arXiv subjects

Mariana Penna-Lima

Publications and source records attributed to Mariana Penna-Lima.

7 recordsLinked to original sources

arXiv2026

Cosmology-dependent covariance in galaxy cluster number counts: consequences for parameter inference

Galaxy clusters provide constraints on cosmology through their abundance as a function of mass and redshift. Parameter inference from cluster counts requires modelling the covariance entering the likelihood, including contributions from Poisson shot noise and super-sample covariance (SSC) induced by long-wavelength density fluctuations. Since evaluating the full covariance during parameter inference can be computationally expensive, particularly for SSC terms, many analyses compute it at a fiducial cosmology and keep it fixed. In this work, we investigate the impact of covariance misspecification on the estimation of $Ω_c$, $σ_8$, and $w$. We perform a systematic analysis in which the covariance is either varied consistently with the sampled cosmology or fixed at displaced cosmological models, including intermediate strategies where only selected components, such as SSC, are held fixed. Our analysis incorporates observational effects relevant for LSST-like optical surveys, including mass-proxy scatter and photometric redshift uncertainties. We find that the estimators of $Ω_c$, $σ_8$, and $w$ remain unbiased even when the covariance is evaluated at an incorrect cosmology. However, fixing the covariance can significantly over- or underestimate confidence regions. The magnitude and sign of this effect are driven primarily by amplitude-related parameters such as $S_8$. For LSST-like surveys, an inconsistent covariance specification can artificially modify the apparent $S_8$ tension inferred from cluster counts. We further show that a single covariance update evaluated at the recovered best-fit cosmology is sufficient to restore the correct uncertainty normalization. These results indicate that fixed-covariance approximations may be adequate for some single-probe analyses, but a fully cosmology-dependent treatment is required for consistent multi-probe studies. ABRIDGED

astro-ph.CO↗

arXiv2024

AutoKnots: Adaptive Knot Allocation for Spline Interpolation

In astrophysical and cosmological analyses, the increasing quality and volume of astronomical data demand efficient and precise computational tools. This work introduces a novel adaptive algorithm for automatic knots (AutoKnots) allocation in spline interpolation, designed to meet user-defined precision requirements. Unlike traditional methods that rely on manually configured knot distributions with numerous parameters, the proposed technique automatically determines the optimal number and placement of knots based on interpolation error criteria. This simplifies configuration, often requiring only a single parameter. The algorithm progressively improves the interpolation by adaptively sampling the function-to-be-approximated, $f(x)$, in regions where the interpolation error exceeds the desired threshold. All function evaluations contribute directly to the final approximation, ensuring efficiency. While each resampling step involves recomputing the interpolation table, this process is highly optimized and usually computationally negligible compared to the cost of evaluating $f(x)$. We show the algorithm's efficacy through a series of precision tests on different functions. However, the study underscores the necessity for caution when dealing with certain function types, notably those featuring plateaus. To address this challenge, a heuristic enhancement is incorporated, improving accuracy in flat regions. This algorithm has been extensively used and tested over the years. NumCosmo includes a comprehensive set of unit tests that rigorously evaluate the algorithm both directly and indirectly, underscoring its robustness and reliability. As a practical application, we compute the surface mass density $Σ(R)$ and the average surface mass density $\overlineΣ(<R)$ for Navarro-Frenk-White and Hernquist halo density profiles, which provide analytical benchmarks. (abridged)

astro-ph.IM↗

arXiv2024

Towards including super-sample covariance in the unbinned likelihood for cluster abundance cosmology

The measurement of the abundance of galaxy clusters in the Universe is a sensitive probe of cosmology, which depends on both the expansion history of the Universe and the growth of structure. Density fluctuations across the finite survey volume add noise to this measurement, this is often referred to as super-sample covariance (SSC). For an unbinned cluster analysis, such noise has not been included in the cluster likelihood, since the effect of SSC was small compared to the Poisson shot-noise for samples of a few hundred clusters. For upcoming large cluster surveys such as the Rubin LSST, which will deliver catalogs of tens of thousands of clusters, this effect will no longer be negligible. In this paper, we propose a new hybrid likelihood based on the Gauss-Poisson Compound model (GPC), by using infinitesimal mass bins and standard redshift bins. This likelihood has the advantages of an unbinned Poisson likelihood whilst successfully incorporating the effects of SSC. Using a simulated dark matter halo catalog, we find that the hybrid likelihood, accounting for both Poisson noise and SSC, increases the dispersion of the parameter posteriors by 20 percent when using 100,000 clusters compared to the standard unbinned likelihood, based on Poisson statistics only.

astro-ph.CO↗

arXiv2023

Testing the accuracy of likelihoods for cluster abundance cosmology

The abundance of galaxy clusters is a sensitive probe to the amplitude of matter density fluctuations, the total amount of matter in the Universe as well as its expansion history. Inferring correct values and accurate uncertainties of cosmological parameters requires accurate knowledge of cluster abundance statistics, encoded in the likelihood function. In this paper, we test the accuracy of cluster abundance likelihoods used in the literature, namely the Poisson and Gaussian likelihoods as well as the more complete description of the Gauss-Poisson Compound likelihood. This is repeated for a variety of binning choices and analysis setups. In order to evaluate the accuracy of a given likelihood, this work compares individual posterior covariances to the covariance of estimators over the 1000 simulated dark matter halo catalogs obtained from PINOCCHIO algorithm. We find that for Rubin/LSST or Euclid-like surveys the Gaussian likelihood gives robust constraints over a large range of binning choices. The Poisson likelihood, that does not account for sample covariance, always underestimates the errors on the parameters, even when the sample volume is reduced or only high-mass clusters are considered. We find no benefit in using the more complex Gauss-Poisson Compound likelihood as it gives essentially the same results as the Gaussian likelihood, but at a greater computational cost. Finally, in this ideal setup, we note only a small gain on the parameter error bars when using a large number of bins in the mass-redshift plane.

astro-ph.CO↗

arXiv2022

New formalism to define vacuum states for scalar fields in curved space-times

The problem of finding a vacuum definition for a single quantum field in curved space-times is discussed under a new geometrical perspective. The phase space dynamics of the quantum field modes are mapped to curves in a 2-dimensional hyperbolic metric space, in which distances between neighbor points are shown to be proportional to the Bogoliubov coefficients associated with their corresponding mode solutions in phase space. The vacuum state for each mode is then defined as the unique trajectory from which all mapped phase space solutions move within thin annular regions around it. This property implies the stability of the vacuum state: solutions evolved from a point in this trajectory stay close to it as both evolve, and the particle creation is therefore minimized. The new approach is applied to the well-known cases of the time-independent dynamics, where the solutions draw circles around this curve, and when the adiabatic approximation is valid. The analysis is then extended to time-dependent cases in which the adiabatic approximation is not applicable, in the super-Hubble or low-frequency regimes. It is shown that stability trajectories can also be found in these situations, and stable quantum vacua can be obtained. This new formalism is applied to two situations: de Sitter space, where the Bunch-Davies vacuum is obtained in a completely different manner through an analysis in the super-Hubble regime, and in the context of cosmological bouncing models, in which the contracting phase is dominated by a cosmological constant in the asymptotic past. A new vacuum state for cosmological perturbations is proposed in this situation.

gr-qc↗

arXiv2019

Selected Topics in Numerical Methods for Cosmology

The large amount of cosmological data already available (and in the near future) makes necessary the development of efficient numerical codes. Many software products have been implemented to perform cosmological analyses considering one or few probes. The need of multi-task software is rapidly increasing, in order to combine numerous cosmological probes along with their specificity (e.g., astrophysical descriptions and systematic errors). In this work we mention some of these libraries, bringing out some challenges they will face in the few-percent error era (on the cosmological parameters). We review some concepts of the standard cosmological model, and examine some specific topics on their implementation, bringing, for example, the discussion on how some quantities are numerically defined in different codes. We also consider implementation differences between public codes, mentioning their advantages/disadvantages.

astro-ph.CO↗

arXiv2018

Cosmological constraints from a joint analysis of cosmic microwave background and spectroscopic tracers of the large-scale structure

The standard model of cosmology, ΛCDM, is the simplest model that matches the current observations, but it relies on two hypothetical components, to wit, dark matter and dark energy. Future galaxy surveys and cosmic microwave background (CMB) experiments will independently shed light on these components, but a joint analysis that includes cross-correlations will be necessary to extract as much information as possible from the observations. In this paper, we carry out a multi-probe analysis based on pseudo-spectra and test it on publicly available data sets. We use CMB temperature anisotropies and CMB lensing observations from Planck as well as the spectroscopic galaxy and quasar samples of SDSS-III/BOSS, taking advantage of the large areas covered by these surveys. We build a likelihood to simultaneously analyse the auto and cross spectra of CMB lensing and tracer overdensity maps before running Monte-Carlo Markov Chains (MCMC) to assess the constraining power of the combined analysis. We then add the CMB temperature anisotropies likelihood and obtain constraints on cosmological parameters ($H_0$, $ω_b$, $ω_c$, ${\ln10^{10}A_s}$, $n_s$ and $z_{re}$) and galaxy biases. We demonstrate that the joint analysis can additionally constrain the total mass of neutrinos ${Σm_ν}$ as well as the dark energy equation of state $w$ at once (for a total of eight cosmological parameters), which is impossible with either of the data sets considered separately. Finally, we discuss limitations of the analysis related to, e.g., the theoretical precision of the models, particularly in the non-linear regime.

astro-ph.CO↗