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: "strange attractor for efficient polar code design"
  Abstract: This paper presents a definition of a construction for long polar codes. Recently, we know that partial order is a universal property of the construction with a sublinear complexity for polar codes. In order to describe the partial order, addition and left-swap operators are only defined as universal up to now. In this study, we first propose $1+\log_2 \log_2 N$ universal operators to describe multiple partial order for the block length $N=2^n$. By using these operators, some known antichains can be universally ordered. #R##N#Furthermore, by using a simple geometric property of Gaussian approximation, we define an attractor that is a pre-defined subset of synthetic channels. They are universally less reliable than the natural channel $W$. Then, we show that the cardinality of this attractor is $(n+2)$-th Fibonacci number which is a significantly large number of channels for long codes. The main contribution is that there are significant number of synthetic channels explicitly defined as almost useless by the help of attractor and multiple partial order. As a result, proposed attractor with multiple partial order can be seen as an efficient tool to investigate and design extremely long codes.

Connected through hyperedge HE-1 (induced by source paper "on the construction of g_n coset codes for parallel decoding"):
  with members:
    - "construction and decoding of product codes with non systematic polar codes"
    - "permutation decoding of polar codes"
    - "a new permutation decoding method for reed muller codes"
    - "a 5 16gbps decoder asic for polar code in 16nm finfet"
    - "a flip syndrome list polar decoder architecture for ultra low latency communications"
    - "reed muller codes achieve capacity on erasure channels"
    - "improved successive cancellation decoding of polar codes"
    - "list decoding of polar codes"

Connected through hyperedge HE-2 (induced by source paper "construction of polar codes with sublinear complexity"):
  with members:
    - "near optimal finite length scaling for polar codes over large alphabets"
    - "algebraic properties of polar codes from a new polynomial formalism"
    - "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors"
    - "finite length scaling for polar codes"
    - "an entropy sumset inequality and polynomially fast convergence to shannon capacity over all alphabets"
    - "polar codes speed of polarization and polynomial gap to capacity"
    - "improved bounds on the finite length scaling of polar codes"
    - "list decoding of polar codes"

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.IT(Information Theory)