Langevin Simulation of Thermally Activated Magnetization Reversal in Nanoscale Pillars

Numerical solutions of the Landau-Lifshitz-Gilbert micromagnetic model incorporating thermal fluctuations and dipole-dipole interactions (calculated by the Fast Multipole Method) are presented for systems composed of nanoscale iron pillars of dimension 9 nm x 9 nm x 150 nm. Hysteresis loops generated under sinusoidally varying fields are obtained, while the coercive field is estimated to be 1979 $\pm$ 14 Oe using linear field sweeps at T=0 K. Thermal effects are essential to the relaxation of magnetization trapped in a metastable orientation, such as happens after a rapid reversal of an external magnetic field less than the coercive value. The distribution of switching times is compared to a simple analytic theory that describes reversal with nucleation at the ends of the nanomagnets. Results are also presented for arrays of nanomagnets oriented perpendicular to a flat substrate. Even at a separation of 300 nm, where the field from neighboring pillars is only $\sim$ 1 Oe, the interactions have a significant effect on the switching of the magnets.Comment: 19 pages RevTeX, including 12 figures, clarified discussion of numerical technique

A Maclaurin-series expansion approach to coupled queues with phase-type distributed service times

International audienc

Closed-Form Bayesian Inferences for the Logit Model via Polynomial Expansions

Articles in Marketing and choice literatures have demonstrated the need for incorporating person-level heterogeneity into behavioral models (e.g., logit models for multiple binary outcomes as studied here). However, the logit likelihood extended with a population distribution of heterogeneity doesn't yield closed-form inferences, and therefore numerical integration techniques are relied upon (e.g., MCMC methods). We present here an alternative, closed-form Bayesian inferences for the logit model, which we obtain by approximating the logit likelihood via a polynomial expansion, and then positing a distribution of heterogeneity from a flexible family that is now conjugate and integrable. For problems where the response coefficients are independent, choosing the Gamma distribution leads to rapidly convergent closed-form expansions; if there are correlations among the coefficients one can still obtain rapidly convergent closed-form expansions by positing a distribution of heterogeneity from a Multivariate Gamma distribution. The solution then comes from the moment generating function of the Multivariate Gamma distribution or in general from the multivariate heterogeneity distribution assumed. Closed-form Bayesian inferences, derivatives (useful for elasticity calculations), population distribution parameter estimates (useful for summarization) and starting values (useful for complicated algorithms) are hence directly available. Two simulation studies demonstrate the efficacy of our approach.Comment: 30 pages, 2 figures, corrected some typos. Appears in Quantitative Marketing and Economics vol 4 (2006), no. 2, 173--20

Statistical properties of inelastic Lorentz gas

The inelastic Lorentz gas in cooling states is studied. It is found that the inelastic Lorentz gas is localized and that the mean square displacement of the inelastic Lorentz gas obeys a power of a logarithmic function of time. It is also found that the scaled position distribution of the inelastic Lorentz gas has an exponential tail, while the distribution is close to the Gaussian near the peak. Using a random walk model, we derive an analytical expression of the mean square displacement as a function of time and the restitution coefficient, which well agrees with the data of our simulation. The exponential tail of the scaled position distribution function is also obtained by the method of steepest descent.Comment: 31pages,9figures, to appear Journal of Physical Society of Japan Vol.70 No.7 (2001

Statistical properties of inelastic Lorentz gas

The inelastic Lorentz gas in cooling states is studied. It is found that the inelastic Lorentz gas is localized and that the mean square displacement of the inelastic Lorentz gas obeys a power of a logarithmic function of time. It is also found that the scaled position distribution of the inelastic Lorentz gas has an exponential tail, while the distribution is close to the Gaussian near the peak. Using a random walk model, we derive an analytical expression of the mean square displacement as a function of time and the restitution coefficient, which well agrees with the data of our simulation. The exponential tail of the scaled position distribution function is also obtained by the method of steepest descent.Comment: 31pages,9figures, to appear Journal of Physical Society of Japan Vol.70 No.7 (2001