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: "spatially coupled code design for partial response channels optimal object minimization approach"
  Abstract: Because of their capacity-approaching performance and their complexity/latency advantages, spatially-coupled (SC) codes are among the most attractive error-correcting codes for use in modern dense storage devices. SC codes are constructed by partitioning an underlying block code and coupling the partitioned components. Here, we focus on circulant-based SC codes. Recently, the optimal overlap (OO)-circulant power optimizer (CPO) approach was introduced to construct high performance SC codes for additive white Gaussian noise (AWGN) and Flash channels. The OO stage operates on the protograph of the SC code to derive the optimal partitioning that minimizes the number of detrimental objects. Then, the CPO optimizes the circulant powers to further reduce this number. Since the nature of detrimental objects in the graph of a code critically depends on the characteristics of the channel of interest, extending the OO-CPO approach to construct SC codes for channels with intrinsic memory is not a straightforward task. In this paper, we tackle one relevant extension; we construct high performance SC codes for practical 1-D magnetic recording channels, i.e., partial-response (PR) channels. Via combinatorial techniques, we carefully build and solve the optimization problem of the OO partitioning, focusing on the objects of interest in the case of PR channels. Then, we customize the CPO to further reduce the number of these objects in the graph of the code. SC codes designed using the proposed OO-CPO approach for PR channels outperform prior state-of-the-art SC codes by around 3 orders of magnitude in frame error rate (FER) and 1.1 dB in signal-to-noise ratio (SNR), and more intriguingly, outperform structured block codes of the same length by around 1.6 orders of magnitude in FER and 0.4 dB in SNR.

Connected through hyperedge HE-1 (induced by source paper "efficient information reconciliation for energy time entanglement quantum key distribution"):
  with members:
    - "finite length construction of high performance spatially coupled codes via optimized partitioning and lifting"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"

Connected through hyperedge HE-2 (induced by source paper "a combinatorial methodology for optimizing non binary graph based codes theoretical analysis and applications in data storage"):
  with members:
    - "finite length construction of high performance spatially coupled codes via optimized partitioning and lifting"
    - "a generalized algebraic approach to optimizing sc ldpc codes"
    - "high performance non binary spatially coupled codes for flash memories"
    - "threshold saturation for nonbinary sc ldpc codes on the binary erasure channel"
    - "spatially coupled ldpc codes constructed from protographs"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "iterative decoding of ldpc codes over the q ary partial erasure channel"
    - "thresholds of absorbing sets in low density parity check codes"

Connected through hyperedge HE-3 (induced by source paper "multi dimensional spatially coupled code design enhancing the cycle properties"):
  with members:
    - "efficient search and elimination of harmful objects in optimized qc sc ldpc codes"
    - "finite length construction of high performance spatially coupled codes via optimized partitioning and lifting"
    - "multi dimensional spatially coupled code design through informed relocation of circulants"
    - "high performance non binary spatially coupled codes for flash memories"
    - "hierarchical and high girth qc ldpc codes"
    - "multi dimensional spatially coupled codes"
    - "new codes on graphs constructed by connecting spatially coupled chains"
    - "on characterization of elementary trapping sets of variable regular ldpc codes"

Connected through hyperedge HE-4 (induced by source paper "a channel aware combinatorial approach to design high performance spatially coupled codes for magnetic recording systems"):
  with members:
    - "a combinatorial methodology for optimizing non binary graph based codes theoretical analysis and applications in data storage"
    - "finite length construction of high performance spatially coupled codes via optimized partitioning and lifting"
    - "high performance non binary spatially coupled codes for flash memories"
    - "threshold saturation for nonbinary sc ldpc codes on the binary erasure channel"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "windowed decoding of protograph based ldpc convolutional codes over erasure channels"
    - "deriving good ldpc convolutional codes from ldpc block 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)