Rotational cut-off and anharmonicity effects on thermodynamic properties of gases at high temperatures

The exact expressions for the partition function (Q) and the coefficient of specific heat at constant volume (Cv) for a rotating-anharmonic oscillator molecule, including coupling and rotational cut-off, have been formulated and values of Q and Cv have been computed in the temperature range of 100 to 100,000 K for O2, N2 and H2 gases. The exact Q and Cv values are also compared with the corresponding rigid-rotator harmonic-oscillator (infinite rotational and vibrational levels) and rigid-rotator anharmonic-oscillator (infinite rotational levels) values. The rigid-rotator harmonic-oscillator approximation can be accepted for temperatures up to about 5000 K for O2 and N2. Beyond these temperatures the error in Cv will be significant, because of anharmonicity and rotational cut-off effects. For H2, the rigid-rotator harmonic-oscillator approximation becomes unacceptable even for temperatures as low as 2000 K.

Modeling ecological and evolutionary processes in spatially structured populations

Many species inhabit fragmented landscapes, resulting either from anthropogenic or from natural processes. The ecological and evolutionary dynamics of spatially structured populations are affected by a complex interplay between endogenous and exogenous factors. The metapopulation approach, simplifying the landscape to a discrete set of patches of breeding habitat surrounded by unsuitable matrix, has become a widely applied paradigm for the study of species inhabiting highly fragmented landscapes. In this thesis, I focus on the construction of biologically realistic models and their parameterization with empirical data, with the general objective of understanding how the interactions between individuals and their spatially structured environment affect ecological and evolutionary processes in fragmented landscapes. I study two hierarchically structured model systems, which are the Glanville fritillary butterfly in the Åland Islands, and a system of two interacting aphid species in the Tvärminne archipelago, both being located in South-Western Finland. The interesting and challenging feature of both study systems is that the population dynamics occur over multiple spatial scales that are linked by various processes. My main emphasis is in the development of mathematical and statistical methodologies. For the Glanville fritillary case study, I first build a Bayesian framework for the estimation of death rates and capture probabilities from mark-recapture data, with the novelty of accounting for variation among individuals in capture probabilities and survival. I then characterize the dispersal phase of the butterflies by deriving a mathematical approximation of a diffusion-based movement model applied to a network of patches. I use the movement model as a building block to construct an individual-based evolutionary model for the Glanville fritillary butterfly metapopulation. I parameterize the evolutionary model using a pattern-oriented approach, and use it to study how the landscape structure affects the evolution of dispersal. For the aphid case study, I develop a Bayesian model of hierarchical multi-scale metapopulation dynamics, where the observed extinction and colonization rates are decomposed into intrinsic rates operating specifically at each spatial scale. In summary, I show how analytical approaches, hierarchical Bayesian methods and individual-based simulations can be used individually or in combination to tackle complex problems from many different viewpoints. In particular, hierarchical Bayesian methods provide a useful tool for decomposing ecological complexity into more tractable components.

Performance reliability of high-maintenance systems

The time–history of the performance of a system is treated as a stochastic corrective process, in which deterioration due to aging is counteracted at brief maintenance checks. Using a diffusion approximation for the deterioration, simple models are proposed for describing maintenance either by component replacement or by performance restoration. Equilibrium solutions of the models show that the performance has a probability distribution with exponential tails: the uncritical use of Gaussians can grossly underestimate the probability of poor performance. The proposed models are supported by recent observational evidence on aircraft track-keeping errors, which are shown to follow the modified exponential distribution derived here. The analysis also brings out the relation between the deterioration characteristics of the system and the intensity of the maintenance effort required to achieve a given performance reliability.

A curve shortening flow rule for closed embedded plane curves with a prescribed rate of change in enclosed area

Motivated by a problem from fluid mechanics, we consider a generalization of the standard curve shortening flow problem for a closed embedded plane curve such that the area enclosed by the curve is forced to decrease at a prescribed rate. Using formal asymptotic and numerical techniques, we derive possible extinction shapes as the curve contracts to a point, dependent on the rate of decreasing area; we find there is a wider class of extinction shapes than for standard curve shortening, for which initially simple closed curves are always asymptotically circular. We also provide numerical evidence that self-intersection is possible for non-convex initial conditions, distinguishing between pinch-off and coalescence of the curve interior.

Ellipsometric study of Atomic Layer Deposited TiO2 thin films

Atomic layer deposition was used to obtain TiO2 thin films on Si (100) and fused quartz, using a novel metal organic precursor. The films were grown at 400 degrees C, varying the amount of oxygen used as the reactive gas. X-ray diffraction showed the films to be crystalline, with a mixture of anatase and rutile phases. To investigate their optical properties, ellipsometric measurements were made in the UV-Vis-NIR range (300-1700 nm). Spectral distribution of various optical constants like refractive index (n), absorption index (k), transmittance (T), reflectance (R), absorption (A) were calculated by employing Bruggemann's effective medium approximation (BEMA) and Maxwell-Garnet effective medium approximation, in conjunction with the Cauchy and Forouhi-Bloomer (FB) dispersion relations. A layered optical model has been proposed which gives the thickness, elemental and molecular composition, amorphicity and roughness (morphology) of the TiO2 film surface and and the film/substrate interface, as a function of oxygen flow rate The spectral distribution of the optical band gap (E-g(opt)), complex dielectric constants (epsilon' and epsilon''), and optical conductivity (sigma(opt)), has also been determined.

Qed On The Groenewold-Moyal Plane

We investigate a version of noncommutative QED where the interaction term, although natural, breaks the spin-statistics connection. We calculate e(-) + e(-) -> e(-) + e(-) and gamma + e(-) -> gamma + e(-) cross-sections in the tree approximation and explicitly display their dependence on theta(mu nu). Remarkably the zero of the elastic e(-) + e(-) -> e(-) + e(-) cross-section at 90 degrees in the center-of-mass system, which is due to Pauli principle, is shifted away as a function of theta(mu nu) and energy.

Expansion of high pressure gas into air - A more realistic blast wave model

In this paper, we consider a more realistic model of a spherical blast wave of moderate strength. An arbitrary number of terms for the series solution in each of the regions behind the main shock - the expansion region, the nearly uniform region outside the main expansion and the region between the contact surface and the main shock, have been generated and matched across the boundaries. We then study the convergence of the solution by using Pade approximation. It constitutes a genuine analytic solution for a moderately strong explosion, which, however, does not involve a secondary shock. The pressure distribution behind the shock however shows some significant changes in the location of the tail of the rarefaction and the interface, in comparison to the planar problem. The theory developed for the spherical blasts is also extended to cylindrical blasts. The results are compared with the numerical solution.

Efficient probabilistic contingency analysis through a stability measure considering wind perturbation

The integration of stochastic wind power has accentuated a challenge for power system stability assessment. Since the power system is a time-variant system under wind generation fluctuations, pure time-domain simulations are difficult to provide real-time stability assessment. As a result, the worst-case scenario is simulated to give a very conservative assessment of system transient stability. In this study, a probabilistic contingency analysis through a stability measure method is proposed to provide a less conservative contingency analysis which covers 5-min wind fluctuations and a successive fault. This probabilistic approach would estimate the transfer limit of a critical line for a given fault with stochastic wind generation and active control devices in a multi-machine system. This approach achieves a lower computation cost and improved accuracy using a new stability measure and polynomial interpolation, and is feasible for online contingency analysis.

Natural actor-critic algorithms

We present four new reinforcement learning algorithms based on actor-critic, natural-gradient and functi approximation ideas,and we provide their convergence proofs. Actor-critic reinforcement learning methods are online approximations to policy iteration in which the value-function parameters are estimated using temporal difference learning and the policy parameters are updated by stochastic gradient descent. Methods based on policy gradients in this way are of special interest because of their compatibility with function-approximation methods, which are needed to handle large or infinite state spaces. The use of temporal difference learning in this way is of special interest because in many applications it dramatically reduces the variance of the gradient estimates. The use of the natural gradient is of interest because it can produce better conditioned parameterizations and has been shown to further reduce variance in some cases. Our results extend prior two-timescale convergence results for actor-critic methods by Konda and Tsitsiklis by using temporal difference learning in the actor and by incorporating natural gradients. Our results extend prior empirical studies of natural actor-critic methods by Peters, Vijayakumar and Schaal by providing the first convergence proofs and the first fully incremental algorithms.

Multicarrier conduction and Boltzmann transport analysis of heavy hole mobility in HgCdTe near room temperature

Magnetotransport measurements in pulsed fields up to 15 T have been performed on mercury cadmium telluride (Hg1-xCdxTe, x similar to 0.2) bulk as well as liquid phase epitaxially grown samples to obtain the resistivity and conductivity tensors in the temperature range 220-300 K. Mobilities and densities of various carriers participating in conduction have been extracted using both conventional multicarrier fitting (MCF) and mobility spectrum analysis. The fits to experimental data, particularly at the highest magnetic fields, were substantially improved when MCF is applied to minimize errors simultaneously on both resistivity and conductivity tensors. The semiclassical Boltzmann transport equation has been solved without using adjustable parameters by incorporating the following scattering mechanisms to fit the mobility: ionized impurity, polar and nonpolar optical phonons, acoustic deformation potential, and alloy disorder. Compared to previous estimates based on the relaxation time approximation with outscattering only, polar optical scattering and ionized impurity scattering limited mobilities are shown to be larger due to the correct incorporation of the inscattering term taking into account the overlap integrals in the valence band.

Dynamics of loop formation in a semiflexible polymer

The dynamics of loop formation by linear polymer chains has been a topic of several theoretical and experimental studies. Formation of loops and their opening are key processes in many important biological processes. Loop formation in flexible chains has been extensively studied by many groups. However, in the more realistic case of semiflexible polymers, not much results are available. In a recent study [K. P. Santo and K. L. Sebastian, Phys. Rev. E 73, 031923 (2006)], we investigated opening dynamics of semiflexible loops in the short chain limit and presented results for opening rates as a function of the length of the chain. We presented an approximate model for a semiflexible polymer in the rod limit based on a semiclassical expansion of the bending energy of the chain. The model provided an easy way to describe the dynamics. In this paper, using this model, we investigate the reverse process, i.e., the loop formation dynamics of a semiflexible polymer chain by describing the process as a diffusion-controlled reaction. We make use of the ``closure approximation'' of Wilemski and Fixman [G. Wilemski and M. Fixman, J. Chem. Phys. 60, 878 (1974)], in which a sink function is used to represent the reaction. We perform a detailed multidimensional analysis of the problem and calculate closing times for a semiflexible chain. We show that for short chains, the loop formation time tau decreases with the contour length of the polymer. But for longer chains, it increases with length obeying a power law and so it has a minimum at an intermediate length. In terms of dimensionless variables, the closing time is found to be given by tau similar to L-n exp(const/L), where n=4.5-6. The minimum loop formation time occurs at a length L-m of about 2.2-2.4. These are, indeed, the results that are physically expected, but a multidimensional analysis leading to these results does not seem to exist in the literature so far.

Geometric Representation of Graphs in Low Dimension Using Axis Parallel Boxes

An axis-parallel k-dimensional box is a Cartesian product R-1 x R-2 x...x R-k where R-i (for 1 <= i <= k) is a closed interval of the form [a(i), b(i)] on the real line. For a graph G, its boxicity box(G) is the minimum dimension k, such that G is representable as the intersection graph of (axis-parallel) boxes in k-dimensional space. The concept of boxicity finds applications in various areas such as ecology, operations research etc. A number of NP-hard problems are either polynomial time solvable or have much better approximation ratio on low boxicity graphs. For example, the max-clique problem is polynomial time solvable on bounded boxicity graphs and the maximum independent set problem for boxicity d graphs, given a box representation, has a left perpendicular1 + 1/c log n right perpendicular(d-1) approximation ratio for any constant c >= 1 when d >= 2. In most cases, the first step usually is computing a low dimensional box representation of the given graph. Deciding whether the boxicity of a graph is at most 2 itself is NP-hard. We give an efficient randomized algorithm to construct a box representation of any graph G on n vertices in left perpendicular(Delta + 2) ln nright perpendicular dimensions, where Delta is the maximum degree of G. This algorithm implies that box(G) <= left perpendicular(Delta + 2) ln nright perpendicular for any graph G. Our bound is tight up to a factor of ln n. We also show that our randomized algorithm can be derandomized to get a polynomial time deterministic algorithm. Though our general upper bound is in terms of maximum degree Delta, we show that for almost all graphs on n vertices, their boxicity is O(d(av) ln n) where d(av) is the average degree.