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Andrea Pezzotta

Publications and source records attributed to Andrea Pezzotta.

10 recordsLinked to original sources

cloelib: A Flexible Python Library for Computing Cosmological Observables in the Euclid Era

cloelib is a Python library developed to compute cosmological observables within the Cosmology Likelihood for Observables in Euclid (CLOE) ecosystem (cloe-org). As cosmology enters a precision era driven by galaxy survey missions such as Euclid, there is a growing need for flexible, efficient, and differentiable software capable of supporting next-generation inference pipelines. cloelib addresses these demands through a modular architecture that interfaces seamlessly with established Boltzmann solvers whilst incorporating JAX-based automatic differentiation to enable gradient-based methods. The library defines consistent protocols for background evolution, perturbations, and non-linear structure formation, and supports a wide range of observables, including photometric and spectroscopic large-scale structure probes, as well as cross-correlations with the Cosmic Microwave Background and galaxy clusters. In its finalised form, cloelib is intended to serve as the reference theory computation infrastructure for Euclid's first cosmological release, bridging traditional numerical cosmology with modern optimisation techniques and emerging machine learning approaches to inference.

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cloelike: A Python Library for Cosmological Likelihood Inference in the Euclid Era

cloelike is a Python package providing modular, composable Gaussian likelihood classes for the main cosmological large-scale structure observables targeted by the ESA Euclid space mission. It is a core component of the CLOE (Cosmology Likelihood for Observables in Euclid) ecosystem and interfaces directly with cloelib for theoretical predictions and euclidlib for reading official Euclid data products. The package implements Gaussian likelihoods covering harmonic angular power spectra and real-space two-point correlation functions for weak lensing (WL), photometric galaxy clustering (GCph), and Galaxy-Galaxy Lensing (GGL) in all joint probe combinations (3x2pt, 2x2pt), as well as spectroscopic full-shape power spectrum multipoles, and baryonic Acoustic oscillations (BAO). cloelike is actively used in internal Euclid Consortium analyses and is openly released to support community validation and reproducibility.

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Boosting galaxy clustering analyses with non-perturbative modelling of redshift-space distortions

Redshift-space distortions (RSD), caused by the peculiar velocities of galaxies, are a key modelling challenge in galaxy clustering analyses, limiting the scales from which cosmological information can be reliably extracted. Unlike dynamical or galaxy bias effects, RSD imprint features that are sensitive to non-linearities across all scales. Yet, no distinction between these effects is made by the state-of-the-art analytical approach - the effective field theory (EFT) - which applies the same perturbative expansion to each of them. This paper explores an alternative approach, where the non-perturbative nature of RSD is partially preserved, and compares its effectiveness against the EFT in analysing power spectrum and bispectrum multipoles from synthetic samples of luminous red galaxies, using the projected sensitivity of a Stage-IV galaxy survey. Our results demonstrate that this distinct treatment of RSD improves the robustness of model predictions for both statistics, extending the validity range of the EFT from approximately $0.2\,h\,\mathrm{Mpc}^{-1}$ to $0.35\,h\,\mathrm{Mpc}^{-1}$ for the one-loop power spectrum and from $0.1\,h\,\mathrm{Mpc}^{-1}$ to $0.14\,h\,\mathrm{Mpc}^{-1}$ for the tree-level bispectrum. This leads to a significant enhancement in the precision of cosmological parameter constraints, with uncertainties on the Hubble rate, matter density, and scalar amplitude of fluctuations reduced by $20$-$40\,\%$ for the power spectrum multipoles alone compared to the EFT, and by $25$-$50\,\%$ for joint analyses with the bispectrum. The RSD treatment proposed here may thus play a crucial role in maximising the scientific return of current and future galaxy surveys. To support this advancement, all models for the power spectrum and bispectrum used in this work are made available through an extended version of the Python package COMET.

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COMET: Clustering Observables Modelled by Emulated perturbation Theory

In this paper we present COMET, a Gaussian process emulator of the galaxy power spectrum multipoles in redshift-space. The model predictions are based on one-loop perturbation theory and we consider two alternative descriptions of redshift-space distortions: one that performs a full expansion of the real- to redshift-space mapping, as in recent effective field theory models, and another that preserves the non-perturbative impact of small-scale velocities by means of an effective damping function. The outputs of COMET can be obtained at arbitrary redshifts (up to $z \sim 3$), for arbitrary fiducial background cosmologies, and for a large parameter space that covers the shape parameters $ω_c$, $ω_b$, and $n_s$, as well as the evolution parameters $h$, $A_s$, $Ω_K$, $w_0$, and $w_a$. This flexibility does not impair COMET's accuracy, since we exploit an exact degeneracy between the evolution parameters that allows us to train the emulator on a significantly reduced parameter space. While the predictions are sped up by at least two orders of magnitude, validation tests reveal an accuracy of $0.1\,\%$ for the monopole and quadrupole ($0.3\,\%$ for the hexadecapole), or alternatively, better than $0.25\,σ$ for all three multipoles in comparison to statistical uncertainties expected for the Euclid survey with a tenfold increase in volume. We show that these differences translate into shifts in mean posterior values that are at most of the same size, meaning that COMET can be used with the same confidence as the exact underlying models. COMET is a publicly available Python package that also provides the tree-level bispectrum multipoles in redshift-space and Gaussian covariance matrices.

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Beyond $Λ$CDM constraints from the full shape clustering measurements from BOSS and eBOSS

We analyse the full shape of anisotropic clustering measurements from the extended Baryon Oscillation Spectroscopic survey (eBOSS) quasar sample together with the combined galaxy sample from the Baryon Oscillation Spectroscopic Survey (BOSS). We obtain constraints on the cosmological parameters independent of the Hubble parameter $h$ for the extensions of the $Λ$CDM models, focusing on cosmologies with free dark energy equation of state parameter $w$. We combine the clustering constraints with those from the latest CMB data from Planck to obtain joint constraints for these cosmologies for $w$ and the additional extension parameters - its time evolution $w_{\rm{a}}$, the physical curvature density $ω_{K}$ and the neutrino mass sum $\sum m_ν$. Our joint constraints are consistent with flat $Λ$CDM cosmological model within 68\% confidence limits. We demonstrate that the Planck data are able to place tight constraints on the clustering amplitude today, $σ_{12}$, in cosmologies with varying $w$ and present the first constraints for the clustering amplitude for such cosmologies, which is found to be slightly higher than the $Λ$CDM value. Additionally, we show that when we vary $w$ and allow for non-flat cosmologies and the physical curvature density is used, Planck prefers a curved universe at $4σ$ significance, which is $\sim2σ$ higher than when using the relative curvature density $Ω_{\rm{K}}$. Finally, when $w$ is varied freely, clustering provides only a modest improvement (of 0.021 eV) on the upper limit of $\sum m_ν$.

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Cosmological implications of the full shape of anisotropic clustering measurements in BOSS and eBOSS

We present the analysis of the full shape of anisotropic clustering measurement from the extended Baryon Oscillation Spectroscopic Survey (eBOSS) quasar sample together with the combined galaxy sample from the Baryon Oscillation Spectroscopic Survey (BOSS), re-analysed using an updated recipe for the non-linear matter power spectrum and the non-local bias parameters. We obtain constraints for flat $Λ$CDM cosmologies, focusing on the cosmological parameters that are independent of the Hubble parameter $h$. Our recovered value for the RMS linear perturbation theory variance as measured on the scale of $12\,{\rm Mpc}$ is $σ_{12}=0.805\pm 0.049$, while using the traditional reference scale of $8\,h^{-1}{\rm Mpc}$ gives $σ_{8}=0.815\pm 0.044$. We quantify the agreement between our measurements and the latest CMB data from Planck using the suspiciousness metric, and find them to be consistent within $0.64 \pm 0.03σ$. Combining our clustering constraints with the $3\times2$pt data sample from the Dark Energy Survey (DES) Year 1 release slightly degrades this agreement to the level of $1.54 \pm 0.08σ$, while still showing an overall consistency with Planck. We furthermore study the effect of imposing a Planck - like prior on the parameters that define the shape of the linear matter power spectrum, and find significantly tighter constraints on the parameters that control the evolution of density fluctuations. In particular, the combination of low-redshift data sets prefers a value of the physical dark energy density $ω_{\rm DE}=0.335 \pm 0.011$, which is 1.7$σ$ higher than the one preferred by Planck.

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Testing one-loop galaxy bias: cosmological constraints from the power spectrum

We investigate the impact of different assumptions in the modeling of one-loop galaxy bias on the recovery of cosmological parameters, as a follow up of the analysis done in the first paper of the series at fixed cosmology. We use three different synthetic galaxy samples whose clustering properties match the ones of the CMASS and LOWZ catalogues of BOSS and the SDSS Main Galaxy Sample. We investigate the relevance of allowing for either short range non-locality or scale-dependent stochasticity by fitting the real-space galaxy auto power spectrum or the combination of galaxy-galaxy and galaxy-matter power spectrum. From a comparison among the goodness-of-fit ($χ^2$), unbiasedness of cosmological parameters (FoB), and figure-of-merit (FoM), we find that a four-parameter model (linear, quadratic, cubic non-local bias, and constant shot-noise) with fixed quadratic tidal bias provides a robust modelling choice for the auto power spectrum of the three samples, up to $k_{\rm max}=0.3\,h\,\mathrm{Mpc}^{-1}$ and for an effective volume of $6\,h^{-3}\,\mathrm{Gpc}^3$. Instead, a joint analysis of the two observables fails at larger scales, and a model extension with either higher derivatives or scale-dependent shot-noise is necessary to reach a similar $k_{\rm max}$, with the latter providing the most stable results. These findings are obtained with three, either hybrid or perturbative, prescriptions for the matter power spectrum, \texttt{RESPRESSO}, gRPT and EFT. In all cases, the inclusion of scale-dependent shot-noise increases the range of validity of the model in terms of FoB and $χ^2$. Interestingly, these model extensions with additional free parameters do not necessarily lead to an increase in the maximally achievable FoM for the cosmological parameters $\left(h,\,Ω_ch^2,\,A_s\right)$, which are generally consistent to those of the simpler model at smaller $k_{\rm max}$.

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Testing one-loop galaxy bias: joint analysis of power spectrum and bispectrum

We present a joint likelihood analysis of the real-space power spectrum and bispectrum measured from a variety of halo and galaxy mock catalogs. A novel aspect of this work is the inclusion of nonlinear triangle configurations for the bispectrum, made possible by a complete next-to-leading order ("one-loop") description of galaxy bias, as is already common practice for the power spectrum. Based on the goodness-of-fit and the unbiasedness of the parameter posteriors, we accomplish a stringent validation of this model compared to the leading order ("tree-level") bispectrum. Using measurement uncertainties that correspond to an effective survey volume of $6\,(\mathrm{Gpc}/h)^3$, we determine that the one-loop corrections roughly double the applicable range of scales, from $\sim 0.17\,h/\mathrm{Mpc}$ (tree-level) to $\sim 0.3\,h/\mathrm{Mpc}$. This converts into a $1.5 - 2$x improvement on constraints of the linear bias parameter at fixed cosmology, and a $1.5 - 2.4$x shrinkage of uncertainties on the amplitude of fluctuations $A_s$, which clearly demonstrates the benefit of extracting information from nonlinear scales despite having to marginalize over a larger number of bias parameters. Besides, our precise measurements of galaxy bias parameters up to fourth order allow for thorough comparisons to coevolution relations, showing excellent agreement for all contributions generated by the nonlocal action of gravity. Using these relations in the likelihood analysis does not compromise the model validity and is crucial for obtaining the quoted improvements on $A_s$. We also analyzed the impact of higher-derivative and scale-dependent stochastic terms, finding that for a subset of our tracers the former can boost the performance of the tree-level model with constraints on $A_s$ that are only slightly degraded compared to the one-loop model.

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Testing one-loop galaxy bias: Power spectrum

We test the regime of validity of one-loop galaxy bias for a wide variety of biased tracers. Our most stringent test asks the bias model to simultaneously match the galaxy-galaxy and galaxy-mass spectrum, using the measured nonlinear matter spectrum from the simulations to test one-loop effects from the bias expansion alone. In addition, we investigate the relevance of short-range nonlocality and halo exclusion through higher-derivative and scale-dependent noise terms, as well as the impact of using co-evolution relations to reduce the number of free fitting parameters. From comparing validity and merit of these assumptions we find that a four-parameter model (linear, quadratic, cubic nonlocal bias, and constant shot noise) with fixed quadratic tidal bias provides a robust modeling choice for the auto power spectrum of the less massive halos in our set of samples and their galaxy populations (up to $k_{\mathrm{max}} = 0.35\,h/\mathrm{Mpc}$ for a sample volume of $6\,(\mathrm{Gpc}/h)^3$). For the more biased tracers it is most beneficial to include scale-dependent noise. This is also the preferred option when considering combinations of the auto and cross power spectrum, which might be relevant in joint studies of galaxy clustering and weak lensing. We also test the use of perturbation theory to account for matter loops through gRPT, EFT and the hybrid approach RESPRESSO. While all these have similar performance, we find the latter to be the best in terms of validity and recovered mean posterior values, in accordance with it being based partially on simulations.

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Accurate fitting functions for peculiar velocity spectra in standard and massive-neutrino cosmologies

We estimate the velocity field in a large set of $N$-body simulations including massive neutrino particles, and measure the auto-power spectrum of the velocity divergence field as well as the cross-power spectrum between the cold dark matter density and the velocity divergence. We perform these measurements at four different redshifts and within four different cosmological scenarios, covering a wide range in neutrino masses. We find that the nonlinear correction to the velocity power spectra largely depend on the degree of nonlinear evolution with no specific dependence on the value of neutrino mass. We provide a fitting formula, based on the value of the r.m.s. of the matter fluctuations in spheres of $8h^{-1}$Mpc, describing the nonlinear corrections with 3\% accuracy on scales below $k=0.7\; h$ Mpc$^{-1}$.

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