Network-wide assessment of 4D trajectory adjustments using an agent-based model

This paper presents results from the SESAR ER3 Domino project. It focuses on an ECAC-wide assessment of two 4D-adjustment mechanisms, implemented separately and conjointly. These reflect flight behaviour en-route and at-gate, optimising given (cost) objective functions. New metrics designed to capture network effects are used to analyse the results of a microscopic, agent based model. The results show that some implementations of the mechanisms allow the protection of the network from ‘domino’ effects. Airlines focusing on costs may trigger additional side-effects on passengers, displaying, in some instances, clear trade-offs between passenger- and flight-centric metrics

Nonlinear diffusion model for Rayleigh-Taylor mixing

The complex evolution of turbulent mixing in Rayleigh-Taylor convection is studied in terms of eddy diffusiviy models for the mean temperature profile. It is found that a non-linear model, derived within the general framework of Prandtl mixing theory, reproduces accurately the evolution of turbulent profiles obtained from numerical simulations. Our model allows to give very precise predictions for the turbulent heat flux and for the Nusselt number in the ultimate state regime of thermal convection.Comment: 4 pages, 4 figure, PRL in pres

Dissecting financial markets: Sectors and states

By analyzing a large data set of daily returns with data clustering technique, we identify economic sectors as clusters of assets with a similar economic dynamics. The sector size distribution follows Zipf's law. Secondly, we find that patterns of daily market-wide economic activity cluster into classes that can be identified with market states. The distribution of frequencies of market states shows scale-free properties and the memory of the market state process extends to long times ($\sim 50$ days). Assets in the same sector behave similarly across states. We characterize market efficiency by analyzing market's predictability and find that indeed the market is close to being efficient. We find evidence of the existence of a dynamic pattern after market's crashes.Comment: 6 pages 4 figures. Additional information available at http://www.sissa.it/dataclustering/fin

Kepler-539: a young extrasolar system with two giant planets on wide orbits and in gravitational interaction

We confirm the planetary nature of Kepler-539b (aka Kepler object of interest K00372.01), a giant transiting exoplanet orbiting a solar-analogue G2 V star. The mass of Kepler-539b was accurately derived thanks to a series of precise radial velocity measurements obtained with the CAFE spectrograph mounted on the CAHA 2.2m telescope. A simultaneous fit of the radial-velocity data and Kepler photometry revealed that Kepler-539b is a dense Jupiter-like planet with a mass of Mp = 0.97 Mjup and a radius of Rp = 0.747 Rjup, making a complete circular revolution around its parent star in 125.6 days. The semi-major axis of the orbit is roughly 0.5 au, implying that the planet is at roughly 0.45 au from the habitable zone. By analysing the mid-transit times of the 12 transit events of Kepler-539b recorded by the Kepler spacecraft, we found a clear modulated transit time variation (TTV), which is attributable to the presence of a planet c in a wider orbit. The few timings available do not allow us to precisely estimate the properties of Kepler-539c and our analysis suggests that it has a mass between 1.2 and 3.6 Mjup, revolving on a very eccentric orbit (0.4<e<0.6) with a period larger than 1000 days. The high eccentricity of planet c is the probable cause of the TTV modulation of planet b. The analysis of the CAFE spectra revealed a relatively high photospheric lithium content, A(Li)=2.48 dex, which, together with both a gyrochronological and isochronal analysis, suggests that the parent star is relatively young.Comment: 11 pages, 14 figures, accepted for publication in Astronomy & Astrophysic

Eclipsing binaries and fast rotators in the Kepler sample. Characterization via radial velocity analysis from Calar Alto

The Kepler mission has provided high-accurate photometric data in a long time span for more than two hundred thousands stars, looking for planetary transits. Among the detected candidates, the planetary nature of around 15% has been established or validated by different techniques. But additional data is needed to characterize the rest of the candidates and reject other possible configurations. We started a follow-up program to validate, confirm, and characterize some of the planet candidates. In this paper we present the radial velocity analysis (RV) of those presenting large variations, compatible with being eclipsing binaries. We also study those showing large rotational velocities, which prevents us from obtaining the necessary precision to detect planetary-like objects. We present new RV results for 13 Kepler objects of interest (KOIs) obtained with the CAFE spectrograph at the Calar Alto Observatory, and analyze their high-spatial resolution images and the Kepler light curves of some interesting cases. We have found five spectroscopic and eclipsing binaries. Among them, the case of KOI-3853 is of particular interest. This system is a new example of the so-called heartbeat stars, showing dynamic tidal distortions in the Kepler light curve. We have also detected duration and depth variations of the eclipse. We suggest possible scenarios to explain such effect, including the presence of a third substellar body possibly detected in our RV analysis. We also provide upper mass limits to the transiting companions of other six KOIs with large rotational velocities. This property prevents the RV method to obtain the necessary precision to detect planetary-like masses. Finally, we analyze the large RV variations of other two KOIs, incompatible with the presence of planetary-mass objects. These objects are likely to be stellar binaries but a longer timespan is still needed.Comment: Accepted for publication in A&A. 18 pages, 9 figures, 17 tables. This version fixes an error affecting the values of tables A.1-A.13. The text remains unaltere

Kepler-447b: a hot-Jupiter with an extremely grazing transit

We present the radial velocity confirmation of the extrasolar planet Kepler-447b, initially detected as a candidate by the Kepler mission. In this work, we analyze its transit signal and the radial velocity data obtained with the Calar Alto Fiber-fed Echelle spectrograph (CAFE). By simultaneously modeling both datasets, we obtain the orbital and physical properties of the system. According to our results, Kepler-447b is a Jupiter-mass planet ($M_p=1.37^{+0.48}_{-0.46}~M_{\rm Jup}$), with an estimated radius of $R_p=1.65^{+0.59}_{-0.56}~R_{\rm Jup}$ (uncertainties provided in this work are $3\sigma$ unless specified). This translates into a sub-Jupiter density. The planet revolves every $\sim7.8$ days in a slightly eccentric orbit ($e=0.123^{+0.037}_{-0.036}$) around a G8V star with detected activity in the Kepler light curve. Kepler-447b transits its host with a large impact parameter ($b=1.076^{+0.112}_{-0.086}$), being one of the few planetary grazing transits confirmed so far and the first in the Kepler large crop of exoplanets. We estimate that only around 20% of the projected planet disk occults the stellar disk. The relatively large uncertainties in the planet radius are due to the large impact parameter and short duration of the transit. Planets with such an extremely large impact parameter can be used to detect and analyze interesting configurations such as additional perturbing bodies, stellar pulsations, rotation of a non-spherical planet, or polar spot-crossing events. All these scenarios would periodically modify the transit properties (depth, duration, and time of mid-transit), what could be detectable with sufficient accurate photometry. Short-cadence photometric data (at the 1 minute level) would help in the search for these exotic configurations in grazing planetary transits like that of Kepler-447b.Comment: Accepted for publication in A&A. 13 pages, 8 figures, 4 tables. This version replaces an earlier version of the pape

Long-range memory model of trading activity and volatility

Earlier we proposed the stochastic point process model, which reproduces a variety of self-affine time series exhibiting power spectral density S(f) scaling as power of the frequency f and derived a stochastic differential equation with the same long range memory properties. Here we present a stochastic differential equation as a dynamical model of the observed memory in the financial time series. The continuous stochastic process reproduces the statistical properties of the trading activity and serves as a background model for the modeling waiting time, return and volatility. Empirically observed statistical properties: exponents of the power-law probability distributions and power spectral density of the long-range memory financial variables are reproduced with the same values of few model parameters.Comment: 12 pages, 5 figure

Measuring the propagation of financial distress with Granger-causality tail risk networks

Using the test of Granger-causality in tail of Hong et al. (2009), we define and construct Granger-causality tail risk networks between 33 systemically important banks (G-SIBs) and 36 sovereign bonds worldwide. Our purpose is to exploit the structure of the Granger-causality tail risk networks to identify periods of distress in financial markets and possible channels of systemic risk propagation. Combining measures of connectedness of these networks with the ratings of the sovereign bonds, we propose a flight-to-quality indicator to identify periods of turbulence in the market. Our measure clearly peaks at the onset of the European sovereign debt crisis, signaling the instability of the financial system. Finally, we use the connectedness measures of the networks to forecast the quality of sovereign bonds. We find that connectedness is a significant predictor of the cross-section of bond quality

New centrality and causality metrics assessing air traffic network interactions

In ATM systems, the massive number of interacting entities makes it difficult to identify critical elements and paths of disturbance propagation, as well as to predict the system-wide effects that innovations might have. To this end, suitable metrics are required to assess the role of the interconnections between the elements and complex network science provides several network metrics to evaluate the network functioning. Here we focus on centrality and causality metrics measuring, respectively, the importance of a node and the propagation of disturbances along links. By investigating a dataset of US flights, we show that existing centrality and causality metrics are not suited to characterise the effect of delays in the system. We then propose generalisations of such metrics that we prove suited to ATM applications. Specifically, the new centrality is able to account for the temporal and multi-layer structure of ATM network, while the new causality metric focuses on the propagation of extreme events along the system