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 "the ising partition function zeros and deterministic approximation"):
  Abstract: We study the problem of approximating the partition function of the ferromagnetic Ising model in graphs and hypergraphs. Our first result is a deterministic approximation scheme (an FPTAS) for the partition function in bounded degree graphs that is valid over the entire range of parameters $\beta$ (the interaction) and $\lambda$ (the external field), except for the case $\vert{\lambda}\vert=1$ (the "zero-field" case). A randomized algorithm (FPRAS) for all graphs, and all $\beta,\lambda$, has long been known. Unlike most other deterministic approximation algorithms for problems in statistical physics and counting, our algorithm does not rely on the "decay of correlations" property. Rather, we exploit and extend machinery developed recently by Barvinok, and Patel and Regts, based on the location of the complex zeros of the partition function, which can be seen as an algorithmic realization of the classical Lee-Yang approach to phase transitions. Our approach extends to the more general setting of the Ising model on hypergraphs of bounded degree and edge size, where no previous algorithms (even randomized) were known for a wide range of parameters. In order to achieve this extension, we establish a tight version of the Lee-Yang theorem for the Ising model on hypergraphs, improving a classical result of Suzuki and Fisher.

Includes members:
  Member "a generalization of permanent inequalities and applications in counting and optimization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "gauges loops and polynomials for partition functions of graphical models")
  Member "convergence of mcmc and loopy bp in the tree uniqueness region for the hard core model":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spectral independence in high dimensional expanders and applications to the hardcore model")
  Member "real stable polynomials and matroids optimization and counting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "dynamic sampling from graphical models")
  Member "random cluster dynamics for the ising model is rapidly mixing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "lower bounds for testing graphical models colorings and antiferromagnetic ising models")
  Member "uniqueness spatial mixing and approximation for ferromagnetic 2 spin systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "zeros of ferromagnetic 2 spin systems")
  Member "fptas for hardcore and ising models on hypergraphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "counting hypergraph matchings up to uniqueness threshold")
  Member "counting hypergraph matchings up to uniqueness threshold":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on local distributed sampling and counting")
  Member "the complexity of approximately counting in 2 spin systems on k uniform bounded degree hypergraphs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "inapproximability of the independent set polynomial below the shearer threshold")

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.DS(Data Structures and Algorithms)