Search Results for author: Savvas Nesseris

Found 6 papers, 2 papers with code

Novel null tests for the spatial curvature and homogeneity of the Universe and their machine learning reconstructions

no code implementations11 Mar 2021 Rubén Arjona, Savvas Nesseris

Second, we present a new test of possible deviations from homogeneity using the combination of two datasets, either the baryon acoustic oscillation (BAO) and $H(z)$ data or the transversal and radial BAO data, while we also introduce two consistency tests for $\Lambda$CDM which could be reconstructed via the transversal and radial BAO data.

Cosmology and Nongalactic Astrophysics General Relativity and Quantum Cosmology High Energy Physics - Phenomenology

Machine Learning and cosmographic reconstructions of quintessence and the Swampland conjectures

no code implementations22 Dec 2020 Rubén Arjona, Savvas Nesseris

Using the Hubble parameter $H(z)$ data from the cosmic chronometers we find that the ML and cosmography reconstructions of the SC are compatible with observations at low redshifts.

Cosmology and Nongalactic Astrophysics General Relativity and Quantum Cosmology High Energy Physics - Phenomenology

Machine learning forecasts of the cosmic distance duality relation with strongly lensed gravitational wave events

no code implementations5 Nov 2020 Rubén Arjona, Hai-Nan Lin, Savvas Nesseris, Li Tang

We use simulated strongly lensed gravitational wave events from the Einstein Telescope to demonstrate how the luminosity and angular diameter distances, $d_L(z)$ and $d_A(z)$ respectively, can be combined to test in a model independent manner for deviations from the cosmic distance duality relation and the standard cosmological model.

Cosmology and Nongalactic Astrophysics General Relativity and Quantum Cosmology High Energy Physics - Phenomenology

Evaporating primordial black holes as varying dark energy

no code implementations Physics of the Dark Universe 2019 Savvas Nesseris, Domenico Sapone, Spyros Sypsas

If light enough primordial black holes (PBH) account for dark matter, then its density decreases with time as they lose mass via Hawking radiation.

What can Machine Learning tell us about the background expansion of the Universe?

2 code implementations3 Oct 2019 Rubén Arjona, Savvas Nesseris

We also confirm a recently reported mild tension between the SnIa/quasar data and the cosmological constant $\Lambda$CDM model at high redshifts $(z\gtrsim1. 5)$ and finally, we show that the GA can be used in complementary null tests of the $\Lambda$CDM via reconstructions of the Hubble parameter and the luminosity distance.

Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics General Relativity and Quantum Cosmology

Is the Jeffreys' scale a reliable tool for Bayesian model comparison in cosmology?

1 code implementation29 Oct 2012 Savvas Nesseris, Juan Garcia-Bellido

In this paper we explicitly calculate the Bayes factors for all models that are linear with respect to their parameters.

Cosmology and Nongalactic Astrophysics High Energy Physics - Experiment Data Analysis, Statistics and Probability

Cannot find the paper you are looking for? You can Submit a new open access paper.