arXiv subjects

Claudia G. Scóccola

Publications and source records attributed to Claudia G. Scóccola.

At least 19 recordsLinked to original sources

arXiv2026

Bias in the tensor-to-scalar ratio from self-interacting dark radiation

We investigate the cosmological imprint of self-interacting dark radiation (DR) on the primordial $B$-mode angular power spectrum and its impact on the estimation of the tensor-to-scalar ratio $r$. We consider a minimal model in which DR is described as an effectively massless axion-like particle with quartic self-interactions. These interactions are incorporated into the Einstein-Boltzmann equations using the relaxation time approximation and implemented in the $\texttt{CLASS}$ code. We show that increasing the strength of DR self-interactions suppresses anisotropic stress, thereby reducing the damping of gravitational waves and leading to an enhancement of the primordial $B$-mode signal relative to the free-streaming case. Using mock CMB data and Markov Chain Monte Carlo analyses, we show that neglecting DR self-interactions may bias the inferred value of $r$ by an amount comparable to the uncertainty expected in forthcoming CMB polarization experiments, such as the ground-based $\textit{Simons Observatory}$ and the satellite missions $\textit{LiteBIRD}$ and PICO. Our results emphasize the importance of properly modeling DR interactions in future precision searches for primordial $B$-modes in order to obtain unbiased constraints on inflationary gravitational waves.

astro-ph.CO↗

arXiv2025

Generalized tension metrics for multiple cosmological datasets

We introduce a novel estimator to quantify statistical tensions among multiple cosmological datasets simultaneously. This estimator generalizes the Difference-in-Means statistic, $Q_{\rm DM}$, to the multi-dataset regime. Our framework enables the detection of dominant tension directions in the shared parameter space. It further provides a geometric interpretation of the tension for the two- and three-dataset cases in two dimensions. According to this approach, the previously reported increase in tension between DESI and Planck from $1.9σ$ (DR1) to $2.3σ$(DR2) is reinterpreted as a more modest shift from $1.18σ^{\rm eff}$ (DR1) to $1.45σ^{\rm eff}$ (DR2). These new tools may also prove valuable across research fields where dataset discrepancies arise.

astro-ph.CO↗

arXiv2025

Evolution of linear matter perturbations with error-bounded bundle physics-informed neural networks

We consider the evolution of linear matter perturbations in the context of the standard cosmological model ($Λ$CDM) and a phenomenological modified gravity model. We use the physics-informed neural network (PINN) bundle method, which allows to integrate differential systems as an alternative to the traditional numerical method. We apply the PINN bundle method to the equation that describes the matter perturbation evolution, to compare its outcomes with recent data on structure growth, $fσ_8$. Unlike our previous works, we can calculate a bound on the error of this observable without using the numerical solution of the equation. For this, we use a method developed previously by ourselves to calculate an exact bound on the PINN-based solution using only the outcomes of the network and its residual. On the other hand, the use of an updated data set allows us to obtain more stringent constraints on the plane $Ω_m-σ_8$ than previous works.

astro-ph.CO↗

arXiv2025

DeepWiener: Neural Networks for CMB polarization maps and power spectrum computation

To study the early Universe, it is essential to estimate cosmological parameters with high accuracy, which depends on the optimal reconstruction of Cosmic Microwave Background (CMB) maps and the measurement of their power spectrum. In this paper, we generalize the neural network developed for applying the Wiener Filter, initially presented for temperature maps in previous work, to polarization maps. Our neural network has a UNet architecture, including an extra channel for the noise variance map, to account for inhomogeneous noise, and a channel for the mask. In addition, we propose an iterative approach for reconstructing the E and B-mode fields, while addressing the E-to-B leakage present in the maps due to incomplete sky coverage. The accuracy achieved is satisfactory compared to the Wiener Filter solution computed with the standard Conjugate Gradient method, and it is highly efficient, enabling the computation of the power spectrum of an unknown signal using the optimal quadratic estimator. We further evaluate the quality of the reconstructed maps at the power spectrum level along with their corresponding errors, finding that these errors are smaller than those obtained using the well-known pseudo-$C_\ell$ approach. Our results show that increasing complexity in the applied mask presents a more significant challenge for B-mode reconstruction.

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arXiv2024

Exact and approximate error bounds for physics-informed neural networks

The use of neural networks to solve differential equations, as an alternative to traditional numerical solvers, has increased recently. However, error bounds for the obtained solutions have only been developed for certain equations. In this work, we report important progress in calculating error bounds of physics-informed neural networks (PINNs) solutions of nonlinear first-order ODEs. We give a general expression that describes the error of the solution that the PINN-based method provides for a nonlinear first-order ODE. In addition, we propose a technique to calculate an approximate bound for the general case and an exact bound for a particular case. The error bounds are computed using only the residual information and the equation structure. We apply the proposed methods to particular cases and show that they can successfully provide error bounds without relying on the numerical solution.

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arXiv2024

Tensions in cosmology: a discussion of statistical tools to determine inconsistencies

We present a comprehensive analysis of statistical tools for evaluating tensions in cosmological parameter estimates arising from distinct datasets. Focusing on the unresolved Hubble constant ($H_0$) tension, we explore the Pantheon Plus + SH0ES (PPS) compilation, which includes low-redshift Cepheid data from the SH0ES collaboration, along with the latest release of CMB data from the Planck collaboration, Cosmic Chronometers (CC) dataset and the most recent Baryonic Acoustic Oscillation (BAO) datasets. Employing various tension metrics, we quantitatively assess the inconsistencies in parameter estimates, emphasizing the importance of capturing multidimensional tensions. Our results reveal substantial tension between PPS and Planck 2018 datasets and moderate tension between the BAO data sets and all other datasets. We highlight the importance of adopting these metrics to enhance the precision of future cosmological analyses and facilitate the resolution of existing tensions.

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arXiv2024

Faster Bayesian inference with neural network bundles and new results for $f(R)$ models

In the last few years, there has been significant progress in the development of machine learning methods tailored to astrophysics and cosmology. We have recently applied one of these, namely, the neural network bundle method, to the cosmological scenario. Moreover, we showed that in some cases the computational times of the Bayesian inference process can be reduced. In this paper, we present an improvement to the neural network bundle method that results in a significant reduction of the computational times of the statistical analysis. The novel aspect consists of the use of the neural network bundle method to calculate the luminosity distance of type Ia supernovae, which is usually computed through an integral with numerical methods. In this work, we have applied this improvement to the Hu-Sawicki and Starobinsky $f(R)$ models. We also performed a statistical analysis with data from type Ia supernovae of the Pantheon+ compilation and cosmic chronometers. Another original aspect of this work is the different treatment we provide for the absolute magnitude of type Ia supernovae during the inference process, which results in different estimates of the distortion parameter than the ones obtained in the literature. We show that the statistical analyses carried out with our new method require lower computational times than the ones performed with both the numerical and the neural network method from our previous work. This reduction in time is more significant in the case of a difficult computational problem such as the ones addressed in this work.

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arXiv2024

Enhancing CMB map reconstruction and power spectrum estimation with convolutional neural networks

The accurate reconstruction of Cosmic Microwave Background (CMB) maps and the measurement of its power spectrum are crucial for studying the early universe. In this paper, we implement a convolutional neural network to apply the Wiener Filter to CMB temperature maps, and use it intensively to compute an optimal quadratic estimation of the power spectrum. Our neural network has a UNet architecture as that implemented in WienerNet, but with novel aspects such as being written in python 3 and TensorFlow 2. It also includes an extra channel for the noise variance map, to account for inhomogeneous noise, and a channel for the mask. The network is very efficient, overcoming the bottleneck that is typically found in standard methods to compute the Wiener Filter, such as those that apply the conjugate gradient. It scales efficiently with the size of the map, making it a useful tool to include in CMB data analysis. The accuracy of the Wiener Filter reconstruction is satisfactory, as compared with the standard method. We heavily use this approach to efficiently estimate the power spectrum, by performing a simulation-based analysis of the optimal quadratic estimator. We further evaluate the quality of the reconstructed maps in terms of the power spectrum and find that we can properly recover the statistical properties of the signal. We find that the proposed architecture can account for inhomogeneous noise efficiently. Furthermore, increasing the complexity of the variance map presents a more significant challenge for the convergence of the network than the noise level does.

astro-ph.CO↗

arXiv2023

Cosmology-informed neural networks to solve the background dynamics of the Universe

The field of machine learning has drawn increasing interest from various other fields due to the success of its methods at solving a plethora of different problems. An application of these has been to train artificial neural networks to solve differential equations without the need of a numerical solver. This particular application offers an alternative to conventional numerical methods, with advantages such as lower memory required to store solutions, parallelization, and, in some cases, a lower overall computational cost than its numerical counterparts. In this work, we train artificial neural networks to represent a bundle of solutions of the differential equations that govern the background dynamics of the Universe for four different models. The models we have chosen are $Λ\mathrm{CDM}$, the Chevallier-Polarski-Linder parametric dark energy model, a quintessence model with an exponential potential, and the Hu-Sawicki $f(R)$ model. We use the solutions that the networks provide to perform statistical analyses to estimate the values of each model's parameters with observational data; namely, estimates of the Hubble parameter from cosmic chronometers, type Ia supernovae data from the Pantheon compilation, and measurements from baryon acoustic oscillations. The results we obtain for all models match similar estimations done in the literature using numerical solvers. In addition, we estimate the error of the solutions that the trained networks provide by comparing them with the analytical solution when there is one, or to a high-precision numerical solution when there is not. Through these estimations we find that the error of the solutions is at most $\sim1\%$ in the region of the parameter space that concerns the $95\%$ confidence regions that we find using the data, for all models and all statistical analyses performed in this work.

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arXiv2022

Testing f(R) gravity models with quasar X-ray and UV fluxes

Recently, Active Galactic Nuclei (AGNs) have been proposed as standardizable candles, thanks to an observed non-linear relation between their X-ray and optical-ultraviolet (UV) luminosities, which provides an independent measurement of their distances. In this paper, we use these observables for the first time to estimate the parameters of f(R) gravity models (specifically the Hu-Sawicki and the exponential models) together with the cosmological parameters. The importance of this type of modified gravity theories lies in the fact that they can explain the late time accelerated expansion of the universe without the inclusion of a dark energy component. We have also included other observable data to the analyses such as estimates of the Hubble parameter H(z) from Cosmic Chronometers, the Pantheon Type Ia supernovae compilation, and Baryon Acoustic Oscillations measurements. Our results show that the allowed space parameter is restricted when both AGN and BAO data are added to CC and SnIa data, being the BAO data set the most restrictive one. We can also conclude that even though our results are consistent with the ones from the LCDM model, small deviations from General Relativity, than can be successfully described by the f(R) models studied in this paper, are also allowed by the considered data sets.

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arXiv2022

Self-Interacting Dark Matter in Cosmology: accurate numerical implementation and observational constraints

This paper presents a systematic and accurate treatment of the evolution of cosmological perturbations in self-interacting dark matter models, for particles which decoupled from the primordial plasma while relativistic. We provide a numerical implementation of the Boltzmann hierarchies developed in a previous paper [JCAP, 09 (2020) 041] in a publicly available Boltzmann code and show how it can be applied to realistic DM candidates such as sterile neutrinos either under resonant or non-resonant production mechanisms, and for different field mediators. At difference with traditional fluid approximations -- also known as a $c_{\rm eff}-c_{\rm vis}$ parametrizations -- our approach follows the evolution of phase-space perturbations under elastic DM interactions for a wide range of interaction models, including the effects of late kinetic decoupling. Finally, we analyze the imprints left by different self interacting models on linear structure formation, which can be constrained using Lyman-$α$ forest and satellite counts. We find new lower bounds on the particle mass that are less restrictive than previous constraints.

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arXiv2016

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological analysis of the DR12 galaxy sample

We present cosmological results from the final galaxy clustering data set of the Baryon Oscillation Spectroscopic Survey, part of the Sloan Digital Sky Survey III. Our combined galaxy sample comprises 1.2 million massive galaxies over an effective area of 9329 deg^2 and volume of 18.7 Gpc^3, divided into three partially overlapping redshift slices centred at effective redshifts 0.38, 0.51, and 0.61. We measure the angular diameter distance DM and Hubble parameter H from the baryon acoustic oscillation (BAO) method after applying reconstruction to reduce non-linear effects on the BAO feature. Using the anisotropic clustering of the pre-reconstruction density field, we measure the product DM*H from the Alcock-Paczynski (AP) effect and the growth of structure, quantified by fσ8(z), from redshift-space distortions (RSD). We combine measurements presented in seven companion papers into a set of consensus values and likelihoods, obtaining constraints that are tighter and more robust than those from any one method. Combined with Planck 2015 cosmic microwave background measurements, our distance scale measurements simultaneously imply curvature Ω_K =0.0003+/-0.0026 and a dark energy equation of state parameter w = -1.01+/-0.06, in strong affirmation of the spatially flat cold dark matter model with a cosmological constant (ΛCDM). Our RSD measurements of fσ_8, at 6 per cent precision, are similarly consistent with this model. When combined with supernova Ia data, we find H0 = 67.3+/-1.0 km/s/Mpc even for our most general dark energy model, in tension with some direct measurements. Adding extra relativistic species as a degree of freedom loosens the constraint only slightly, to H0 = 67.8+/-1.2 km/s/Mpc. Assuming flat ΛCDM we find Ω_m = 0.310+/-0.005 and H0 = 67.6+/-0.5 km/s/Mpc, and we find a 95% upper limit of 0.16 eV/c^2 on the neutrino mass sum.

astro-ph.CO↗

arXiv2015

Cosmological implications of baryon acoustic oscillation (BAO) measurements

We derive constraints on cosmological parameters and tests of dark energy models from the combination of baryon acoustic oscillation (BAO) measurements with cosmic microwave background (CMB) and Type Ia supernova (SN) data. We take advantage of high-precision BAO measurements from galaxy clustering and the Ly-alpha forest (LyaF) in the BOSS survey of SDSS-III. BAO data alone yield a high confidence detection of dark energy, and in combination with the CMB angular acoustic scale they further imply a nearly flat universe. Combining BAO and SN data into an "inverse distance ladder" yields a 1.7% measurement of $H_0=67.3 \pm1.1$ km/s/Mpc. This measurement assumes standard pre-recombination physics but is insensitive to assumptions about dark energy or space curvature, so agreement with CMB-based estimates that assume a flat LCDM cosmology is an important corroboration of this minimal cosmological model. For open LCDM, our BAO+SN+CMB combination yields $Ω_m=0.301 \pm 0.008$ and curvature $Ω_k=-0.003 \pm 0.003$. When we allow more general forms of evolving dark energy, the BAO+SN+CMB parameter constraints remain consistent with flat LCDM. While the overall $χ^2$ of model fits is satisfactory, the LyaF BAO measurements are in moderate (2-2.5 sigma) tension with model predictions. Models with early dark energy that tracks the dominant energy component at high redshifts remain consistent with our constraints. Expansion history alone yields an upper limit of 0.56 eV on the summed mass of neutrino species, improving to 0.26 eV if we include Planck CMB lensing. Standard dark energy models constrained by our data predict a level of matter clustering that is high compared to most, but not all, observational estimates. (Abridged)

astro-ph.CO↗

arXiv2012

The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: constraints on the time variation of fundamental constants from the large-scale two-point correlation function

We obtain constraints on the variation of the fundamental constants from the full shape of the redshift-space correlation function of a sample of luminous galaxies drawn from the Data Release 9 of the Baryonic Oscillations Spectroscopic Survey. We combine this information with data from recent CMB, BAO and H_0 measurements. We focus on possible variations of the fine structure constant αand the electron mass m_e in the early universe, and study the degeneracies between these constants and other cosmological parameters, such as the dark energy equation of state parameter w_DE, the massive neutrinos fraction f_ν, the effective number of relativistic species N_eff, and the primordial helium abundance Y_He. When only one of the fundamental constants is varied, our final bounds are α/ α_0 = 0.9957_{-0.0042}^{+0.0041} and m_e /(m_e)_0 = 1.006_{-0.013}^{+0.014}. For their joint variation, our results are α/ α_0 = 0.9901_{-0.0054}^{+0.0055} and m_e /(m_e)_0 = 1.028 +/- 0.019. Although when m_e is allowed to vary our constraints on w_DE are consistent with a cosmological constant, when αis treated as a free parameter we find w_DE = -1.20 +/- 0.13; more than 1 σaway from its standard value. When f_νand αare allowed to vary simultaneously, we find f_ν< 0.043 (95% CL), implying a limit of \sum m_ν< 0.46 eV (95% CL), while for m_e variation, we obtain f_nu < 0.086 (95% CL), which implies \sum m_ν< 1.1 eV (95% CL). When N_eff or Y_He are considered as free parameters, their simultaneous variation with αprovides constraints close to their standard values (when the H_0 prior is not included in the analysis), while when m_e is allowed to vary, their preferred values are significantly higher. In all cases, our results are consistent with no variations of αor m_e at the 1 or 2 σlevel.

astro-ph.CO↗

arXiv2012

Cosmological constraints on non-standard inflationary quantum collapse models

We briefly review an important shortcoming --unearthed in previous works-- of the standard version of the inflationary model for the emergence of the seeds of cosmic structure. We consider here some consequences emerging from a proposal inspired on ideas of Penrose and Diósi about a quantum-gravity induced reduction of the wave function, which has been put forward to address the shortcomings, arguing that its effect on the inflaton field is what can lead to the emergence of the seeds of cosmic structure. The proposal leads to a deviation of the primordial spectrum from the scale-invariant Harrison-Zel'dovich one, and consequently, to a different CMB power spectrum. We perform statistical analyses to test two quantum collapse schemes with recent data from the CMB, including the 7-yr release of WMAP and the matter power spectrum measured using LRGs by the Sloan Digital Sky Survey. Results from the statistical analyses indicate that several collapse models are compatible with CMB and LRG data, and establish constraints on the free parameters of the models. The data put no restriction on the timescale for the collapse of the scalar field modes.

astro-ph.CO↗

arXiv2012

Constraints on variation in $α$ and $m_e$ from WMAP 7-year data

We update the constraints on the time variation of the fine structure constant $α$ and the electron mass $m_e$, using the latest CMB data, including the 7-yr release of WMAP. We made statistical analyses of the variation of each one of the constants and of their joint variation, together with the basic set of cosmological parameters. We used a modified version of CAMB and COSMOMC to account for these possible variations. We present bounds on the variation of the constants for different data sets, and show how results depend on them. When using the latest CMB data plus the power spectrum from Sloan Digital Sky Survey LRG, we find that $α/ α_0=0.986 \pm 0.007$ at 1-$σ$ level, when the 6 basic cosmological parameters were fitted, and only variation in $α$ was allowed. The constraints in the case of variation in both constants are $ α/ α_0= 0.986 \pm 0.009$ and $m_e / m_{e0} = 0.999 \pm 0.035$. In the case of only variation in $m_e$, the bound is $m_e /m_{e0}=0.964 \pm 0.025$.

astro-ph.CO↗

arXiv2009

WMAP 5-year constraints on time variation of $α$ and $m_e$

We studied the role of fundamental constants in an updated recombination scenario, focusing on the time variation of the fine structure constant αand the electron mass m_e in the early Universe. Using CMB data including WMAP 5-yr release, and the 2dFGRS power spectrum, we put bounds on variations of these constants, when both constants are allowed to vary, and in the case that only one of them is variable. In particular, we have found that -0.019 < Δα/ α_0 < 0.017 (95% c.l.), in our joint estimation of αand cosmological parameters. Finally, we analyze how the constraints depends on the recombination scenario.

astro-ph.CO↗

arXiv2009

Variation of the fine structure constant and the electron mass at early Universe

In this thesis, we focus on the study of the variation of the electron mass $m_e$, and the fine structure constant $α$, at different cosmic times. We analyze the details of the recombination physics, including helium recombination, in order to find the dependences of the physical quantities on the fundamental constants. Using up-to-date CMB data, and the final 2dFGRS power spectrum, we set limits to the possible variation of the constants at recombination. We analyze the variation of $α$ and $m_e$ independently, and the case in which both variations are allowed, fitting also a set of cosmological parameters. We find a fenomenological relationship between the variation of $α$ and the variation of $m_e$, between decoupling and present time. We analyze the Barrow-Magueijo fenomenological model, which propose a variation in the electron mass induced by changes in a space-time scalar field. We present improved solutions and we estimate the model parameters using bounds on the variation of the electron mass at different cosmic times. On the other hand, from results of experiments that test the Weak Equivalence Principle, we find a limit for the model's parameter, that comes from the variation of the electron mass induced by spatial variations of the scalar field. By comparing both limits, we arrive at the conclusion that the model should be ruled-out. Lastly, we reanalyze the effects of the variation of $α$ or $m_e$ upon planetary radii. We explain why the variation of the electron mass does not induce observable changes on the radii. We present a local and independent bound on the variation of $α$, obtained from very general statements. (TEXT IN SPANISH)

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