Context. Open clusters (OCs) are popular tracers of the structure and evolutionary history of the Galactic disk. The OC population is often considered to be complete within 1.8 kpc of the Sun. The recent Gaia Data Release 2 (DR2) allows the latter claim to be challenged. Aims. We perform a systematic search for new OCs in the direction of Perseus using precise and accurate astrometry from Gaia DR2. Methods. We implement a coarse-to-fine search method. First, we exploit spatial proximity using a fast density-aware partitioning of the sky via a k-d tree in the spatial domain of Galactic coordinates, (l, b). Secondly, we employ a Gaussian mixture model in the proper motion space to quickly tag fields around OC candidates. Thirdly, we apply an unsupervised membership assignment method, UPMASK, to scrutinise the candidates. We visually inspect colour-magnitude diagrams to validate the detected objects. Finally, we perform a diagnostic to quantify the significance of each identified overdensity in proper motion and in parallax space. Results. We report the discovery of 41 new stellar clusters. This represents an increment of at least 20% of the previously known OC population in this volume of the Milky Way. We also report on the clear identification of NGC 886, an object previously considered an asterism. This study challenges the previous claim of a near-complete sample of open clusters up to 1.8 kpc. Our results reveal that this claim requires revision, and a complete census of nearby open clusters is yet to be found.

We study 21cm and Lyα fluctuations, as well as Hα, while distinguishing between Lyα emission of galactic, diffuse, and scattered intergalactic medium (IGM) origin. Cross-correlation information about the state of the IGM is obtained, testing neutral versus ionized medium cases with different tracers in a seminumerical simulation setup. In order to pave the way toward constraints on reionization history and modeling beyond power spectrum information, we explore parameter dependencies of the cross-power signal between 21 cm and Lyα, which displays a characteristic morphology and a turnover from negative to positive correlation at scales of a couple Mpc −1 . In a proof of concept for the extraction of further information on the state of the IGM using different tracers, we demonstrate the use of the 21 cm and Hα cross-correlation signal to determine the relative strength of galactic and IGM emission in Lyα. We conclude by showing the detectability of the 21 cm and Lyα cross-correlation signal over more than one decade in scale at high signal-to-noise ratio for upcoming probes like SKA and the proposed all-sky intensity mapping satellites SPHEREx and CDIM, while also including the Lyα damping tail and 21cm foreground avoidance in the modeling.

The use of advanced statistical analysis tools is crucial in order to improve cosmological parameter estimates via removal of systematic errors and identification of previously unaccounted for cosmological signals. Here we demonstrate the application of a new fully-Bayesian method, the internal robustness formalism, to scan for systematics and new signals in the recent supernova Ia Union compilations. Our analysis is tailored to maximize chances of detecting the anomalous subsets by means of a variety of sorting algorithms. We analyse supernova Ia distance moduli for effects depending on angular separation, redshift, surveys and hemispherical directions. The data have proven to be robust within 2σ, giving an independent confirmation of successful removal of systematics-contaminated supernovae. Hints of new cosmology, as for example the anisotropies reported by Planck, do not seem to be reflected in the supernova Ia data.

The new generation of deep photometric surveys requires unprecedentedly precise shape and photometry measurements of billions of galaxies to achieve their main science goals. At such depths, one major limiting factor is the blending of galaxies due to line-of-sight projection, with an expected fraction of blended galaxies of up to 50%. Current deblending approaches are in most cases either too slow or not accurate enough to reach the level of requirements. This work explores the use of deep neural networks to estimate the photometry of blended pairs of galaxies in monochrome space images, similar to the ones that will be delivered by the Euclid space telescope. Using a clean sample of isolated galaxies from the CANDELS survey, we artificially blend them and train two different network models to recover the photometry of the two galaxies. We show that our approach can recover the original photometry of the galaxies before being blended with ∼ 7% accuracy without any human intervention and without any assumption on the galaxy shape. This represents an improvement of at least a factor of 4 compared to the classical SExtractor approach. We also show that forcing the network to simultaneously estimate a binary segmentation map results in a slightly improved photometry. All data products and codes will be made public to ease the comparison with other approaches on a common data set.

We constrain cold dark energy of negligible sound speed using galaxy cluster abundance observations. In contrast to standard quasi-homogeneous dark energy, negligible sound speed implies clustering of the dark energy fluid at all scales, allowing us to measure the effects of dark energy perturbations at cluster scales. We compare those models and set the stage for using non-linear information from semi-analytical modelling in cluster growth data analyses. For this, we recalibrate the halo mass function with nonlinear characteristic quantities, the spherical collapse threshold and virial overdensity, that account for model and redshift dependent behaviours, as well as an additional mass contribution for cold dark energy. We present the first constraints from this cold dark matter plus cold dark energy mass function using our cluster abundance likelihood, which self-consistently accounts for selection effects, covariances and systematic uncertainties. We combine cluster growth data with CMB, SNe Ia and BAO data, and find a shift between cold versus quasi-homogeneous dark energy of up to 1σ . We make a Fisher matrix forecast of constraints attainable with cluster growth data from the on-going Dark Energy Survey (DES). For DES, we predict ∼50% tighter constraints on (Ω m , w) for cold dark energy versus wCDM models, with the same free parameters. Overall, we show that cluster abundance analyses are sensitive to cold dark energy, an alternative, viable model that should be routinely investigated alongside the standard dark energy scenario.

Galaxies can be characterized by many internal properties such as stellar mass, gas metallicity, and star formation rate. We quantify the amount of cosmological and astrophysical information that the internal properties of individual galaxies and their host dark matter halos contain. We train neural networks using hundreds of thousands of galaxies from 2000 state-of-the-art hydrodynamic simulations with different cosmologies and astrophysical models of the CAMELS project to perform likelihood-free inference on the value of the cosmological and astrophysical parameters. We find that knowing the internal properties of a single galaxy allows our models to infer the value of Ωm, at fixed Ωb, with a ∼10% precision, while no constraint can be placed on σ 8. Our results hold for any type of galaxy, central or satellite, massive or dwarf, at all considered redshifts, z ≤ 3, and they incorporate uncertainties in astrophysics as modeled in CAMELS. However, our models are not robust to changes in subgrid physics due to the large intrinsic differences the two considered models imprint on galaxy properties. We find that the stellar mass, stellar metallicity, and maximum circular velocity are among the most important galaxy properties to determine the value of Ωm. We believe that our results can be explained by considering that changes in the value of Ωm, or potentially Ωb/Ωm, affect the dark matter content of galaxies, which leaves a signature in galaxy properties distinct from the one induced by galactic processes. Our results suggest that the low-dimensional manifold hosting galaxy properties provides a tight direct link between cosmology and astrophysics.

Line intensity mapping opens up a new and exciting window for probing cosmology and fundamental physics during the Epoch of Reionisation, extending to redshifts previously untested by galaxy surveys. The power spectra of these line fluctuations are a promising tool to test gravity over a large range of scales and redshifts. We simulate cosmological volumes of 21cm fluctuations in general parametrisations of modified gravity, in order to calculate the corresponding power spectra, where additional parameters are the initial condition of matter perturbations α and the scale-dependent modified gravity parameter Y (also known as G eff ) that measures deviations from GR in the Poisson equation. We show the impact of these model-independent modifications of gravity, to either delay or expedite reionisation. For the 21cm intensity mapping survey to be performed by the SKA mission, we forecast the ability of line intensity mapping to constrain the parameters Y and α at redshifts z = 6 − 11, where Y is assumed constant during this epoch (but without requiring constancy at all times). In our most conservative scenario, the Y parameter can be constrained at the tens of percent level, while for improved modelling of foregrounds as well as of the (mildly) non-linear regime, up to sub-percent level constraints are attainable. We show the impact of jointly estimating reionisation model parameters and corresponding parameter correlations, as well as of foreground removal. We note, that tomography is crucial to break degeneracies and for constraints not to degrade significantly when adding reionisation model parameters, with most constraining power coming from the redshift bins z = 7 − 10 where the shape of the 21cm power spectrum is evolving fastest.

Cross-correlating 21 cm with known cosmic signals will be invaluable proof of the cosmic origin of the first 21-cm detections. As some of the widest fields available, comprising thousands of sources with reasonably known redshifts, narrow-band Lyman-α emitter (LAE) surveys are an obvious choice for such cross-correlation. Here, we revisit the 21-cm–LAE cross-correlation, relaxing the common assumption of reionization occurring in a pre-heated intergalactic medium (IGM). Using specifications from the Square Kilometre Array and the Subaru Hyper Supreme-Cam, we present new forecasts of the 21-cm–LAE cross-correlation function at z ∼ 7. We sample a broad parameter space of the mean IGM neutral fraction and spin temperature, ($\bar{x}_{\rm H\,{\small I}}$, $\bar{T}_{\rm S}$). The sign of the cross-correlation roughly follows the sign of the 21-cm signal: Ionized regions that surround LAEs correspond to relative hot spots in the 21-cm signal when the neutral IGM is colder than the CMB, and relative cold spots when the neutral IGM is hotter than the CMB. The amplitude of the cross-correlation function generally increases with increasing $\bar{x}_{\rm H\,{\small I}}$, following the increasing bias of the cosmic H ii regions. As is the case for 21 cm, the strongest cross signal occurs when the IGM is colder than the CMB, providing a large contrast between the neutral regions and the ionized regions, which host LAEs. We also vary the topology of reionization and the epoch of X-ray heating. The cross-correlation during the first half of reionization is sensitive to these topologies, and could thus be used to constrain them.