human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "second order asymptotics for communication under strong asynchronism"):
  Abstract: The capacity under strong asynchronism was recently shown to be essentially unaffected by the imposed output sampling rate $\rho$ and decoding delay $d$---the elapsed time between when information is available at the transmitter and when it is decoded. This paper examines this result in the finite blocklength regime and shows that, by contrast with capacity, the second order term in the rate expansion is sensitive to both parameters. When the receiver must exactly locate the sent codeword, that is $d=n$ where $n$ denotes blocklength, the second order term in the rate expansion is of order $\Theta(1/\rho)$ for any $\rho=O(1/\sqrt{n})$---and $\rho =\omega(1/n)$ for otherwise reliable communication is impossible. However, if $\rho=\omega(1/\sqrt{n})$ then the second order term is the same as under full sampling and is given by a standard $O(\sqrt{n})$ term whose dispersion constant only depends on the level of asynchronism. This second order term also corresponds to the case of the slightly relaxed delay constraint $d\leq n(1+o(1))$ for any $\rho=\omega(1/n)$.

Includes members:
  Member "sampling constrained asynchronous communication how to sleep efficiently":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "channel detection in coded communication")
  Member "channel detection in coded communication":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "large deviations behavior of the logarithmic error probability of random codes")
  Member "asynchronous communication capacity bounds and suboptimality of training":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the strongly asynchronous massive access channel")
  Member "asynchronous capacity per unit cost":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "concurrent coding a reason to think differently about encoding against noise burst errors and jamming")
  Member "communication under strong asynchronism":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the reliability function of distributed hypothesis testing under optimal detection")
  Member "optimal sequential frame synchronization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the strongly asynchronous massive access channel")

Question: Please tell me which class the source paper 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)