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 "alignment of polarized sets"):
  Abstract: Arkan’s polar coding technique is based on the idea of synthesizing   $n$   channels from the   $n$   instances of the physical channel by a simple linear encoding transformation. Each synthesized channel corresponds to a particular input to the encoder. For large   $n$  , the synthesized channels become either essentially noiseless or almost perfectly noisy, but in total carry as much information as the original   $n$   channels. Capacity can therefore be achieved by transmitting messages over the essentially noiseless synthesized channels. Unfortunately, the set of inputs corresponding to reliable synthesized channels is poorly understood, in particular, how the set depends on the underlying physical channel. In this work, we present two analytic conditions sufficient to determine if the reliable inputs corresponding to different discrete memoryless channels are  aligned  or not, i.e., if one set is contained in the other. Understanding the alignment of the polarized sets is important as it is directly related to universality properties of the induced polar codes, which are essential in particular for network coding problems. We demonstrate the performance of our conditions on a few examples for wiretap and broadcast channels. Finally, we show that these conditions imply that the simple quantum polar coding scheme of Renes  et al.  [ Phys. Rev. Lett.,  109, 050504, 2012] requires entanglement assistance for general channels, but also show such assistance to be unnecessary in many cases of interest.

Includes members:
  Member "polar codes for broadcast channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "polar codes simplicity random codes durability")
  Member "universal polar codes for more capable and less noisy channels and sources":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "universal polarization for processes with memory")
  Member "achieving secrecy capacity of the wiretap channel and broadcast channel with a confidential component":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "explicit codes for the wiretap channel a unified design framework")
  Member "polar coding for the general wiretap channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "secure polar coding with delayed wiretapping information")
  Member "polar codes speed of polarization and polynomial gap to capacity":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polar codes simplicity random codes durability")
  Member "efficient one way secret key agreement and private channel coding via polarization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "explicit codes for the wiretap channel a unified design framework")
  Member "universal polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "on the construction of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "polar codes and their quantum domain counterparts")

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)