arXiv subjects

Karim Carrion

Publications and source records attributed to Karim Carrion.

7 recordsLinked to original sources

arXiv2026

Early against Late: A contrast on dark energy in the light of DESI DR2

Recent findings from Dark Energy Spectroscopic Instrument (DESI) Baryon Acoustic Oscillation (BAO) measurements, combined with Type Ia supernovae and Cosmic Microwave Background (CMB) data, suggest potential parameter-level deviations from $\Lambda\text{CDM}$. However, parameter exclusions omit prior-volume penalties, whereas Bayesian evidence uncovers a stark dichotomy between early- and late-time dynamics. To quantify this effect, we perform a Bayesian model comparison that explicitly accounts for the cosmological epoch of dark energy dynamics, contrasting two schemes acting in opposite epochs of cosmic history: pre-recombination Early Dark Energy (EDE) and late-time Chevallier--Polarski--Linder (CPL), both measured against a baseline $\Lambda$CDM. We validate the learned harmonic-mean estimator against \texttt{UltraNest} (at background level) before applying it to the CMB analysis. Background-only data already disfavor both extensions, yielding $\ln B_{\Lambda\text{CDM},\text{EDE}} = 2.45 \pm 0.25$ and $\ln B_{\Lambda\text{CDM},\text{CPL}} = 3.45 \pm 0.24$. Including CMB sharpens this result: EDE is decisively rejected ($\ln B_{\Lambda\text{CDM},\text{EDE}} = 12.44 \pm 0.05$) with its early-time fraction constrained to $10^3\,\Omega_e^{\rm EDE} = 2.0^{+0.6}_{-1.0}$, whereas CPL remains moderately disfavored ($\ln B_{\Lambda\text{CDM},\text{CPL}} = 2.33 \pm 0.06$), even though 2D parameter posteriors for both models display a multi-$\sigma$ deviation from $\Lambda\text{CDM}$. Thus, Bayesian evidence weakens reported preferences for dark energy dynamics, with the impact depending on the cosmic epoch involved, confirmed by our functional reconstructions of $w_{\rm de}(z)$ and $\Omega_{\rm de}(z)$ from posterior samples.

astro-ph.CO↗

arXiv2026

Bayesian analysis of $\alpha$-Starobinsky model with Planck, ACT and DESI data

We present a joint Bayesian analysis to impose constraints on the generalized $\alpha$-Starobinsky inflationary model using the high-precision cosmological datasets: Planck, CMB lensing from ACT DR6, and Baryon Acoustic Oscillations (BAO) from DESI DR2. For the parameter inference, we introduce an alternative sampling approach. Rather than imposing priors on the cosmological parameters of the inflationary potential $(V_0, \, \alpha, \, N_*)$, we place priors directly on the primordial physical observables $(A_s,\, n_s,\, r)$ through analytical slow-roll consistency relations. Our pipeline internally maps these sampled observables to the corresponding $\alpha$-Starobinsky parameters. These values are then passed to a modified version of $\tt{CLASS}$, which solves the exact inflationary dynamics numerically. This pipeline ensures that the final reported posteriors for the observables are computed exactly, completely free from the slow-roll approximation. Applying this methodology, we explore the viability of the $\alpha$-Starobinsky model. We show that, when the full combined dataset is considered, the pure Starobinsky model (i.e., the canonical limit $\alpha = 1$) shows signs of breaking down, since it requires a large number of $e$-folds of inflation after horizon crossing ($N_* > 60$) due to the shift in the scalar spectral index, $n_s$. In contrast, allowing the deformation parameter $\alpha$ as a free parameter yields a clear $1\sigma$ preference for $\log_{10} \alpha > 0$, present across all datasets. Notably, we also show that the addition of ACT DR6 lensing data introduces no significant impact on these primordial constraints, confirming that our robust posteriors are primarily driven by Planck and DESI measurements.

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arXiv2025

Accelerating cosmological inference of interacting dark energy with neural emulators

The present thesis aims to tackle two critical aspects of present and future cosmological analysis of Large-Scale Structure (LSS): accurate modelling of the nonlinear matter power spectrum beyond $Λ$CDM, and efficient computational techniques for Bayesian parameter estimation. Both are crucial for testing alternative cosmologies and avoiding spurious results. We focus on the Dark Scattering (DS) model, describing pure momentum transfer between dark matter -- dark energy through the parameter $A_{\rm ds}$. To capture DS effects, we adopt the halo model reaction framework within $\tt{ReACT}$, compute the nonlinear DS spectrum, and validate it against $N$-body simulations. We further include baryonic feedback and massive neutrinos, finding degeneracies between DS and baryonic effects but not with neutrinos. We then constrain DS using cosmic shear from KiDS-1000, accelerated by neural emulators from $\tt{CosmoPower}$, which speed up predictions by $\mathcal{O}(10^4)$. Our DS emulator, trained on halo model reaction outputs, preserves percent-level accuracy and incorporates baryonic feedback. Analysing KiDS shear statistics, we obtain $\vert A_{\rm ds}\vert \lesssim 20$ b/GeV at $68 \%$ C.L. Combining KiDS with Planck CMB and BAO data, we find $A_{\rm ds}=10.6^{+4.5}_{-7.3}$ b/GeV at $68 \%$ C.L., suggesting the DS model as a promising resolution to the $S_8$ tension. Finally, we present weak lensing forecasts for Stage IV surveys using an automatically differentiable pipeline with $\tt{jax-cosmo}$ and gradient-based samplers in $\tt{NumPyro}$, reducing computational cost from months on CPUs to days on GPUs. Model evidence is evaluated with $\tt{harmonic}$ under multiple scale cuts. To put things into perspective, the modelling strategies and machine learning accelerations developed here provide powerful tools for the next generation of LSS cosmology.

astro-ph.CO↗

arXiv2025

Testing interacting dark energy with Stage IV cosmic shear surveys through differentiable neural emulators

We employ a novel framework for accelerated cosmological inference, based on neural emulators and gradient-based sampling methods, to forecast constraints on dark energy models from Stage IV cosmic shear surveys. We focus on dark scattering (DS), an interacting dark energy model with pure momentum exchange in the dark sector, and train COSMOPOWER emulators to accurately and efficiently model the DS non-linear matter power spectrum produced by the halo model reaction framework, including the effects of baryon feedback and massive neutrinos. We embed the emulators within a fully-differentiable pipeline for gradient-based cosmological inference for which the batch likelihood call is up to $O(10^5)$ times faster than with traditional approaches, producing parameter constraints from simulated Stage IV cosmic shear data running on a single graphics processing unit (GPU). We also perform model comparison on the output chains from the inference process, employing the learnt harmonic mean estimator implemented in the software HARMONIC. We investigate degeneracies between dark energy and systematics parameters and assess the impact of scale cuts on the final constraints. Assuming a DS model for the mock data vector, we find that a Stage IV survey cosmic shear analysis can constrain the DS amplitude parameter $A_{\mathrm{ds}}$ with an uncertainty roughly an order of magnitude smaller than current constraints from Stage III surveys, even after marginalising over baryonic feedback, intrinsic alignments and redshift distribution uncertainties. These results show great promise for constraining DS with Stage IV data; furthermore, our methodology can be straightforwardly extended to a wide range of dark energy and modified gravity models.

astro-ph.CO↗

arXiv2024

Dark Scattering: accelerated constraints from KiDS-1000 with $\tt{ReACT}$ and $\tt{CosmoPower}$

We present constraints on the Dark Scattering model through cosmic shear measurements from the Kilo Degree Survey (KiDS-1000), using an accelerated pipeline with novel emulators produced with $\tt{CosmoPower}$. Our main emulator, for the Dark Scattering non-linear matter power spectrum, is trained on predictions from the halo model reaction framework, previously validated against simulations. Additionally, we include the effects of baryonic feedback from $\tt{HMcode2016}$, whose contribution is also emulated. We analyse the complete set of statistics of KiDS-1000, namely Band Powers, COSEBIs and Correlation Functions, for Dark Scattering in two distinct cases. In the first case, taking into account only KiDS cosmic shear data, we constrain the amplitude of the dark energy - dark matter interaction to be $\vert A_{\rm ds} \vert \lesssim 20$ $\rm b/GeV$ at 68% C.L. Furthermore, we add information from the cosmic microwave background (CMB) from Planck, along with baryon acoustic oscillations (BAO) from 6dFGS, SDSS and BOSS, approximating a combined weak lensing + CMB + BAO analysis. From this combination, we constrain $A_{\rm ds} = 10.6^{+4.5}_{-7.3}$ $\rm b/GeV$ at 68% C.L. We confirm that with this estimated value of $A_{\rm ds}$ the interacting model considered in this work offers a promising alternative to solve the $S_8$ tension.

astro-ph.CO↗

arXiv2022

On the road to percent accuracy VI: the nonlinear power spectrum for interacting dark energy with baryonic feedback and massive neutrinos

Understanding nonlinear structure formation is crucial for fully exploring the data generated by stage IV surveys, requiring accurate modelling of the power spectrum. This is challenging for deviations from $Λ$CDM, but we must ensure that alternatives are well tested, to avoid false detections. We present an extension of the halo model reaction framework for interacting dark energy. We modify the halo model including the additional force present in the Dark Scattering model and implement it into ReACT. The reaction is combined with a pseudo spectrum from EuclidEmulator2 and compared to N-body simulations. Using standard mass function and concentration-mass relation, we find predictions to be 1 % accurate at $z=0$ up to $k=0.8~h/{\rm Mpc}$ for the largest interaction strength tested ($ξ=50$ b/GeV), improving to $2~h/{\rm Mpc}$ at $z=1$. For smaller interaction strength ($10$ b/GeV), we find 1 % agreement at $z=1$ up to scales above $3.5~h/{\rm Mpc}$, being close to $1~h/{\rm Mpc}$ at $z=0$. Finally, we improve our predictions with the inclusion of baryonic feedback and massive neutrinos and study degeneracies between the effects of these contributions and those of the interaction. Limiting the scales to where our modelling is 1 % accurate, we find a degeneracy between the interaction and feedback, but not with massive neutrinos. We expect the degeneracy with feedback to be resolvable by including smaller scales. This work represents the first analytical tool for calculating the nonlinear spectrum for interacting dark energy models.

astro-ph.CO↗

arXiv2021

Complex Scalar Field Reheating and Primordial Black Hole production

We study perturbations of a complex scalar field during reheating with no self-interaction in the regime $ μ\gg H$, when the scalar field has a fast oscillatory behaviour (close to a pressure-less fluid). We focus on the precise determination of the instability scale and find it differs from that associated with a real scalar field. We further look at the probability that unstable fluctuations form Primordial Black Holes (PBHs) obtaining a significant production of tiny PBHs which quickly evaporate and may subsequently leave a population of Planck-mass relics. We finally impose restrictions on the duration and energy scale of the fast oscillations period by considering that such relics constitute, at most, the totality of dark matter in the Universe.

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