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 4 3 additive spanner exponent is tight"
  Abstract: A spanner is a sparse subgraph that approximately preserves the pairwise distances of the original graph. It is well known that there is a smooth tradeoff between the sparsity of a spanner and the quality of its approximation, so long as distance error is measured multiplicatively. A central open question in the field is to prove or disprove whether such a tradeoff exists also in the regime of additive error. That is, is it true that for all $e>0$, there is a constant $k_e$ such that every graph has a spanner on $O(n^{1+e})$ edges that preserves its pairwise distances up to $+k_e$? Previous lower bounds are consistent with a positive resolution to this question, while previous upper bounds exhibit the beginning of a tradeoff curve: all graphs have $+2$ spanners on $O(n^{3/2})$ edges, $+4$ spanners on $\tilde{O}(n^{7/5})$ edges, and $+6$ spanners on $O(n^{4/3})$ edges. However, progress has mysteriously halted at the $n^{4/3}$ bound, and despite significant effort from the community, the question has remained open for all $0<e<1/3$. #R##N#Our main result is a surprising negative resolution of the open question, even in a highly generalized setting. We show a new information theoretic incompressibility bound: there is no mathematical function that compresses graphs into $O(n^{4/3 - e})$ bits so that distance information can be recovered within $+n^{o(1)}$ error. As a special case of our theorem, we get a tight lower bound on the sparsity of additive spanners: the $+6$ spanner on $O(n^{4/3})$ edges cannot be improved in the exponent, even if any subpolynomial amount of additive error is allowed. Our theorem implies new lower bounds for related objects as well; for example, the twenty-year-old $+4$ emulator on $O(n^{4/3})$ edges also cannot be improved in the exponent unless the error allowance is polynomial.

Connected through hyperedge HE-1 (induced by source paper "weighted additive spanners"):
  with members:
    - "some general structure for extremal sparsification problems"
    - "almost shortest paths and pram distance oracles in weighted graphs"
    - "lower bounds on sparse spanners emulators and diameter reducing shortcuts"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "linear size distance preservers"
    - "better distance preservers and additive spanners"
    - "additive spanners a simple construction"
    - "on pairwise spanners"

Connected through hyperedge HE-2 (induced by source paper "graph spanners a tutorial review"):
  with members:
    - "near additive spanners and near exact hopsets a unified view"
    - "some general structure for extremal sparsification problems"
    - "weighted additive spanners"
    - "near additive spanners in low polynomial deterministic congest time"
    - "multi level graph sketches via single level solvers"
    - "almost shortest paths and pram distance oracles in weighted graphs"
    - "an fpt algorithm for minimum additive spanner problem"
    - "distributed construction of light networks"

Connected through hyperedge HE-3 (induced by source paper "distributed construction of light networks"):
  with members:
    - "light spanners for high dimensional norms via stochastic decompositions"
    - "greedy spanners are optimal in doubling metrics"
    - "distributed exact shortest paths in sublinear time"
    - "improved distributed algorithms for exact shortest paths"
    - "a simple deterministic distributed mst algorithm with near optimal time and message complexities"
    - "constructing light spanners deterministically in near linear time"
    - "minor free graphs have light spanners"
    - "the greedy spanner is existentially optimal"

Connected through hyperedge HE-4 (induced by source paper "new alpha beta spanners and hopsets"):
  with members:
    - "almost shortest paths and pram distance oracles in weighted graphs"
    - "linear size hopsets with small hopbound and distributed routing with low memory"
    - "thorup zwick emulators are universally optimal hopsets"
    - "distributed exact shortest paths in sublinear time"
    - "efficient algorithms for constructing very sparse spanners and emulators"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "on efficient distributed construction of near optimal routing schemes"

Connected through hyperedge HE-5 (induced by source paper "almost shortest paths and pram distance oracles in weighted graphs"):
  with members:
    - "thorup zwick emulators are universally optimal hopsets"
    - "efficient algorithms for constructing very sparse spanners and emulators"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "a linear size logarithmic stretch path reporting distance oracle for general graphs"
    - "parallel metric tree embedding based on an algebraic view on moore bellman ford"
    - "a deterministic almost tight distributed algorithm for approximating single source shortest paths"
    - "decremental single source shortest paths on undirected graphs in near linear total update time"

Connected through hyperedge HE-6 (induced by source paper "lossless prioritized embeddings"):
  with members:
    - "near isometric terminal embeddings for doubling metrics"
    - "nonlinear dimension reduction via outer bi lipschitz extensions"
    - "optimal terminal dimensionality reduction in euclidean space"
    - "metric embedding via shortest path decompositions"
    - "efficient algorithms for constructing very sparse spanners and emulators"
    - "on notions of distortion and an almost minimum spanning tree with constant average distortion"
    - "prioritized metric structures and embedding"
    - "lower stretch spanning trees"

Connected through hyperedge HE-7 (induced by source paper "near additive spanners in low polynomial deterministic congest time"):
  with members:
    - "deterministic distributed ruling sets of line graphs"
    - "improved deterministic distributed construction of spanners"
    - "efficient algorithms for constructing very sparse spanners and emulators"
    - "a hierarchy of lower bounds for sublinear additive spanners"
    - "hopsets with constant hopbound and applications to approximate shortest paths"
    - "a fast network decomposition algorithm and its applications to constant time distributed computation"
    - "a deterministic almost tight distributed algorithm for approximating single source shortest paths"

Connected through hyperedge HE-8 (induced by source paper "graph spanners in the message passing model"):
  with members:
    - "distributed computation of large scale graph problems"
    - "when distributed computation is communication expensive"
    - "lower bounds for number in hand multiparty communication complexity made easy"
    - "tight bounds for distributed functional monitoring"

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.DS(Data Structures and Algorithms)