Accurate determination of Fe(II) concentrations in the presence of a very high soluble Fe(III) background

Analytical methods used for determining dissolved Fe(II) often yield inaccurate results in the presence of high Fe(III) concentrations. Accurate analysis of Fe(II) in solution when it is less than 1% of the total dissolved Fe concentration (Fe_T) is sometimes required in both geochemical and environmental studies. For example, such analysis is imperative for obtaining the ratio Fe(II)/Fe(III) in rocks, soils and sediments, for determining the kinetic constants of Fe(II) oxidation in chemical or biochemical systems operating at low pH, and is also important in environmental engineering projects, e.g. for proper control of the regeneration step (oxidation of Fe(II) into Fe(III)) applied in ferric-based gas desulphurization processes. In this work a method capable of yielding accurate Fe(II) concentrations at Fe(II) to Fe_T ratios as low as 0.05% is presented. The method is based on a pretreatment procedure designed to separate Fe(II) species from Fe(III) species in solution without changing the original Fe(II) concentration. Once separated, a modified phenanthroline method is used to determine the Fe(II) concentration, in the virtual absence of Fe(III) species. The pretreatment procedure consists of pH elevation to pH 4.2–4.65 using NaHCO₃ under N₂(g) environment, followed by filtration of the solid ferric oxides formed, and subsequent acidification of the Fe(II)-containing filtrate. Accuracy of Fe(II) analyses obtained for samples (Fe(II)/Fe_T ratios between 2% and 0.05%) to which the described pretreatment was applied was >95%. Elevating pH to above 4.65 during pretreatment was shown to result in a higher error in Fe(II) determination, likely resulting from adsorption of Fe(II) species and their removal from solution with the ferric oxide precipitate.     

Estimating the significance of a signal in a multi-dimensional search

In experiments that are aimed at detecting astrophysical sources such as neutrino telescopes, one usually performs a search over a continuous parameter space (e.g. the angular coordinates of the sky, and possibly time), looking for the most significant deviation from the background hypothesis. Such a procedure inherently involves a “look elsewhere effect”, namely, the possibility for a signal-like fluctuation to appear anywhere within the search range. Correctly estimating the p-value of a given observation thus requires repeated simulations of the entire search, a procedure that may be prohibitively expansive in terms of CPU resources. Recent results from the theory of random fields provide powerful tools which may be used to alleviate this difficulty, in a wide range of applications. We review those results and discuss their implementation, with a detailed example applied for neutrino point source analysis in the IceCube experiment.     

Cosmological parameters from velocities, cosmic microwave background and supernovae

We compare and combine likelihood functions of the cosmological parameters Ω_m, h and σ ₈, from peculiar velocities, cosmic microwave background (CMB) and type Ia supernovae. These three data sets directly probe the mass in the Universe, without the need to relate the galaxy distribution to the underlying mass via a 'biasing' relation. We include the recent results from the CMB experiments BOOMERANG and MAXIMA-1. Our analysis assumes a flat Λ cold dark matter (ΛCDM) cosmology with a scale-invariant adiabatic initial power spectrum and baryonic fraction as inferred from big-bang nucleosynthesis. We find that all three data sets agree well, overlapping significantly at the 2 σ level. This therefore justifies a joint analysis, in which we find a joint best-fitting point and 95 per cent confidence limits of     (0.17,0.39),     (0.64,0.86) and     (0.98,1.37). In terms of the natural parameter combinations for these data     (0.40,0.73),     (0.16,0.27). Also for the best-fitting point,     and the age of the Universe is 13.2 Gyr.     

The 2dF Galaxy Redshift Survey: luminosity dependence of galaxy clustering

We investigate the dependence of the strength of galaxy clustering on intrinsic luminosity using the Anglo-Australian two degree field galaxy redshift survey (2dFGRS). The 2dFGRS is over an order of magnitude larger than previous redshift surveys used to address this issue. We measure the projected two-point correlation function of galaxies in a series of volume-limited samples. The projected correlation function is free from any distortion of the clustering pattern induced by peculiar motions and is well described by a power law in pair separation over the range     . The clustering of     galaxies in real space is well-fitted by a correlation length     and power-law slope     . The clustering amplitude increases slowly with absolute magnitude for galaxies fainter than M *, but rises more strongly at higher luminosities. At low luminosities, our results agree with measurements from the Southern Sky Redshift Survey 2 by Benoist et al. However, we find a weaker dependence of clustering strength on luminosity at the highest luminosities. The correlation function amplitude increases by a factor of 4.0 between     and −22.5, and the most luminous galaxies are 3.0 times more strongly clustered than L * galaxies. The power-law slope of the correlation function shows remarkably little variation for samples spanning a factor of 20 in luminosity. Our measurements are in very good agreement with the predictions of the hierarchical galaxy formation models of Benson et al.