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: "a numerical framework for diffusion controlled bimolecular reactive systems to enforce maximum principles and the non negative constraint"
  Abstract: We present a novel computational framework for diffusive-reactive systems that satisfies the non-negative constraint and maximum principles on general computational grids. The governing equations for the concentration of reactants and product are written in terms of tensorial diffusion-reaction equations. We restrict our studies to fast irreversible bimolecular reactions. If one assumes that the reaction is diffusion-limited and all chemical species have the same diffusion coefficient, one can employ a linear transformation to rewrite the governing equations in terms of invariants, which are unaffected by the reaction. This results in two uncoupled tensorial diffusion equations in terms of these invariants, which are solved using a novel non-negative solver for tensorial diffusion-type equations. The concentrations of the reactants and the product are then calculated from invariants using algebraic manipulations. The novel aspect of the proposed computational framework is that it will always produce physically meaningful non-negative values for the concentrations of all chemical species. Several representative numerical examples are presented to illustrate the robustness, convergence, and the numerical performance of the proposed computational framework. We will also compare the proposed framework with other popular formulations. In particular, we will show that the Galerkin formulation (which is the standard single-field formulation) does not produce reliable solutions, and the reason can be attributed to the fact that the single-field formulation does not guarantee non-negative solutions. We will also show that the clipping procedure (which produces non-negative solutions but is considered as a variational crime) does not give accurate results when compared with the proposed computational framework.

Connected through hyperedge HE-1 (induced by source paper "unsupervised machine learning based on non negative tensor factorization for analyzing reactive mixing"):
  with members:
    - "identification of release sources in advection diffusion system by machine learning combined with green s function inverse method"
    - "large scale optimization based non negative computational framework for diffusion equations parallel implementation and performance studies"
    - "nonnegative matrix factorization for identification of unknown number of sources emitting delayed signals"
    - "parallel tensor compression for large scale scientific data"
    - "on mesh restrictions to satisfy comparison principles maximum principles and the non negative constraint recent developments and new results"
    - "julia a fast dynamic language for technical computing"

Connected through hyperedge HE-2 (induced by source paper "a scalable variational inequality approach for flow through porous media models with pressure dependent viscosity"):
  with members:
    - "a performance spectrum for parallel computational frameworks that solve pdes"
    - "firedrake automating the finite element method by composing abstractions"
    - "large scale optimization based non negative computational framework for diffusion equations parallel implementation and performance studies"
    - "an algorithm for the optimization of finite element integration loops"
    - "variational inequality approach to enforcing the non negative constraint for advection diffusion equations"
    - "cross loop optimization of arithmetic intensity for finite element local assembly"
    - "on mesh restrictions to satisfy comparison principles maximum principles and the non negative constraint recent developments and new results"
    - "a numerical methodology for enforcing maximum principles and the non negative constraint for transient diffusion equations"

Connected through hyperedge HE-3 (induced by source paper "variational inequality approach to enforcing the non negative constraint for advection diffusion equations"):
  with members:
    - "firedrake automating the finite element method by composing abstractions"
    - "large scale optimization based non negative computational framework for diffusion equations parallel implementation and performance studies"
    - "an algorithm for the optimization of finite element integration loops"
    - "a parallel edge orientation algorithm for quadrilateral meshes"
    - "a structure exploiting numbering algorithm for finite elements on extruded meshes and its performance evaluation in firedrake"
    - "cross loop optimization of arithmetic intensity for finite element local assembly"
    - "on mesh restrictions to satisfy comparison principles maximum principles and the non negative constraint recent developments and new results"
    - "a numerical methodology for enforcing maximum principles and the non negative constraint for transient diffusion equations"

Connected through hyperedge HE-4 (induced by source paper "large scale optimization based non negative computational framework for diffusion equations parallel implementation and performance studies"):
  with members:
    - "flexible scalable mesh and data management using petsc dmplex"
    - "on mesh restrictions to satisfy comparison principles maximum principles and the non negative constraint recent developments and new results"
    - "achieving high performance with unified residual evaluation"
    - "a numerical methodology for enforcing maximum principles and the non negative constraint for transient diffusion equations"
    - "enforcing the non negativity constraint and maximum principles for diffusion with decay on general computational grids"
    - "non negative mixed finite element formulations for a tensorial diffusion equation"
    - "mesh algorithms for pde with sieve i mesh distribution"

Connected through hyperedge HE-5 (induced by source paper "a hybrid multi time step framework for pore scale and continuum scale modeling of solute transport in porous media"):
  with members:
    - "do current lattice boltzmann methods for diffusion and advection diffusion equations respect maximum principle and the non negative constraint"
    - "a monolithic multi time step computational framework for first order transient systems with disparate scales"
    - "on multi time step monolithic coupling algorithms for elastodynamics"
    - "the numpy array a structure for efficient numerical computation"

Connected through hyperedge HE-6 (induced by source paper "do current lattice boltzmann methods for diffusion and advection diffusion equations respect maximum principle and the non negative constraint"):
  with members:
    - "a numerical methodology for enforcing maximum principles and the non negative constraint for transient diffusion equations"
    - "non negative mixed finite element formulations for a tensorial diffusion equation"

Connected through hyperedge HE-7 (induced by source paper "on mesh restrictions to satisfy comparison principles maximum principles and the non negative constraint recent developments and new results"):
  with members:
    - "a numerical methodology for enforcing maximum principles and the non negative constraint for transient diffusion equations"
    - "a mixed formulation for a modification to darcy equation based on picard linearization and numerical solutions to large scale realistic problems"
    - "a framework for coupled deformation diffusion analysis with application to degradation healing"
    - "enforcing the non negativity constraint and maximum principles for diffusion with decay on general computational grids"
    - "well centered triangulation"
    - "non negative mixed finite element formulations for a tensorial diffusion equation"

Connected through hyperedge HE-8 (induced by source paper "a monolithic multi time step computational framework for first order transient systems with disparate scales"):
  with members:
    - "on multi time step monolithic coupling algorithms for elastodynamics"
    - "on dual schur domain decomposition method for linear first order transient problems"

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.NA(Numerical Analysis)