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S. Sartori

Publications and source records attributed to S. Sartori.

4 recordsLinked to original sources

Euclid preparation. Probing galaxy evolution within cosmic voids in Euclid-like simulations

The evolution of galaxies is profoundly influenced by the environment in which they reside. Cosmic voids serve as pristine laboratories for studying galaxy evolution in the relative absence of the complex physical processes that dominate denser environments. In this study, we investigate galaxy properties and merger histories as a function of environment using the GAlaxy Evolution and Assembly (GAEA) mock-observation lightcone replicating the Euclid Deep Survey as foreseen for the first Euclid data release. The H$α$-selected galaxy sample spans the redshift range $0.4 < z < 1.8$, corresponding to the interval over which H$α$ is accessible to Euclid slitless spectroscopy. We classify galaxies based on their void-centric distance and local density contrast, and compare their stellar mass, specific star formation rate, bulge-to-total stellar mass ratio, and halo mass across different environments. We further analyse the merger histories of these galaxies to study their assembly evolution. We find that galaxies located closer to void centres ($d_{\rm cc} \lesssim 0.7 R_{\rm v}$) are less massive, more actively star-forming, and more disc-dominated than galaxies in denser regions. Merger histories indicate that void galaxies do not experience fewer mergers, but rather that mergers occur later relative to galaxies in high-density regions. These results support a scenario in which the environment regulates the timing and nature of mergers rather than their overall frequency, producing a slower evolutionary path in low-density regions. We conclude by discussing the extent to which these trends are shaped by environmental parametrisation methods and observational selection effects. Our analysis provides a framework for interpreting forthcoming Euclid data and demonstrates Euclid's potential to identify cosmic voids and probe environmental effects on galaxy evolution.

astro-ph.GA↗

Beyond Stage IV: Quasar and Galaxy Clustering and the Fundamental Physics of the 2040s

Stage IV galaxy surveys (DESI, 4MOST, MOONS, Euclid) are establishing precision constraints on cosmological parameters through baryon acoustic oscillations and redshift-space distortions, yet fundamental questions on neutrino masses, inflationary physics, and the nature of gravity remain beyond their reach. We present a science case for next-generation wide-field spectroscopic surveys targeting $1 < z < 6$ with simultaneous observations of thousands of galaxies, quasars, and emission-line galaxies. Such surveys would deliver transformative advances: (i) cosmological constraints on absolute neutrino masses ($Σm_ν\lesssim 0.015\,\mathrm{eV}$), three times more stringent than Stage IV, enabling resolution of the neutrino mass hierarchy; (ii) detection of primordial non-Gaussianity at the level of $f_{\mathrm{NL}} \sim 1$, probing multi-field inflation; (iii) measurements of structure growth $fσ_8(z)$ spanning cosmic time to constrain dark energy and test gravitational modifications. Achieving these goals requires revolutionary advances in spectroscopic multiplexing ($\mathcal{O}(1000)$ simultaneous spectra), sub-$2\times10^{-4}(1+z)$ redshift precision at scale, and field-level inference techniques exploiting higher-order clustering statistics. We demonstrate that the proposed Wide-field Spectroscopic Telescope concept provides a technically feasible and scientifically compelling path to unlock the physics of neutrinos, inflation, and gravity that will remain inaccessible to Stage IV surveys.

astro-ph.CO↗

pastamarkers 2: pasta sauce colormaps for your flavorful results

In the big data era of Astrophysics, the improvement of visualization techniques can greatly enhance the ability to identify and interpret key features in complex datasets. This aspect of data analysis will become even more relevant in the near future, with the expected growth of data volumes. With our studies, we aim to drive progress in this field and inspire further research. We present the second release of pastamarkers, a Python-based matplotlib package that we initially presented last year. In this new release we focus on big data visualization and update the content of our first release. We find that analyzing complex problems and mining large data sets becomes significantly more intuitive and engaging when using the familiar and appetizing colors of pasta sauces instead of traditional colormaps.

astro-ph.IM↗

The imprint of cosmic voids from the DESI Legacy Survey DR9 LRGs in the Planck 2018 lensing map through spectroscopically calibrated mocks

The cross-correlation of cosmic voids with the lensing convergence ($κ$) map of the Cosmic Microwave Background (CMB) fluctuations provides a powerful tool to refine our understanding of the cosmological model. However, several studies have reported a moderate tension between the lensing imprint of cosmic voids on the observed CMB and the simulated $\mathrmΛ$CDM signal. To address this "lensing-is-low" tension and to obtain new, precise measurements, we exploit the large DESI Legacy Survey Luminous Red Galaxy (LRG) dataset, covering approximately 19,500 $°^2$ of the sky and including about 10 million LRGs at $z < 1.05$. Our $\mathrmΛ$CDM template was created using the Buzzard mocks, which we specifically calibrated to match the clustering properties of the observed galaxy sample by exploiting more than one million DESI spectra. We identified our catalogs of 3D voids in the range $0.35 < z < 0.95$, dividing the sample into bins according to the redshift and $λ_\mathrm{v}$ values of the voids. We report a 14$σ$ detection of the lensing signal, with $A_κ= 1.016 \pm 0.054$, which increases to 17$σ$ when considering the void-in-void ($A_κ= 0.944 \pm 0.064$) and the void-in-cloud ($A_κ= 0.975 \pm 0.060$) populations individually, the highest detection significance for studies of this kind. We observe a full agreement between the observations and $\mathrmΛ$CDM predictions across all redshift bins, sky regions, and void populations considered. In addition to these findings, our analysis highlights the importance of matching sparseness and redshift error distributions between mocks and observations, as well as the role of $λ_\mathrm{v}$ in enhancing the signal-to-noise ratio.

astro-ph.CO↗