The cause of the weak solar cycle 24

The ongoing 11-year cycle of solar activity is considerably less vigorous than the three cycles before. It was preceded by a very deep activity minimum with a low polar magnetic flux, the source of the toroidal field responsible for solar magnetic activity in the subsequent cycle. Simulation of the evolution of the solar surface field shows that the weak polar fields and thus the weakness of the present cycle 24 are mainly caused by a number of bigger bipolar regions emerging at low latitudes with a `wrong' (i.e., opposite to the majority for this cycle) orientation of their magnetic polarities in the North-South direction, which impaired the growth of the polar field. These regions had a particularly strong effect since they emerged within $\pm10^\circ$ latitude from the solar equator.Comment: 15 pages, 5 figures, accepted for publication in ApJ

Solar cycle 25: another moderate cycle?

Surface flux transport simulations for the descending phase of cycle 24 using random sources (emerging bipolar magnetic regions) with empirically determined scatter of their properties provide a prediction of the axial dipole moment during the upcoming activity minimum together with a realistic uncertainty range. The expectation value for the dipole moment around 2020 $(2.5\pm1.1\,$G) is comparable to that observed at the end of cycle 23 (about $2\,$G). The empirical correlation between the dipole moment during solar minimum and the strength of the subsequent cycle thus suggests that cycle 25 will be of moderate amplitude, not much higher than that of the current cycle. However, the intrinsic uncertainty of such predictions resulting from the random scatter of the source properties is considerable and fundamentally limits the reliability with which such predictions can be made before activity minimum is reached.Comment: 13 papges, 4 figures,Accepted for publication in ApJ

Multitask Diffusion Adaptation over Networks

Adaptive networks are suitable for decentralized inference tasks, e.g., to monitor complex natural phenomena. Recent research works have intensively studied distributed optimization problems in the case where the nodes have to estimate a single optimum parameter vector collaboratively. However, there are many important applications that are multitask-oriented in the sense that there are multiple optimum parameter vectors to be inferred simultaneously, in a collaborative manner, over the area covered by the network. In this paper, we employ diffusion strategies to develop distributed algorithms that address multitask problems by minimizing an appropriate mean-square error criterion with $\ell_2$-regularization. The stability and convergence of the algorithm in the mean and in the mean-square sense is analyzed. Simulations are conducted to verify the theoretical findings, and to illustrate how the distributed strategy can be used in several useful applications related to spectral sensing, target localization, and hyperspectral data unmixing.Comment: 29 pages, 11 figures, submitted for publicatio

Insider trading, costly monitoring, and managerial incentives

In this paper we show, in an incomplete contracts framework that combines asymmetric information and moral hazard, that by permitting insiders to trade on personal account the equilibrium level of output can be increased and shareholder welfare can be improved. There are two reasons for this. First, insider trading impounds information regarding the costs and benefits of effort and perk consumption into asset prices, which allows shareholders to choose more efficient portfolio allocations. Second, allowing insider trading can induce managers to increase their stake in the firm beyond that obtained through bargaining with shareholders. This effect leads to a reduction in managerial perk consumption and/or increased managerial effort. Insider trading can also be costly for shareholders' intermediate range of monitoring costs and project difficulty because, in such cases, the efforts of managers are quite sensitive to the exact level of fractional shareownership, which managers can endogenously change if they are able to trade on personal account. Interestingly, when monitoring and effort costs are low, managers may prefer restrictions on their ability to trade as such restrictions will force shareholders to offer them a larger fraction of output.Financial markets ; Stock market

Single-particle machine for quantum thermalization

The long time accumulation of the \textit{random} actions of a single particle "reservoir" on its coupled system can transfer some temperature information of its initial state to the coupled system. This dynamic process can be referred to as a quantum thermalization in the sense that the coupled system can reach a stable thermal equilibrium with a temperature equal to that of the reservoir. We illustrate this idea based on the usual micromaser model, in which a series of initially prepared two-level atoms randomly pass through an electromagnetic cavity. It is found that, when the randomly injected atoms are initially prepared in a thermal equilibrium state with a given temperature, the cavity field will reach a thermal equilibrium state with the same temperature as that of the injected atoms. As in two limit cases, the cavity field can be cooled and "coherently heated" as a maser process, respectively, when the injected atoms are initially prepared in ground and excited states. Especially, when the atoms in equilibrium are driven to possess some coherence, the cavity field may reach a higher temperature in comparison with the injected atoms. We also point out a possible experimental test for our theoretical prediction based on a superconducting circuit QED system.Comment: 9 pages,4 figures

Analyzing Competing Risk Data Using the R timereg Package

In this paper we describe flexible competing risks regression models using the comp.risk() function available in the timereg package for R based on Scheike et al. (2008). Regression models are specified for the transition probabilities, that is the cumulative incidence in the competing risks setting. The model contains the Fine and Gray (1999) model as a special case. This can be used to do goodness-of-fit test for the subdistribution hazardsâ proportionality assumption (Scheike and Zhang 2008). The program can also construct confidence bands for predicted cumulative incidence curves. We apply the methods to data on follicular cell lymphoma from Pintilie (2007), where the competing risks are disease relapse and death without relapse. There is important non-proportionality present in the data, and it is demonstrated how one can analyze these data using the flexible regression models.

New Anomalies in Topological String Theory

We show that the topological string partition function with D-branes on a compact Calabi-Yau manifold has new anomalies that spoil the recursive structure of the holomorphic anomaly equation and introduce dependence on wrong moduli (such as complex structure moduli in the A-model), unless the disk one-point functions vanish. This provides a microscopic explanation for the recent result of Walcher in arXiv:0712.2775 on counting of BPS states in M-theory using the topological string partition function. The relevance of vanishing disk one-point functions to large N duality for compact Calabi-Yau manifolds is noted

Gravitational Lensing by Dark Matter Halos with Non-universal Density Profiles

The statistics of gravitational lensing can provide us with a very powerful probe of the mass distribution of matter in the universe. By comparing predicted strong lensing probabilities with observations, we can test the mass distribution of dark matter halos, in particular, the inner density slope. In this letter, unlike previous work that directly models the density profiles of dark matter halos semi-analytically, we generalize the density profiles of dark matter halos from high-resolution N-body simulations by means of generalized Navarro-Frenk-White (GNFW) models of three populations with slopes, $\alpha$, of about -1.5, -1.3 and -1.1 for galaxies, groups and clusters, respectively. This approach is an alternative and independent way to examine the slopes of mass density profiles of halos. We present calculations of lensing probabilities using these GNFW profiles for three populations in various spatially flat cosmological models with a cosmological constant $\Lambda$. It is shown that the compound model of density profiles does not match well with the observed lensing probabilities derived from the Jodrell-Bank VLA Astrometric Survey data in combination with the Cosmic Lens All-Sky Survey data. Together with the previous work on lensing probability, our results suggest that a singular isothermal sphere mass model of less than about 10^{13}h^{-1}M_{\sun} can predict strong lensing probabilities that are consistent with observations of small splitting angles.Comment: 11 pages, 2 figures, Accepted by ApJL for publication (February 10 issue 2004