5,660 research outputs found
A Logarithmic Conformal Field Theory Solution For Two Dimensional Magnetohydrodynamics In Presence of The Alf'ven Effect
When Alf`ven effect is peresent in magnetohydrodynamics one is naturally lead
to consider conformal field theories, which have logarithmic terms in their
correlation functions. We discuss the implications of such logarithmic terms
and find a unique conformal field theory with centeral charge
, within the border of the minimal series, which satisfies
all the constraints. The energy espectrum is found to be \newline .Comment: Latex, 9 page
Analysis of Non-stationary Data for Heart-Rate Fluctuations in Terms of Drift and Diffusion Coefficients
We describe a method for analyzing the stochasticity in the non-stationary
data for the beat-to-beat fluctuations in the heart rates of healthy subjects,
as well as those with congestive heart failure. The method analyzes the returns
time series of the data as a Markov process, and computes the Markov time
scale, i.e., the time scale over which the data are a Markov process. We also
construct an effective stochastic continuum equation for the return series. We
show that the drift and diffusion coefficients, as well as the amplitude of the
returns time series for healthy subjects are distinct from those with CHF.
Thus, the method may potentially provide a diagnostic tool for distinguishing
healthy subjects from those with congestive heart failure, as it can
distinguish small differences between the data for the two classes of subjects
in terms of well-defined and physically-motivated quantities.Comment: 6 pages, two columns, 6 figure
On conformal Jordan cells of finite and infinite rank
This work concerns in part the construction of conformal Jordan cells of
infinite rank and their reductions to conformal Jordan cells of finite rank. It
is also discussed how a procedure similar to Lie algebra contractions may
reduce a conformal Jordan cell of finite rank to one of lower rank. A conformal
Jordan cell of rank one corresponds to a primary field. This offers a picture
in which any finite conformal Jordan cell of a given conformal weight may be
obtained from a universal covering cell of the same weight but infinite rank.Comment: 9 pages, LaTeX, v2: typo corrected, comments added, version to be
publishe
Temperature Dependence Of The Electrical Resistivity Of LaxLu1-xAs
We investigate the temperature-dependent resistivity of single-crystalline films of LaxLu1-xAs over the 5-300 K range. The resistivity was separated into lattice, carrier and impurity scattering regions. The effect of impurity scattering is significant below 20 K, while carrier scattering dominates at 20-80 K and lattice scattering dominates above 80 K. All scattering regions show strong dependence on the La content of the films. While the resistivity of 600 nm LuAs films agree well with the reported bulk resistivity values, 3 nm films possessed significantly higher resistivity, suggesting that interfacial roughness significantly impacts the scattering of carriers at the nanoscale limit. (C) 2013 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 Unported License.Microelectronics Research Cente
Pseudospectral Model Predictive Control under Partially Learned Dynamics
Trajectory optimization of a controlled dynamical system is an essential part
of autonomy, however many trajectory optimization techniques are limited by the
fidelity of the underlying parametric model. In the field of robotics, a lack
of model knowledge can be overcome with machine learning techniques, utilizing
measurements to build a dynamical model from the data. This paper aims to take
the middle ground between these two approaches by introducing a semi-parametric
representation of the underlying system dynamics. Our goal is to leverage the
considerable information contained in a traditional physics based model and
combine it with a data-driven, non-parametric regression technique known as a
Gaussian Process. Integrating this semi-parametric model with model predictive
pseudospectral control, we demonstrate this technique on both a cart pole and
quadrotor simulation with unmodeled damping and parametric error. In order to
manage parametric uncertainty, we introduce an algorithm that utilizes Sparse
Spectrum Gaussian Processes (SSGP) for online learning after each rollout. We
implement this online learning technique on a cart pole and quadrator, then
demonstrate the use of online learning and obstacle avoidance for the dubin
vehicle dynamics.Comment: Accepted but withdrawn from AIAA Scitech 201
Boson Sampling from Gaussian States
We pose a generalized Boson Sampling problem. Strong evidence exists that
such a problem becomes intractable on a classical computer as a function of the
number of Bosons. We describe a quantum optical processor that can solve this
problem efficiently based on Gaussian input states, a linear optical network
and non-adaptive photon counting measurements. All the elements required to
build such a processor currently exist. The demonstration of such a device
would provide the first empirical evidence that quantum computers can indeed
outperform classical computers and could lead to applications
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