28,354 research outputs found
Superconductivity-induced Phonon Renormalization on NaFeCoAs
We report a study of the lattice dynamics in superconducting NaFeAs (Tc = 8
K) and doped NaFe0.97Co0.03As (Tc = 20 K) using Raman light scattering. Five of
the six phonon modes expected from group theory are observed. In contrast with
results obtained on iso-structural and iso-electronic LiFeAs, anomalous
broadening of Eg(As) and A1g(Na) modes upon cooling is observed in both
samples. In addition, in the Co-doped sample, a superconductivity-induced
renormalization of the frequency and linewidth of the B1g(Fe) vibration is
observed. This renormalization can not be understood within a single band and
simple multi-band approaches. A theoretical model that includes the effects of
SDW correlations along with sign-changing s-wave pairing state and interband
scattering has been developed to explain the observed behavior of the B1g(Fe)
mode.Comment: 10 pages; 6 figure
Comparing Deep Recurrent Networks Based on the MAE Random Sampling, a First Approach
Recurrent neural networks have demonstrated to be good at tackling prediction problems, however due to their high sensitivity to
hyper-parameter configuration, finding an appropriate network is a tough task. Automatic hyper-parameter optimization methods have emerged to find the most suitable configuration to a given problem, but these methods are not generally adopted because of their high computational cost. Therefore, in this study we extend the MAE random sampling, a low-cost method to compare single-hidden layer architectures, to multiple-hidden-layer ones. We validate empirically our proposal and show that it is possible to predict and compare the expected performance of an hyper-parameter configuration in a low-cost way.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
This research was partially funded by Ministerio de Economı́a, Industria y Competitividad, Gobierno de España, and European Regional Development Fund grant numbers TIN2016-81766-REDT (http://cirti.es) and TIN2017-88213-R (http://6city.lcc.uma.es)
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