249 research outputs found
Group Iterative Spectrum Thresholding for Super-Resolution Sparse Spectral Selection
Recently, sparsity-based algorithms are proposed for super-resolution
spectrum estimation. However, to achieve adequately high resolution in
real-world signal analysis, the dictionary atoms have to be close to each other
in frequency, thereby resulting in a coherent design. The popular convex
compressed sensing methods break down in presence of high coherence and large
noise. We propose a new regularization approach to handle model collinearity
and obtain parsimonious frequency selection simultaneously. It takes advantage
of the pairing structure of sine and cosine atoms in the frequency dictionary.
A probabilistic spectrum screening is also developed for fast computation in
high dimensions. A data-resampling version of high-dimensional Bayesian
Information Criterion is used to determine the regularization parameters.
Experiments show the efficacy and efficiency of the proposed algorithms in
challenging situations with small sample size, high frequency resolution, and
low signal-to-noise ratio
-wave Pairing in BiS Superconductors
Recent angle resolved photoemission spectroscopy(ARPES) experiments have
suggested that BiS based superconductors are at very low electron doping.
Using random phase approximation(RPA) and functional renormalization group(FRG)
methods, we find that -wave pairing symmetry belonging to A
irreducible representation is dominant at electron doping . The pairing
symmetry is determined by inter-pocket nesting and orbital characters on the
Fermi surfaces and is robust in a two-orbital model including both Hund's
coupling , and Hubbard-like Coulomb interactions and with
relatively small (). With the increasing electron doping, the
g-wave state competes with both the s-wave and d-wave states
and no pairing symmetry emerges dominantly.Comment: published version, EPL(editor's choice
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