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Estimating rates of COVID-19 infection and associated mortality is challenging due to uncertainties in case ascertainment. We perform a counterfactual time series analysis on overall mortality data from towns in Italy, comparing the population mortality in 2020 with previous years, to estimate mortality from COVID-19. We find that the number of COVID-19 deaths in Italy in 2020 until September 9 was 59,000–62,000, compared to the official number of 36,000. The proportion of the population that died was 0.29% in the most affected region, Lombardia, and 0.57% in the most affected province, Bergamo. Combining reported test positive rates from Italy with estimates of infection fatality rates from the Diamond Princess cruise ship, we estimate the infection rate as 29% (95% confidence interval 15–52%) in Lombardy, and 72% (95% confidence interval 36–100%) in Bergamo. Estimates of COVID-19-related mortality are limited by incomplete testing. Here, the authors perform counterfactual analyses and estimate that there were 59,000–62,000 deaths from COVID-19 in Italy until 9 th September 2020, approximately 1.5 times higher than official statistics.

Semi-solid processes of aluminium alloys, characterised by the coexistence of solid and liquid phases, offer advantages in terms of mechanical properties and fatigue resistance, thanks to the more globular microstructure. Thermodynamic models can be used to analyse the solidification behaviour and to predict the solidification window, ΔT. The CALPHAD method enables the calculation of the phases formed during solidification and the optimisation of alloy composition to meet specific industrial requirements. This study aims to assess how thermodynamic properties in both liquid and solid phases affect the ΔT. Initially, the influence of thermodynamic properties of pure components and interaction parameters was analysed in simplified regular binary systems. To compare these findings with real industrial systems, Al-based alloys were examined. Using available databases, the ΔT was estimated via the CALPHAD method adding alloying elements commonly found in secondary Al-alloys. Finally, the same minority alloying elements were added to Al-Si 8 and 11 wt.% alloys, and the corresponding ΔT were calculated. Cr, Fe, Mg, Mn, and Ti increase the ΔT, while Cu, Ni, and Zn decrease it. The obtained results may serve as a valuable tool for interpreting phenomenological observations and understanding the role of minority elements in the semi-solid processing of secondary Al-Si casting alloys.

Galaxy redshift surveys, such as the 2-Degree-Field Survey (2dF) 1 , Sloan Digital Sky Survey (SDSS) 2 , 6-Degree-Field Survey (6dF) 3 , Galaxy And Mass Assembly survey (GAMA) 4 and VIMOS Public Extragalactic Redshift Survey (VIPERS) 5 , have shown that the spatial distribution of matter forms a rich web, known as the cosmic web 6 . Most galaxy survey analyses measure the amplitude of galaxy clustering as a function of scale, ignoring information beyond a small number of summary statistics. Because the matter density field becomes highly non-Gaussian as structure evolves under gravity, we expect other statistical descriptions of the field to provide us with additional information. One way to study the non-Gaussianity is to study filaments, which evolve non-linearly from the initial density fluctuations produced in the primordial Universe. In our study, we report the detection of lensing of the cosmic microwave background (CMB) by filaments, and we apply a null test to confirm our detection. Furthermore, we propose a phenomenological model to interpret the detected signal, and we measure how filaments trace the matter distribution on large scales through filament bias, which we measure to be around 1.5. Our study provides new scope to understand the environmental dependence of galaxy formation. In the future, the joint analysis of lensing and Sunyaev–Zel’dovich observations might reveal the properties of ‘missing baryons’, the vast majority of the gas that resides in the intergalactic medium, which has so far evaded most observations. Cosmic filaments evolve nonlinearly from density fluctuations produced in the primordial Universe. Detection of cosmic microwave background lensing by filaments allows the measurement of how filaments trace the matter distribution on large scales.

The unifying theme of this dissertation is using cosmological observations as a tool to discover new physics and astrophysics. The first part focuses on the effects of primordial non-Gaussianity on the large-scale distribution of dark matter halos. The statistical properties of the primordial fluctuation contain a wealth of information about the Universe's early moments, and these properties are imprinted on the late-time distribution of matter. The first chapter serves as an introduction to the effects of non-Gaussianity on halo bias, summarizing previous work and extending it to the cubic local model (the gNL model). Chapter 2 generalizes some of the techniques of Chapter 1, allowing for the calculation of halo bias with arbitrary initial conditions, while Chapter 3 shows the relationship between the seemingly different techniques existing in the literature. Detailed forecasts for upcoming surveys are presented in Chapter 4, including the effect of marginalization over shot-noise and Gaussian part of the bias, photometric redshifts uncertainties and multi-tracer analysis to reduce the effect of cosmic variance. The second part contains work on two secondary anisotropies of the Cosmic Microwave Background radiation (CMB), namely the Integrated Sachs-Wolfe (ISW) effect and the kinetic Sunyaev-Zel'dovich (kSZ) effect. The late-time ISW effect arises because of decay of the large-scale gravitational potential due to the accelerated expansion and is therefore a powerful probe of dark energy. Chapter 5 presents a new detection of the ISW effect, using WISE galaxies and AGN as tracers of the gravitational potential, whose bias is measured in cross-correlation with CMB lensing maps. An appendix discusses the contamination of this measurement due to the linear part of the kSZ effect, the Doppler shift of photon energy due to scattering off coherently moving electrons. The last chapter explores the prospects of detecting the kSZ signal from sources for which accurate redshift information is not available (such as the WISE catalog). Forecasts are presented, as well as comparison with simulations and a discussion of the main sources of contamination.

CMB photons redshift and blueshift as they move through gravitational potentials \\(\\Phi\\) while propagating across the Universe. If the potential is not constant in time, the photons will pick up a net redshift or blueshift, known as the Integrated Sachs-Wolfe (ISW) effect. In the \\(z \\ll 1000\\) universe, \\(\\dot{\\Phi}\\) is nonzero on large scales when the Universe transitions from matter to dark energy domination. This effect is only detectable in cross-correlation with large-scale structure at \\(z \\sim 1\\). In this paper we present a 3.2\\(\\sigma\\) detection of the ISW effect using cross-correlations between unWISE infrared galaxies and Planck CMB temperature maps. We use 3 tomographic galaxy samples spanning \\(0 < z < 2\\), allowing us to fully probe the dark energy domination era and the transition into matter domination. This measurement is consistent with \\(\\Lambda\\)CDM (\\(A_{\\rm ISW} = 0.96 \\pm 0.30\\)). We study constraints on a particular class of dynamical dark energy models (where the dark energy equation of state is different in matter and dark energy domination), finding that unWISE-ISW improves constraints from type Ia supernovae due to improved constraints on the time evolution of dark energy. When combining with BAO measurements, we obtain the tightest constraints on specific dynamical dark energy models. In the context of a phenomenological model for freezing quintessence, the Mocker model, we constrain the dark energy density within 10% at \\(z < 2\\) using ISW, BAO and supernovae. Moreover, the ISW measurement itself provides an important independent check when relaxing assumptions about the theory of gravity, as it is sensitive to the gravitational potential rather than the expansion history.

Upcoming surveys will measure the cosmic microwave background (CMB) weak lensing power spectrum in exquisite detail, allowing for strong constraints on the sum of neutrino masses among other cosmological parameters. Standard CMB lensing power spectrum estimators aim to extract the connected non-Gaussian trispectrum of CMB temperature maps. However, they are generically dominated by a large Gaussian noise bias, which thus needs to be subtracted at high accuracy. This is currently done with realistic map simulations of the CMB and noise, whose finite accuracy currently limits our ability to recover CMB lensing on small-scales. In this paper, we propose a novel estimator which instead avoids this large Gaussian bias. This estimator relies only on the data and avoids the need for bias subtraction with simulations. Thus our bias avoidance method is (1) insensitive to misestimates in simulated CMB and noise models and (2) avoids the large computational cost of standard simulation-based methods like \"realization-dependent \\(N^{(0)}\\)\" (\\({\\rm RDN}^{(0)}\\)). We show that our estimator is as robust as standard methods in the presence of realistic inhomogeneous noise (e.g. from scan strategy) and masking. Moreover, our method can be combined with split-based methods, making it completely insensitive to mode coupling from inhomogeneous atmospheric and detector noise. We derive the corresponding expressions for our estimator when estimating lensing from CMB temperature and polarization. Although we specifically consider CMB weak lensing power spectrum estimation in this paper, we illuminate the relation between our new estimator, \\({\\rm RDN}^{(0)}\\) subtraction, and general optimal trispectrum estimation. Through this discussion we conclude that our estimator is applicable to analogous problems in other fields which rely on estimating connected trispectra/four-point functions like large-scale structure.

CMB photons redshift and blueshift as they move through gravitational potentials \\(\\Phi\\) while propagating across the Universe. If the potential is not constant in time, the photons will pick up a net redshift or blueshift, known as the Integrated Sachs-Wolfe (ISW) effect. In the \\(z \\ll 1000\\) universe, \\(\\dot{\\Phi}\\) is nonzero on large scales when the Universe transitions from matter to dark energy domination. This effect is only detectable in cross-correlation with large-scale structure at \\(z \\sim 1\\). In this paper we present a 3.2\\(\\sigma\\) detection of the ISW effect using cross-correlations between unWISE infrared galaxies and Planck CMB temperature maps. We use 3 tomographic galaxy samples spanning \\(0 < z < 2\\), allowing us to fully probe the dark energy domination era and the transition into matter domination. This measurement is consistent with \\(\\Lambda\\)CDM (\\(A_{\\rm ISW} = 0.96 \\pm 0.30\\)). We study constraints on a particular class of dynamical dark energy models (where the dark energy equation of state is different in matter and dark energy domination), finding that unWISE-ISW improves constraints from type Ia supernovae due to improved constraints on the time evolution of dark energy. When combining with BAO measurements, we obtain the tightest constraints on specific dynamical dark energy models. In the context of a phenomenological model for freezing quintessence, the Mocker model, we constrain the dark energy density within 10% at \\(z < 2\\) using ISW, BAO and supernovae. Moreover, the ISW measurement itself provides an important independent check when relaxing assumptions about the theory of gravity, as it is sensitive to the gravitational potential rather than the expansion history.

Local-type primordial non-Gaussianity (PNG), predicted by many non-minimal models of inflation, creates a scale-dependent contribution to the power spectrum of large-scale structure (LSS) tracers. Its amplitude is characterized by the product \\(b_\\phi f_{\\rm NL}^{\\rm loc}\\), where \\(b_\\phi\\) is an astrophysical parameter dependent on the properties of the tracer. However, \\(b_\\phi\\) exhibits significant secondary dependence on halo concentration and other astrophysical properties, which may bias and weaken the constraints on \\(f_{\\rm NL}^{\\rm loc}\\). In this work, we demonstrate that incorporating knowledge of the relation between Lagrangian bias parameters and \\(b_\\phi\\) can significantly enhance PNG constraints. We employ the Hybrid Effective Field Theory (HEFT) approach at the field-level and a linear regression model to seek a connection between the bias parameters and \\(b_{\\phi}\\) for halo and galaxy samples, constructed using the \\textsc{AbacusSummit} simulation suite and mimicking the luminous red galaxies (LRGs) and quasi-stellar objects (QSOs) of the Dark Energy Spectroscopic Instrument (DESI) survey. For the fixed-mass halo samples, our full bias model reduces the uncertainty by more than 70\\%, with most of that improvement coming from \\(b_\\nabla\\), which we find to be an excellent proxy for concentration. For the galaxy samples, our model reduces the uncertainty on \\(b_\\phi\\) by 80\\% for all tracers. By adopting Lagrangian-bias informed priors on the parameter \\(b_\\phi\\), future analyses can thus constrain \\(f_{\\rm NL}^{\\rm loc}\\) with less bias and smaller errors.

Reconstructing the initial conditions of the Universe from late-time observations has the potential to optimally extract cosmological information. Due to the high dimensionality of the parameter space, a differentiable forward model is needed for convergence, and recent advances have made it possible to perform reconstruction with nonlinear models based on galaxy (or halo) positions. In addition to positions, future surveys will provide measurements of galaxies' peculiar velocities through the kinematic Sunyaev-Zel'dovich effect (kSZ), type Ia supernovae, and the fundamental plane or Tully-Fisher relations. Here we develop the formalism for including halo velocities, in addition to halo positions, to enhance the reconstruction of the initial conditions. We show that using velocity information can significantly improve the reconstruction accuracy compared to using only the halo density field. We study this improvement as a function of shot noise, velocity measurement noise, and angle to the line of sight. We also show how halo velocity data can be used to improve the reconstruction of the final nonlinear matter overdensity and velocity fields. We have built our pipeline into the differentiable Particle-Mesh FlowPM package, paving the way to perform field-level cosmological inference with joint velocity and density reconstruction. This is especially useful given the increased ability to measure peculiar velocities in the near future.

Over the past decade, the kinematic Sunyaev-Zel'dovich (kSZ) effect has emerged as an observational probe of the distribution of baryons and velocity fields in the late Universe. Of the many ways to detect the kSZ, the 'projected-fields kSZ estimator' has the promising feature of not being limited to galaxy samples with accurate redshifts. The current theoretical modeling of this estimator involves an approximate treatment only applicable at small scales. As the measurement fidelity rapidly improves, we find it necessary to move beyond the original treatment and hence derive an improved theoretical model for this estimator without these previous approximations. We show that the differences between the predicted signal from the two models are scale-dependent and will be significant for future measurements from the Simons Observatory and CMB-S4 in combination with galaxy data from WISE or the Rubin Observatory, which have high forecasted signal-to-noise ratios (\\(>100\\)). Thus, adopting our improved model in future analyses will be important to avoid biases. Equipped with our model, we explore the cosmological dependence of this kSZ signal for future measurements. With a Planck prior, residual uncertainty on \\(\\Lambda\\)CDM parameters leads to \\(\\sim7\\%\\) marginalized uncertainties on the signal amplitude, compared to a sub-percent level forecasted with a fixed cosmology. To illustrate the potential of this kSZ estimator as a cosmological probe, we forecast initial constraints on \\(\\Lambda\\)CDM parameters and the sum of neutrino masses, paving the way for jointly fitting both baryonic astrophysics and cosmology in future analyses.