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Register a new userA robust method for fitting peculiar velocity field models
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We present a new method for fitting peculiar velocity models to complete flux limited magnitude-redshifts catalogues, using the luminosity function of the sources as a distance indicator.The method is characterised by its robustness. In particular, no assumptions are made concerning the spatial distribution of sources and their luminosity function. Moreover, selection effects in redshift are allowed. Furthermore the inclusion of additional observables correlated with the absolute magnitude -- such as for example rotation velocity information as described by the Tully-Fisher relation -- is straightforward. As an illustration of the method, the predicted IRAS peculiar velocity model characterised by the density parameter beta is tested on two samples. The application of our method to the Tully-Fisher MarkIII MAT sample leads to a value of beta=0.6 pm 0.125, fully consistent with the results obtained previously by the VELMOD and ITF methods on similar datasets. Unlike these methods however, we make a very conservative use of the Tully-Fisher information. Specifically, we require to assume neither the linearity of the Tully-Fisher relation nor a gaussian distribution of its residuals. Moreover, the robustness of the method implies that no Malmquist corrections are required. A second application is carried out, using the fluxes of the IRAS 1.2 Jy sample as the distance indicator. In this case the effective depth of the volume in which the velocity model is compared to the data is almost twice the effective depth of the MarkIII MAT sample. The results suggest that the predicted IRAS velocity model, while successful in reproducing locally the cosmic flow, fails to describe the kinematics on larger scales.
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The Tully-Fisher (Tully and Fisher 1977; TF) relation is applied to obtain peculiar velocities of field spirals galaxies and to calculate dipoles of the peculiar velocity field to cz ~ 8000 km/s. The field galaxy sample is spatially co-extensive with and completely independent on a cluster sample, for which dipole characteristics are given in a separate paper. Dipoles of the peculiar velocity field are obtained separately by applying (i) an inverse version of the TF relation and selecting galaxies by redshift windowing and (ii) a direct TF relation, with velocities corrected for the inhomogeneous Malmquist bias, and windowing galaxies by TF distance. The two determinations agree, as they do with the cluster sample. When measured in a reference frame in which the Local Group is at rest, the dipole moment of field galaxies farther than ~4000 km/s is in substantial agreement, both in amplitude and direction, with that exhibited by the Cosmic Microwave Background radiation field.
We estimate the velocity field in a large set of $N$-body simulations including massive neutrino particles, and measure the auto-power spectrum of the velocity divergence field as well as the cross-power spectrum between the cold dark matter density and the velocity divergence. We perform these measurements at four different redshifts and within four different cosmological scenarios, covering a wide range in neutrino masses. We find that the nonlinear correction to the velocity power spectra largely depend on the degree of nonlinear evolution with no specific dependence on the value of neutrino mass. We provide a fitting formula, based on the value of the r.m.s. of the matter fluctuations in spheres of $8h^{-1}$Mpc, describing the nonlinear corrections with 3% accuracy on scales below $k=0.7; h$ Mpc$^{-1}$.
We propose to use spatial correlations of the kinetic Sunyaev-Zeldovich (KSZ) flux as an estimator of the peculiar velocity power spectrum. In contrast with conventional techniques, our new method does not require measurements of the thermal SZ signal or the X-ray temperature. Moreover, this method has the special advantage that the expected systematic errors are always sub-dominant to statistical errors on all scales and redshifts of interest. We show that future large sky coverage KSZ surveys may allow a peculiar velocity power spectrum estimates of an accuracy reaching ~10%.
The standard technique for sub-pixel estimation of atom positions from atomic resolution scanning transmission electron microscopy images relies on fitting intensity maxima or minima with a two-dimensional Gaussian function. While this is a widespread method of measurement, it can be error prone in images with non-zero aberrations, strong intensity differences between adjacent atoms or in situations where the neighboring atom positions approach the resolution limit of the microscope. Here we demonstrate mpfit, an atom finding algorithm that iteratively calculates a series of overlapping two-dimensional Gaussian functions to fit the experimental dataset and then subsequently uses a subset of the calculated Gaussian functions to perform sub-pixel refinement of atom positions. Based on both simulated and experimental datasets presented in this work, this approach gives lower errors when compared to the commonly used single Gaussian peak fitting approach and demonstrates increased robustness over a wider range of experimental conditions.
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