7,092 research outputs found
Electron Monte Carlo Simulations of Nanoporous Si Thin Films -- The Influence of Pore-Edge Charges
Electron transport within nanostructures can be important to varied
engineering applications, such as thermoelectrics and nanoelectronics. In
theoretical studies, electron Monte Carlo simulations are widely used as an
alternative approach to solving the electron Boltzmann transport equation,
where the energy-dependent electron scattering, exact structure shape, and
detailed electric field distribution can be fully incorporated. In this work,
such electron Monte Carlo simulations are employed to predict the electrical
conductivity of periodic nanoporous Si films that have been widely studied for
thermoelectric applications. The focus is on the influence of pore-edge charges
on the electron transport. The results are further compared to our previous
modeling [Hao et al., J. Appl. Phys. 121, 094308 (2017)], where the pore-edge
electric field has its own scattering rate to be added to the scattering rates
of other mechanisms
Precise photoproduction of the charged top-pions at the LHC with forward detector acceptances
We study the photoproduction of the charged top-pion predicted by the top
triangle moose () model (a deconstructed version of the topcolor-assisted
technicolor model) via the processes at the 14 Large Hadron Collider ()
including next-to-leading order () corrections. Our results show
that the production cross sections and distributions are sensitive to the free
parameters and . Typical correction value is and does not depend much on as well as the forward
detector acceptances.Comment: 21pages, 7figures. arXiv admin note: text overlap with
arXiv:1201.4364 by other author
Multiple Change-point Detection: a Selective Overview
Very long and noisy sequence data arise from biological sciences to social
science including high throughput data in genomics and stock prices in
econometrics. Often such data are collected in order to identify and understand
shifts in trend, e.g., from a bull market to a bear market in finance or from a
normal number of chromosome copies to an excessive number of chromosome copies
in genetics. Thus, identifying multiple change points in a long, possibly very
long, sequence is an important problem. In this article, we review both
classical and new multiple change-point detection strategies. Considering the
long history and the extensive literature on the change-point detection, we
provide an in-depth discussion on a normal mean change-point model from aspects
of regression analysis, hypothesis testing, consistency and inference. In
particular, we present a strategy to gather and aggregate local information for
change-point detection that has become the cornerstone of several emerging
methods because of its attractiveness in both computational and theoretical
properties.Comment: 26 pages, 2 figure
Fairness of machine learning applications in criminal justice: Insights from evaluation of COMPAS
Machine learning has been widely applied in facilitating high-staked decision making, however, there is an increasing concern on hidden biases behind these methodologies. In the criminal justice context, there is a lasting debate on the fairness of Correctional Defendant Management Profiling for Alternative Sanctions (COMPAS) which uses Random Forest as foundation for recidivism risk predictions. But we noticed that fairness of the algorithm is genuinely measured by two different criterion: calibration and equalized odds. In this research we trained a Random Forest classifier and examined why its application is not eligible in achieving fairness based on different measures. Results show that both of the scales were not achieved on all the six racial groups in COMPAS data set which calls for further evaluation on the algorithm design and more efforts in defining a universal definition and measuring standard on algorithms fairness
Scale Invariance vs. Conformal Invariance: Holographic Two-Point Functions in Horndeski Gravity
We consider Einstein-Horndeski gravity with a negative bare constant as a
holographic model to investigate whether a scale invariant quantum field theory
can exist without the full conformal invariance. Einstein-Horndeski gravity can
admit two different AdS vacua. One is conformal, and the holographic two-point
functions of the boundary energy-momentum tensor are the same as the ones
obtained in Einstein gravity. The other AdS vacuum, which arises at some
critical point of the coupling constants, preserves the scale invariance but
not the special conformal invariance due to the logarithmic radial dependence
of the Horndeski scalar. In addition to the transverse and traceless graviton
modes, the theory admits an additional trace/scalar mode in the scale invariant
vacuum. We obtain the two-point functions of the corresponding boundary
operators. We find that the trace/scalar mode gives rise to an non-vanishing
two-point function, which distinguishes the scale invariant theory from the
conformal theory. The two-point function vanishes in , where the full
conformal symmetry is restored. Our results indicate the strongly coupled scale
invariant unitary quantum field theory may exist in without the full
conformal symmetry. The operator that is dual to the bulk trace/scalar mode
however violates the dominant energy condition.Comment: Latex, 28 pages, comments and references adde
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