Nonparametric Bayesian Density Modeling with Gaussian Processes

We present the Gaussian process density sampler (GPDS), an exchangeable generative model for use in nonparametric Bayesian density estimation. Samples drawn from the GPDS are consistent with exact, independent samples from a distribution defined by a density that is a transformation of a function drawn from a Gaussian process prior. Our formulation allows us to infer an unknown density from data using Markov chain Monte Carlo, which gives samples from the posterior distribution over density functions and from the predictive distribution on data space. We describe two such MCMC methods. Both methods also allow inference of the hyperparameters of the Gaussian process.

Auxiliary particle implementation of the probability hypothesis density filter

Optimal Bayesian multi-target filtering is, in general, computationally impractical owing to the high dimensionality of the multi-target state. The Probability Hypothesis Density (PHD) filter propagates the first moment of the multi-target posterior distribution. While this reduces the dimensionality of the problem, the PHD filter still involves intractable integrals in many cases of interest. Several authors have proposed Sequential Monte Carlo (SMC) implementations of the PHD filter. However, these implementations are the equivalent of the Bootstrap Particle Filter, and the latter is well known to be inefficient. Drawing on ideas from the Auxiliary Particle Filter (APF), we present a SMC implementation of the PHD filter which employs auxiliary variables to enhance its efficiency. Numerical examples are presented for two scenarios, including a challenging nonlinear observation model.

QM/MM simulation of liquid water with an adaptive quantum region.

The simulation of complex chemical systems often requires a multi-level description, in which a region of special interest is treated using a computationally expensive quantum mechanical (QM) model while its environment is described by a faster, simpler molecular mechanical (MM) model. Furthermore, studying dynamic effects in solvated systems or bio-molecules requires a variable definition of the two regions, so that atoms or molecules can be dynamically re-assigned between the QM and MM descriptions during the course of the simulation. Such reassignments pose a problem for traditional QM/MM schemes by exacerbating the errors that stem from switching the model at the boundary. Here we show that stable, long adaptive simulations can be carried out using density functional theory with the BLYP exchange-correlation functional for the QM model and a flexible TIP3P force field for the MM model without requiring adjustments of either. Using a primary benchmark system of pure water, we investigate the convergence of the liquid structure with the size of the QM region, and demonstrate that by using a sufficiently large QM region (with radius 6 Å) it is possible to obtain radial and angular distributions that, in the QM region, match the results of fully quantum mechanical calculations with periodic boundary conditions, and, after a smooth transition, also agree with fully MM calculations in the MM region. The key ingredient is the accurate evaluation of forces in the QM subsystem which we achieve by including an extended buffer region in the QM calculations. We also show that our buffered-force QM/MM scheme is transferable by simulating the solvated Cl(-) ion.

Growth of ultrahigh density single-walled carbon nanotube forests by improved catalyst design.

We have grown vertically aligned single-walled carbon nanotube forests with an area density of 1.5 × 10(13) cm(-2), the highest yet achieved, by reducing the average diameter of the nanotubes. We use a nanolaminate Fe-Al(2)O(3) catalyst design consisting of three layers of Al(2)O(3), Fe, and Al(2)O(3), in which the lower Al(2)O(3) layer is densified by an oxygen plasma treatment to increase its diffusion barrier properties, to allow a thinner catalyst layer to be used. This high nanotube density is desirable for using carbon nanotubes as interconnects in integrated circuits.

The Gaussian process density sampler

We present the Gaussian Process Density Sampler (GPDS), an exchangeable generative model for use in nonparametric Bayesian density estimation. Samples drawn from the GPDS are consistent with exact, independent samples from a fixed density function that is a transformation of a function drawn from a Gaussian process prior. Our formulation allows us to infer an unknown density from data using Markov chain Monte Carlo, which gives samples from the posterior distribution over density functions and from the predictive distribution on data space. We can also infer the hyperparameters of the Gaussian process. We compare this density modeling technique to several existing techniques on a toy problem and a skullreconstruction task.

Density of photon states in dye-doped chiral nematic liquid crystal cells in the presence of losses and gain

We calculate the density of photon states (DOS) of the normal modes in dye-doped chiral nematic liquid crystal (LC) cells in the presence of various loss mechanisms. Losses and gain are incorporated into the transmission characteristics through the introduction of a small imaginary part in the dielectric constant perpendicular and along the director, for which we assume no frequency dispersion. Theoretical results are presented on the DOS in the region of the photonic band gap for a range of values of the loss coefficient and different values of the optical anisotropy. The obtained values of the DOS at the photonic band gap edges predict a reversal of the dominant modes in the structure. Our results are found to be in good agreement with the experimentally obtained excitation thresholds in chiral nematic LC lasers. The behavior of the DOS is also discussed for amplifying LC cells providing additional insight to the lasing mechanism of these structures. © 2012 American Physical Society.

Density of photon states in dye-doped chiral nematic liquid crystal cells in the presence of losses and gain.

We calculate the density of photon states (DOS) of the normal modes in dye-doped chiral nematic liquid crystal (LC) cells in the presence of various loss mechanisms. Losses and gain are incorporated into the transmission characteristics through the introduction of a small imaginary part in the dielectric constant perpendicular and along the director, for which we assume no frequency dispersion. Theoretical results are presented on the DOS in the region of the photonic band gap for a range of values of the loss coefficient and different values of the optical anisotropy. The obtained values of the DOS at the photonic band gap edges predict a reversal of the dominant modes in the structure. Our results are found to be in good agreement with the experimentally obtained excitation thresholds in chiral nematic LC lasers. The behavior of the DOS is also discussed for amplifying LC cells providing additional insight to the lasing mechanism of these structures.

Density stratified environments: The double-tank method

We present an alternative method of producing density stratifications in the laboratory based on the 'double-tank' method proposed by Oster (Sci Am 213:70-76, 1965). We refer to Oster's method as the 'forced-drain' approach, as the volume flow rates between connecting tanks are controlled by mechanical pumps. We first determine the range of density profiles that may be established with the forced-drain approach other than the linear stratification predicted by Oster. The dimensionless density stratification is expressed analytically as a function of three ratios: the volume flow rate ratio n, the ratio of the initial liquid volumes λ and the ratio of the initial densities ψ. We then propose a method which does not require pumps to control the volume flow rates but instead allows the connecting tanks to drain freely under gravity. This is referred to as the 'free-drain' approach. We derive an expression for the density stratification produced and compare our predictions with saline stratifications established in the laboratory using the 'free-drain' extension of Oster's method. To assist in the practical application of our results we plot the region of parameter space that yield concave/convex or linear density profiles for both forced-drain and free-drain approaches. The free-drain approach allows the experimentalist to produce a broad range of density profiles by varying the initial liquid depths, cross-sectional and drain opening areas of the tanks. One advantage over the original Oster approach is that density profiles with an inflexion point can now be established. © 2008 Springer-Verlag.

Low temperature growth of ultra-high mass density carbon nanotube forests on conductive supports

We grow ultra-high mass density carbon nanotube forests at 450°C on Ti-coated Cu supports using Co-Mo co-catalyst. X-ray photoelectron spectroscopy shows Mo strongly interacts with Ti and Co, suppressing both aggregation and lifting off of Co particles and, thus, promoting the root growth mechanism. The forests average a height of 0.38 μm and a mass density of 1.6 g cm -3. This mass density is the highest reported so far, even at higher temperatures or on insulators. The forests and Cu supports show ohmic conductivity (lowest resistance ∼22 kΩ), suggesting Co-Mo is useful for applications requiring forest growth on conductors. © 2013 AIP Publishing LLC.

On the variation of the 2DEG charge density with the density of the surface donor traps in AiGaN/GaN transistors

Gallium nitride (GaN) has a bright future in high voltage device owing to its remarkable physical properties and the possibility of growing heterostructures on silicon substrates. GaN High Electron Mobility Transistors (HEMTs) are expected to make a strong impact in off line applications and LED drives. However, unlike in silicon-based power devices, the on-state resistance of HEMT devices is hugely influenced by donor and acceptor traps at interfaces and in the bulk. This study focuses on the influence of donor traps located at the top interface between the semiconductor layer and the silicon nitride on the 2DEG density. It is shown through TCAD simulations and analytical study that the 2DEG charge density has an 'S' shape variation with two distinctive 'flat' regions, wherein it is not affected by the donor concentration, and one linear region. wherein the channel density increases proportionally with the donor concentration. We also show that the upper threshold value of the donor concentration within this 'S' shape increases significantly with the AIGaN thickness and the Al mole fraction and is highly affected by the presence of a thin GaN cap layer. © 2013 IEEE.