Calculation of surface temperature and surface fluxes in the GLAS GOM

Because the GLAS model's surface fluxes of sensible and latent heat exhibit strong 2 delta t oscillations at the individual grid points as well as in the zonal hemispheric averages and because a basic weakness of the GLAS model lower evaporation over oceans and higher evaporation over land in a typical monthly simulation, the GLAS model PBL parameterization was changed to calculate the mixed layer temperature gradient by solution of a quadratic equation for a stable PBL and by a curve fit relation for an unstable PBL. The new fluxes without any 2 delta t oscillation. Also, the geographical distributions of the surface fluxes are improved. The parameterization presented is incorporated into the new GLAS climate model. Some results which compare the evaporation over land and ocean between old and new calculations are appended

Compound transfer matrices: Constructive and destructive interference

Scattering from a compound barrier, one composed of a number of distinct non-overlapping sub-barriers, has a number of interesting and subtle mathematical features. If one is scattering classical particles, where the wave aspects of the particle can be ignored, the transmission probability of the compound barrier is simply given by the product of the transmission probabilities of the individual sub-barriers. In contrast if one is scattering waves (whether we are dealing with either purely classical waves or quantum Schrodinger wavefunctions) each sub-barrier contributes phase information (as well as a transmission probability), and these phases can lead to either constructive or destructive interference, with the transmission probability oscillating between nontrivial upper and lower bounds. In this article we shall study these upper and lower bounds in some detail, and also derive bounds on the closely related process of quantum excitation (particle production) via parametric resonance.Comment: V1: 28 pages. V2: 21 pages. Presentation significantly streamlined and shortened. This version accepted for publication in the Journal of Mathematical Physic

Dynamical mean-filed approximation to small-world networks of spiking neurons: From local to global, and/or from regular to random couplings

By extending a dynamical mean-field approximation (DMA) previously proposed by the author [H. Hasegawa, Phys. Rev. E {\bf 67}, 41903 (2003)], we have developed a semianalytical theory which takes into account a wide range of couplings in a small-world network. Our network consists of noisy $N$-unit FitzHugh-Nagumo (FN) neurons with couplings whose average coordination number $Z$ may change from local ($Z \ll N$) to global couplings ($Z=N-1$) and/or whose concentration of random couplings $p$ is allowed to vary from regular ($p=0$) to completely random (p=1). We have taken into account three kinds of spatial correlations: the on-site correlation, the correlation for a coupled pair and that for a pair without direct couplings. The original $2 N$-dimensional {\it stochastic} differential equations are transformed to 13-dimensional {\it deterministic} differential equations expressed in terms of means, variances and covariances of state variables. The synchronization ratio and the firing-time precision for an applied single spike have been discussed as functions of $Z$ and $p$. Our calculations have shown that with increasing $p$, the synchronization is {\it worse} because of increased heterogeneous couplings, although the average network distance becomes shorter. Results calculated by out theory are in good agreement with those by direct simulations.Comment: 19 pages, 2 figures: accepted in Phys. Rev. E with minor change

STUDIES OF THE MECHANISM OF ACTION OF COBAMIDE COENZYMES

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73404/1/j.1749-6632.1964.tb45046.x.pd

Superconductivity-Related Insulating Behavior

We present the results of an experimental study of superconducting, disordered, thin-films of amorphous Indium Oxide. These films can be driven from the superconducting phase to a reentrant insulating state by the application of a perpendicular magnetic field ($B$). We find that the high-$B$ insulator exhibits activated transport with a characteristic temperature, $T_I$. $T_I$ has a maximum value ($T_{I}^p$) that is close to the superconducting transition temperature ($T_c$) at $B$ = 0, suggesting a possible relation between the conduction mechanisms in the superconducting and insulating phases. $T_{I}^p$ and $T_c$ display opposite dependences on the disorder strength.Comment: Tex file and 5 figures; Revised version; To appear in Phys. Rev. Lett. (2004

Clustering and Synchronization of Oscillator Networks

Using a recently described technique for manipulating the clustering coefficient of a network without changing its degree distribution, we examine the effect of clustering on the synchronization of phase oscillators on networks with Poisson and scale-free degree distributions. For both types of network, increased clustering hinders global synchronization as the network splits into dynamical clusters that oscillate at different frequencies. Surprisingly, in scale-free networks, clustering promotes the synchronization of the most connected nodes (hubs) even though it inhibits global synchronization. As a result, scale-free networks show an additional, advanced transition instead of a single synchronization threshold. This cluster-enhanced synchronization of hubs may be relevant to the brain with its scale-free and highly clustered structure.Comment: Submitted to Phys. Rev.

Nonlocal mechanism for cluster synchronization in neural circuits

The interplay between the topology of cortical circuits and synchronized activity modes in distinct cortical areas is a key enigma in neuroscience. We present a new nonlocal mechanism governing the periodic activity mode: the greatest common divisor (GCD) of network loops. For a stimulus to one node, the network splits into GCD-clusters in which cluster neurons are in zero-lag synchronization. For complex external stimuli, the number of clusters can be any common divisor. The synchronized mode and the transients to synchronization pinpoint the type of external stimuli. The findings, supported by an information mixing argument and simulations of Hodgkin Huxley population dynamic networks with unidirectional connectivity and synaptic noise, call for reexamining sources of correlated activity in cortex and shorter information processing time scales.Comment: 8 pges, 6 figure