Characterizing mixed mode oscillations shaped by noise and bifurcation structure

Many neuronal systems and models display a certain class of mixed mode oscillations (MMOs) consisting of periods of small amplitude oscillations interspersed with spikes. Various models with different underlying mechanisms have been proposed to generate this type of behavior. Stochastic versions of these models can produce similarly looking time series, often with noise-driven mechanisms different from those of the deterministic models. We present a suite of measures which, when applied to the time series, serves to distinguish models and classify routes to producing MMOs, such as noise-induced oscillations or delay bifurcation. By focusing on the subthreshold oscillations, we analyze the interspike interval density, trends in the amplitude and a coherence measure. We develop these measures on a biophysical model for stellate cells and a phenomenological FitzHugh-Nagumo-type model and apply them on related models. The analysis highlights the influence of model parameters and reset and return mechanisms in the context of a novel approach using noise level to distinguish model types and MMO mechanisms. Ultimately, we indicate how the suite of measures can be applied to experimental time series to reveal the underlying dynamical structure, while exploiting either the intrinsic noise of the system or tunable extrinsic noise.Comment: 22 page

Numerical renormalization group study of the correlation functions of the antiferromagnetic spin-12\frac{1}{2} Heisenberg chain

We use the density-matrix renormalization group technique developed by White \cite{white} to calculate the spin correlation functions $=(-1)^l \omega(l,N)$ for isotropic Heisenberg rings up to $N=70$ sites. The correlation functions for large $l$ and $N$ are found to obey the scaling relation $\omega(l,N)=\omega(l,\infty)f_{XY}^{\alpha} (l/N)$ proposed by Kaplan et al. \cite{horsch} , which is used to determine $\omega(l,\infty)$. The asymptotic correlation function $\omega(l,\infty)$ and the magnetic structure factor $S(q=\pi)$ show logarithmic corrections consistent with $\omega(l,\infty)\sim a\sqrt{\ln{cl}}/l$, where $c$ is related to the cut-off dependent coupling constant $g_{eff}(l_0)=1/\ln(cl_0)$, as predicted by field theoretical treatments.Comment: Accepted in Phys. Rev. B. 4 pages of text in Latex + 5 figures in uuencoded form containing the 5 postscripts (mailed separately

Evolution of X-ray cluster scaling relations in simulations with radiative cooling and non-gravitational heating

We investigate the redshift dependence of X-ray cluster scaling relations drawn from three hydrodynamic simulations of the LCDM cosmology: a Radiative model that incorporates radiative cooling of the gas, a Preheating model that additionally heats the gas uniformly at high redshift, and a Feedback model that self-consistently heats cold gas in proportion to its local star-formation rate. While all three models are capable of reproducing the observed local Lx-Tx relation, they predict substantially different results at high redshift (to z=1.5), with the Radiative, Preheating and Feedback models predicting strongly positive, mildly positive and mildly negative evolution, respectively. The physical explanation for these differences lies in the structure of the intracluster medium. All three models predict significant temperature fluctuations at any given radius due to the presence of cool subclumps and, in the case of the Feedback simulation, reheated gas. The mean gas temperature lies above the dynamical temperature of the halo for all models at z=0, but differs between models at higher redshift with the Radiative model having the lowest mean gas temperature at z=1.5. We have not attempted to model the scaling relations in a manner that mimics the observational selection effects, nor has a consistent observational picture yet emerged. Nevertheless, evolution of the scaling relations promises to be a powerful probe of the physics of entropy generation in clusters. First indications are that early, widespread heating is favored over an extended period of heating that is associated with galaxy formation.Comment: Accepted for publication in ApJ. Minor changes following referee's comment

MESAS: Measuring the Emission of Stellar Atmospheres at Submm/mm wavelengths

In the early stages of planet formation, small dust grains grow to become mm sized particles in debris disks around stars. These disks can in principle be characterized by their emission at submillimeter and millimeter wavelengths. Determining both the occurrence and abundance of debris in unresolved circumstellar disks of A-type main-sequence stars requires that the stellar photospheric emission be accurately modeled. To better constrain the photospheric emission for such systems, we present observations of Sirius A, an A-type star with no known debris, from the JCMT, SMA, and VLA at 0.45, 0.85, 0.88, 1.3, 6.7, and 9.0 mm. We use these observations to inform a PHOENIX model of Sirius A's atmosphere. We find the model provides a good match to these data and can be used as a template for the submm/mm emission of other early A-type stars where unresolved debris may be present. The observations are part of an ongoing observational campaign entitled Measuring the Emission of Stellar Atmospheres at Submm/mm wavelengths (MESAS)Comment: 17 pages, 1 figure, Accepted to AJ on April 25th 201

A Technique for Foreground Subtraction in Redshifted 21 cm Observations

One of the main challenges for future 21 cm observations is to remove foregrounds which are several orders of magnitude more intense than the HI signal. We propose a new technique for removing foregrounds of the redshifted 21 cm observations. We consider multi-frequency interferometer observations. We assume that the 21 cm signals in different frequency channels are uncorrelated and the foreground signals change slowly as a function of frequency. When we add the visibilities of all channels, the foreground signals increase roughly by a factor of ~N because they are highly correlated. However, the 21 cm signals increase by a factor of ~\sqrt{N} because the signals in different channels contribute randomly. This enables us to obtain an accurate shape of the foreground angular power spectrum. Then, we obtain the 21-cm power spectrum by subtracting the foreground power spectrum obtained this way. We describe how to obtain the average power spectrum of the 21 cm signal.Comment: 5 pages, 1 figure; To appear on the Astrophysical Journa

Tetracycline resistance genes in Salmonella from growing pigs and their relationship to antimicrobial use and resistance to other antimicrobials

The aim of this study was to describe the occurrence of three genes coding for tetracycline resistance in Salmonellae isolated from normal slaughter weight pigs, and to test for relationships between the occurrence of these genes, phenotypic resistance, and the use of antimicrobials in feed and water