum communication speed up distributed computation"):
  Abstract: The focus of this paper is on {\em quantum distributed} computation, where we investigate whether quantum communication can help in {\em speeding up} distributed network algorithms. Our main result is that for certain fundamental network problems such as minimum spanning tree, minimum cut, and shortest paths, quantum communication {\em does not} help in substantially speeding up distributed algorithms for these problems compared to the classical setting. #R##N#In order to obtain this result, we extend the technique of Das Sarma et al. [SICOMP 2012] to obtain a uniform approach to prove non-trivial lower bounds for quantum distributed algorithms for several graph optimization (both exact and approximate versions) as well as verification problems, some of which are new even in the classical setting, e.g. tight randomized lower bounds for Hamiltonian cycle and spanning tree verification, answering an open problem of Das Sarma et al., and a lower bound in terms of the weight aspect ratio, matching the upper bounds of Elkin [STOC 2004]. Our approach introduces the {\em Server model} and {\em Quantum Simulation Theorem} which together provide a connection between distributed algorithms and communication complexity. The Server model is the standard two-party communication complexity model augmented with additional power; yet, most of the hardness in the two-party model is carried over to this new model. The Quantum Simulation Theorem carries this hardness further to quantum distributed computing. Our techniques, except the proof of the hardness in the Server model, require very little knowledge in quantum computing, and this can help overcoming a usual impediment in proving bounds on quantum distributed algorithms.

Includes members:
  Member "almost tight distributed minimum cut algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "improved algorithm for min cuts in distributed networks")
  Member "near optimal distributed approximation of minimum weight connected dominating set":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deterministic distributed dominating set approximation in the congest model")
  Member "distributed approximation algorithms for weighted shortest paths":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed edge connectivity in sublinear time")
  Member "brief announcement almost tight approximation distributed algorithm for minimum cut":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distributed approximation algorithms for weighted shortest paths")
  Member "distributed minimum cut approximation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "beyond alice and bob improved inapproximability for maximum independent set in congest")
  Member "distributed computation of sparse cuts":
    also connected through other hyperedges:
      (none)
  Member "distributed connectivity decomposition":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "distributed edge connectivity in sublinear time")
  Member "distributed random walks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "walking randomly massively and efficiently")

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)