In this article, it has been theoretically shown that broad angle negative refraction is possible with asymmetric anisotropic metamaterials constructed by only dielectrics or loss less semiconductors at the telecommunication and relative wavelength r
ange. Though natural uniaxial materials can exhibit negative refraction, the maximum angle of negative refraction and critical incident angle lie in a very narrow range. This notable problem can be overcome by our proposed structure. In our structures, negative refraction originates from the highly asymmetric elliptical iso-frequency.This is artificially created by the rotated multilayer sub-wavelength dielectric/semiconductor stack, which act as an effective asymmetric anisotropic metamaterial.This negative refraction is achieved without using any negative permittivity materials such as metals. As we are using simple dielectrics, fabrication of such structures would be less complex than that of the metal based metamaterials. Our proposed ideas have been validated numerically and also by the full wave simulations considering both the effective medium approach and realistic structure model. This device might find some important applications in photonics and optoelectronics.
We determine the rate region of the vector Gaussian one-helper source-coding problem under a covariance matrix distortion constraint. The rate region is achieved by a simple scheme that separates the lossy vector quantization from the lossless spatia
l compression. The converse is established by extending and combining three analysis techniques that have been employed in the past to obtain partial results for the problem.
We study a hypothesis testing problem in which data is compressed distributively and sent to a detector that seeks to decide between two possible distributions for the data. The aim is to characterize all achievable encoding rates and exponents of th
e type 2 error probability when the type 1 error probability is at most a fixed value. For related problems in distributed source coding, schemes based on random binning perform well and often optimal. For distributed hypothesis testing, however, the use of binning is hindered by the fact that the overall error probability may be dominated by errors in binning process. We show that despite this complication, binning is optimal for a class of problems in which the goal is to test against conditional independence. We then use this optimality result to give an outer bound for a more general class of instances of the problem.
