87 research outputs found
Experimental Demonstration of Dual Polarization Nonlinear Frequency Division Multiplexed Optical Transmission System
Multi-eigenvalues transmission with information encoded simultaneously in
both orthogonal polarizations is experimentally demonstrated. Performance below
the HD-FEC limit is demonstrated for 8-bits/symbol 1-GBd signals after
transmission up to 207 km of SSMF
Dual polarization nonlinear Fourier transform-based optical communication system
New services and applications are causing an exponential increase in internet
traffic. In a few years, current fiber optic communication system
infrastructure will not be able to meet this demand because fiber nonlinearity
dramatically limits the information transmission rate. Eigenvalue communication
could potentially overcome these limitations. It relies on a mathematical
technique called "nonlinear Fourier transform (NFT)" to exploit the "hidden"
linearity of the nonlinear Schr\"odinger equation as the master model for
signal propagation in an optical fiber. We present here the theoretical tools
describing the NFT for the Manakov system and report on experimental
transmission results for dual polarization in fiber optic eigenvalue
communications. A transmission of up to 373.5 km with bit error rate less than
the hard-decision forward error correction threshold has been achieved. Our
results demonstrate that dual-polarization NFT can work in practice and enable
an increased spectral efficiency in NFT-based communication systems, which are
currently based on single polarization channels
Assessing the Time Evolution of COVID-19 Effective Reproduction Number in Brazil
In this paper, we use a Bayesian method to estimate the effective
reproduction number (R(t)), in the context of monitoring the time evolution of
the COVID-19 pandemic in Brazil at different geographic levels. The focus of
this study is to investigate the similarities between the trends in the
evolution of such indicators at different subnational levels with the trends
observed nationally. The underlying question addressed is whether national
surveillance of such variables is enough to provide a picture of the epidemic
evolution in the country or if it may hide important localized trends. This is
particularly relevant in the scenario where health authorities use information
obtained from such indicators in the design of non-pharmaceutical intervention
policies to control the epidemic. A comparison between R(t) estimates and the
moving average (MA) of daily reported infections is also presented, which is
another commonly monitored variable. The analysis carried out in this paper is
based on the data of confirmed infected cases provided by a public repository.
The correlations between the time series of R(t) and MA in different geographic
levels are assessed. Comparing national with subnational trends, higher degrees
of correlation are found for the time series of R(t) estimates, compared to the
MA time series. Nevertheless, differences between national and subnational
trends are observed for both indicators, suggesting that local epidemiological
surveillance would be more suitable as an input to the design of
non-pharmaceutical intervention policies in Brazil, particularly for the least
populated states.Comment: Preprint of the manuscript accepted for publication at the Anais da
Academia Brasileira de Ci\^encias (AABC) in May 202
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