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: "channel simulation and coded source compression"
  Abstract: Coded source compression, also known as source compression with helpers, has been a major variant of distributed source compression, but has hitherto received little attention in the quantum regime. This letter treats and solves the corresponding quantum coded source compression through an observation that connects coded source compression with channel simulation. First, we consider classical source coding with quantum side information, where the quantum side information is observed by a helper and sent to the decoder via a classical channel. We derive a single-letter characterization of the achievable rate region for this problem. The direct coding theorem of our result is proved via the measurement compression theory of Winter, a quantum-to-classical channel simulation. Our result reveals that a helper’s scheme which separately conducts a measurement and a compression is suboptimal, and measurement compression seems necessary to achieve the optimal rate region. We then study coded source compression in the fully quantum regime, where two different scenarios are considered depending on the types of communication channels between the legitimate source and the receiver. We further allow entanglement assistance from the quantum helper in both scenarios. We characterize the involved quantum resources and derive single-letter expressions of the achievable rate region. The direct coding proofs are based on well-known quantum protocols, the quantum state merging protocol, and the fully quantum Slepian–Wolf protocol, together with the quantum reverse Shannon theorem.

Connected through hyperedge HE-1 (induced by source paper "communication over random parameter quantum channels with parameter estimation"):
  with members:
    - "entanglement assisted capacity of quantum channels with side information"
    - "causal state communication"
    - "a constrained channel coding approach to joint communication and channel estimation"

Connected through hyperedge HE-2 (induced by source paper "communication over quantum channels with parameter estimation"):
  with members:
    - "entanglement assisted capacity of quantum channels with side information"
    - "causal state communication"
    - "a constrained channel coding approach to joint communication and channel estimation"

Connected through hyperedge HE-3 (induced by source paper "communication for generating correlation a unifying survey"):
  with members:
    - "secret key capacity for multipleaccess channel with public feedback"
    - "exact exponent for soft covering"
    - "exact channel synthesis"
    - "strong converse using change of measure arguments"
    - "coding for positive rate in the source model key agreement problem"
    - "wiretap channels nonasymptotic fundamental limits"
    - "channel resolvability theorems for general sources and channels"
    - "strong functional representation lemma and applications to coding theorems"

Connected through hyperedge HE-4 (induced by source paper "communication for generating correlation a survey"):
  with members:
    - "secret key capacity for multipleaccess channel with public feedback"
    - "exact soft covering exponent"
    - "on exact and infty r enyi common informations"
    - "exact channel synthesis"
    - "strong converse using change of measure arguments"
    - "coding for positive rate in the source model key agreement problem"
    - "wiretap channels nonasymptotic fundamental limits"
    - "channel resolvability theorems for general sources and channels"

Connected through hyperedge HE-5 (induced by source paper "entanglement assisted capacity of quantum channels with side information"):
  with members:
    - "causal state communication"

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)