9,177 research outputs found
Suitability for Global Maize Production: A Methodology Based on Spatial Analysis
A methodology based on spatial analysis is proposed to investigate suitability of crop, and then applied to analyzing the suitability for global maize production. The suitable and unsuitable maize cultivated regions are given based on the analysis, and maize cultivated regions sensitive to economic incentive is also illustrated and discussed.Crop Production/Industries,
Photon Entanglement Through Brain Tissue.
Photon entanglement, the cornerstone of quantum correlations, provides a level of coherence that is not present in classical correlations. Harnessing it by study of its passage through organic matter may offer new possibilities for medical diagnosis technique. In this work, we study the preservation of photon entanglement in polarization, created by spontaneous parametric down-conversion, after one entangled photon propagates through multiphoton-scattering brain tissue slices with different thickness. The Tangle-Entropy (TS) plots show the strong preservation of entanglement of photons propagating in brain tissue. By spatially filtering the ballistic scattering of an entangled photon, we find that its polarization entanglement is preserved and non-locally correlated with its twin in the TS plots. The degree of entanglement correlates better with structure and water content than with sample thickness
On-board monitoring of 2-D spatially-resolved temperatures in cylindrical lithium-ion batteries: Part II. State estimation via impedance-based temperature sensing
Impedance-based temperature detection (ITD) is a promising approach for rapid
estimation of internal cell temperature based on the correlation between
temperature and electrochemical impedance. Previously, ITD was used as part of
an Extended Kalman Filter (EKF) state-estimator in conjunction with a thermal
model to enable estimation of the 1-D temperature distribution of a cylindrical
lithium-ion battery. Here, we extend this method to enable estimation of the
2-D temperature field of a battery with temperature gradients in both the
radial and axial directions.
An EKF using a parameterised 2-D spectral-Galerkin model with ITD measurement
input (the imaginary part of the impedance at 215 Hz) is shown to accurately
predict the core temperature and multiple surface temperatures of a 32113
LiFePO cell, using current excitation profiles based on an Artemis HEV
drive cycle. The method is validated experimentally on a cell fitted with a
heat sink and asymmetrically cooled via forced air convection.
A novel approach to impedance-temperature calibration is also presented,
which uses data from a single drive cycle, rather than measurements at multiple
uniform cell temperatures as in previous studies. This greatly reduces the time
required for calibration, since it overcomes the need for repeated cell thermal
equalization.Comment: 11 pages, 8 figures, submitted to the Journal of Power Source
Matrix-free GPU implementation of a preconditioned conjugate gradient solver for anisotropic elliptic PDEs
Many problems in geophysical and atmospheric modelling require the fast
solution of elliptic partial differential equations (PDEs) in "flat" three
dimensional geometries. In particular, an anisotropic elliptic PDE for the
pressure correction has to be solved at every time step in the dynamical core
of many numerical weather prediction models, and equations of a very similar
structure arise in global ocean models, subsurface flow simulations and gas and
oil reservoir modelling. The elliptic solve is often the bottleneck of the
forecast, and an algorithmically optimal method has to be used and implemented
efficiently. Graphics Processing Units have been shown to be highly efficient
for a wide range of applications in scientific computing, and recently
iterative solvers have been parallelised on these architectures. We describe
the GPU implementation and optimisation of a Preconditioned Conjugate Gradient
(PCG) algorithm for the solution of a three dimensional anisotropic elliptic
PDE for the pressure correction in NWP. Our implementation exploits the strong
vertical anisotropy of the elliptic operator in the construction of a suitable
preconditioner. As the algorithm is memory bound, performance can be improved
significantly by reducing the amount of global memory access. We achieve this
by using a matrix-free implementation which does not require explicit storage
of the matrix and instead recalculates the local stencil. Global memory access
can also be reduced by rewriting the algorithm using loop fusion and we show
that this further reduces the runtime on the GPU. We demonstrate the
performance of our matrix-free GPU code by comparing it to a sequential CPU
implementation and to a matrix-explicit GPU code which uses existing libraries.
The absolute performance of the algorithm for different problem sizes is
quantified in terms of floating point throughput and global memory bandwidth.Comment: 18 pages, 7 figure
Efficient separation of the orbital angular momentum eigenstates of light
Orbital angular momentum (OAM) of light is an attractive degree of freedom
for funda- mentals studies in quantum mechanics. In addition, the discrete
unbounded state-space of OAM has been used to enhance classical and quantum
communications. Unambiguous mea- surement of OAM is a key part of all such
experiments. However, state-of-the-art methods for separating single photons
carrying a large number of different OAM values are limited to a theoretical
separation efficiency of about 77 percent. Here we demonstrate a method which
uses a series of unitary optical transformations to enable the measurement of
lights OAM with an experimental separation efficiency of more than 92 percent.
Further, we demonstrate the separation of modes in the angular position basis,
which is mutually unbiased with respect to the OAM basis. The high degree of
certainty achieved by our method makes it particu- larly attractive for
enhancing the information capacity of multi-level quantum cryptography systems
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