X-ray variability of AGNs in the soft and the hard X-ray bands

We investigate the X-ray variability characteristics of hard X-ray selected AGNs (based on Swift/BAT data) in the soft X-ray band using the RXTE/ASM data. The uncertainties involved in the individual dwell measurements of ASM are critically examined and a method is developed to combine a large number of dwells with appropriate error propagation to derive long duration flux measurements (greater than 10 days). We also provide a general prescription to estimate the errors in variability derived from rms values from unequally spaced data. Though the derived variability for individual sources are not of very high significance, we find that, in general, the soft X-ray variability is higher than those in hard X-rays and the variability strengths decrease with energy for the diverse classes of AGN. We also examine the strength of variability as a function of the break time scale in the power density spectrum (derived from the estimated mass and bolometric luminosity of the sources) and find that the data are consistent with the idea of higher variability at time scales longer than the break time scale.Comment: 17 pages, 15 Postscript figures, 3 tables, accepted for publication in Ap

On critical pilot tasks

Critical pilot performance in decision making proces

Risk and Utility in Portfolio Optimization

Modern portfolio theory(MPT) addresses the problem of determining the optimum allocation of investment resources among a set of candidate assets. In the original mean-variance approach of Markowitz, volatility is taken as a proxy for risk, conflating uncertainty with risk. There have been many subsequent attempts to alleviate that weakness which, typically, combine utility and risk. We present here a modification of MPT based on the inclusion of separate risk and utility criteria. We define risk as the probability of failure to meet a pre-established investment goal. We define utility as the expectation of a utility function with positive and decreasing marginal value as a function of yield. The emphasis throughout is on long investment horizons for which risk-free assets do not exist. Analytic results are presented for a Gaussian probability distribution. Risk-utility relations are explored via empirical stock-price data, and an illustrative portfolio is optimized using the empirical data.Comment: 10 pages, 1 figure, presented at 2002 Conference on Econophysics in Bali Indonesi

Portfolio Optimization Using SPEA2 with Resampling

Proceeding of: Intelligent Data Engineering and Automated Learning – IDEAL 2011: 12th International Conference, Norwich, UK, September 7-9, 2011The subject of financial portfolio optimization under real-world constraints is a difficult problem that can be tackled using multiobjective evolutionary algorithms. One of the most problematic issues is the dependence of the results on the estimates for a set of parameters, that is, the robustness of solutions. These estimates are often inaccurate and this may result on solutions that, in theory, offered an appropriate risk/return balance and, in practice, resulted being very poor. In this paper we suggest that using a resampling mechanism may filter out the most unstable. We test this idea on real data using SPEA2 as optimization algorithm and the results show that the use of resampling increases significantly the reliability of the resulting portfolios.The authors acknowledge financial support granted by the Spanish Ministry of Science under contract TIN2008-06491-C04-03 (MSTAR) and Comunidad de Madrid (CCG10- UC3M/TIC-5029).Publicad

Optimal Investment in the Development of Oil and Gas Field

Let an oil and gas field consists of clusters in each of which an investor can launch at most one project. During the implementation of a particular project, all characteristics are known, including annual production volumes, necessary investment volumes, and profit. The total amount of investments that the investor spends on developing the field during the entire planning period we know. It is required to determine which projects to implement in each cluster so that, within the total amount of investments, the profit for the entire planning period is maximum. The problem under consideration is NP-hard. However, it is solved by dynamic programming with pseudopolynomial time complexity. Nevertheless, in practice, there are additional constraints that do not allow solving the problem with acceptable accuracy at a reasonable time. Such restrictions, in particular, are annual production volumes. In this paper, we considered only the upper constraints that are dictated by the pipeline capacity. For the investment optimization problem with such additional restrictions, we obtain qualitative results, propose an approximate algorithm, and investigate its properties. Based on the results of a numerical experiment, we conclude that the developed algorithm builds a solution close (in terms of the objective function) to the optimal one

Adaptive Investment Strategies For Periodic Environments

In this paper, we present an adaptive investment strategy for environments with periodic returns on investment. In our approach, we consider an investment model where the agent decides at every time step the proportion of wealth to invest in a risky asset, keeping the rest of the budget in a risk-free asset. Every investment is evaluated in the market via a stylized return on investment function (RoI), which is modeled by a stochastic process with unknown periodicities and levels of noise. For comparison reasons, we present two reference strategies which represent the case of agents with zero-knowledge and complete-knowledge of the dynamics of the returns. We consider also an investment strategy based on technical analysis to forecast the next return by fitting a trend line to previous received returns. To account for the performance of the different strategies, we perform some computer experiments to calculate the average budget that can be obtained with them over a certain number of time steps. To assure for fair comparisons, we first tune the parameters of each strategy. Afterwards, we compare the performance of these strategies for RoIs with different periodicities and levels of noise.Comment: Paper submitted to Advances in Complex Systems (November, 2007) 22 pages, 9 figure

Connection between the Accretion Disk and Jet in the Radio Galaxy 3C 111

We present the results of extensive multi-frequency monitoring of the radio galaxy 3C 111 between 2004 and 2010 at X-ray (2.4--10 keV), optical (R band), and radio (14.5, 37, and 230 GHz) wave bands, as well as multi-epoch imaging with the Very Long Baseline Array (VLBA) at 43 GHz. Over the six years of observation, significant dips in the X-ray light curve are followed by ejections of bright superluminal knots in the VLBA images. This shows a clear connection between the radiative state near the black hole, where the X-rays are produced, and events in the jet. The X-ray continuum flux and Fe line intensity are strongly correlated, with a time lag shorter than 90 days and consistent with zero. This implies that the Fe line is generated within 90 light-days of the source of the X-ray continuum. The power spectral density function of X-ray variations contains a break, with steeper slope at shorter timescales. The break timescale of 13 (+12,-6) days is commensurate with scaling according to the mass of the central black hole based on observations of Seyfert galaxies and black hole X-ray binaries (BHXRBs). The data are consistent with the standard paradigm, in which the X-rays are predominantly produced by inverse Compton scattering of thermal optical/UV seed photons from the accretion disk by a distribution of hot electrons --- the corona --- situated near the disk. Most of the optical emission is generated in the accretion disk due to reprocessing of the X-ray emission. The relationships that we have uncovered between the accretion disk and the jet in 3C 111, as well as in the FR I radio galaxy 3C 120 in a previous paper, support the paradigm that active galactic nuclei and Galactic BHXRBs are fundamentally similar, with characteristic time and size scales proportional to the mass of the central black holeComment: Accepted for publication in ApJ. 18 pages, 17 figures, 11 tables (full machine readable data-tables online in ApJ website

Influence of Charge and Energy Imbalances on the Tunneling Current through a Superconductor-Normal Metal Junction

We consider quasiparticle charge and energy imbalances in a thin superconductor weakly coupled with two normal-metal electrodes via tunnel junctions at low temperatures. Charge and energy imbalances, which can be created by injecting quasiparticles at one junction, induce excess tunneling current $I_{\rm ex}$ at the other junction. We numerically obtain $I_{\rm ex}$ as a function of the bias voltage $V_{\rm det}$ across the detection junction. We show that $I_{\rm ex}$ at the zero bias voltage is purely determined by the charge imbalance, while the energy imbalance causes a nontrivial $V_{\rm det}$-dependence of $I_{\rm ex}$. The obtained voltage-current characteristics qualitatively agree with the experimental result by R. Yagi [Phys. Rev. B {\bf 73} (2006) 134507].Comment: 10 pages, 5 figure

Role of anisotropic impurity scattering in anisotropic superconductors

A theory of nonmagnetic impurities in an anisotropic superconductor including the effect of anisotropic (momentum-dependent) impurity scattering is given. It is shown that for a strongly anisotropic scattering the reduction of the pair-breaking effect of the impurities is large. For a significant overlap between the anisotropy functions of the scattering potential and that of the pair potential and for a large amount of anisotropic scattering rate in impurity potential the superconductivity becomes robust vis a vis impurity concentration. The implications of our result for YBCO high-temperature superconductor are discussed.Comment: 14 pages, RevTeX, 5 PostScript figures, to be published in Phys. Rev. B (December 1, 1996