arXiv subjects

Andrina Nicola

Publications and source records attributed to Andrina Nicola.

At least 19 recordsLinked to original sources

arXiv2026

Baryonification IV: Constraining baryonic feedback with X-ray gas fractions

Baryonic feedback redistributes gas around dark matter halos, suppressing the matter power spectrum at scales now probed by weak lensing surveys. X-ray observations directly trace this hot gas, and are one of the main probes of its distribution and properties. We present a forward-modelling framework, built on the baryonification model, linking the three-dimensional gas density and temperature profiles of groups and clusters to observed X-ray surface brightness and luminosity profiles on one side, and to matter power spectrum suppression on the other. We validate the model against independent three-dimensional density reconstructions from the literature, and examine our temperature and metallicity treatment in the group-scale regime. Applying this framework to the SZ-selected CHEX-MATE and X-ray-selected eFEDs samples, we measure gas fractions across the group-to-cluster mass range while accounting for X-ray selection effects, with the first published gas fractions based on CHEX-MATE data. Combining both samples, we derive a joint constraint on the hot gas fraction retained by groups and clusters as a function of mass and on the baryonic suppression of the matter power spectrum. We find $f_{\rm gas} = 0.029 \pm 0.006$ at $M_{500c} = 3\times 10^{13}M_\odot$, $f_{\rm gas} = 0.078 \pm 0.004$ at $M_{500c} = 3\times 10^{14}M_\odot$, and suppression of 6% at $k=1\,h/\rm Mpc$ and 23% at $k=5\,h/\rm Mpc$. Our findings are consistent with recent kinematic Sunyaev-Zel'dovich results, hinting at strong feedback. We also show that the $L_X$-$M$ relation is degenerate with feedback strength, and that different feedback scenarios produce distinct X-ray profile shapes that map onto the same $L_X$-$M$ point. This work is a first step toward extending the framework to forward-model diffuse X-ray emission at the map level for simulation-based inference in upcoming wide-area X-ray surveys such as eROSITA.

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arXiv2026

Statistical Field Theory for Weak Gravitational Lensing

Standard weak-lensing calculations treat lensing as a linear remapping of the matter field along the line of sight. We instead formulate lensing as a stochastic field theory for the Sachs optical scalars, driven by random Ricci-focusing and Weyl-shearing fields. The resulting path integral generates a diagrammatic expansion for arbitrary $n$-point correlation functions of lensing observables, organised into linear response, nonlinear propagation, and driving-field cumulants. The conventional calculation emerges as the lowest-order, linear-propagation limit. Beyond it, nonlinear Sachs evolution couples to driving-field non-Gaussianity, mixing the matter cumulant hierarchy into the lensing hierarchy. A selection rule governs the couplings: an $n$-point observable receives a direct contribution from the $n$-point driving-field cumulant, and its leading hierarchy-mixing correction from the $(n+1)$-point cumulant via one nonlinear Sachs interaction, with higher cumulants entering only at higher order. The two-point function, for instance, is corrected by three-point cumulants of Ricci focusing and Weyl shearing, letting small-scale modes feed the lensing signal across scales and populating the $E$- and $B$-modes in comparable measure. Rather than a restrictive approximation scheme, the formalism is a paradigm shift: a unified framework naturally accommodating path corrections, higher-order matter statistics, stochasticity, and small-scale effects.

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arXiv2026

Analytical covariances for catalogue-based pseudo-$C_\ell$s

Multiple cosmological observables, such as the galaxy overdensity or cosmic shear, consist of fields sampled at the discrete positions of astrophysical sources. Recent work has presented methods to estimate the angular power spectra of such fields, avoiding the construction of pixelated sky maps and the finite-resolution effects associated with them. In this work, we present a method to estimate the disconnected (also known as "Gaussian") covariance of these angular power spectra, addressing subtle effects such as the effective area overlap between different catalogue-based fields and the additional Poisson-like variance arising from the discrete nature of the catalogues. The method relies on the so-called Narrow-Kernel Approximation to account for the contribution of distinct source pairs to the estimator, while including the noise-like contributions from self-pairs exactly. We explicitly compare this approach with a brute-force method that can produce the exact covariance for sparse samples, and validate it against simulations. We show that the method is accurate in realistic scenarios, spanning both dense and noise-dominated datasets (e.g., cosmic shear) and sparse, noise-dominated observables (e.g., fast radio bursts). The method is implemented in the public code NaMaster.

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arXiv2026

Baryonification III: An accurate analytical model for the dispersion measure probability density function of fast radio bursts

We develop an analytical framework to predict the one-point probability distribution function (PDF) of dispersion measures (DMs) for fast radio bursts (FRBs) within the baryonification (BFC) model. BFC provides a computationally efficient alternative to expensive hydrodynamical simulations for modelling baryonic effects on cosmological scales. By applying the halo mass function and halo bias, we convolve contributions from individual halos across a range of masses and redshifts to derive the large-scale structure contribution to the DM PDF. We validate our analytical predictions against consistency-check simulations and compare them with the IllustrisTNG hydrodynamical simulation over the redshift range $ z = 0$ to $z = 5$, demonstrating excellent agreement. We demonstrate that our model produces consistent results when fitting gas profiles and predicting the PDF, and vice versa. We show that the BFC parameters controlling the gas profile, particularly the halo mass scale ($M_\mathrm{c}$), mass-dependent slope ($μ$), and outer truncation ($δ$), are the primary drivers of the PDF shape. Additionally, we investigate the validity of the log-normal approximation commonly used for DM distributions, finding that it provides a sufficient description for a few hundred FRBs. Our work provides a self-consistent model that links gas density profiles to integrated DM statistics, enabling future constraints on baryonic feedback processes from FRB observations.

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arXiv2026

Constraints from CMB lensing tomography with projected bispectra

We measure the angular power spectrum and bispectrum of the projected overdensity of photometric DESI luminous red galaxies, and its cross-correlation with maps of the Cosmic Microwave Background lensing convergence from \planck. This analysis is enabled by the use of the ``filtered-squared bispectrum'' approach, introduced in previous work, which we generalise here to the case of cross-correlations between multiple fields. The projected galaxy bispectrum is detected at very high significance (above $30σ$ in all redshift bins), and the galaxy-galaxy-convergence bispectrum is detected above $5σ$ in the three highest-redshift bins. We find that the bispectrum is reasonably well described over a broad range of scales by a tree-level prediction using the linear galaxy bias measured from the power spectrum. We carry out the first cosmological analysis combining projected power spectra and bispectra under a relatively simple model, and show that the galaxy bispectrum can be used in combination with the power spectrum to place a constraint on the amplitude of matter fluctuations, $σ_8$, an on the non-relativistic matter fraction $Ω_m$. We find that data combinations involving the galaxy bispectrum recover constraints on these parameters that are in good agreement with those found from the traditional ``2$\times$2-point'' combination of galaxy-galaxy and galaxy-convergence power spectra, across all redshift bins.

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arXiv2025

Baryonification: An alternative to hydrodynamical simulations for cosmological studies

We present an improved baryonification (BFC) model that modifies dark-matter-only $N$-body simulations to generate particle-level outputs for gas, dark matter, and stars. Unlike previous implementations, our approach first splits each simulation particle into separate dark matter and baryonic components, which are then displaced individually using the BFC technique. By applying the hydrostatic and ideal gas equations, we assign pressure and temperature values to individual gas particles. The model is validated against hydrodynamical simulations from the FLAMINGO and TNG suites (which feature varied feedback prescriptions) showing good agreement at the level of density and pressure profiles across a wide range of halo masses. As a further step, we calibrate the BFC model parameters to gas and stellar mass ratio profiles from the hydrodynamical simulations. Based on these calibrations, we baryonify $N$-body simulations and compare the resulting total matter power spectrum suppressions to the ones from the same hydrodynamical simulation. Carrying out this test of the BFC method at each redshift individually, we obtain a 2 percent agreement up to $k=5\,h$/Mpc across all tested feedback scenarios. We also define a reduced, 2+1 parameter BFC model that simultaneously accounts for feedback variations (2 parameters) and redshift evolution (1 parameter). The 2+1 parameter model agrees with the hydrodynamical simulations to better than 2.5 percent over the scales and redshifts relevant for cosmological surveys. Finally, we present a map-level comparison between a baryonified $N$-body simulation and a full hydrodynamical run from the TNG simulation suite. Visual inspection of dark matter, gas, and stellar density fields, along with the integrated pressure map, shows promising agreement. Further work is needed to quantify the accuracy at the level of observables.

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arXiv2025

Cross-correlation of Luminous Red Galaxies with ML-selected AGN in HSC-SSP III: HOD Parameters for Type I and Type II Quasars

Understanding the dark matter (DM) halo environment in which galaxies that host active galactic nuclei (AGN) reside is a window into the nature of supermassive black hole (SMBH) accretion. We apply halo occupation distribution (HOD) modeling tools to interpret the angular cross-correlation functions between $1.5\times10^6$ luminous red galaxies (LRGs) and our $\sim28,500$ Hyper Suprime-Cam + Wide-field Infrared Survey Explorer-selected (and $L_{6 μm}$-limited) AGN to infer the halo properties of distinct quasar samples at physical scales $s>0.1\,{\rm Mpc}$, for $z\in0.7-1.0$. We find that Type I (unobscured) and Type II (obscured) AGN cluster differently, both on small and large physical scales. The derived HODs imply that Type I AGN reside, on average, in substantially ($\sim3\times$) more massive halos ($M_h \sim 10^{13.4} M_\odot$) than Type II AGN ($M_h \sim 10^{12.9} M_\odot$) at $>5σ$ significance. While Type II AGN show one-halo correlations similar to that of galaxies of their average halo mass, the Type I AGN intra-halo clustering signal is significantly shallower. We interpret this observation with HOD methods and find Type I AGN are significantly less likely ($f_{sat}\sim0.05^{+1}_{-0.05}\%$) to be found in satellite galaxies than Type II AGN. We find reddened + obscured AGN to have typical satellite fractions for their inferred average halo mass ($\sim10^{13} M_\odot$), with $f_{sat} \sim 20^{+10}_{-5}\%$. Taken together, these results pose a significant challenge to the strict unified AGN morphological model, and instead suggest that a quasar's spectral class is strongly correlated with its host galaxy's dark matter halo environment. These intriguing results have provided a more complex picture of the SMBH -- DM halo connection, and motivate future analyses of the intrinsic galaxy and accretion properties of AGN.

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arXiv2025

Multiprobe constraints on early and late time dark energy

We perform a multiprobe analysis combining cosmic microwave background (CMB) data from Planck and the Atacama Cosmology Telescope (ACT), ACT CMB lensing, and large-scale structure (LSS) measurements from the Dark Energy Spectroscopic Instrument (DESI), including DESI Legacy Imaging Survey (LS) galaxies and baryon acoustic oscillations (BAOs). We present the first $5\times2$pt analysis of ACT DR6 lensing, DESI LS, and Planck ISW. Within $Λ$CDM, this yields $S_8 = σ_8(Ω_m/0.3)^{0.5} = 0.819 \pm 0.016$, in good agreement with primary CMB inferences and provides a sound-horizon-free Hubble constant constraint of $H_0 = 70.0 \pm 4.4$ km s$^{-1}$ Mpc$^{-1}$. Then, combining with CMB primary and BAO, we reconfirm a CMB-BAO discrepancy in the $Ω_m$-$\frac{D_v}{r_d}$ plane, which is heightened when combining BAO with the $5\times2$pt data vector. We explore two dark-energy extensions that may reconcile this: an early-time modification, early dark energy (EDE), and late-time dynamical dark energy (DDE) parameterized by $w_0w_a$. For CMB primary+BAO+$5\times2$pt, we find a $3.3σ$ preference for DDE over $Λ$CDM, while EDE is modestly favoured at $2.3σ$. The models address different shortcomings of $Λ$CDM: DDE relaxes the neutrino mass bound ($M_ν<0.17$eV vs. $<0.050$eV under $Λ$CDM), making it compatible with neutrino oscillation measurements, while EDE raises the Hubble constant to $H_0=70.5\pm1.2\,\mathrm{km\,s^{-1}\,Mpc^{-1}}$, easing the discrepancy with SH0ES. However, neither model resolves both issues simultaneously. Our analysis indicates that both DDE and EDE remain viable extensions of $Λ$CDM within current uncertainties and demonstrates the capacity of combined probes to place increasingly stringent constraints on cosmological parameters.

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arXiv2025

An analytical model for the dispersion measure of Fast Radio Burst host galaxies

The dispersion measure (DM) of fast radio bursts (FRBs) is sensitive to the electron distribution in the Universe, making it a promising probe of cosmology and astrophysical processes such as baryonic feedback. However, cosmological analyses of FRBs require knowledge of the contribution to the observed DM coming from the FRB host. The size and distribution of this contribution is still uncertain, thus significantly limiting current cosmological FRB analyses. In this study, we extend the baryonification (BCM) approach to derive a physically-motivated, analytic model for predicting the host contribution to FRB DMs. By focusing on the statistical properties of FRB host DMs, we find that our simple model is able to reproduce the probability distribution function (PDF) of host halo DMs measured from the CAMELS suite of hydrodynamic simulations, as well as their mass- and redshift dependence. Furthermore, we demonstrate that our model allows for self-consistent predictions of the host DM PDF and the matter power spectrum suppression due to baryonic effects, as observed in these simulations, making it promising for modelling host-DM-related systematics in FRB analyses. In general, we find that the shape of the host DM PDF is determined by the interplay between the FRB and gas distributions in halos. Our findings indicate that more compact FRB profiles require shallower gas profiles (and vice versa) in order to match the observed DM distributions in hydrodynamic simulations. Furthermore, the analytic model presented here shows that the shape of the host DM PDF is highly sensitive to the parameters of the BCM. This suggests that this observable could be used as an interesting test bed for baryonic processes, complementing other probes due to its sensitivity to feedback on galactic scales. We further discuss the main limitations of our analysis, and point out potential avenues for future work.

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arXiv2025

Constraining the primordial power spectrum using a differentiable likelihood

The simplest inflationary models predict the primordial power spectrum (PPS) of curvature perturbations to be nearly scale-invariant. However, various other models of inflation predict deviations from this behaviour, motivating a data-driven approach to reconstruct the PPS and constrain its shape. In this work, we present a novel method that employs a fully differentiable pipeline to reconstruct the PPS using Gaussian Processes and uses neural network emulators for fast and differentiable theoretical predictions. By leveraging gradient-based sampling techniques, such as Hamiltonian Monte Carlo, our approach efficiently samples the high-dimensional parameter space of cosmological parameters and the free-form PPS, enabling joint constraints on both. Applying this framework to Planck 2018 Cosmic Microwave Background (CMB) temperature anisotropy data we find our reconstructed PPS to be consistent with near scale-invariance on small scales, while exhibiting large uncertainties at large scales, driven mostly by cosmic variance. Our results show an overestimation of the PPS amplitude compared to $Λ$CDM predictions from the Planck 2018 analysis, which we attribute to our choice of a wider prior on the optical depth $τ$ based on Planck 2015 measurements. Adopting a prior consistent with Planck 2018 measurements brings our results into full agreement with previous work. To ensure robustness of our results, we validate our differentiable pipeline against a non-differentiable framework, and also demonstrate that our results are insensitive to the choice of Gaussian process hyperparameters. These promising results and the flexibility of our pipeline make it ideally suited for application to additional data sets such as CMB polarisation as well as Large-Scale Structure probes, thus moving towards multi-probe primordial power spectrum reconstruction.

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arXiv2025

Constraining the dispersion measure redshift relation with simulation-based inference

We use the dispersion measure (DM) of localised Fast Radio Bursts (FRBs) to constrain cosmological and host galaxy parameters using simulation-based inference (SBI) for the first time. By simulating the large-scale structure of the electron density with the Generator for Large-Scale Structure (GLASS), we generate log-normal realisations of the free electron density field, accurately capturing the correlations between different FRBs. For the host galaxy contribution, we rigorously test various models, including log-normal, truncated Gaussian and Gamma distributions, while modelling the Milky Way component using pulsar data. Through these simulations, we employ the truncated sequential neural posterior estimation method to obtain the posterior. Using current observational data, we successfully recover the amplitude of the DM-redshift relation, consistent with Planck, while also fitting both the mean host contribution and its shape. Notably, we find no clear preference for a specific model of the host galaxy contribution. Although SBI may not yet be strictly necessary for FRB inference, this work lays the groundwork for the future, as the increasing volume of FRB data will demand precise modelling of both the host and large-scale structure components. Our modular simulation pipeline offers flexibility, allowing for easy integration of improved models as they become available, ensuring scalability and adaptability for upcoming analyses using FRBs. The pipeline is made publicly available under https://github.com/koustav-konar/FastNeuralBurst.

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arXiv2025

Baryonification II: Constraining feedback with X-ray and kinematic Sunyaev-Zel'dovich observations

Baryonic feedback alters the matter distribution on small and intermediate scales, posing a challenge for precision cosmology. The new, component-wise baryonification (BFC) approach provides a self-consistent framework to model feedback effects for different observables. In this paper we use this framework to fit kinematic Sunyaev-Zel'dovich (kSZ) observations from the Atacama Cosmology Telescope (ACT) alongside halo X-ray gas fractions from eROSITA, investigating baryonic feedback in a cosmological context. We first show that the kSZ data from ACT is consistent with the gas fractions from eROSITA, both suggesting a feedback model that is stronger than what is assumed in most hydrodynamical simulations. This finding is in contrast to older, pre-eROSITA gas fraction measurements that point towards weaker feedback in tension with the kSZ results. We suspect these discrepancies to be due to selection bias in the pre-eROSITA sample, or differences in halo mass estimation between the two data sets. In a further step, we use the BFC model to predict the baryonic suppression of the matter power spectrum. Based on our combined fit to data from ACT and eROSITA, we find a power spectrum suppression that exceeds the percent-level at modes above $k=0.3-0.6 \,h\,\mathrm{Mpc}^{-1}$, growing to 2-8 percent at $k=1\,h\,\mathrm{Mpc}^{-1}$, and to 20-25 percent at $k=5\,h\,\mathrm{Mpc}^{-1}$, consistent with strong-feedback hydrodynamical simulations. Finally, we compare our best-fitting model to the observed gas density and pressure profiles of massive galaxy clusters from the X-COP sample, finding excellent agreement. These results show that BFC provides a self-consistent picture of feedback across mass- and length scales as well as different cosmological observables, thus making it promising for applications to multiwavelength studies to jointly constrain cosmology and baryonic effects.

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arXiv2025

Tuning the cosmic instrument: robust cosmology through combined probes

As wide-field surveys yield increasingly precise data, multiprobe analyses offer significant advantages. In this work, we use our previously developed framework for jointly analyzing cosmic microwave background (CMB) and large-scale structure data. We analyze combinations of three CMB (Planck PR3, Planck PR4, and ACT+WMAP) datasets, DESI Y1 Baryon Acoustic Oscillation (BAO) data, and a $9\times 2$pt low-$z$ dataset comprising KiDS-1000, BOSS DR12, and Planck CMB lensing/Integrated Sachs Wolfe (including all cross-correlations). We first assess internal consistency, finding a mild ($<2σ$) tension between CMB and low-$z$ datasets in the full parameter space and hints of systematics in Planck PR3 and KiDS-1000. We then derive constraints in $Λ\mathrm{CDM}$ and, motivated by recent DESI results, dynamical dark energy ($w_0w_a\mathrm{CDM}$) and free neutrino mass extensions. In $Λ\mathrm{CDM}$, we derive a novel $9\times2$pt constraint of $S8=0.777^{+0.17}_{-0.17}$ and find strong consistency among CMB datasets. In $w_0w_a\mathrm{CDM}$, adding low-$z$ to CMB+BAO tightens $(w_0,w_a)$ constraints by 50\% (in figure-of-merit terms) in our baseline combination of Planck PR4 + low-$z$ + BAO. The posterior accommodates a cosmological constant ($w_0 = -1, w_a = 0$) within $1σ$, in contrast to the $\sim2σ$ preference for evolving dark energy from CMB+BAO alone. For neutrino masses, our baseline dataset yields a systematics-robust constraint of $M_ν<0.12\mathrm{eV}$ in $νΛ\mathrm{CDM}$. Allowing dynamical dark energy and free neutrino mass ($νw_0w_a\mathrm{CDM}$) broadens and shifts the neutrino mass posterior higher, yielding a $1.8σ$ constraint ($M_ν=0.16^{+0.09}_{-0.09}\mathrm{eV}$) in our baseline. Our analysis demonstrates the power of multiprobe analyses for assessing tensions, identifying systematics and providing robust constraints.

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arXiv2025

Cross-correlation between soft X-rays and galaxies A new benchmark for galaxy evolution models

This article presents the construction and validation of complete stellar mass-selected, volume-limited galaxy samples using the Legacy Survey (data release 10) galaxy catalogs, covering $\sim16,800$ deg$^2$ of extra-galactic sky, and extending to redshift $z<0.35$. We measure the correlation function of these galaxies with tiny statistical uncertainties at the percent level and systematic uncertainties up to 5\%. A 4-parameter halo occupation distribution (HOD) model is fitted to retrieve the population of host halos, yielding results on the stellar to halo mass relation consistent with the current models of galaxy formation and evolution. Using these complete galaxy samples, we measure and analyze the cross-correlation (X-corr) between galaxies and all soft X-ray photons observed by SRG/eROSITA in the 0.5-2 keV band over $\sim13,000$ deg$^2$. The cross correlation measurements have unprecedented sub-percent statistical uncertainty and ~5-10\% systematic uncertainty. An extension to the halo model is introduced to interpret the X-corr, decomposing contributions from X-ray point sources, hot gas (CGM), satellites, and the 2-halo term. For low stellar mass thresholds ($\log M^*/M_{\odot}>$ 10, 10.25, 10.5), we find that the point source emission dominates the X-corr at small separation ($r<80$kpc). Then, in the range ($80 2$Mpc), the 2-halo term becomes dominant. Interestingly, there is no scale at which the CGM dominates. In the range ($20<r<200$kpc), the CGM contributes to more than 10\% of the signal. Progressively, with the minimum stellar mass increasing, the CGM emission increases. We constrain the $M_{500c}-L_X$ scaling relation slope, $1.629^{+0.091}_{-0.089}$, at the 5\% level using the samples with the lowest mass threshold.

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arXiv2025

Fast Projected Bispectra: the filter-square approach

The study of third-order statistics in large-scale structure analyses has been hampered by the increased complexity of bispectrum estimators (compared to power spectra), the large dimensionality of the data vector, and the difficulty in estimating its covariance matrix. In this paper we present the filtered-squared bispectrum (FSB), an estimator of the projected bispectrum effectively consisting of the cross-correlation between the square of a field filtered on a range of scales and the original field. Within this formalism, we are able to recycle much of the infrastructure built around power spectrum measurement to construct an estimator that is both fast and robust against mode-coupling effects caused by incomplete sky observations. Furthermore, we demonstrate that the existing techniques for the estimation of analytical power spectrum covariances can be used within this formalism to calculate the bispectrum covariance at very high accuracy, naturally accounting for the most relevant Gaussian and non-Gaussian contributions in a model-independent manner.

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arXiv2024

A 1% accurate method to include baryonic effects in galaxy-galaxy lensing models

Galaxy clustering and galaxy-galaxy lensing are two of the main observational probes in Stage-IV large-scale structure surveys. Unfortunately, the complicated relationship between galaxies and matter limits the exploitation of this data. Galaxy bias models -- such as the hybrid Lagrangian bias expansion -- allow describing galaxy clustering down to scales as small as $k = 0.7h$/Mpc. However, the galaxy-matter cross-power spectra are already affected by baryons on these scales, directly impacting the modelling of galaxy-galaxy lensing. We propose to extend models of the galaxy-matter cross-power spectrum $P_{\rm gm}(k)$ (currently only accounting for dark matter) by including a baryonic correction inferred from the matter component ($S_{\rm mm}(k)$), so that $P_{\rm gm, full \, physics} (k) = \sqrt{S_{\rm mm}} P_{\rm gm, gravity \, only}$. We use the FLAMINGO simulations to measure the effect of baryons on the galaxy-matter cross-power spectrum and to assess the performance of our model. We perform a Bayesian analysis of synthetic data, implementing a model based on BACCO's hybrid Lagrangian bias expansion (for the nonlinear galaxy bias) and Baryon Correction Model. Ignoring baryons in the galaxy-matter cross-power spectrum leads to a biased inference of the galaxy bias, while ignoring baryons in both the galaxy-matter and matter-matter power spectra leads to a biased inference of both the galaxy bias and cosmological parameters. In contrast, our method is 1% accurate compared to all physics variations in FLAMINGO and on all scales described by hybrid perturbative models ($k < 0.7h$/Mpc). Moreover, our model leads to inferred bias and cosmological parameters compatible within 1$σ$ with their reference values. We anticipate that our method will be a promising candidate for analysing forthcoming Stage-IV survey data.

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arXiv2024

Catalog-based pseudo-$C_\ell$s

We present a formalism to extract the angular power spectrum of fields sampled at a finite number of points with arbitrary positions -- a common situation for several catalog-based astrophysical probes -- through a simple extension of the standard pseudo-$C_\ell$ algorithm. A key complication in this case is the need to handle the shot noise component of the associated discrete angular mask which, for sparse catalogs, can lead to strong coupling between very different angular scales. We show that this problem can be solved easily by estimating this contribution analytically and subtracting it. The resulting estimator is immune to small-scale pixelization effects and aliasing, and, more interestingly, unbiased against the contribution from measurement noise uncorrelated between different sources. We demonstrate the validity of the method in the context of cosmic shear datasets, and showcase its usage in the case of other spin-0 and spin-1 astrophysical fields of interest. We incorporate the method in the public $\texttt{NaMaster}$ code (https://github.com/LSSTDESC/NaMaster).

astro-ph.CO↗

arXiv2023

$\mathbf{12\times2}$pt combined probes: pipeline, neutrino mass, and data compression

With the rapid advance of wide-field surveys it is increasingly important to perform combined cosmological probe analyses. We present a new pipeline for simulation-based multi-probe analyses, which combines tomographic large-scale structure (LSS) probes (weak lensing and galaxy clustering) with cosmic microwave background (CMB) primary and lensing data. These are combined at the $C_\ell$-level, yielding 12 distinct auto- and cross-correlations. The pipeline is based on $\texttt{UFalconv2}$, a framework to generate fast, self-consistent map-level realizations of cosmological probes from input lightcones, which is applied to the $\texttt{CosmoGridV1}$ N-body simulation suite. It includes a non-Gaussian simulation-based covariance for the LSS tracers, several data compression schemes, and a neural network emulator for accelerated theoretical predictions. We validate our framework, apply it to a simulated $12\times2$pt tomographic analysis of KiDS, BOSS, and $\textit{Planck}$, and forecast constraints for a $Λ$CDM model with a variable neutrino mass. We find that, while the neutrino mass constraints are driven by the CMB data, the addition of LSS data helps to break degeneracies and improves the constraint by up to 35%. For a fiducial $M_ν=0.15\mathrm{eV}$, a full combination of the above CMB+LSS data would enable a $3σ$ constraint on the neutrino mass. We explore data compression schemes and find that MOPED outperforms PCA. We also study the impact of an internal lensing tension in the CMB data, parametrized by $A_L$, on the neutrino mass constraint, finding that the addition of LSS to CMB data including all cross-correlations is able to mitigate the impact of this systematic. $\texttt{UFalconv2}$ and a MOPED compressed $\textit{Planck}$ CMB primary + CMB lensing likelihood are made publicly available. [abridged]

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