Viscous instability of a compressible round jet

The compressible linear stability equations are derived from the Navier Stokes equations in cylindrical polar coordinates. Numerical solutions for locally parallel flow are found using a direct matrix method. Discretization with compact finite difference is found to have better convergence properties than a Chebyshev spectral method for a round jet test case. The method is validated against previous results and convergence is tested for a range of jet profiles. Finally and en method is used to determine the dominant frequency of a Mach 0.9 jet

Calculation of Mutual Information for Partially Coherent Gaussian Channels with Applications to Fiber Optics

The mutual information between a complex-valued channel input and its complex-valued output is decomposed into four parts based on polar coordinates: an amplitude term, a phase term, and two mixed terms. Numerical results for the additive white Gaussian noise (AWGN) channel with various inputs show that, at high signal-to-noise ratio (SNR), the amplitude and phase terms dominate the mixed terms. For the AWGN channel with a Gaussian input, analytical expressions are derived for high SNR. The decomposition method is applied to partially coherent channels and a property of such channels called "spectral loss" is developed. Spectral loss occurs in nonlinear fiber-optic channels and it may be one effect that needs to be taken into account to explain the behavior of the capacity of nonlinear fiber-optic channels presented in recent studies.Comment: 30 pages, 9 figures, accepted for publication in IEEE Transactions on Information Theor

Steady advection-diffusion around finite absorbers in two-dimensional potential flows

We perform an exhaustive study of the simplest, nontrivial problem in advection-diffusion -- a finite absorber of arbitrary cross section in a steady two-dimensional potential flow of concentrated fluid. This classical problem has been studied extensively in the theory of solidification from a flowing melt, and it also arises in Advection-Diffusion-Limited Aggregation. In both cases, the fundamental object is the flux to a circular disk, obtained by conformal mapping from more complicated shapes. We construct the first accurate numerical solution using an efficient new method, which involves mapping to the interior of the disk and using a spectral method in polar coordinates. Our method also combines exact asymptotics and an adaptive mesh to handle boundary layers. Starting from a well-known integral equation in streamline coordinates, we also derive new, high-order asymptotic expansions for high and low P\'eclet numbers (\Pe). Remarkably, the `high' \Pe expansion remains accurate even for such low \Pe as $10^{-3}$. The two expansions overlap well near \Pe = 0.1, allowing the construction of an analytical connection formula that is uniformly accurate for all \Pe and angles on the disk with a maximum relative error of 1.75%. We also obtain an analytical formula for the Nusselt number ($\Nu$) as a function of the P\'eclet number with a maximum relative error of 0.53% for all possible geometries. Because our finite-plate problem can be conformally mapped to other geometries, the general problem of two-dimensional advection-diffusion past an arbitrary finite absorber in a potential flow can be considered effectively solved.Comment: 29 pages, 12 figs (mostly in color

A method to localize gamma-ray bursts using POLAR

The hard X-ray polarimeter POLAR aims to measure the linear polarization of the 50-500 keV photons arriving from the prompt emission of gamma-ray bursts (GRBs). The position in the sky of the detected GRBs is needed to determine their level of polarization. We present here a method by which, despite of the polarimeter incapability of taking images, GRBs can be roughly localized using POLAR alone. For this purpose scalers are attached to the output of the 25 multi-anode photomultipliers (MAPMs) that collect the light from the POLAR scintillator target. Each scaler measures how many GRB photons produce at least one energy deposition above 50 keV in the corresponding MAPM. Simulations show that the relative outputs of the 25 scalers depend on the GRB position. A database of very strong GRBs simulated at 10201 positions has been produced. When a GRB is detected, its location is calculated searching the minimum of the chi2 obtained in the comparison between the measured scaler pattern and the database. This GRB localization technique brings enough accuracy so that the error transmitted to the 100% modulation factor is kept below 10% for GRBs with fluence Ftot \geq 10^(-5) erg cm^(-2) . The POLAR localization capability will be useful for those cases where no other instruments are simultaneously observing the same field of view.Comment: 13 pages, 10 figure

SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels

We present Spline-based Convolutional Neural Networks (SplineCNNs), a variant of deep neural networks for irregular structured and geometric input, e.g., graphs or meshes. Our main contribution is a novel convolution operator based on B-splines, that makes the computation time independent from the kernel size due to the local support property of the B-spline basis functions. As a result, we obtain a generalization of the traditional CNN convolution operator by using continuous kernel functions parametrized by a fixed number of trainable weights. In contrast to related approaches that filter in the spectral domain, the proposed method aggregates features purely in the spatial domain. In addition, SplineCNN allows entire end-to-end training of deep architectures, using only the geometric structure as input, instead of handcrafted feature descriptors. For validation, we apply our method on tasks from the fields of image graph classification, shape correspondence and graph node classification, and show that it outperforms or pars state-of-the-art approaches while being significantly faster and having favorable properties like domain-independence.Comment: Presented at CVPR 201

Spectral solver for Cauchy problems in polar coordinates using discrete Hankel transforms

We introduce a Fourier-Bessel-based spectral solver for Cauchy problems featuring Laplacians in polar coordinates under homogeneous Dirichlet boundary conditions. We use FFTs in the azimuthal direction to isolate angular modes, then perform discrete Hankel transform (DHT) on each mode along the radial direction to obtain spectral coefficients. The two transforms are connected via numerical and cardinal interpolations. We analyze the boundary-dependent error bound of DHT; the worst case is $\sim N^{-3/2}$, which governs the method, and the best $\sim e^{-N}$, which then the numerical interpolation governs. The complexity is $O[N^3]$. Taking advantage of Bessel functions being the eigenfunctions of the Laplacian operator, we solve linear equations for all times. For non-linear equations, we use a time-splitting method to integrate the solutions. We show examples and validate the method on the two-dimensional wave equation, which is linear, and on two non-linear problems: a time-dependent Poiseuille flow and the flow of a Bose-Einstein condensate on a disk