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Register a new userBiases from neutrino bias: to worry or not to worry?
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Alvise Raccanelli
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The relation between the halo field and the matter fluctuations (halo bias), in the presence of massive neutrinos depends on the total neutrino mass, massive neutrinos introduce an additional scale-dependence of the bias which is usually neglected in cosmological analyses. We investigate the magnitude of the systematic effect on interesting cosmological parameters induced by neglecting this scale dependence, finding that while it is not a problem for current surveys, it is non-negligible for future, denser or deeper ones depending on the neutrino mass, the maximum scale used for the analyses and the details of the nuisance parameters considered. However there is a simple recipe to account for the bulk of the effect as to make it fully negligible, which we illustrate and advocate should be included in analysis of forthcoming large-scale structure surveys.
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In cosmologies with massive neutrinos, the galaxy bias defined with respect to the total matter field (cold dark matter, baryons, and non-relativistic neutrinos) depends on the sum of the neutrino masses $M_{ u}$, and becomes scale-dependent even on large scales. This effect has been usually neglected given the sensitivity of current surveys, but becomes a severe systematic for future surveys aiming to provide the first detection of non-zero $M_{ u}$. The effect can be corrected for by defining the bias with respect to the density field of cold dark matter and baryons instead of the total matter field. In this work, we provide a simple prescription for correctly mitigating the neutrino-induced scale-dependent bias effect in a practical way. We clarify a number of subtleties regarding how to properly implement this correction in the presence of redshift-space distortions and non-linear evolution of perturbations. We perform a MCMC analysis on simulated galaxy clustering data that match the expected sensitivity of the textit{Euclid} survey. We find that the neutrino-induced scale-dependent bias can lead to important shifts in both the inferred mean value of $M_{ u}$, as well as its uncertainty. We show how these shifts propagate to other cosmological parameters correlated with $M_{ u}$, such as the cold dark matter physical density $Omega_{cdm} h^2$ and the scalar spectral index $n_s$. In conclusion, we find that correctly accounting for the neutrino-induced scale-dependent bias will be of crucial importance for future galaxy clustering analyses. We encourage the cosmology community to correctly account for this effect using the simple prescription we present in our work. The tools necessary to easily correct for the neutrino-induced scale-dependent bias will be made publicly available in an upcoming release of the Boltzmann solver texttt{CLASS}.
When an object impacts the free surface of a liquid, it ejects a splash curtain upwards and creates an air cavity below the free surface. As the object descends into the liquid, the air cavity eventually closes under the action of hydrostatic pressure (deep seal). In contrast, the surface curtain may splash outwards or dome over and close, creating a surface seal. In this paper we experimentally investigate how the splash curtain dynamics are governed by the interplay of cavity pressure difference, gravity, and surface tension and how they control the occurrence, or not, of surface seal. Based on the experimental observations and measurements, we develop an analytical model to describe the trajectory and dynamics of the splash curtain. The model enables us to reveal the scaling relationship for the dimensionless surface seal time and discover the existence of a critical dimensionless number that predicts the occurrence of surface seal. This scaling indicates that the most significant parameter governing the occurrence of surface seal is the velocity of the airflow rushing into the cavity. This is in contrast to the current understanding which considers the impact velocity as the determinant parameter.
We reveal critical insights into problems of bias in state-of-the-art facial recognition (FR) systems using a novel Balanced Faces In the Wild (BFW) dataset: data balanced for gender and ethnic groups. We show variations in the optimal scoring threshold for face-pairs across different subgroups. Thus, the conventional approach of learning a global threshold for all pairs resulting in performance gaps among subgroups. By learning subgroup-specific thresholds, we not only mitigate problems in performance gaps but also show a notable boost in the overall performance. Furthermore, we do a human evaluation to measure the bias in humans, which supports the hypothesis that such a bias exists in human perception. For the BFW database, source code, and more, visit github.com/visionjo/facerec-bias-bfw.
We use the NewHorizon simulation to study the redshift evolution of bar properties and fractions within galaxies in the stellar masses range $M_{star} = 10^{7.25} - 10^{11.4} rm{M}_{odot}$ over the redshift range $z = 0.25 - 1.3$. We select disc galaxies using stellar kinematics as a proxy for galaxy morphology. We employ two different automated bar detection methods, coupled with visual inspection, resulting in observable bar fractions of $f_{rm bar} = 0.070_{{-0.012}}^{{+0.018}}$ at $zsim$ 1.3, decreasing to $f_{rm bar} = 0.011_{{-0.003}}^{{+0.014}}$ at $zsim$ 0.25. Only one galaxy is visually confirmed as strongly barred in our sample. This bar is hosted by the most massive disk and only survives from $z=1.3$ down to $z=0.7$. Such a low bar fraction, in particular amongst Milky Way-like progenitors, highlights a missing bars problem, shared by literally all cosmological simulations with spatial resolution $<$100 pc to date. The analysis of linear growth rates, rotation curves and derived summary statistics of the stellar, gas and dark matter components suggest that galaxies with stellar masses below $10^{9.5}-10^{10} rm{M}_{odot}$ in NewHorizon appear to be too dominated by dark matter to bar, while more massive galaxies typically have formed large bulges that prevent bar persistence at low redshift. This investigation confirms that the evolution of the bar fraction puts stringent constraints on the assembly history of baryons and dark matter onto galaxies.
Large surveys of the local Universe have shown that galaxies with different intrinsic properties, such as colour, luminosity and morphological type display a range of clustering amplitudes. Galaxies are therefore not faithful tracers of the underlying matter distribution. This modulation of galaxy clustering, called bias, contains information about the physics behind galaxy formation. It is also a systematic to be overcome before the large-scale structure of the Universe can be used as a cosmological probe. Two types of approaches have been developed to model the clustering of galaxies. The first class is empirical and filters or weights the distribution of dark matter to reproduce the measured clustering. In the second approach an attempt is made to model the physics which governs fate of baryons in order to predict the number of galaxies in dark matter haloes. I will review the development of both approaches and summarize what we have learnt about galaxy bias.
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