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: "control principles of complex networks"
  Abstract: A reflection of our ultimate understanding of a complex system is our ability to control its behavior. Typically, control has multiple prerequisites: It requires an accurate map of the network that governs the interactions between the system's components, a quantitative description of the dynamical laws that govern the temporal behavior of each component, and an ability to influence the state and temporal behavior of a selected subset of the components. With deep roots in nonlinear dynamics and control theory, notions of control and controllability have taken a new life recently in the study of complex networks, inspiring several fundamental questions: What are the control principles of complex systems? How do networks organize themselves to balance control with functionality? To address these here we review recent advances on the controllability and the control of complex networks, exploring the intricate interplay between a system's structure, captured by its network topology, and the dynamical laws that govern the interactions between the components. We match the pertinent mathematical results with empirical findings and applications. We show that uncovering the control principles of complex systems can help us explore and ultimately understand the fundamental laws that govern their behavior.

Connected through hyperedge HE-1 (induced by source paper "nonlinearity networks a 2020 vision"):
  with members:
    - "models of continuous time networks with tie decay diffusion and convection"
    - "tunable eigenvector based centralities for multiplex and temporal networks"
    - "architecture and evolution of semantic networks in mathematics texts"
    - "supracentrality analysis of temporal networks with directed interlayer coupling"
    - "using persistent homology to quantify a diurnal cycle in hurricane felix"
    - "persistent homology of geospatial data a case study with voting"
    - "network structure from rich but noisy data"
    - "random walks on simplicial complexes and the normalized hodge 1 laplacian"

Connected through hyperedge HE-2 (induced by source paper "on the controllability of clustered scale free networks"):
  with members:
    - "cyber social systems modeling inference and optimal design"
    - "distributed estimation recovery under sensor failure"
    - "controllability of social networks and the strategic use of random information"
    - "observational equivalence in system estimation contractions in complex networks"
    - "measurement partitioning and observational equivalence in state estimation"
    - "graph theoretic distributed inference in social networks"
    - "on the genericity properties in distributed estimation topology design and sensor placement"
    - "multi agent consensus with relative state dependent measurement noises"

Connected through hyperedge HE-3 (induced by source paper "new phenomena in large scale internet traffic"):
  with members:
    - "ell_0 motivated low rank sparse subspace clustering"
    - "interactive supercomputing on 40 000 cores for machine learning and data analysis"
    - "hyperscaling internet graph analysis with d4m on the mit supercloud"
    - "scaling in internet traffic a 14 year and 3 day longitudinal study with multiscale analyses and random projections"
    - "technological networks and the spread of computer viruses"

Connected through hyperedge HE-4 (induced by source paper "deriving pairwise transfer entropy from network structure and motifs"):
  with members:
    - "idtxl the information dynamics toolkit xl a python package for the efficient analysis of multivariate information dynamics in networks"
    - "leveraging information storage to select forecast optimal parameters for delay coordinate reconstructions"
    - "causal network inference by optimal causation entropy"

Connected through hyperedge HE-5 (induced by source paper "optimal network topology for responsive collective behavior"):
  with members:
    - "swarm enabling technology for multi robot systems"
    - "adapting low cost platforms for robotics research"

Connected through hyperedge HE-6 (induced by source paper "herdability of linear systems based on sign patterns and graph structures"):
  with members:
    - "herdable systems over signed directed graphs"
    - "minimal reachability is hard to approximate"

Connected through hyperedge HE-7 (induced by source paper "a new method k method of calculating the mutual influence of nodes indirected weight complex networks"):
  with members:
    - "probing the topological properties of complex networks modeling short written texts"

Connected through hyperedge HE-8 (induced by source paper "deterministic and randomized actuator scheduling with guaranteed performance bounds"):
  with members:
    - "an alon boppana type bound for weighted graphs and lowerbounds for spectral sparsification"
    - "an sdp based algorithm for linear sized spectral sparsification"
    - "minimal reachability is hard to approximate"
    - "structural analysis and optimal design of distributed system throttlers"
    - "graph distances and controllability of networks"
    - "minimal reachability problems"
    - "controllability metrics limitations and algorithms for complex networks"
    - "near optimal column based matrix reconstruction"

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.SY(Systems and Control)