Graduate School in Physics and Astrophysics ------------------------------------------- ANNUAL REPORT ------------------------------------------- Fill with a text editor (without TAB or formatting) Repeat fields for each course as necessary. ------------------------------------------- name: Michele Pizzardo email: michele.pizzardo@unito.it ciclo: XXXIV year completed (1,2 or 3): 2 supervisor: Prof. Antonaldo Diaferio ------------------------------------------- GRADUATE SCHOOL COURSES (only completed courses, with examination passed in the year) code: 15 title: Search and characterization for extrasolar planets teacher: Alessandro Sozzetti hours: 16 cfu: 4 code: 14 title: Introduction to relativistic theory of cosmological perturbations teacher: Stefano Camera hours: 12 cfu: 3 ------------------------------------------- CONFERENCES, WORKSHOP (only those attended in the current year) title: Cosmology from Home 2020 place: Online conference webpage: https://www.cosmologyfromhome.com/ days: 10 (24/08/2020-04/09/2020) talk (Y/N): Y poster (Y/N): N --------------------------------------------------- Research activity/Publications in the current year (max characters 2500) During the 2nd year of my PhD, I carried on with the investigation on the mass accretion rate (MAR) of galaxy clusters started in the 1st year. I optimized the procedure of validation of the pipeline for the estimation of the MAR from spectroscopic data. The recipe is based on the caustic technique [1,2] and the spherical accretion prescription [3]. From LCDM N-body simulations I extracted about 6000 synthetic halo catalogues per redshift and mass bin. I considered two mass bins (10^14 and 10^15 M_sun/h) and six redshift bins (in the range [0.00; 0.44]). I found that the MARs from my recipe are unbiased and agree within the 17% with the 3D MARs, in the tested bins. Hence I applied the recipe to real clusters of galaxies from CIRS [4] and HeCS [5]. I paid particular attention to possible observative biases to the MAR induced by the selection of the cluster galaxies samples, namely photometric and spectroscopic incompleteness. I tackled the former issue by undersampling the CIRS clusters to match the loss of blue galaxies detected in HeCS, and comparing the results with those from the full CIRS samples. I addressed the latter by generating synthetic stacked clusters mocking the spectroscopic incompleteness of the real data, and comparing them with fully complete mock stacked clusters. I found these effects to be unobservable within the sensitivity of our results. Basing on their R-v profiles, I carefully selected the real clusters of galaxies to be used for the estimation of the MAR in the real Universe. Then I estimated their MAR and found an agreement with the LCDM model. Indeed, the MAR, the mass and the redshift of real clusters are as expected in LCDM simulations. I proved the robustness of these results by comparing them to those obtained via the stacking of the real clusters. I considered different procedures of stacking in order to test different sources of systematics. I found an overall agreement between these different methods and the results from individual clusters. All of this work resulted in a paper, that is currently under peer review [6]. At present, I am investigating the potential of galaxy clusters in detecting signatures of deviations from LCDM. I am focusing on various observables related to the mass accretion of galaxy clusters, using N-body simulations to analyze their ability in showing deviations from LCDM. In particular, the point of minimum of the differential radial mass profile of clusters appears to be dependent on the adopted cosmological model, at given mass and redshift bin. I detected this feature in real data, and currently I am comparing with expectations. I plan to progress in this program and, if time allows, to begin addressing the estimation of the abundance of substructures in clusters of galaxies. This, joined with a theoretical framework, in future could provide another interesting probe of modified gravity. References [1] - Diaferio, A., 1999, MNRAS, 309, 610 [2] - Serra, A. L. et al., 2011, MNRAS, 412, 800 [3] - De Boni, C., et al., 2016, ApJ, 818, 188 [4] - Rines, K., and Diaferio, A., 2006, AJ, 132, 1275 [5] - Rines, K. et al., 2013, ApJ, 767, 15 [6] - Pizzardo, M. et al., arXiv:2005.11562 BE AWARE: visits and stages,research activity and pubs are not evaluated as didactic credits, but are requested to trace the PhD students' career