arXiv subjects

S. Nesseris

Publications and source records attributed to S. Nesseris.

At least 19 recordsLinked to original sources

arXiv2025

Euclid: Forecasts on $\Lambda$CDM consistency tests with growth rate data

The large-scale structure (LSS) of the Universe is an important probe for deviations from the canonical cosmological constant $\Lambda$ and cold dark matter ($\Lambda$CDM) model. A statistically significant detection of any deviations would signify the presence of new physics or the breakdown of any number of the underlying assumptions of the standard cosmological model or possible systematic errors in the data. In this paper, we quantify the ability of the LSS data products of the spectroscopic survey of the Euclid mission, together with other contemporary surveys, to improve the constraints on deviations from $\Lambda$CDM in the redshift range $0<z<1.75$. We consider both currently available growth rate data and simulated data with specifications from Euclid and external surveys, based on $\Lambda$CDM and a modified gravity (MoG) model with an evolving Newton's constant (denoted $\mu$CDM), and carry out a binning method and a machine learning reconstruction, based on genetic algorithms (GAs), of several LSS null tests. Using the forecast Euclid growth data from the spectroscopic survey in the range $0.95<z<1.75$, we find that in combination with external data products (covering the range $0<z<0.95$), Euclid will be able to improve on current constraints of null tests of the LSS on average by a factor of eight when using a binning method and a factor of six when using the GAs. Our work highlights the need for synergies between Euclid and other surveys, but also the usefulness of statistical analyses, such as GAs, in order to disentangle any degeneracies in the cosmological parameters. Both are necessary to provide tight constraints over an extended redshift range and to probe for deviations from the $\Lambda$CDM model.

astro-ph.CO↗

arXiv2025

Updated constraints on modified gravity from binary pulsars

Binary pulsars offer a unique natural laboratory to test General Relativity (GR) and probe for deviations from its paradigm, as predicted by alternative theories of gravity. In this paper, we study two such possible deviations: a time variation of Newton's constant $G$ and the emission of dipolar gravitational radiation. We use updated data for some well-known pulsars, namely PSR J1738+0333, PSR J1012+5307, and PSR J1713+0747, to extract the Keplerian and post-Keplerian parameters that characterize their orbital dynamics, using recent high-precision pulsar timing data and a Bayesian parameter estimation with Markov chain Monte Carlo (MCMC) techniques. We do this via the TEMPO2 software, the MCMC4Tempo2 plugin, and a unified python pipeline to analyze the data. We then perform a combined analysis of different binary systems to constrain both the time evolution of Newton's constant and the dipolar emission parameter $\kappa_D$. For the best of our three pulsars (PSR J1713+0747), we obtain $\dot{G}/G = (0.32 \pm 0.31) \times 10^{-12}~\text{yr}^{-1}$ at 95\% confidence, along with a stringent constraint on the dipolar emission parameter, $\kappa_D = (-0.04 \pm 0.14) \times 10^{-4}$. Thanks to the recent high-precision timing data sets, we provide updated bounds on key parameters relevant to modified gravity theories, and we find that our results are consistent with GR.

gr-qc↗

arXiv2025

Euclid preparation: Expected constraints on initial conditions

The Euclid mission of the European Space Agency will deliver galaxy and cosmic shear surveys, which will be used to constrain initial conditions and statistics of primordial fluctuations. We present highlights for the Euclid scientific capability to test initial conditions beyond LCDM with the main probes, i.e. 3D galaxy clustering from the spectroscopic survey, the tomographic approach to 3x2pt statistics from photometric galaxy survey, and their combination. We provide Fisher forecasts from the combination of Euclid spectroscopic and photometric surveys for spatial curvature, running of the spectral index of the power spectrum of curvature perturbations, isocurvature perturbations, and primordial features. For the parameters of these models we also provide the combination of Euclid forecasts (pessimistic and optimistic) with current and future measurements of the cosmic microwave background (CMB) anisotropies., i.e. Planck, the Simons Observatory (SO), and CMB-S4. We provide Fisher forecasts for how the power spectrum and bispectrum from the Euclid spectroscopic survey will constrain the local, equilateral, and orthogonal shapes of primordial non-Gaussianity. We also review how Bayesian field-level inference of primordial non-Gaussianity can constrain local primordial non-Gaussianity. We show how Euclid, with its unique combination of the main probes, will provide the tightest constraints on low redshift to date. By targeting a markedly different range in redshift and scale, Euclid's expected uncertainties are complementary to those obtained by CMB primary anisotropy, returning the tightest combined constraints on the physics of the early Universe.

astro-ph.CO↗

arXiv2024

Distinguishing Coupled Dark Energy Models with Neural Networks

We investigate whether neural networks (NNs) can accurately differentiate between growth-rate data of the large-scale structure (LSS) of the Universe simulated via two models: a cosmological constant and $\Lambda$ cold dark matter (CDM) model and a tomographic coupled dark energy (CDE) model. We built an NN classifier and tested its accuracy in distinguishing between cosmological models. For our dataset, we generated $f\sigma_8(z)$ growth-rate observables that simulate a realistic Stage IV galaxy survey-like setup for both $\Lambda$CDM and a tomographic CDE model for various values of the model parameters. We then optimised and trained our NN with \texttt{Optuna}, aiming to avoid overfitting and to maximise the accuracy of the trained model. We conducted our analysis for both a binary classification, comparing between $\Lambda$CDM and a CDE model where only one tomographic coupling bin is activated, and a multi-class classification scenario where all the models are combined. For the case of binary classification, we find that our NN can confidently (with $>86\%$ accuracy) detect non-zero values of the tomographic coupling regardless of the redshift range at which coupling is activated and, at a $100\%$ confidence level, detect the $\Lambda$CDM model. For the multi-class classification task, we find that the NN performs adequately well at distinguishing $\Lambda$CDM, a CDE model with low-redshift coupling, and a model with high-redshift coupling, with 99\%, 79\%, and 84\% accuracy, respectively. By leveraging the power of machine learning, our pipeline can be a useful tool for analysing growth-rate data and maximising the potential of current surveys to probe for deviations from general relativity.

astro-ph.CO↗

arXiv2024

Neural Networks for cosmological model selection and feature importance using Cosmic Microwave Background data

The measurements of the temperature and polarisation anisotropies of the Cosmic Microwave Background (CMB) by the ESA Planck mission have strongly supported the current concordance model of cosmology. However, the latest cosmological data release from ESA Planck mission still has a powerful potential to test new data science algorithms and inference techniques. In this paper, we use advanced Machine Learning (ML) algorithms, such as Neural Networks (NNs), to discern among different underlying cosmological models at the angular power spectra level, using both temperature and polarisation Planck 18 data. We test two different models beyond $\Lambda$CDM: a modified gravity model: the Hu-Sawicki model, and an alternative inflationary model: a feature-template in the primordial power spectrum. Furthermore, we also implemented an interpretability method based on SHAP values to evaluate the learning process and identify the most relevant elements that drive our architecture to certain outcomes. We find that our NN is able to distinguish between different angular power spectra successfully for both alternative models and $\Lambda$CDM. We conclude by explaining how archival scientific data has still a strong potential to test novel data science algorithms that are interesting for the next generation of cosmological experiments.

astro-ph.CO↗

arXiv2022

Euclid: Testing the Copernican principle with next-generation surveys

The Copernican principle, the notion that we are not at a special location in the Universe, is one of the cornerstones of modern cosmology and its violation would invalidate the Friedmann-Lema\^ıtre-Robertson-Walker (FLRW) metric, causing a major change in our understanding of the Universe. Thus, it is of fundamental importance to perform observational tests of this principle. We determine the precision with which future surveys will be able to test the Copernican principle and their ability to detect any possible violations. We forecast constraints on the inhomogeneous Lema\^ıtre-Tolman-Bondi model with a cosmological constant $Λ$ ($Λ$LTB), basically a cosmological constant $Λ$ and cold dark matter ($Λ$CDM) model, but endowed with a spherical inhomogeneity. We consider combinations of currently available data and simulated Euclid data, together with external data products, based on both $Λ$CDM and $Λ$LTB fiducial models. These constraints are compared to the expectations from the Copernican principle. When considering the $Λ$CDM fiducial model, we find that Euclid data, in combination with other current and forthcoming surveys, will improve the constraints on the Copernican principle by about $30\%$, with $\pm10\%$ variations depending on the observables and scales considered. On the other hand, when considering a $Λ$LTB fiducial model, we find that future Euclid data, combined with other current and forthcoming data sets, will be able to detect Gpc-scale inhomogeneities of contrast $-0.1$. Next-generation surveys, such as Euclid, will thoroughly test homogeneity at large scales, tightening the constraints on possible violations of the Copernican principle.

astro-ph.CO↗

arXiv2022

Euclid: Forecast constraints on consistency tests of the $Λ$CDM model

The standard cosmological model is based on the fundamental assumptions of a spatially homogeneous and isotropic universe on large scales. An observational detection of a violation of these assumptions at any redshift would immediately indicate the presence of new physics. We quantify the ability of the Euclid mission, together with contemporary surveys, to improve the current sensitivity of null tests of the canonical cosmological constant $Λ$ and the cold dark matter (LCDM) model in the redshift range $0<z<1.8$. We considered both currently available data and simulated Euclid and external data products based on a LCDM fiducial model, an evolving dark energy model assuming the Chevallier-Polarski-Linder (CPL) parameterization or an inhomogeneous Lema\^ıtre-Tolman-Bondi model with a cosmological constant $Λ$ (LLTB), and carried out two separate but complementary analyses: a machine learning reconstruction of the null tests based on genetic algorithms, and a theory-agnostic parametric approach based on Taylor expansion and binning of the data, in order to avoid assumptions about any particular model. We find that in combination with external probes, Euclid can improve current constraints on null tests of the LCDM by approximately a factor of three when using the machine learning approach and by a further factor of two in the case of the parametric approach. However, we also find that in certain cases, the parametric approach may be biased against or missing some features of models far from LCDM. Our analysis highlights the importance of synergies between Euclid and other surveys. These synergies are crucial for providing tighter constraints over an extended redshift range for a plethora of different consistency tests of some of the main assumptions of the current cosmological paradigm.

astro-ph.CO↗

arXiv2021

Euclid: constraining dark energy coupled to electromagnetism using astrophysical and laboratory data

In physically realistic scalar-field based dynamical dark energy models (including, e.g., quintessence) one naturally expects the scalar field to couple to the rest of the model's degrees of freedom. In particular, a coupling to the electromagnetic sector leads to a time (redshift) dependence of the fine-structure constant and a violation of the Weak Equivalence Principle. Here we extend the previous Euclid forecast constraints on dark energy models to this enlarged (but physically more realistic) parameter space, and forecast how well Euclid, together with high-resolution spectroscopic data and local experiments, can constrain these models. Our analysis combines simulated Euclid data products with astrophysical measurements of the fine-structure constant, $α$, and local experimental constraints, and includes both parametric and non-parametric methods. For the astrophysical measurements of $α$ we consider both the currently available data and a simulated dataset representative of Extremely Large Telescope measurements and expected to be available in the 2030s. Our parametric analysis shows that in the latter case the inclusion of astrophysical and local data improves the Euclid dark energy figure of merit by between $8\%$ and $26\%$, depending on the correct fiducial model, with the improvements being larger in the null case where the fiducial coupling to the electromagnetic sector is vanishing. These improvements would be smaller with the current astrophysical data. Moreover, we illustrate how a genetic algorithms based reconstruction provides a null test for the presence of the coupling. Our results highlight the importance of complementing surveys like Euclid with external data products, in order to accurately test the wider parameter spaces of physically motivated paradigms.

astro-ph.CO↗

arXiv2021

Hints for possible low redshift oscillation around the best fit $Λ$CDM model in the expansion history of the Universe

We search for possible deviations from the expectations of the concordance $Λ$CDM model in the expansion history of the Universe by analysing the Pantheon Type Ia Supernovae (SnIa) compilation along with its Monte Carlo simulations using redshift binning. We demonstrate that the redshift binned best fit $Λ$CDM matter density parameter $Ω_{0m}$ and the best fit effective absolute magnitude $\cal M$ oscillate about their full dataset best fit values with considerably large amplitudes. Using the full covariance matrix of the data taking into account systematic and statistical errors, we show that at the redshifts below $z\approx0.5$ such oscillations can only occur in 4 to 5$\%$ of the Monte Carlo simulations. While statistical fluctuations can be responsible for this apparent oscillation, we might have observed a hint for some behaviour beyond the expectations of the concordance model or a possible additional systematic in the data. If this apparent oscillation is not due to statistical or systematic effects, it could be due to either the presence of coherent inhomogeneities at low $z$ or due to oscillations of a quintessence scalar field.

astro-ph.CO↗

arXiv2021

Euclid: Forecast constraints on the cosmic distance duality relation with complementary external probes

In metric theories of gravity with photon number conservation, the luminosity and angular diameter distances are related via the Etherington relation, also known as the distance-duality relation (DDR). A violation of this relation would rule out the standard cosmological paradigm and point at the presence of new physics. We quantify the ability of Euclid, in combination with contemporary surveys, to improve the current constraints on deviations from the DDR in the redshift range $0<z<1.6$. We start by an analysis of the latest available data, improving previously reported constraints by a factor of 2.5. We then present a detailed analysis of simulated Euclid and external data products, using both standard parametric methods (relying on phenomenological descriptions of possible DDR violations) and a machine learning reconstruction using Genetic Algorithms. We find that for parametric methods Euclid can (in combination with external probes) improve current constraints by approximately a factor of six, while for non-parametric methods Euclid can improve current constraints by a factor of three. Our results highlight the importance of surveys like Euclid in accurately testing the pillars of the current cosmological paradigm and constraining physics beyond the standard cosmological model.

astro-ph.CO↗

arXiv2019

Electromagnetic probes of primordial black holes as dark matter

The LIGO discoveries have rekindled suggestions that primordial black holes (BHs) may constitute part to all of the dark matter (DM) in the Universe. Such suggestions came from 1) the observed merger rate of the BHs, 2) their unusual masses, 3) their low/zero spins, and 4) also from the independently uncovered cosmic infrared background (CIB) fluctuations signal of high amplitude and coherence with unresolved cosmic X-ray background (CXB). Here we summarize the prospects to resolve this important issue with electromagnetic observations using the instruments and tools expected in the 2020's. These prospects appear promising to make significant, and potentially critical, advances. We demonstrate that in the next decade, new space- and ground-borne electromagnetic instruments, combined with concurrent theoretical efforts, should shed critical light on the long-considered link between primordial BHs and DM. Specifically the new data and methodologies under this program will involve: I) Probing with high precision the spatial spectrum of source-subtracted CIB with Euclid and WFIRST, and its coherence with unresolved cosmic X-ray background using eROSITA and Athena, II) Advanced searches for microlensing of Galactic stars by the intervening Galactic Halo BHs with OGLE, Gaia, LSST and WFIRST, III) Supernovae (SNe) lensing in the upcoming surveys with WFIRST, LSST and also potentially with Euclid and JWST, IV) Advanced theoretical work to understand the details of PBH accretion and evolution and their influence on cosmic microwave background (CMB) anisotropies in light of the next generation CMB experiments, V) Better new samples and theoretical understanding involving stability and properties of ultra faint dwarf galaxies, pulsar timing, and cosmological quasar lensing.

astro-ph.CO↗

arXiv2018

Updated constraints on $f(T)$ models using direct and indirect measurements of the Hubble parameter

We extract observational constraints on $f(T)$ gravity, using the recently proposed statistical method which is not affected by the value of $H_0$ and thus it bypasses the problem of the disagreement in its exact numerical value between Planck and direct measurements. We use direct measurements of the Hubble parameter with the corresponding covariance matrix, and for completeness we perform a joint analysis using the latest data from Supernovae type Ia based on JLA sample, quasi-stellar objects, and Cosmic Microwave Background shift parameter from Planck. We analyze a large family of $f(T)$ models, and we compare the fitting results with $Λ$CDM cosmology using the AIC statistical test. Utilizing only the Hubble parameter data we find that in the case of the power-law $f(T)$ model a small but non-zero deviation from $Λ$CDM cosmology is slightly favored at 1-$σ$, nevertheless the corresponding AIC value shows a statistical equivalence with it. Finally, the join analysis reveals that all $f(T)$ models are very efficient and in very good agreement with observations.

astro-ph.CO↗

arXiv2016

A Comparison of Thawing and Freezing Dark Energy Parametrizations

Dark energy equation of state $w(z)$ parametrizations with two parameters and given monotonicity are generically either convex or concave functions. This makes them suitable for fitting either freezing or thawing quintessence models but not both simultaneously. Fitting a dataset based on a freezing model with an unsuitable (concave when increasing) $w(z)$ parametrization (like CPL) can lead to significant misleading features like crossing of the phantom divide line, incorrect $w(z=0)$, incorrect slope \etc that are not present in the underlying cosmological model. To demonstrate this fact we generate scattered cosmological data both at the level of $w(z)$ and the luminosity distance $D_L(z)$ based on either thawing or freezing quintessence models and fit them using parametrizations of convex and of concave type. We then compare statistically significant features of the best fit $w(z)$ with actual features of the underlying model. We thus verify that the use of unsuitable parametrizations can lead to misleading conclusions. In order to avoid these problems it is important to either use both convex and concave parametrizations and select the one with the best $χ^2$ or use principal component analysis thus splitting the redshift range into independent bins. In the latter case however, significant information about the slope of $w(z)$ at high redshifts is lost. Finally, we propose a new family of parametrizations (nCPL) $w(z)=w_0+w_a (\frac{z}{1+z})^n$ which generalizes the CPL and interpolates between thawing and freezing parametrizations as the parameter $n$ increases to values larger than 1.

astro-ph.CO↗

arXiv2013

Viable f(T) models are practically indistinguishable from LCDM

We investigate the cosmological predictions of several $f(T)$ models, with up to two parameters, at both the background and the perturbation levels. Using current cosmological observations (geometric supernovae type Ia, cosmic microwave background and baryonic acoustic oscillation and dynamical growth data) we impose constraints on the distortion parameter, which quantifies the deviation of these models from the concordance $Λ$ cosmology at the background level. In addition we constrain the growth index $γ$ predicted in the context of these models using the latest perturbation growth data in the context of three parametrizations for $γ$. The evolution of the best fit effective Newton constant, which incorporates the $f(T)$-gravity effects, is also obtained along with the corresponding $1σ$ error regions. We show that all the viable parameter sectors of the $f(T)$ gravity models considered practically reduce these models to $Λ$CDM. Thus, the degrees of freedom that open up to $Λ$CDM in the context of $f(T)$ gravity models are not utilized by the cosmological data leading to an overall disfavor of these models.

astro-ph.CO↗

arXiv2009

Comparison of Recent SnIa datasets

We rank the six latest Type Ia supernova (SnIa) datasets (Constitution (C), Union (U), ESSENCE (Davis) (E), Gold06 (G), SNLS 1yr (S) and SDSS-II (D)) in the context of the Chevalier-Polarski-Linder (CPL) parametrization $w(a)=w_0+w_1 (1-a)$, according to their Figure of Merit (FoM), their consistency with the cosmological constant ($Λ$CDM), their consistency with standard rulers (Cosmic Microwave Background (CMB) and Baryon Acoustic Oscillations (BAO)) and their mutual consistency. We find a significant improvement of the FoM (defined as the inverse area of the 95.4% parameter contour) with the number of SnIa of these datasets ((C) highest FoM, (U), (G), (D), (E), (S) lowest FoM). Standard rulers (CMB+BAO) have a better FoM by about a factor of 3, compared to the highest FoM SnIa dataset (C). We also find that the ranking sequence based on consistency with $Λ$CDM is identical with the corresponding ranking based on consistency with standard rulers ((S) most consistent, (D), (C), (E), (U), (G) least consistent). The ranking sequence of the datasets however changes when we consider the consistency with an expansion history corresponding to evolving dark energy $(w_0,w_1)=(-1.4,2)$ crossing the phantom divide line $w=-1$ (it is practically reversed to (G), (U), (E), (S), (D), (C)). The SALT2 and MLCS2k2 fitters are also compared and some peculiar features of the SDSS-II dataset when standardized with the MLCS2k2 fitter are pointed out. Finally, we construct a statistic to estimate the internal consistency of a collection of SnIa datasets. We find that even though there is good consistency among most samples taken from the above datasets, this consistency decreases significantly when the Gold06 (G) dataset is included in the sample.

astro-ph.CO↗

arXiv2008

Is the CMB shift parameter connected with the growth of cosmological perturbations?

We verify numerically that in the context of general relativity (GR), flat models which have the same $Ω_{\rm m}$ and CMB shift parameter $R$ but different $H(a)$ and $w(a)$ also have very similar (within less than 8%) growth of perturbations even though the dark energy density evolution is quite different. This provides a direct connection between geometrical and dynamical tests of dark energy and may be used as a cosmological test of general relativity.

astro-ph↗

arXiv2007

Comparison of Standard Ruler and Standard Candle constraints on Dark Energy Models

We compare the dark energy model constraints obtained by using recent standard ruler data (Baryon Acoustic Oscillations (BAO) at z=0.2 and z=0.35 and Cosmic Microwave Background (CMB) shift parameters R and l_a) with the corresponding constraints obtained by using recent Type Ia Supernovae (SnIa) standard candle data (ESSENCE+SNLS+HST from Davis et. al.). We find that, even though both classes of data are consistent with LCDM at the 2σlevel, there is a systematic difference between the two classes of data. In particular, we find that for practically all values of the parameters (Ω_0m,Ω_b) in the 2σrange of the the 3-year WMAP data (WMAP3) best fit, LCDM is significantly more consistent with the SnIa data than with the CMB+BAO data. For example for (Ω_0m,Ω_b)=(0.24,0.042) corresponding to the best fit values of WMAP3, the dark energy equation of state parametrization w(z)=w_0 + w_1 (z/(1+z)) best fit is at a 0.5σdistance from LCDM (w_0=-1,w_1=0) using the SnIa data and 1.7σaway from LCDM using the CMB+BAO data. There is a similar trend in the earlier data (SNLS vs CMB+BAO at z=0.35). This trend is such that the standard ruler CMB+BAO data show a mild preference for crossing of the phantom divide line w=-1, while the recent SnIa data favor LCDM. Despite of this mild difference in trends, we find no statistically significant evidence for violation of the cosmic distance duality relation η\equiv d_L(z)/(d_A(z) (1+z)^2)=1. For example, using a prior of Ω_0m=0.24, we find η=0.95 \pm 0.025 in the redshift range 0<z<2, which is consistent with distance duality at the 2σlevel.

astro-ph↗

arXiv2007

Testing LCDM with the Growth Function δ(a): Current Constraints

We have compiled a dataset consisting of 22 datapoints at a redshift range (0.15,3.8) which can be used to constrain the linear perturbation growth rate f=\frac{d\lnδ}{d\ln a}. Five of these data-points constrain directly the growth rate f through either redshift distortions or change of the power spectrum with redshift. The rest of the datapoints constrain f indirectly through the rms mass fluctuation σ_8(z) inferred from Ly-αat various redshifts. Our analysis tests the consistency of the LCDM model and leads to a constraint of the Wang-Steinhardt growth index γ(defined from f=Ω_m^γ) as γ=0.67^{+0.20}_{-0.17}. This result is clearly consistent at $1σ$ with the value γ={6/11}=0.55 predicted by LCDM. A first order expansion of the index γin redshift space leads to similar results.We also apply our analysis on a new null test of LCDM which is similar to the one recently proposed by Chiba and Nakamura (arXiv:0708.3877) but does not involve derivatives of the expansion rate $H(z)$. This also leads to the fact that LCDM provides an excellent fit to the current linear growth data.

astro-ph↗