10,399 research outputs found
Massive Dirac surface states in topological insulator/magnetic insulator heterostructures
Topological insulators are new states of matter with a bulk gap and robust
gapless surface states protected by time-reversal symmetry. When time-reversal
symmetry is broken, the surface states are gapped, which induces a topological
response of the system to electromagnetic field--the topological
magnetoelectric effect. In this paper we study the behavior of topological
surface states in heterostructures formed by a topological insulator and a
magnetic insulator. Several magnetic insulators with compatible magnetic
structure and relatively good lattice matching with topological insulators
are identified, and the best
candidate material is found to be MnSe, an anti-ferromagnetic insulator. We
perform first-principles calculation in superlattices and
obtain the surface state bandstructure. The magnetic exchange coupling with
MnSe induces a gap of 54 meV at the surface states. In addition we tune
the distance between Mn ions and TI surface to study the distance dependence of
the exchange coupling.Comment: 8 pages, 7 figure
Linearly Supporting Feature Extraction For Automated Estimation Of Stellar Atmospheric Parameters
We describe a scheme to extract linearly supporting (LSU) features from
stellar spectra to automatically estimate the atmospheric parameters ,
log, and [Fe/H]. "Linearly supporting" means that the atmospheric
parameters can be accurately estimated from the extracted features through a
linear model. The successive steps of the process are as follow: first,
decompose the spectrum using a wavelet packet (WP) and represent it by the
derived decomposition coefficients; second, detect representative spectral
features from the decomposition coefficients using the proposed method Least
Absolute Shrinkage and Selection Operator (LARS); third, estimate the
atmospheric parameters , log, and [Fe/H] from the detected
features using a linear regression method. One prominent characteristic of this
scheme is its ability to evaluate quantitatively the contribution of each
detected feature to the atmospheric parameter estimate and also to trace back
the physical significance of that feature. This work also shows that the
usefulness of a component depends on both wavelength and frequency. The
proposed scheme has been evaluated on both real spectra from the Sloan Digital
Sky Survey (SDSS)/SEGUE and synthetic spectra calculated from Kurucz's NEWODF
models. On real spectra, we extracted 23 features to estimate , 62
features for log, and 68 features for [Fe/H]. Test consistencies between
our estimates and those provided by the Spectroscopic Sarameter Pipeline of
SDSS show that the mean absolute errors (MAEs) are 0.0062 dex for log
(83 K for ), 0.2345 dex for log, and 0.1564 dex for [Fe/H]. For
the synthetic spectra, the MAE test accuracies are 0.0022 dex for log
(32 K for ), 0.0337 dex for log, and 0.0268 dex for [Fe/H].Comment: 21 pages, 7 figures, 8 tables, The Astrophysical Journal Supplement
Series (accepted for publication
Combining the Transcorrelated Method with Full Configuration Interaction Quantum Monte Carlo: Application to the Homogeneous Electron Gas.
We suggest an efficient method to resolve electronic cusps in electronic structure calculations through the use of an effective transcorrelated Hamiltonian. This effective Hamiltonian takes a simple form for plane wave bases, containing up to two-body operators only, and its use incurs almost no additional computational overhead compared to that of the original Hamiltonian. We apply this method in combination with the full configuration interaction quantum Monte Carlo (FCIQMC) method to the homogeneous electron gas. As a projection technique, the non-Hermitian nature of the transcorrelated Hamiltonian does not cause complications or numerical difficulties for FCIQMC. The rate of convergence of the total energy to the complete basis set limit is improved from [Formula: see text] to [Formula: see text], where M is the total number of orbital basis functions
Peer-to-Peer EnergyTrade: A Distributed Private Energy Trading Platform
Blockchain is increasingly being used as a distributed, anonymous, trustless
framework for energy trading in smart grids. However, most of the existing
solutions suffer from reliance on Trusted Third Parties (TTP), lack of privacy,
and traffic and processing overheads. In our previous work, we have proposed a
Secure Private Blockchain-based framework (SPB) for energy trading to address
the aforementioned challenges. In this paper, we present a proof-on-concept
implementation of SPB on the Ethereum private network to demonstrates SPB's
applicability for energy trading. We benchmark SPB's performance against the
relevant state-of-the-art. The implementation results demonstrate that SPB
incurs lower overheads and monetary cost for end users to trade energy compared
to existing solutions
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