The Fractal Geometry of the Cosmic Web and its Formation

The cosmic web structure is studied with the concepts and methods of fractal geometry, employing the adhesion model of cosmological dynamics as a basic reference. The structures of matter clusters and cosmic voids in cosmological N-body simulations or the Sloan Digital Sky Survey are elucidated by means of multifractal geometry. A non-lacunar multifractal geometry can encompass three fundamental descriptions of the cosmic structure, namely, the web structure, hierarchical clustering, and halo distributions. Furthermore, it explains our present knowledge of cosmic voids. In this way, a unified theory of the large-scale structure of the universe seems to emerge. The multifractal spectrum that we obtain significantly differs from the one of the adhesion model and conforms better to the laws of gravity. The formation of the cosmic web is best modeled as a type of turbulent dynamics, generalizing the known methods of Burgers turbulence.Comment: 35 pages, 8 figures; corrected typos, added references; further discussion of cosmic voids; accepted by Advances in Astronom

Constraining f(R)f(R) gravity by the Large Scale Structure

Over the past decades, General Relativity and the concordance $\Lambda$CDM model have been successfully tested using several different astrophysical and cosmological probes based on large datasets ({\it precision cosmology}). Despite their successes, some shortcomings emerge due to the fact that General Relativity should be revised at infrared and ultraviolet limits and to the fact that the fundamental nature of Dark Matter and Dark Energy is still a puzzle to be solved. In this perspective, $f(R)$ gravity have been extensively investigated being the most straightforward way to modify General Relativity and to overcame some of the above shortcomings. In this paper, we review various aspects of $f(R)$ gravity at extragalactic and cosmological levels. In particular, we consider cluster of galaxies, cosmological perturbations, and N-Body simulations, focusing on those models that satisfy both cosmological and local gravity constraints. The perspective is that some classes of $f(R)$ models can be consistently constrained by Large Scale Structure.Comment: 37 pages, 3 Tables, 6 Figures. Invited Review belonging "Special Issue Modified Gravity Cosmology: From Inflation to Dark Energy". The manuscript matches the accepted version. References update

Dark Energy vs. Modified Gravity

Understanding the reason for the observed accelerated expansion of the Universe represents one of the fundamental open questions in physics. In cosmology, a classification has emerged among physical models for the acceleration, distinguishing between Dark Energy and Modified Gravity. In this review, we give a brief overview of models in both categories as well as their phenomenology and characteristic observable signatures in cosmology. We also introduce a rigorous distinction between Dark Energy and Modified Gravity based on the strong and weak equivalence principles.Comment: 29 pages, 4 figures; invited review submitted to Annual Reviews of Nuclear and Particle Science; v2: some pertinent references added; v3: table with constraints added, reflects published version; v4 [trivial]: fixed missing references in arxiv versio

Modeling and Optimal Design of Machining-Induced Residual Stresses in Aluminium Alloys Using a Fast Hierarchical Multiobjective Optimization Algorithm

The residual stresses induced during shaping and machining play an important role in determining the integrity and durability of metal components. An important issue of producing safety critical components is to find the machining parameters that create compressive surface stresses or minimise tensile surface stresses. In this paper, a systematic data-driven fuzzy modelling methodology is proposed, which allows constructing transparent fuzzy models considering both accuracy and interpretability attributes of fuzzy systems. The new method employs a hierarchical optimisation structure to improve the modelling efficiency, where two learning mechanisms cooperate together: NSGA-II is used to improve the model’s structure while the gradient descent method is used to optimise the numerical parameters. This hybrid approach is then successfully applied to the problem that concerns the prediction of machining induced residual stresses in aerospace aluminium alloys. Based on the developed reliable prediction models, NSGA-II is further applied to the multi-objective optimal design of aluminium alloys in a ‘reverse-engineering’ fashion. It is revealed that the optimal machining regimes to minimise the residual stress and the machining cost simultaneously can be successfully located

Primordial non-Gaussianity in the Bispectrum of the Halo Density Field

The bispectrum vanishes for linear Gaussian fields and is thus a sensitive probe of non-linearities and non-Gaussianities in the cosmic density field. Hence, a detection of the bispectrum in the halo density field would enable tight constraints on non-Gaussian processes in the early Universe and allow inference of the dynamics driving inflation. We present a tree level derivation of the halo bispectrum arising from non-linear clustering, non-linear biasing and primordial non-Gaussianity. A diagrammatic description is developed to provide an intuitive understanding of the contributing terms and their dependence on scale, shape and the non-Gaussianity parameter fNL. We compute the terms based on a multivariate bias expansion and the peak-background split method and show that non-Gaussian modifications to the bias parameters lead to amplifications of the tree level bispectrum that were ignored in previous studies. Our results are in a good agreement with published simulation measurements of the halo bispectrum. Finally, we estimate the expected signal to noise on fNL and show that the constraint obtainable from the bispectrum analysis significantly exceeds the one obtainable from the power spectrum analysis.Comment: 34 pages, 15 figures, (v3): matches JCAP published versio