Carbon Ignition in Type Ia Supernovae: An Analytic Model

The observable properties of a Type Ia supernova are sensitive to how the nuclear runaway ignites in a Chandrasekhar mass white dwarf - at a single point at its center, off-center, or at multiple points and times. We present a simple analytic model for the runaway based upon a combination of stellar mixing-length theory and recent advances in understanding Rayleigh-Benard convection. The convective flow just prior to runaway is likely to have a strong dipolar component, though higher multipoles may contribute appreciably at the very high Rayleigh number (10$^{25}$) appropriate to the white dwarf core. A likely outcome is multi-point ignition with an exponentially increasing number of ignition points during the few tenths of a second that it takes the runaway to develop. The first sparks ignite approximately 150 - 200 km off center, followed by ignition at smaller radii. Rotation may be important to break the dipole asymmetry of the ignition and give a healthy explosion.Comment: 14 pages, 0 figures, submitted to ApJ, corrected typo in first author's nam

Dielectric function and plasmons in graphene

The electromagnetic response of graphene, expressed by the dielectric function, and the spectrum of collective excitations are studied as a function of wave vector and frequency. Our calculation is based on the full band structure, calculated within the tight-binding approximation. As a result, we find plasmons whose dispersion is similar to that obtained in the single-valley approximation by Dirac fermions. In contrast to the latter, however, we find a stronger damping of the plasmon modes due to inter-band absorption. Our calculation also reveals effects due to deviations from the linear Dirac spectrum as we increase the Fermi energy, indicating an anisotropic behavior with respect to the wave vector of the external electromagnetic field

Neural-Network Vector Controller for Permanent-Magnet Synchronous Motor Drives: Simulated and Hardware-Validated Results

This paper focuses on current control in a permanentmagnet synchronous motor (PMSM). The paper has two main objectives: The first objective is to develop a neural-network (NN) vector controller to overcome the decoupling inaccuracy problem associated with conventional PI-based vector-control methods. The NN is developed using the full dynamic equation of a PMSM, and trained to implement optimal control based on approximate dynamic programming. The second objective is to evaluate the robust and adaptive performance of the NN controller against that of the conventional standard vector controller under motor parameter variation and dynamic control conditions by (a) simulating the behavior of a PMSM typically used in realistic electric vehicle applications and (b) building an experimental system for hardware validation as well as combined hardware and simulation evaluation. The results demonstrate that the NN controller outperforms conventional vector controllers in both simulation and hardware implementation

Double Quantum Dots in Carbon Nanotubes

We study the two-electron eigenspectrum of a carbon-nanotube double quantum dot with spin-orbit coupling. Exact calculation are combined with a simple model to provide an intuitive and accurate description of single-particle and interaction effects. For symmetric dots and weak magnetic fields, the two-electron ground state is antisymmetric in the spin-valley degree of freedom and is not a pure spin-singlet state. When double occupation of one dot is favored by increasing the detuning between the dots, the Coulomb interaction causes strong correlation effects realized by higher orbital-level mixing. Changes in the double-dot configuration affect the relative strength of the electron-electron interactions and can lead to different ground state transitions. In particular, they can favor a ferromagnetic ground state both in spin and valley degrees of freedom. The strong suppression of the energy gap can cause the disappearance of the Pauli blockade in transport experiments and thereby can also limit the stability of spin-qubits in quantum information proposals. Our analysis is generalized to an array of coupled dots which is expected to exhibit rich many-body behavior.Comment: 14 pages, 11 pages and 1 table. Typos in text and Figs.4 and 6 correcte

Electron-electron interaction and charging effects in graphene quantum dots

We analyze charging effects in graphene quantum dots. Using a simple model, we show that, when the Fermi level is far from the neutrality point, charging effects lead to a shift in the electrostatic potential and the dot shows standard Coulomb blockade features. Near the neutrality point, surface states are partially occupied and the Coulomb interaction leads to a strongly correlated ground state which can be approximated by either a Wigner crystal or a Laughlin like wave function. The existence of strong correlations modify the transport properties which show non equilibrium effects, similar to those predicted for tunneling into other strongly correlated systems.Comment: Extended version accepted for publication at Phys. Rev.

Dynamic Re-Optimization of a Fed-Batch Fermentor using Adaptive Critic Designs

Traditionally, fed-batch biochemical process optimization and control uses complicated off-line optimizers, with no online model adaptation or re-optimization. This study demonstrates the applicability of a class of adaptive critic designs for online re-optimization and control of an aerobic fed-batch fermentor. Specifically, the performance of an entire class of adaptive critic designs, viz., heuristic dynamic programming, dual heuristic programming and generalized dual heuristic programming, was demonstrated to be superior to that of a heuristic random optimizer, on optimization of a fed-batch fermentor operation producing monoclonal antibodie

Dynamic Re-Optimization of a Fed-Batch Fermentor using Heuristic Dynamic Programming

Traditionally, fed-batch biochemical process optimization and control uses complicated theoretical off-line optimizers, with no online model adaptation or re-optimization. This study demonstrates the applicability, effectiveness, and economic potential of a simple phenomenological model for modeling, and an adaptive critic design, heuristic dynamic programming, for online re-optimization and control of an aerobic fed-batch fermentor. The results are compared with those obtained using a heuristic random optimize

Fed-Batch Dynamic Optimization using Generalized Dual Heuristic Programming

Traditionally fed-batch biochemical process optimization and control uses complicated theoretical off-line optimizers, with no online model adaptation or re-optimization. This study demonstrates the applicability, effectiveness, and economic potential of a simple phenomenological model for modeling, and an adaptive critic design, generalized dual heuristic programming, for online re-optimization and control of an aerobic fed-batch fermentor. The results are compared with those obtained using a heuristic random optimize