Euclid:Cosmology forecasts from the void-galaxy cross-correlation function with reconstruction

We have investigated the cosmological constraints that can be expected from measurement of the cross-correlation of galaxies with cosmic voids identified in the Euclid spectroscopic survey, which will include spectroscopic information for tens of millions of galaxies over 15 000 deg2 of the sky in the redshift range 0.9 ≤ z &lt; 1.8. We have done this using simulated measurements obtained from the Flagship mock catalogue, the official Euclid mock that closely matches the expected properties of the spectroscopic dataset. To mitigate anisotropic selection-bias effects, we have used a velocity field reconstruction method to remove large-scale redshift-space distortions from the galaxy field before void-finding. This allowed us to accurately model contributions to the observed anisotropy of the cross-correlation function arising from galaxy velocities around voids as well as from the Alcock-Paczynski effect, and we studied the dependence of constraints on the efficiency of reconstruction. We find that Euclid voids will be able to constrain the ratio of the transverse comoving distance DM and Hubble distance DH to a relative precision of about 0:3%, and the growth rate fσ8 to a precision of between 5% and 8% in each of the four redshift bins covering the full redshift range. In the standard cosmological model, this translates to a statistical uncertainty δωm = ±0.0028 on the matter density parameter from voids, which is better than what can be achieved from either Euclid galaxy clustering and weak lensing individually. We also find that voids alone can measure the dark energy equation of state to a 6% precision.</p

Neuroimmunology - the past, present and future

Neuroimmunology as a separate discipline has its roots in the fields of neurology, neuroscience and immunology. Early studies of the brain by Golgi and Cajal, the detailed clinical and neuropathology studies of Charcot and Thompson’s seminal paper on graft acceptance in the central nervous system, kindled a now rapidly expanding research area, with the aim of understanding pathological mechanisms of inflammatory components of neurological disorders. While neuroimmunologists originally focused on classical neuroinflammatory disorders, such as multiple sclerosis and infections, there is strong evidence to suggest that the immune response contributes to genetic white matter disorders, epilepsy, neurodegenerative diseases, neuropsychiatric disorders, peripheral nervous system and neuro‐oncological conditions, as well as ageing. Technological advances have greatly aided our knowledge of how the immune system influences the nervous system during development and ageing, and how such responses contribute to disease as well as regeneration and repair. Here, we highlight historical aspects and milestones in the field of neuroimmunology and discuss the paradigm shifts that have helped provide novel insights into disease mechanisms. We propose future perspectives including molecular biological studies and experimental models that may have the potential to push many areas of neuroimmunology. Such an understanding of neuroimmunology will open up new avenues for therapeutic approaches to manipulate neuroinflammation

Managing the Euclid Data Model

The Euclid common data model is central in, and essential to, the Euclid science ground segment. It defines the format of all data exchanged between the pipelines and stored in the Euclid Archive, and ensures all components can communicate with each other. But with more than 25 active contributors, managing the data model has been a challenge. Care must be taken that changes in the XML of the data model do not break its Python, C++, or database bindings. We describe recent progress in tackling these problems. The former problem has been mitigated with a new data model validator tool run during continuous integration. The latter has partially been solved via git management rules. Both approaches have only been possible after the migration of SVN to git, allowing the introduction of modern tooling

Euclid preparation:XXVIII. Modelling of the weak lensing angular power spectrum

This work considers which higher-order effects in modelling the cosmic shear angular power spectra must be taken into account for Euclid. We identify which terms are of concern, and quantify their individual and cumulative impact on cosmological parameter inference from Euclid. We compute the values of these higher-order effects using analytic expressions, and calculate the impact on cosmological parameter estimation using the Fisher matrix formalism. We review 24 effects and find the following potentially need to be accounted for: the reduced shear approximation, magnification bias, source-lens clustering, source obscuration, local Universe effects, and the flat Universe assumption. Upon computing these explicitly, and calculating their cosmological parameter biases, using a maximum multipole of $\ell=5000$, we find that the magnification bias, source-lens clustering, source obscuration, and local Universe terms individually produce significant (\,>0.25\sigma) cosmological biases in one or more parameters, and accordingly must be accounted for. In total, over all effects, we find biases in $\Omega_{\rm m}$, $\Omega_{\rm b}$, $h$, and $\sigma_{8}$ of $0.73\sigma$, $0.28\sigma$, $0.25\sigma$, and $-0.79\sigma$, respectively, for flat $\Lambda$CDM. For the $w_0w_a$CDM case, we find biases in $\Omega_{\rm m}$, $\Omega_{\rm b}$, $h$, $n_{\rm s}$, $\sigma_{8}$, and $w_a$ of $1.49\sigma$, $0.35\sigma$, $-1.36\sigma$, $1.31\sigma$, $-0.84\sigma$, and $-0.35\sigma$, respectively; which are increased relative to the $\Lambda$CDM due to additional degeneracies as a function of redshift and scale

Euclid preparation:XXVIII. Modelling of the weak lensing angular power spectrum

This work considers which higher-order effects in modelling the cosmic shear angular power spectra must be taken into account for Euclid. We identify which terms are of concern, and quantify their individual and cumulative impact on cosmological parameter inference from Euclid. We compute the values of these higher-order effects using analytic expressions, and calculate the impact on cosmological parameter estimation using the Fisher matrix formalism. We review 24 effects and find the following potentially need to be accounted for: the reduced shear approximation, magnification bias, source-lens clustering, source obscuration, local Universe effects, and the flat Universe assumption. Upon computing these explicitly, and calculating their cosmological parameter biases, using a maximum multipole of $\ell=5000$, we find that the magnification bias, source-lens clustering, source obscuration, and local Universe terms individually produce significant (\,>0.25\sigma) cosmological biases in one or more parameters, and accordingly must be accounted for. In total, over all effects, we find biases in $\Omega_{\rm m}$, $\Omega_{\rm b}$, $h$, and $\sigma_{8}$ of $0.73\sigma$, $0.28\sigma$, $0.25\sigma$, and $-0.79\sigma$, respectively, for flat $\Lambda$CDM. For the $w_0w_a$CDM case, we find biases in $\Omega_{\rm m}$, $\Omega_{\rm b}$, $h$, $n_{\rm s}$, $\sigma_{8}$, and $w_a$ of $1.49\sigma$, $0.35\sigma$, $-1.36\sigma$, $1.31\sigma$, $-0.84\sigma$, and $-0.35\sigma$, respectively; which are increased relative to the $\Lambda$CDM due to additional degeneracies as a function of redshift and scale