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: "density matrix based algorithm for solving eigenvalue problems"
  Abstract: A new numerical algorithm for solving the symmetric eigenvalue problem is presented. The technique deviates fundamentally from the traditional Krylov subspace iteration based techniques (Arnoldi and Lanczos algorithms) or other Davidson-Jacobi techniques, and takes its inspiration from the contour integration and density matrix representation in quantum mechanics. It will be shown that this new algorithm - named FEAST - exhibits high efficiency, robustness, accuracy and scalability on parallel architectures. Examples from electronic structure calculations of Carbon nanotubes (CNT) are presented, and numerical performances and capabilities are discussed.

Connected through hyperedge HE-1 (induced by source paper "chase chebyshev accelerated subspace iteration eigensolver for sequences of hermitian eigenvalue problems"):
  with members:
    - "an optimized and scalable eigensolver for sequences of eigenvalue problems"
    - "block iterative eigensolvers for sequences of correlated eigenvalue problems"
    - "high performance solvers for dense hermitian eigenproblems"

Connected through hyperedge HE-2 (induced by source paper "a robust iterative scheme for symmetric indefinite systems"):
  with members:
    - "sym ildl incomplete ldl t factorization of symmetric indefinite and skew symmetric matrices"

Connected through hyperedge HE-3 (induced by source paper "ghost building blocks for high performance sparse linear algebra on heterogeneous systems"):
  with members:
    - "pipelined iterative solvers with kernel fusion for graphics processing units"
    - "performance engineering of the kernel polynomal method on large scale cpu gpu systems"
    - "a unified sparse matrix data format for efficient general sparse matrix vector multiplication on modern processors with wide simd units"
    - "asynchronous mpi for the masses"
    - "pt scotch a tool for efficient parallel graph ordering"

Connected through hyperedge HE-4 (induced by source paper "distributed estimation of generalized matrix rank efficient algorithms and lower bounds"):
  with members:
    - "on the communication complexity of linear algebraic problems in the message passing model"
    - "principal component analysis and higher correlations for distributed data"
    - "efficient estimation of eigenvalue counts in an interval"
    - "bpr bayesian personalized ranking from implicit feedback"
    - "randomized algorithms for matrices and data"
    - "robust principal component analysis"

Connected through hyperedge HE-5 (induced by source paper "efficient estimation of eigenvalue counts in an interval"):
  with members:
    - "improved bounds on sample size for implicit matrix trace estimators"
    - "optimal query complexity for estimating the trace of a matrix"
    - "dissecting the feast algorithm for generalized eigenproblems"
    - "feast eigenvalue solver v3 0 user guide"

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.CE(Computational Engineering, Finance, and Science)