相关论文: A new perspective on Dark Energy modeling via Gene…

There are many kinds of models which describe the dynamics of dark energy (DE). Among all we adopt an equation of state (EoS) which varies as a function of time. We adopt Markov Chain Monte Carlo method to constrain the five parameters of…

We study the degeneracies between dark energy dynamics, dark matter and curvature using a non-parametric and non-perturbative approach. This allows us to examine the knock-on bias induced in the reconstructed dark energy equation of state,…

An important issue in cosmology is reconstructing the effective dark energy equation of state directly from observations. With so few physically motivated models, future dark energy studies cannot only be based on constraining a dark energy…

We study the evidence for dark energy (DE) evolution at low redshift, using baryonic acoustic oscillations (BAOs) from the DESI Early Data Release, Pantheon+ Type Ia supernovae (SNe-Ia), and redshift space distortions (RSDs) to constrain…

We implement Crossing Statistics to reconstruct in a model-agnostic manner the expansion history of the universe and properties of dark energy, using DESI Data Release 1 (DR1) BAO data in combination with one of three different supernova…

We reconstruct the expansion history of the Universe using type Ia supernovae (SN Ia) in a manner independent of any cosmological model assumptions. To do so, we implement a non-parametric iterative smoothing method on the Joint Light-curve…

Observational growth rate data had been derived from observations of redshift distortions in galaxy redshift surveys. Here we use the growth rate data to place constraints on the dark energy model parameters. By performing a joint analysis…

We combine cosmic chronometer and growth of structure data to derive the redshift evolution of the dark energy equation of state $w$, using a novel agnostic approach. The background and perturbation equations lead to two expressions for…

We make a comparative analysis of the various independent methods proposed in the literature for studying the nature of dark energy, using four different mocks of SnIa data. In particular, we explore a generic principal components analysis…

The cause of the accelerated expansion of the Universe poses one of the most fundamental questions in physics today. In the absence of a compelling theory to explain the observations, a first task is to develop a robust phenomenology. If…

Genetic Algorithms (GA) are a powerful tool for stochastic optimisation and non-parametric symbolic regression, already widely used in cosmology. They are capable of reconstructing analytical functions directly from data points without…

In this paper, we use the joint measurement of geometry and growth rate from matter density perturbations to constrain the holographic dark energy model. The geometry measurement includes type Ia supernovae (SN Ia) Union2.1, full…

For a large class of dark energy (DE) models, for which the effective gravitational constant is a constant and there is no direct exchange of energy between DE and dark matter (DM), knowledge of the expansion history suffices to reconstruct…

We use a particular machine learning approach, called the genetic algorithms (GA), in order to place constraints on deviations from general relativity (GR) via a possible evolution of Newton's constant $\mu\equiv…

Not much by themselves, aparently. We try to reconstruct the scale factor $a(t)$ of the universe from the SNe Ia data, i.e. the luminosity distance $d_{L}(z)$, using only the cosmological principle and the assumption that gravitation is…

We adopt a model independent method to reconstruct the dark energy equation of state by analyzing 5 sets of SNe Ia data along with Baryon Acoustic Oscillation (BAO) and Observational Hubble Data (OHD). The SNe Ia data sets include the most…

The equation of state (EoS) of dark energy plays an important role in the evolution of the universe and arouses great interests in recent years. With the progress on observational technique, precise constraint on the EoS of dark energy…

Cosmological analyses with Type Ia Supernovae (SNe Ia) have traditionally been reliant on spectroscopy for both classifying the type of supernova and obtaining reliable redshifts to measure the distance-redshift relation. While obtaining a…

Using redshift space distortion data, we perform model-independent reconstructions of the growth history of matter inhomogeneity in the expanding Universe using two methods: crossing statistics and Gaussian processes. We then reconstruct…

The behavior of the dark energy equation of state (EOS) is crucial in distinguishing different cosmological models. With a model independent approach, we constrain the possible evolution of the dark energy EOS. Gamma-ray bursts (GRBs) of…