Bayesian evidence for two companions orbiting HIP 5158

We present results of a Bayesian analysis of radial velocity (RV) data for the star HIP 5158, confirming the presence of two companions and also constraining their orbital parameters. Assuming Keplerian orbits, the two-companion model is found to be e^{48} times more probable than the one-planet model, although the orbital parameters of the second companion are only weakly constrained. The derived orbital periods are 345.6 +/- 2.0 d and 9017.8 +/- 3180.7 d respectively, and the corresponding eccentricities are 0.54 +/- 0.04 and 0.14 +/- 0.10. The limits on planetary mass (m \sin i) and semimajor axis are (1.44 +/- 0.14 M_{J}, 0.89 +/- 0.01 AU) and (15.04 +/- 10.55 M_{J}, 7.70 +/- 1.88 AU) respectively. Owing to large uncertainty on the mass of the second companion, we are unable to determine whether it is a planet or a brown dwarf. The remaining `noise' (stellar jitter) unaccounted for by the model is 2.28 +/- 0.31 m/s. We also analysed a three-companion model, but found it to be e^{8} times less probable than the two-companion model.Comment: 5 pages, 4 figures, 3 tables. Added a couple of figures showing the residuals after one and two companion fits. Accepted for publication in MNRAS Letter

Floating Offshore Wind Turbines Oscillations Damping.

This article deals with the modelling and control of oscillations that appear on floating offshore wind turbines (FOWT). First, these offshore wind energy systems, located in deep waters, are described and the modeling approach is presented. Secondly, the traditional structural control strategies based on tuned mass-damper (TMD) systems for oscillations reduction are complemented with a passive mechanism called inerter in order to improve the performance of the structural controller. This work is based on a previous work by the authors in which the inerter was located in parallel to an existing TMD in the nacelle of the FOWT. In this work, the inerter is located between the tower and the barge and results are compared to those obtained previously showing better performance. The results here presented are promising in terms of oscillations damping, both in amplitude and frequency, and constitute preliminary results of the ongoing current research of the authors

Testing the mutual consistency of different supernovae surveys

It is now common practice to constrain cosmological parameters using supernovae (SNe) catalogues constructed from several different surveys. Before performing such a joint analysis, however, one should check that parameter constraints derived from the individual SNe surveys that make up the catalogue are mutually consistent. We describe a statistically-robust mutual consistency test, which we calibrate using simulations, and apply it to each pairwise combination of the surveys making up, respectively, the UNION2 catalogue and the very recent JLA compilation by Betoule et al. We find no inconsistencies in the latter case, but conclusive evidence for inconsistency between some survey pairs in the UNION2 catalogue.Comment: 8 pages, 9 figures, submitted to MNRA

Weak lensing by triaxial galaxy clusters

Weak gravitational lensing studies of galaxy clusters often assume a spherical cluster model to simplify the analysis, but some recent studies have suggested this simplifying assumption may result in large biases in estimated cluster masses and concentration values, since clusters are expected to exhibit triaxiality. Several such analyses have, however, quoted expressions for the spatial derivatives of the lensing potential in triaxial models, which are open to misinterpretation. In this paper, we give a clear description of weak lensing by triaxial NFW galaxy clusters and also present an efficient and robust method to model these clusters and obtain parameter estimates. By considering four highly triaxial NFW galaxy clusters, we re-examine the impact of simplifying spherical assumptions and found that while the concentration estimates are largely unbiased except in one of our traixial NFW simulated clusters, for which the concentration is only slightly biased, the masses are significantly biased, by up to 40%, for all the clusters we analysed. Moreover, we find that such assumptions can lead to the erroneous conclusion that some substructure is present in the galaxy clusters or, even worse, that multiple galaxy clusters are present in the field. Our cluster fitting method also allows one to answer the question of whether a given cluster exhibits triaxiality or a simple spherical model is good enough.Comment: 8 pages, 3 figures, 2 tables, minor changes in response to referee's comments, accepted for publication in MNRA

A Coverage Study of the CMSSM Based on ATLAS Sensitivity Using Fast Neural Networks Techniques

We assess the coverage properties of confidence and credible intervals on the CMSSM parameter space inferred from a Bayesian posterior and the profile likelihood based on an ATLAS sensitivity study. In order to make those calculations feasible, we introduce a new method based on neural networks to approximate the mapping between CMSSM parameters and weak-scale particle masses. Our method reduces the computational effort needed to sample the CMSSM parameter space by a factor of ~ 10^4 with respect to conventional techniques. We find that both the Bayesian posterior and the profile likelihood intervals can significantly over-cover and identify the origin of this effect to physical boundaries in the parameter space. Finally, we point out that the effects intrinsic to the statistical procedure are conflated with simplifications to the likelihood functions from the experiments themselves.Comment: Further checks about accuracy of neural network approximation, fixed typos, added refs. Main results unchanged. Matches version accepted by JHE

Classifying LISA gravitational wave burst signals using Bayesian evidence

We consider the problem of characterisation of burst sources detected with the Laser Interferometer Space Antenna (LISA) using the multi-modal nested sampling algorithm, MultiNest. We use MultiNest as a tool to search for modelled bursts from cosmic string cusps, and compute the Bayesian evidence associated with the cosmic string model. As an alternative burst model, we consider sine-Gaussian burst signals, and show how the evidence ratio can be used to choose between these two alternatives. We present results from an application of MultiNest to the last round of the Mock LISA Data Challenge, in which we were able to successfully detect and characterise all three of the cosmic string burst sources present in the release data set. We also present results of independent trials and show that MultiNest can detect cosmic string signals with signal-to-noise ratio (SNR) as low as ~7 and sine-Gaussian signals with SNR as low as ~8. In both cases, we show that the threshold at which the sources become detectable coincides with the SNR at which the evidence ratio begins to favour the correct model over the alternative.Comment: 21 pages, 11 figures, accepted by CQG; v2 has minor changes for consistency with accepted versio

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