Related papers: Extended models of gravity in SNIa cosmological da…
This is a brief sketch of the use of supernovae to measure cosmological parameters. It traces the early work, the events surrounding the discovery and verification of cosmic acceleration using SN Ia, and the efforts today to make sound…
In this work, we construct the logical framework of the Poincar\'e gauge gravity cosmology based on five postulations, and introduce the modified redshift relation within this framework. Then we solve a system with quadratic action and some…
The bimetric generalization of general relativity has been proven to be able to give an accelerated background expansion consistent with observations. Apart from the energy densities coupling to one or both of the metrics, the expansion…
It has been recently shown that the presence of a vector field over cosmological scales could explain the observed accelerated expansion of the universe without introducing neither new scales nor unnatural initial conditions in the early…
Measurements of the growth index $\gamma(z)$ provide a clue as to whether Einstein's field equations encompass gravity also on large cosmic scales, those where the expansion of the universe accelerates. We show that the information encoded…
This paper presents capabilities of using genetic algorithms to find approximations of function extrema, which cannot be found using analytic ways. To enhance effectiveness of calculations, algorithm has been parallelized using OpenMP…
The $(1+(\lambda,\lambda))$ genetic algorithm is one of the few algorithms for which a super-constant speed-up through the use of crossover could be proven. So far, this algorithm has been used with parameters based also on intuitive…
In recent years, machine learning has seen an increasing presencein a large variety of fields, especially in health care and bioinformatics.More specifically, the field where machine learning algorithms have found most applications is…
We combine new Cosmic Microwave Background (CMB) data from Planck with Baryon Acoustic Oscillation (BAO) data to constrain the Brans-Dicke (BD) theory, in which the gravitational constant $G$ evolves with time. Observations of type Ia…
The research community continues to seek increasingly more advanced synthetic data generators to reliably evaluate the strengths and limitations of machine learning methods. This work aims to increase the availability of datasets…
LISA might detect gravitational waves from mergers of massive black hole binaries strongly lensed by intervening galaxies (Sereno et al. 2010). The detection of multiple gravitational lensing events would provide a new tool for cosmography.…
We propose a genetic algorithm (GA) based method for modifying n-best lists produced by a machine translation (MT) system. Our method offers an innovative approach to improving MT quality and identifying weaknesses in evaluation metrics.…
In this study, we investigate the cosmological history within the framework of modified $f(Q)$ gravity, which proposes an alternative theory of gravity where the gravitational force is described by a non-metricity scalar. By employing a…
Machine learning techniques offer a precious tool box for use within astronomy to solve problems involving so-called big data. They provide a means to make accurate predictions about a particular system without prior knowledge of the…
Satellite imagery and remote sensing provide explanatory variables at relatively high resolutions for modeling geospatial phenomena, yet regional summaries are often desirable for analysis and actionable insight. In this paper, we propose a…
In this study, we investigate a Palatini $f(R)$ gravity model featuring a quadratic term correction, aligning it with the most recent expansion rate data, with a particular focus on the latest SNIa and BAO data. Our analysis employs CC data…
General Relativity (GR) describes gravitation well at the energy scales which we have so far been able to achieve or detect. However, we do not know whether GR is behind the physics governing stronger gravitational field regimes, such as…
Peculiar velocities of galaxies hosting Type Ia supernovae generate a significant systematic effect in deriving the dark energy equation of state w, at level of a few percent. Here we illustrate how the peculiar velocity effect in SN Ia…
Since the discovery of the accelerated expansion of the present Universe, significant theoretical developments have been made in the area of modified gravity. In the meantime, cosmological observations have been providing more high-quality…
Graph neural networks (GNNs) are powerful machine learning models for various graph learning tasks. Recently, the limitations of the expressive power of various GNN models have been revealed. For example, GNNs cannot distinguish some…