Related papers: A comparison between Shapefit compression and Full…

We explore linear and non-linear dimensionality reduction techniques for statistical inference of parameters in cosmology. Given the importance of compressing the increasingly complex data vectors used in cosmology, we address questions…

In order to explain the current acceleration of the Universe, the fine tuning problem of the cosmological constant $\Lambda$ and the cosmic coincidence problem, different alternative models have been proposed in the literature. We use the…

A novel evolutionary method is introduced that can be used for constraining the parameters and theoretical models of Cosmology. The newly proposed algorithm, which is inherently parallel by design, is able to obtain the full potential of…

Using various latest cosmological datasets including Type-Ia supernovae, cosmic microwave background radiation, baryon acoustic oscillations, and estimations of the Hubble parameter, we test some dark energy models with parameterized…

We explore the role of redshift-space galaxy clustering data in constraining non-gravitational interactions between dark energy (DE) and dark matter (DM), for which state-of-the-art limits have so far been obtained from late-time background…

We examine the nature of galaxy clustering in redshift space using a method based on an expansion of the galaxian density field in Spherical Harmonics and linear theory. We derive a compact and self-consistent expression for the distortion…

Cosmological constraints on the total neutrino mass, $\sum m_\nu$, are strongly shaped by assumptions about the dark-energy equation of state due to the well-known degeneracy between massive neutrinos and late-time cosmic acceleration. In…

We review and update constraints on the Early Dark Energy (EDE) model from cosmological data sets, in particular Planck PR3 and PR4 cosmic microwave background (CMB) data and large-scale structure (LSS) data sets including galaxy clustering…

We present a joint $3\times2$-pt cosmological analysis of auto- and cross-correlations between the Dark Energy Spectroscopic Instrument Data Release 1 (DESI-DR1) Bright Galaxy Survey (BGS) and Luminous Red Galaxy (LRG) samples and…

The Multi-coupled Dark Energy (McDE) scenario has been recently proposed as a specific example of a cosmological model characterized by a non-standard physics of the dark sector of the universe that nevertheless gives an expansion history…

We investigate a dynamical reconstruction of the dark energy equation of state parameter by assuming that it satisfies a law of motion described by an autonomous second-order differential equation, with the limit of the cosmological…

In this paper we constrain four alternative models to the late cosmic acceleration in the Universe: Chevallier-Polarski-Linder (CPL), interacting dark energy (IDE), Ricci holographic dark energy (HDE), and modified polytropic Cardassian…

In this paper, we discuss improvements of the Suto et al. (2000) model, in the light of recent theoretical developments (new theoretical mass functions, a more accurate mass-temperature relation and an improved bias model) to predict the…

Spectroscopic redshift errors, including redshift uncertainty and catastrophic failures, can bias cosmological measurements from galaxy redshift surveys at sub-percent level. In this work, we investigate their impact on the full-shape…

In this work, we present a study on cosmological constraints of dark energy (DE) parametrizations after the observations of Dark Energy Spectroscopic Instruments (DESI) for Baryon Acoustic Oscillations (BAO) in 2024, suggesting potential…

We present the largest set of N-body and hydrodynamical simulations to date for cosmological models featuring a direct interaction between the Dark Energy (DE) scalar field, responsible of the observed cosmic acceleration, and the Cold Dark…

Bayesian optimization works effectively optimizing parameters in black-box problems. However, this method did not work for high-dimensional parameters in limited trials. Parameters can be efficiently explored by nonlinearly embedding them…

It is well-known in the field of lossless data compression that probabilistic next-symbol prediction can be used to compress sequences of symbols. Deep neural networks are able to capture rich dependencies in data, offering a powerful means…

Cosmological emulators of observables such as the Cosmic Microwave Background (CMB) spectra and matter power spectra commonly use training data sampled from a Latin hypercube. This method often incurs high computational costs by covering…

The relationship linking a galaxy cluster's total mass with the concentration of its mass profile and its redshift is a fundamental prediction of the Cold Dark Matter (CDM) paradigm of cosmic structure formation. However, confronting those…