arXiv subjects

J. Fonseca

Publications and source records attributed to J. Fonseca.

6 recordsLinked to original sources

arXiv2026

Beyond {\Lambda}CDM with the SKA Observatory -- I: Probing Gravity on Cosmological Scales

General relativity (GR) is currently the best description of the gravitational interaction at our disposal and is one of the foundations of the concordance cosmological model. For as much as we know that GR is not the final theory of gravitation - we still lack an understanding of its fundamental, quantum nature - it has demonstrated a remarkable success in describing observed phenomena and predicting effects that have later been confirmed by laboratory experiments or astronomical observations. Since gravity is extremely weak compared to the other three fundamental interactions, it has so far been tested with exquisite precision only in the strong-field regime. On the immense scales of the cosmos, on the other hand, the gravitational field is extremely weak and spacetime curvature is almost negligible. But crucially, it is on these scales that we see hints at the need for exotic components, such as dark matter and dark energy. The question of whether they really exist or their presence is but an artefact of the incompleteness of our understanding of gravity on cosmological scales then naturally arises. It is therefore paramount to test the validity of GR on these scales, either to further confirm its robustness or to detect deviations that could lead us to the formulation of a more general and conclusive theory of gravitation. To this purpose, the SKA Observatory is especially suited, thanks both to the enormous volumes it will probe, and to the variety and complementarity of cosmological observables that its surveys will make available to us.

gr-qc↗

arXiv2026

Euclid preparation. Impact of redshift distribution uncertainties on the joint analysis of photometric galaxy clustering and weak gravitational lensing

One of the $\textit{Euclid}$ mission's key projects is the so-called 3$\times$2pt analysis, that is, the combination of cosmic shear, photometric galaxy clustering, and galaxy-galaxy lensing. Although $\textit{Euclid}$ has established quality requirements for the photo-$z$ accuracy needed for the weak lensing galaxy sample, no such requirements have been set for the photometric clustering sample. In this paper, we investigate the impact of redshift uncertainties on $\textit{Euclid}$'s photometric galaxy clustering analysis and its combination with weak gravitational lensing, focusing on data release 1 (DR1). In particular, we study whether having precise knowledge of the mean of the redshift distributions per bin is sufficient to avoid biases in the resulting cosmological constraints or whether accuracy in the higher-order moments of the distribution is required. We evaluate the results based on their constraining power on $w_{\mathrm{0}}$ and $w_{a}$ and define thresholds for the precision and accuracy of $\textit{Euclid}$'s redshift distribution of the photometric clustering sample. We find that the redshift distributions of the photometric clustering sample must be known at an accuracy of 0.004(1+$z$) in the mean in order to recover 80$\%$ of the constraining power in $\textit{Euclid}$'s DR1 $w_{\mathrm{0}}w_{a}$CDM 3$\times$2pt analysis. The impact of the uncertainty on the width is negligible, provided the mean redshift is constrained with sufficient accuracy. For most sources of redshift distribution error, attaining the requirement on the mean will also reduce uncertainty in the width well below the required level.

astro-ph.CO↗

arXiv2026

From photometric surveys to HI intensity mapping: Improving constraints on magnification biases while testing gravity

The observed large-scale structure of the Universe is not a direct measure on the underlying distribution of matter. These observations are subtly distorted by gravitational lensing effects, which leave imprints on the statistical distribution of galaxies and offer powerful test of general relativity. In this work, we investigate whether HI intensity mapping from current and forthcoming surveys can improve constraints on magnification lensing obtained from photometric galaxy surveys. In particular, can we jointly constrain the magnification bias parameters $s^\mathrm{G}(z)$ and the amplitude of the Weyl potential, which we parametrise as $\beta$. We employ a Fisher matrix formalism in order to estimate future constrains on the magnification biases and $\beta$. We forecast constraints for three photometric surveys (DES-like, LSST-like, Euclid-like) individually and with two HI intensity mapping surveys (MeerKLASS, SKAO). We apply the multi-tracer technique by combining each galaxy survey with each HI survey, exploiting the combined constraining in the overlapping sky area. The multi-tracer approach dramatically improves constraints on $\beta$ by factors of 25 to 50, depending on the surveys considered. For $s^\mathrm{G}(z)$, improvements can be marginal or by a factors of 2 to 8. We also verify that $\beta$ and $s^\mathrm{G}(z)$ can be constrained simultaneously as the cross-correlations between tracers break the degeneracies among them. We conclude that the multi-tracer combination of photometric galaxy surveys and HI intensity mapping surveys enables high-precision measurements of both $s^\mathrm{G}(z)$ and $\beta$. This opens an additional pathway to constrain $\Phi+\Psi$ and test the validity of general relativity on cosmological scales.

astro-ph.CO↗

arXiv2025

A gradient boosting and broadband approach to finding Lyman-{\alpha} emitting galaxies beyond narrowband surveys

In this work, we test whether gradient-boosting algorithms, trained on broadband photometric data from traditional Lyman-$\alpha$ emitting (LAE) surveys, can efficiently and accurately identify LAE candidates from typical star-forming galaxies at similar redshifts and brightness levels. Using galaxy samples at $z \in [2,6]$ derived from the COSMOS2020 and SC4K catalogs, we trained gradient-boosting machine-learning algorithms (LGBM, XGBoost, and CatBoost) using optical and near-infrared broadband photometry. To ensure balanced performance, the models were trained on carefully selected datasets with similar redshift and i-band magnitude distributions. Additionally, the models were tested for robustness by perturbing the photometric data using the associated observational uncertainties. Our classification models achieved F1-scores of $\sim 87\%$ and successfully identified about $7,000$ objects with an unanimous agreement across all models. This more than doubles the number of LAEs identified in the COSMOS field compared with the SC4K dataset. We managed to spectroscopically confirm 60 of these LAE candidates using the publicly available catalogs in the COSMOS field. These results highlight the potential of machine learning in efficiently identifying LAEs candidates. This lays the foundations for applications to larger photometric surveys, such as Euclid and LSST. By complementing traditional approaches and providing robust preselection capabilities, our models facilitate the analysis of these objects. This is crucial to increase our knowledge of the overall LAE population.

astro-ph.GA↗

arXiv2019

Fundamental Physics with the Square Kilometre Array

The Square Kilometre Array (SKA) is a planned large radio interferometer designed to operate over a wide range of frequencies, and with an order of magnitude greater sensitivity and survey speed than any current radio telescope. The SKA will address many important topics in astronomy, ranging from planet formation to distant galaxies. However, in this work, we consider the perspective of the SKA as a facility for studying physics. We review four areas in which the SKA is expected to make major contributions to our understanding of fundamental physics: cosmic dawn and reionisation; gravity and gravitational radiation; cosmology and dark energy; and dark matter and astroparticle physics. These discussions demonstrate that the SKA will be a spectacular physics machine, which will provide many new breakthroughs and novel insights on matter, energy and spacetime.

astro-ph.CO↗

arXiv2015

Energetics of ion competition in the DEKA selectivity filter of neuronal sodium channels

The energetics of ionic selectivity in the neuronal sodium channels is studied. A simple model constructed for the selectivity filter of the channel is used. The selectivity filter of this channel type contains aspartate (D), glutamate (E), lysine (K), and alanine (A) residues (the DEKA locus). We use Grand Canonical Monte Carlo simulations to compute equilibrium binding selectivity in the selectivity filter and to obtain various terms of the excess chemical potential from a particle insertion procedure based on Widom's method. We show that K$^{+}$ ions in competition with Na$^{+}$ are efficiently excluded from the selectivity filter due to entropic hard sphere exclusion. The dielectric constant of protein has no effect on this selectivity. Ca$^{2+}$ ions, on the other hand, are excluded from the filter due to a free energetic penalty which is enhanced by the low dielectric constant of protein.

cond-mat.soft↗