Constraints on Ωm\Omega_\mathrm{m} and σ8\sigma_8 from the potential-based cluster temperature function

The abundance of galaxy clusters is in principle a powerful tool to constrain cosmological parameters, especially $\Omega_\mathrm{m}$ and $\sigma_8$, due to the exponential dependence in the high-mass regime. While the best observables are the X-ray temperature and luminosity, the abundance of galaxy clusters, however, is conventionally predicted as a function of mass. Hence, the intrinsic scatter and the uncertainties in the scaling relations between mass and either temperature or luminosity lower the reliability of galaxy clusters to constrain cosmological parameters. In this article, we further refine the X-ray temperature function for galaxy clusters by Angrick et al., which is based on the statistics of perturbations in the cosmic gravitational potential and proposed to replace the classical mass-based temperature function, by including a refined analytic merger model and compare the theoretical prediction to results from a cosmological hydrodynamical simulation. Although we find already a good agreement if we compare with a cluster temperature function based on the mass-weighted temperature, including a redshift-dependent scaling between mass-based and spectroscopic temperature yields even better agreement between theoretical model and numerical results. As a proof of concept, incorporating this additional scaling in our model, we constrain the cosmological parameters $\Omega_\mathrm{m}$ and $\sigma_8$ from an X-ray sample of galaxy clusters and tentatively find agreement with the recent cosmic microwave background based results from the Planck mission at 1$\sigma$-level.Comment: 10 pages, 5 figures, 2 tables; accepted by MNRAS; some typos correcte

Relativistic virialization in the Spherical Collapse model for Einstein-de Sitter and \Lambda CDM cosmologies

Spherical collapse has turned out to be a successful semi-analytic model to study structure formation in different DE models and theories of gravity. Nevertheless, the process of virialization is commonly studied on the basis of the virial theorem of classical mechanics. In the present paper, a fully generally-relativistic virial theorem based on the Tolman-Oppenheimer-Volkoff (TOV) solution for homogeneous, perfect-fluid spheres is constructed for the Einstein-de Sitter and \Lambda CDM cosmologies. We investigate the accuracy of classical virialization studies on cosmological scales and consider virialization from a more fundamental point of view. Throughout, we remain within general relativity and the class of FLRW models. The virialization equation is set up and solved numerically for the virial radius, y_{vir}, from which the virial overdensity \Delta_{V} is directly obtained. Leading order corrections in the post-Newtonian framework are derived and quantified. In addition, problems in the application of this formalism to dynamical DE models are pointed out and discussed explicitly. We show that, in the weak field limit, the relative contribution of the leading order terms of the post-Newtonian expansion are of the order of 10^{-3}% and the solution of Wang & Steinhardt (1998) is precisely reproduced. Apart from the small corrections, the method could provide insight into the process of virialization from a more fundamental point of view.Comment: 15 pages, 2 figure

The impact of tethered recording techniques on activity and sleep patterns in rats

Funding Information: The project was supported by grants of Deutsche Forschungsgemeinschaft (FOR 2591, GZ: PO681/9-1 and 9-2). The authors thank Sarah Glisic, Helen Stirling, Claudia Siegl, Sieglinde Fischlein, Andreas Kutschka and Isabella Waclawczyk for their excellent technical assistance. The authors thank Helen Stirling for language revision. Open Access funding enabled and organized by Projekt DEALPeer reviewedPublisher PD

Hybrid Powertrain Technology Assessment through an Integrated Simulation Approach

Global automotive fuel economy and emissions pressures mean that 48 V hybridisation will become a significant presence in the passenger car market. The complexity of powertrain solutions is increasing in order to further improve fuel economy for hybrid vehicles and maintain robust emissions performance. However, this results in complex interactions between technologies which are difficult to identify through traditional development approaches, resulting in sub-optimal solutions for either vehicle attributes or cost. The results presented in this paper are from a simulation programme focussed on the optimisation of various advanced powertrain technologies on 48 V hybrid vehicle platforms. The technologies assessed include an electrically heated catalyst, an insulated turbocharger, an electric water pump and a thermal management module. The novel simulation approach undertaken uses an integrated toolchain capturing thermal, electrical and mechanical energy usage across all powertrain sub-systems. Through integrating 0-D and 1-D sub-models into a single modelling environment, the operating strategy of the technologies can be optimised while capturing the synergies that exist between them. This approach enables improved and more informed cost/benefit ratios for the technologies to be produced and better attributes by identifying the optimum strategy for the vehicle. The results show the potential for CO2 reductions in the range of 2-5% at no additional cost, through co-optimisation of the technologies in a single simulation environment. The simulation work forms part of the THOMSON project, a collaborative research project aiming to develop cost effective 48 V solutions, in order to reduce the environmental impact of the transportation sector.</p

Hybrid Powertrain Technology Assessment through an Integrated Simulation Approach

Global automotive fuel economy and emissions pressures mean that 48 V hybridisation will become a significant presence in the passenger car market. The complexity of powertrain solutions is increasing in order to further improve fuel economy for hybrid vehicles and maintain robust emissions performance. However, this results in complex interactions between technologies which are difficult to identify through traditional development approaches, resulting in sub-optimal solutions for either vehicle attributes or cost. The results presented in this paper are from a simulation programme focussed on the optimisation of various advanced powertrain technologies on 48 V hybrid vehicle platforms. The technologies assessed include an electrically heated catalyst, an insulated turbocharger, an electric water pump and a thermal management module. The novel simulation approach undertaken uses an integrated toolchain capturing thermal, electrical and mechanical energy usage across all powertrain sub-systems. Through integrating 0-D and 1-D sub-models into a single modelling environment, the operating strategy of the technologies can be optimised while capturing the synergies that exist between them. This approach enables improved and more informed cost/benefit ratios for the technologies to be produced and better attributes by identifying the optimum strategy for the vehicle. The results show the potential for CO2 reductions in the range of 2-5% at no additional cost, through co-optimisation of the technologies in a single simulation environment. The simulation work forms part of the THOMSON project, a collaborative research project aiming to develop cost effective 48 V solutions, in order to reduce the environmental impact of the transportation sector.</p

Heteroskedasticity of Unknown Form in Spatial Autoregressive Models with Moving Average Disturbance Term

In this study, I investigate the necessary condition for the consistency of the maximum likelihood estimator (MLE) of spatial models with a spatial moving average process in the disturbance term. I show that the MLE of spatial autoregressive and spatial moving average parameters is generally inconsistent when heteroskedasticity is not considered in the estimation. I also show that the MLE of parameters of exogenous variables is inconsistent and determine its asymptotic bias. I provide simulation results to evaluate the performance of the MLE. The simulation results indicate that the MLE imposes a substantial amount of bias on both autoregressive and moving average parameters