Explore the vast range of titles available.

In a self-similar paradigm of structure formation, the thermal pressure of the hot intra-cluster gas follows a universal distribution once the profile of each cluster is normalised based on the proper mass and redshift dependencies. The reconstruction of such a universal pressure profile requires an individual estimate of the mass of each cluster. In this context, we present a method to jointly fit, for the first time, the universal pressure profile and individual cluster \\(M_{500}\\) masses over a sample of galaxy clusters, properly accounting for correlations between the profile shape and amplitude, and masses scaling the individual profiles. We demonstrate the power of the method and show that a consistent exploitation of the universal pressure profile and cluster mass estimates when modelling the thermal pressure in clusters is necessary to avoid biases. In particular, the method, informed by a cluster mass scale, outputs individual cluster masses with same accuracy and better precision than input masses. Using data from the {\\guillemotleft}Cluster HEritage project with XMM-Newton: Mass Assembly and Thermodynamics at the Endpoint of structure formation{\\guillemotright}, we investigate a sample of \\(\\sim 25\\) galaxy clusters spanning mass and redshift ranges of \\(2 \\lesssim M_{500}/10^{14} \\; \\mathrm{M}_{\\odot} \\lesssim 14\\) and \\(0.07 < z < 0.6\\).

Within the self-similar framework of structure formation, the thermal pressure of the hot intra-cluster medium follows a universal distribution that is independent of the cluster mass scale. Once normalised to the proper mass and redshift dependencies, this pressure distribution becomes common to all clusters. Reconstructing such a universal pressure profile requires individual estimates of each cluster’s mass. In this work, we present a methodology to simultaneously fit the universal pressure profile alongside the masses of individual clusters in a sample, while properly accounting for correlations between the profile’s shape, its amplitude, and cluster masses. We apply this method to a sub-sample of clusters from the CHEX-MATE project and demonstrate the strong impact that the assumed pressure profile has on the measured signal. This effect propagates into the thermal Sunyaev-Zel’dovich (tSZ) power spectrum and, in turn, influences the determination of cosmological parameters.

The nature of the elusive dark matter can be probed by comparing the predictions of the cold dark matter framework with the gravitational field of massive galaxy clusters. However, a robust test of dark matter can only be achieved if the systematic uncertainties in the reconstruction of the gravitational potential are minimized. Techniques based on the properties of intracluster gas rely on the assumption that the gas is in hydrostatic equilibrium within the potential well, whereas gravitational lensing is sensitive to projection effects. Here we attempt to minimize systematics in galaxy cluster mass reconstructions by jointly exploiting the weak gravitational lensing signal and the properties of the hot intracluster gas determined from X-ray and millimeter (Sunyaev-Zel'dovich) observations. We construct a model to fit the multi-probe information within a common framework, accounting for non-thermal pressure support and elongation of the dark matter halo along the line of sight. We then apply our framework to the massive cluster Abell 1689, which features unparalleled multi-wavelength data. In accordance with previous works, we find that the cluster is significantly elongated along the line of sight. Accounting for line-of-sight projections, we require a non-thermal pressure support of \\(30-40\\%\\) at \\(r_500\\) to match the gas and weak lensing observables. The joint model retrieves a concentration \\(c_2007\\), which is lower and more realistic than the high concentration retrieved from weak lensing data alone under the assumption of spherical symmetry (\\(c_20015\\)). Application of our method to a larger sample will allow us to study at the same time the shape of dark matter mass profiles and the level of non-thermal pressure support in galaxy clusters.

Foreground components in the Cosmic Microwave Background (CMB) are sparse in a needlet representation, due to their specific morphological features (anisotropy, non-Gaussianity). This leads to the possibility of applying needlet thresholding procedures as a component separation tool. In this work, we develop algorithms based on different needlet-thresholding schemes and use them as extensions of existing, well-known component separation techniques, namely ILC and template-fitting. We test soft- and hard-thresholding schemes, using different procedures to set the optimal threshold level. We find that thresholding can be useful as a denoising tool for internal templates in experiments with few frequency channels, in conditions of low signal-to-noise. We also compare our method with other denoising techniques, showing that thresholding achieves the best performance in terms of reconstruction accuracy and data compression while preserving the map resolution. The best results in our tests are in particular obtained when considering template-fitting in an LSPE like experiment, especially for B-mode spectra.

Thermodynamic profiles from X-ray and millimetre observations of galaxy clusters are often compared under the simplifying assumptions of smooth, spherically symmetric intracluster medium. These approximations lead to expected discrepancies in the inferred profiles, which can provide insights about the cluster structure or cosmology. Motivated by this, we present a joint XMM-\\textit{Newton} and \\textit{Planck} analysis of 116 CHEX-MATE clusters to measure \\(\\eta_T = T_X/T_{SZ,X}\\), the ratio between spectroscopic X-ray temperatures and a temperature proxy derived from Sunyaev-Zel'dovich (SZ) pressures and X-ray densities. We considered relativistic corrections to the thermal SZ signal and implemented X-ray absorption by Galactic molecular hydrogen. The \\(\\eta_T\\) distribution has a mean of \\(1.01 \\pm 0.03\\), with average changes of \\(8.1\\%\\) and \\(2.7\\%\\) when relativistic corrections and molecular hydrogen absorption are not included, respectively. The \\(\\eta_T\\) distribution is positively skewed, with the scatter mostly affected by cluster morphology: relaxed clusters are closer to unity and less scattered than mixed and disturbed systems. We find little or no correlation with redshift, mass, or temperature.

Galaxy cluster abundance measurements are a valuable tool for constraining cosmological parameters like the mass density (\\(\\Omega_m\\)) and density fluctuation amplitude (\\(\\sigma_8\\)). Wide area surveys detect clusters based on observables, such as the total integrated Sunyaev-Zel'dovich effect signal (\\(Y_{SZ}\\)) in the case of Planck. Quantifying the survey selection function is necessary for a cosmological analysis, with completeness representing the probability of detecting a cluster as a function of its intrinsic properties. Employing a Monte-Carlo method, we inject triaxial cluster profiles into random positions within the Planck all-sky maps, and subsequently determine the completeness of the Planck-selected CHEXMATE sample as a function of both geometry and SZ brightness. This is then used to generate 1000 mock CHEX-MATE cluster catalogs, and the distribution of shapes and orientations of the detected clusters, along with any associated bias in weak lensing-derived mass (\\(M_{WL}\\)) due to this orientation-dependent selection, denoted as \\(1 - b_{\\chi}\\), is obtained. We show that cluster orientation impacts completeness, with a higher probability of detecting clusters elongated along the line of sight (LOS). This leads to \\(1 - b_{\\chi}\\) values of \\(0-4\\%\\) for CHEXMATE clusters relative to a random population. The largest increase in \\(M_{WL}\\) is observed in the lowest mass objects, which are most impacted by orientation-related selection bias. This bias is relevant for upcoming SZ surveys like CMB-S4, and should be considered for surveys utilizing other probes for cluster detection, such as Euclid.

We analyse the Planck full-mission cosmic microwave background (CMB) temperature and E-mode polarization maps to obtain constraints on primordial non-Gaussianity (NG). We compare estimates obtained from separable template-fitting, binned, and modal bispectrum estimators, finding consistent values for the local, equilateral, and orthogonal bispectrum amplitudes. Our combined temperature and polarization analysis produces the following results: f_NL^local = -0.9 +\\- 5.1; f_NL^equil = -26 +\\- 47; and f_NL^ortho = - 38 +\\- 24 (68%CL, statistical). These results include the low-multipole (4 <= l < 40) polarization data, not included in our previous analysis, pass an extensive battery of tests, and are stable with respect to our 2015 measurements. Polarization bispectra display a significant improvement in robustness; they can now be used independently to set NG constraints. We consider a large number of additional cases, e.g. scale-dependent feature and resonance bispectra, isocurvature primordial NG, and parity-breaking models, where we also place tight constraints but do not detect any signal. The non-primordial lensing bispectrum is detected with an improved significance compared to 2015, excluding the null hypothesis at 3.5 sigma. We present model-independent reconstructions and analyses of the CMB bispectrum. Our final constraint on the local trispectrum shape is g_NLl^local = (-5.8 +\\-6.5) x 10^4 (68%CL, statistical), while constraints for other trispectra are also determined. We constrain the parameter space of different early-Universe scenarios, including general single-field models of inflation, multi-field and axion field parity-breaking models. Our results provide a high-precision test for structure-formation scenarios, in complete agreement with the basic picture of the LambdaCDM cosmology regarding the statistics of the initial conditions (abridged).

The Greater Caucasus mountain belt is characterized by deep valleys, steep slopes and frequent seismic activity, the combination of which results in major landslide hazard. Along the eastern side of the Enguri water reservoir lies the active Khoko landslide, whose head scarp zone affects the important Jvari–Khaishi–Mestia road, one of the few connections with the interior of the Greater Caucasus. Here, we present a database of measurement time series taken over a period of 4 years (2016–2019) that enables us to compare slope deformation with meteorological factors and human-induced perturbations owing to variations in the water level of the reservoir. The monitoring system we used is composed of two digital extensometers, placed within two artificial trenches excavated across the landslide head scarp. The stations are also equipped with internal and near-ground surface thermometers. The dataset is integrated by daily measurements of rainfall and lake level. The monitoring system – the first installed in Georgia – was set up in the framework of a NATO-funded project, aimed at assessing different types of geohazards affecting the Enguri artificial reservoir and the related hydroelectrical plant. Our results indicate that the Khoko landslide displacements appear to be mainly controlled by variations in hydraulic load, in turn induced by lake level oscillations. Rainfall variations might also have contributed, though this is not always evident for all the studied period. The full databases are freely available online at the following DOI: https://doi.org/10.20366/unimib/unidata/SI384-2.0 (Tibaldi et al., 2020).

Our work is intended to present the new macroseismic intensity database for the Republic of Georgia—hereby named GeoInt—which includes earthquakes from the historical (from 1250 B.C. onwards) to the instrumental era. Such database is composed of 111 selected earthquakes and related 3944 intensity data points (IDPs) for 1509 different localities, reported in the Medvedev-Sponheuer-Karnik scale (MSK). Regarding the earthquakes, the MS is in the 3.3–7 range and the depth is in the 2–36 km range. The entire set of IDPs is characterized by intensities ranging from 2–3 to 9–10 and covers an area spanning from 39.508° N to 45.043° N in a N-S direction and from 37.324° E to 48.500° E in an E-W direction, with some of the IDPs located outside the Georgian border, in the (i) Republic of Armenia, (ii) Russian Federation, (iii) Republic of Turkey, and (iv) Republic of Azerbaijan. We have revised each single IDP and have reevaluated and homogenized intensity values to the MSK scale. In particular, regarding the whole set of 3944 IDPs, 348 belong to the Historical era (pre-1900) and 3596 belong to the instrumental era (post-1900). With particular regard to the 3596 IDPs, 105 are brand new (3%), whereas the intensity values for 804 IDPs have been reevaluated (22%); for 2687 IDPs (75%), intensities have been confirmed from previous interpretations. We introduce this database as a key input for further improvements in seismic hazard modeling and seismic risk calculation for this region, based on macroseismic intensity; we report all the 111 earthquakes with available macroseismic information. The GeoInt database is also accessible online at http://www.enguriproject.unimib.it and will be kept updated in the future.

Objective: To assess whether tissue Doppler myocardial imaging (TDI) indices can predict postoperative left ventricular function in patients with mitral regurgitation (MR) after surgical correction. Methods: 84 patients (mean (SD) age 54.3 (10.8) years) with asymptomatic severe MR, an end systolic diameter < 45 mm, and an ejection fraction (EF) > 60% were subdivided in two groups: 43 patients with a postoperative EF reduction < 10% (group 1) and 41 patients with a postoperative EF reduction ⩾ 10% (group 2).TDI systolic indices of the lateral annulus were analysed preoperatively to assess myocardial systolic wave (Sm) velocity, myocardial precontraction time (PCTm), myocardial contraction time (CTm), and the PCTm:CTm ratio. Results: Postoperative EF decreased significantly (from 67 (5)% to 60 (5.5)%, p  =  0.0001). Group 2 had a higher PCTm, CTm, and PCTm:CTm ratio and a lower Sm velocity than group 1 (PCTm 100.4 (19) ms v 82 (21.8) ms, p  =  0.004; CTm 222 (3.1) ms v 215 (2.3) ms, p  =  0.01; PCTm:CTm 0.45 (0.08) v 0.38 (0.09), p  =  0.001; Sm velocity 10.4 (1.1) cm/s v 13 (1.3) cm/s, p  =  0.0001). Multivariate regression analysis showed that the combination of PCTm:CTm ratio ⩾ 40 ms and Sm velocity ⩽ 10.5 cm/s was the main independent predictor of postoperative EF reduction ⩾ 10% (sensitivity 78%, specificity 95%). Conclusions: TDI systolic indices can predict postoperative left ventricular function in patients with asymptomatic MR undergoing surgical correction.