Solar UV variability is extremely relevant for the stratospheric ozone. It has an impact on Earth's atmospheric structure and dynamics through radiative heating and ozone photochemistry. Our goal is to study the slope of the solar UV spectrum in two UV bands important to the stratospheric ozone production. In order to investigate the solar spectral variability, we use data from SOLSTICE (the Solar Stellar Irradiance Comparison Experiment) on board the Solar Radiation and Climate Experiment (SORCE) satellite. Datasets used are far UV (115-180 nm) and middle UV (180-310 nm), as well as the Mg II index (the Bremen composite). We introduce the SOLSTICE [FUV-MUV] colour to study the solar spectral characteristics, as well as to analyse the colour versus Mg II index. To isolate the 11-year scale variation, we used Empirical Mode Decomposition (EMD) on the datasets. The [FUV-MUV] colour strongly correlates with the Mg II index. The [FUV-MUV] colour shows a time-dependent behaviour when plotted versus the Mg II index. To explain this dependence we hypothesize an efficiency reduction of SOLSTICE FUV irradiance using an exponential ageing law.
The quest for understanding the late-time acceleration is haunted by an immense freedom in the analysis of dynamical models for dark energy in extended parameter spaces. Often-times having no prior knowledge at our disposal, arbitrary choices are implemented to reduce the degeneracies between parameters. We also encounter this issue in the case of quintessence fields, where a scalar degree of freedom drives the late-time acceleration. In this study, we implement a more physical prescription, the flow condition, to fine-tune the quintessence evolution for several field potentials. We find that this prescription agrees well with the most recent catalogue of data, namely supernovae type Ia, baryon acoustic oscillations, cosmic clocks and distance to last scattering surface, and it enables us to infer the initial conditions for the field, both potential and cosmological parameters. At 2σ we find stricter bounds on the potential parameters f /m pl > 0.26 and n < 0.15 for the PNGB and IPL potentials, respectively, while constraints on cosmological parameters remain extremely consistent across all assumed potentials. By implementing information criteria to assess their ability to fit the data, we do not find any evidence against thawing models, which in fact are statistically equivalent to ΛCDM, and the freezing ones are moderately disfavoured. Through our analysis we place upper bounds on the slope of quintessence potentials, consequently revealing a strong tension with the recently proposed swampland criterion, finding the 2σ upper bound of λ ∼ 0.31 for the exponential potential. * federico.tosone@roma2.infn.it †
Lagrangian algorithms to simulate the evolution of cold dark matter (CDM) are invaluable tools to generate large suites of mock halo catalogues. In this paper, we first show that the main limitation of current semi-analytical schemes to simulate the displacement of CDM is their inability to model the evolution of overdensities in the initial density field, a limit that can be circumvented by detecting halo particles in the initial conditions. We thus propose ‘MUltiscale Spherical Collapse Lagrangian Evolution Using Press-Schechter’ (muscle-ups), a new scheme that reproduces the results from Lagrangian perturbation theory on large scales, while improving the modelling of overdensities on small scales. In muscle-ups, we adapt the extended Press and Schechter (EPS) formalism to Lagrangian algorithms of the displacement field. For regions exceeding a collapse threshold in the density smoothed at a radius R, we consider all particles within a radius R collapsed. Exploiting a multi-scale smoothing of the initial density, we build a halo catalogue on the fly by optimizing the selection of halo candidates. This allows us to generate a density field with a halo mass function that matches one measured in N-body simulations. We further explicitly gather particles in each halo together in a profile, providing a numerical, Lagrangian-based implementation of the halo model. Compared to previous semi-analytical Lagrangian methods, we find that muscle-ups improves the recovery of the statistics of the density field at the level of the probability density function (PDF), the power spectrum, and the cross correlation with the N-body result.
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