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Nora Elisa Chisari

Publications and source records attributed to Nora Elisa Chisari.

At least 19 recordsLinked to original sources

Fisher Forecasting for the DESC with $\texttt{Augur}$

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) has begun its ten-year survey of the entire visible southern hemisphere. To ensure robust cosmological measurements, computationally inexpensive investigations of modeling choices must be made to gauge the performance of proposed cosmological analyses. In this paper, we introduce the $\texttt{Augur}$ tool of the Dark Energy Science Collaboration (DESC), which provides Fisher forecasts for cosmological inference for the LSST using software frameworks designed for DESC science. We test the pipeline by comparing it to forecasts produced by external code and direct sampling of the posterior via nested sampling methods, finding good agreement between all methods. We additionally investigate a range of modeling and hyperparameter choices for a 3$\times$2pt investigation in harmonic space, providing users with diagnostics to obtain reliable forecasts. $\texttt{Augur}$ will be continually updated to be compatible with the other tools in the DESC software ecosystem as additional probes and functionality become available.

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Three-point intrinsic alignments of galaxies and haloes in the FLAMINGO simulations

Third-order statistics provide information beyond two-point measures, but extracting this information requires accurate and consistent modelling. We measure and detect the three-point correlation function and third-order aperture mass statistics of intrinsic alignments (IA) for galaxies and for haloes with $M_{\rm halo} > 10^{13}\,{\rm M}_\odot$ in the $(2.8\,\mathrm{Gpc})^3$ simulation volume of the FLAMINGO hydrodynamical simulation suite. We model the third-order aperture mass statistics and show that on large scales both the galaxy and halo samples are well described by the tree-level effective field theory (EFT) of IA across the three dark matter density-shape combinations and a wide range of triangle configurations, with the alignment amplitude consistent with that inferred from two-point statistics. We compare the full EFT to several other models: a version neglecting the velocity-shear term, the non-linear alignment model, and a reduced EFT assuming co-evolution relations that follow from the assumption that alignment is linear in Lagrangian space. The first two models yield biased constraints on the alignment amplitude, but the reduced EFT performs remarkably well, achieving a low reduced chi-squared and minimal bias. We examine the redshift and mass dependence of the higher-order bias parameters, finding that the linear Lagrangian bias assumption is approximately satisfied across the explored halo mass and redshift ranges for both galaxies and haloes. These co-evolution relations can be valuable for photometric shear surveys, where limited constraining power on IA parameters favours models with fewer free parameters.

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KiDS-Legacy: Constraining dark energy, neutrino mass, and curvature

We constrained minimally extended cosmological models with the cosmic shear analysis of the final data release from the Kilo-Degree Survey (KiDS-Legacy) in combination with external probes. Due to the consistency of the KiDS-Legacy analysis with the cosmic microwave background (CMB), we could combine these datasets reliably for the first time. Additionally, we used CMB lensing, galaxy redshift-space distortions, and baryon acoustic oscillations. We assessed, in turn, the effects of spatial curvature, varying neutrino masses, and an evolving dark energy component on cosmological constraints from KiDS-Legacy alone and from KiDS-Legacy combined with external probes. We find KiDS-Legacy to be consistent with the fiducial flat $Λ$-cold dark matter ($Λ$CDM) analysis with $c^2 \sum m_ν\leq 1.5\,$eV, $w_0 = -1.0\pm 0.7$, and $w_a = -1.3^{+1.9}_{-2.0}$ while $Ω_K = 0.08^{+0.16}_{-0.17}$ (1$σ$ bounds) with an almost equal goodness of fit. The $w_0w_a$CDM model is not a significant improvement over $Λ$CDM when cosmic shear and CMB lensing are combined, yielding a Bayes factor $B = 0.07$. If all probes are combined, however, $B$ increases to 2.73, corresponding to a $2.6σ$ suspiciousness tension. The constraint on $S_8 = σ_8\sqrt{Ω_\mathrm{m}/0.3}$ is robust to opening up the parameter space for cosmic shear. Adding all external datasets to KiDS-Legacy, we find $S_8 = 0.816 \pm 0.006$ in $Λ$CDM and $S_8 = 0.837 \pm 0.008$ in $w_0 w_a$CDM for all probes combined.

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Smokescreen: A Python package for data vector blinding and encryption in cosmological analyses

Smokescreen is an open-source Python library for data-vector concealment (blinding) in cosmological analyses. Data-vector blinding works by applying cosmology-dependent shifts to the observed data vector, moving it away from the true cosmological signal without affecting its statistical properties, so that analysts cannot infer the true result until the analysis is frozen and the blinding is lifted. The package computes these shifts using Firecrown likelihoods applied to data vectors stored in the SACC format, ensuring that the theoretical model used for blinding is identical to that used for inference whilst remaining agnostic to the specific observable being blinded. To prevent accidental unblinding, the original SACC file, containing the true cosmology, is encrypted. Although developed for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Smokescreen is applicable to any experiment using Firecrown likelihoods and the SACC data format.

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Inverting Fisher biases for fast systematics exploration

Upcoming cosmological surveys will achieve increasingly precise constraints in cosmological parameter estimation. To guarantee the robustness of cosmological analyses, it is essential to account for and model systematic effects that can bias cosmological constraints, shifting the best fit parameters away from their fiducial values. It is possible to approximately infer the biases that un-modelled systematic effects might introduce in cosmological parameter estimation by means of the Fisher matrix formalism. In this paper, we introduce a new application of this formalism, where by inverting the process, we investigate whether a specific missing or mis-modelled systematic effect can explain away a given tension between two different probes or experiments. We showcase the proposed methodology by examining two representative systematics: galaxy intrinsic alignments and baryonic feedback. As the method is agnostic to the systematic effect and can be applied to a wider range of scenarios, we discuss more possible future applications. While the proposed approach is accurate in the limit of small offsets in the cosmological parameters, where the likelihood can be considered linear in both the cosmological parameters and the systematics, in practice, the region of validity depends on the systematic effect. In general, even beyond this region, the approach still provides a useful test that helps indicate the magnitude and direction of potential biases from systematic effects in data.

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$X+y$: insights on gas thermodynamics from the combination of X-ray and thermal Sunyaev-Zel'dovich data cross-correlated with cosmic shear

We measure the cross-correlation between cosmic shear from the third-year release of the Dark Energy Survey, thermal Sunyaev-Zel'dovich (tSZ) maps from Planck, and X-ray maps from ROSAT. We investigate the possibility of developing a physical model able to jointly describe both measurements, simultaneously constraining the spatial distribution and thermodynamic properties of hot gas. We find that a relatively simple model is able to describe both sets of measurements and to make reasonably accurate predictions for other observables (the tSZ auto-correlation, its cross-correlation with X-rays, and tomographic measurements of the bias-weighted mean gas pressure). We show, however, that contamination from X-ray AGN, as well as the impact of non-thermal pressure support, must be incorporated in order to fully resolve tensions in parameter space between different data combinations. We obtain simultaneous constraints on the mass scale at which half of the gas content has been expelled from the halo, $\mathrm{log}_{10}(M_c)=14.83^{+0.16}_{-0.23}$, on the polytropic index of the gas, $Γ=1.144^{+0.016}_{-0.013}$, and on the ratio of the central gas temperature to the virial temperature $α_T=1.30^{+0.15}_{-0.28}$.

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Intrinsic alignments of galaxies in multiple projections

Intrinsic alignments of galaxies are measured and modelled to gain cosmological information, to further understand the interactions between galaxies and to mitigate their effects on gravitational weak lensing studies. Hydrodynamical simulations are often used to constrain priors or calibrate models. Therefore, obtaining the maximum amount of information possible from these simulations is imperative. In this work, we have combined the information of shapes projected over two or three axes ($x,y,z$), for intrinsic alignment signals ($w_{g+},\ \tildeξ_{g+,2}$), showing a consistent gain in signal-to-noise ratio (SNR) for all cases studied using TNG300-1. The gain in SNR is found to be higher for the addition of the second projection than for the third, and higher for shapes calculated using the reduced inertia tensor rather than the simple one. The two shape samples studied, $n_\star>300$ and $\mathrm{log}(M_\star \ h/\mathrm{M_\odot})>10.5$, where the latter has a much higher signal amplitude, show similar gains in SNR when more projections are added. We also model the correlation functions with the non-linear alignment model. The SNR gains from the measurements are higher but consistent with the constraints on the non-linear alignment amplitude $A_{\rm IA}$ and galaxy bias $b_{\rm g}$. Using multiple projection axes increases SNR overall, enabling more efficient use of numerically expensive hydrodynamical simulations.

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Rapid cosmological inference with the two-loop matter power spectrum

We compute the two-loop effective field theory (EFT) power spectrum of dark matter density fluctuations in $Λ$CDM using the recently proposed COBRA method (Bakx. et al, 2025). With COBRA, we are able to evaluate the two-loop matter power spectrum in $\sim 1$ millisecond at $ \sim 0.1 \%$ precision on one CPU for arbitrary redshifts and on scales where perturbation theory applies. As an application, we use the nonlinear matter power spectrum from the Dark Sky simulation to assess the performance of the two-loop EFT power spectrum compared to the one-loop EFT power spectrum at $z=0$. We find that, for volumes typical for Stage IV galaxy surveys, $V = 25 \,(\text{Gpc}/h)^3$, the two-loop EFT can provide unbiased cosmological constraints on $Ω_m,H_0$ and $A_s$ using scales up to $k_\text{max}=0.26\, h/\text{Mpc}$, thereby outperforming the constraints from the one-loop EFT ($k_\text{max}=0.11\, h/\text{Mpc}$). The Figure of Merit on these three parameters increases by a factor $\sim 2.6$ and the one-dimensional marginalized constraints improve by $\sim35\%$ for $Ω_m$, $\sim20\%$ for $H_0$ and $\sim 15\%$ for $A_s$.

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Imaging systematics induced by galaxy sub-sample fluctuation: new systematics at second order

Imaging systematics refers to the inhomogeneous distribution of a galaxy sample caused by varying observing conditions and astrophysical foregrounds. Current mitigation methods correct the galaxy density fluctuations caused by imaging systematics assuming that all galaxies in a sample have the same galaxy density fluctuations. Under this assumption, the corrected sample cannot perfectly recover the true correlation function. We name this effect sub-sample systematics. For a galaxy sample, even if its overall sample statistics (redshift distribution n(z), galaxy bias b(z)), are accurately measured, n(z), b(z) can still vary across the observed footprint. It makes the correlation function amplitude of galaxy clustering higher, while correlation functions for galaxy-galaxy lensing and cosmic shear do not have noticeable change. Such a combination could potentially degenerate with physical signals on small angular scales, such as the amplitude of galaxy clustering, the impact of neutrino mass on the matter power spectrum, etc. Sub-sample systematics cannot be corrected using imaging systematics mitigation approaches that rely on the cross-correlation signal between imaging systematics maps and the observed galaxy density field. In this paper, we derive formulated expressions of sub-sample systematics, demonstrating its fundamental difference with other imaging systematics. We also provide several toy models to visualize this effect. Finally, we discuss a potential method to estimate and mitigate sub-sample systematics by forward modeling its behavior using Synthetic Source Injection.

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The Bispectrum of Intrinsic Alignments: II. Precision Comparison Against Dark Matter Simulations

We measure three-dimensional bispectra of halo intrinsic alignments (IA) and dark matter overdensities in real space from N-body simulations for halos of mass $10^{12}-10^{12.5} M_\odot /h$. We show that their multipoles with respect to the line of sight can be accurately described by a tree-level perturbation theory model on large scales ($k\lesssim 0.11\,h$/Mpc) at $z=0$. For these scales and in a simulation volume of 1 (Gpc/$h)^3$, we detect the bispectrum monopole $B_{δδE}^{00}$ at SNR $\sim 30$ and the two quadrupoles $B_{δδE}^{11}$ and $B_{δδE}^{20}$ at SNR $\sim 25$ and SNR $\sim 15$, respectively. We also report similar SNR for the lowest order multipoles of $B_{δEE}$ and $B_{EEE}$, although these are largely driven by stochastic contributions. We show that the first and second order EFT parameters are consistent with those obtained from fitting the IA power spectrum analysis at next-to-leading order, without requiring any priors to break degeneracies for the quadratic bias parameters. Moreover, the inclusion of higher multipole moments of $B_{δδE}$ greatly reduces the errors on second order bias parameters, by factors of 5 or more. The IA bispectrum thus provides an effective means of determining higher order shape bias parameters, thereby characterizing the scale dependence of the IA signal. We also detect parity-odd bispectra such as $B_{δδB}$ and $B_{δEB}$ at $\sim 10 σ$ significance or more for $k<0.15\,h$/Mpc and they are consistent with the parity-even sector. Furthermore, we check that the Gaussian covariance approximation works reasonably well on the scales we consider here. These results lay the groundwork for using the bispectrum of IA in cosmological analyses.

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A rising tide: Intrinsic alignments since the turn of the millennium

The alignments of galaxies across the large-scale structure of the Universe are known to be a source of contamination for gravitational lensing, but they can also probe cosmology and the physics of galaxy evolution in many ways. In this review, I cover developments in our understanding of intrinsic alignments over the past 25 years on: (1) different approaches to model intrinsic alignments across a range of scales, (2) existing observational constraints, (3) predictions from cosmological numerical $N$-body and hydrodynamical simulations, (4) mitigation strategies to account for their contamination to lensing observables and (5) cosmological and astrophysical applications. While the review focuses mostly on two-point statistics of intrinsic alignments, I also give a summary of other statistics beyond two-point. Finally, I point out some of the open problems hindering the understanding or application of intrinsic alignments and how they might be overcome in the future.

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KiDS-Legacy: Cosmological constraints from cosmic shear with the complete Kilo-Degree Survey

We present cosmic shear constraints from the completed Kilo-Degree Survey (KiDS), where the cosmological parameter $S_8\equivσ_8\sqrt{Ω_{\rm m}/0.3} = 0.815^{+0.016}_{-0.021}$, is found to be in agreement ($0.73σ$) with results from the Planck Legacy cosmic microwave background experiment. The final KiDS footprint spans $1347$ square degrees of deep nine-band imaging across the optical and near-infrared, along with an extra $23$ square degrees of KiDS-like calibration observations of deep spectroscopic surveys. Improvements in our redshift distribution estimation methodology, combined with our enhanced calibration data and multi-band image simulations, allow us to extend our lensed sample out to a photometric redshift of $z_{\rm B}\leq2.0$. Compared to previous KiDS analyses, the increased survey area and redshift depth results in a $\sim32\%$ improvement in constraining power in terms of $Σ_8\equivσ_8\left(Ω_{\rm m}/0.3\right)^α= 0.821^{+0.014}_{-0.016}$, where $α= 0.58$ has been optimised to match the revised degeneracy direction of $σ_8$ and $Ω_{\rm m}$. We adopt a new physically motivated intrinsic alignment model that depends jointly on the galaxy sample's halo mass and spectral type distributions, and that is informed by previous direct alignment measurements. We also marginalise over our uncertainty on the impact of baryon feedback on the non-linear matter power spectrum. Comparing to previous KiDS analyses, we conclude that the increase seen in $S_8$ primarily results from our improved redshift distribution estimation and calibration, as well as new survey area and improved image reduction. Our companion paper Stölzner et al. (submitted) presents a full suite of internal and external consistency tests, finding the KiDS-Legacy data set to be the most internally robust sample produced by KiDS to date.

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KiDS-Legacy: Redshift distributions and their calibration

We present the redshift calibration methodology and bias estimates for the cosmic shear analysis of the fifth and final data release (DR5) of the Kilo-Degree Survey (KiDS). KiDS-DR5 includes a greatly expanded compilation of calibrating spectra, drawn from $27$ square degrees of dedicated optical and near-IR imaging taken over deep spectroscopic fields. The redshift distribution calibration leverages a range of new methods and updated simulations to produce the most precise $N(z)$ bias estimates used by KiDS to date. Improvements to our colour-based redshift distribution measurement method (SOM) mean that we are able to use many more sources per tomographic bin for our cosmological analyses, and better estimate the representation of our source sample given the available spec-$z$. We validate our colour-based redshift distribution estimates with spectroscopic cross-correlations (CC). We find that improvements to our cross-correlation redshift distribution measurement methods mean that redshift distribution biases estimated between the SOM and CC methods are fully consistent on simulations, and the data calibration is consistent to better than $2σ$ in all tomographic bins.

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KiDS-Legacy: Consistency of cosmic shear measurements and joint cosmological constraints with external probes

We present a cosmic shear consistency analysis of the final data release from the Kilo-Degree Survey (KiDS-Legacy). By adopting three tiers of consistency metrics, we compare cosmological constraints between subsets of the KiDS-Legacy dataset split by redshift, angular scale, galaxy colour and spatial region. We also review a range of two-point cosmic shear statistics. With the data passing all our consistency metric tests, we demonstrate that KiDS-Legacy is the most internally consistent KiDS catalogue to date. In a joint cosmological analysis of KiDS-Legacy and DES Y3 cosmic shear, combined with data from the Pantheon+ Type Ia supernovae compilation and baryon acoustic oscillations from DESI Y1, we find constraints consistent with Planck measurements of the cosmic microwave background with $S_8\equiv σ_8\sqrt{Ω_{\rm m}/0.3} = 0.814^{+0.011}_{-0.012}$ and $σ_8 = 0.802^{+0.022}_{-0.018}$.

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The Bispectrum of Intrinsic Alignments: Theory Modelling and Forecasts for Stage IV Galaxy Surveys

We present a complete treatment of the bispectrum of intrinsic alignments, both in three spatial dimensions and in projection in the flat-sky approximation. Since intrinsic alignment is a spin-2 observable, the bispectrum of intrinsic alignments contains a parity-even and a parity-odd part, the latter being nonzero even in the absence of parity violation. Moreover, all possible combinations of scalar, E- and B-mode bispectra are nonzero in the absence of parity violation. In analogy to the galaxy bispectrum in redshift space, we construct a complete set of multipoles for anisotropic bispectra of projected spin-2 fields. We then construct separable bispectrum estimators, both for parity-even and parity-odd bispectra, which can be computed by means of Fast Fourier Transforms (FFTs). We compare several different choices of angular weighting in terms of signal-to-noise ratios (SNR) for a Stage IV setup using luminous red galaxies (LRGs) from the Dark Energy Spectroscopic Instrument (DESI) with galaxy shapes measured by the Legacy Survey of Space and Time (LSST). Assuming an overlapping area of $\sim 4,000$ square degrees (yielding $\sim 1.3$ million LRGs) and including scales up to $k_\text{max} = 0.14\,h$/Mpc, we find that the position-position-E-mode bispectrum $B_{DDE}$ (which is parity-even) can be strongly detected at SNR $\sim 30$, while detecting parity-odd bispectra (such as $B_{DDB}$, SNR $\sim 5$) or bispectra with more than one shape field (such as $B_{DEE}$, SNR $\sim 5$) may also be possible.

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KiDS-Legacy: Covariance validation and the unified OneCovariance framework for projected large-scale structure observables

We introduce OneCovariance, an open-source software designed to accurately compute covariance matrices for an arbitrary set of two-point summary statistics across a variety of large-scale structure tracers. Utilising the halo model, we estimated the statistical properties of matter and biased tracer fields, incorporating all Gaussian, non-Gaussian, and super-sample covariance terms. The flexible configuration permits user-specific parameters, such as the complexity of survey geometry, the halo occupation distribution employed to define each galaxy sample, or the form of the real-space and/or Fourier space statistics to be analysed. We illustrate the capabilities of OneCovariance within the context of a cosmic shear analysis of the final data release of the Kilo-Degree Survey (KiDS-Legacy). Upon comparing our estimated covariance with measurements from mock data and calculations from independent software, we ascertain that OneCovariance achieves accuracy at the per cent level. When assessing the impact of ignoring complex survey geometry in the cosmic shear covariance computation, we discover misestimations at approximately the $10\%$ level for cosmic variance terms. Nonetheless, these discrepancies do not significantly affect the KiDS-Legacy recovery of cosmological parameters. We derive the cross-covariance between real-space correlation functions, bandpowers, and COSEBIs, facilitating future consistency tests among these three cosmic shear statistics. Additionally, we calculate the covariance matrix of photometric-spectroscopic galaxy clustering measurements, validating the jackknife covariance estimates for calibrating KiDS-Legacy redshift distributions. The OneCovariance can be found on GitHub, together with comprehensive documentation and examples.

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Intrinsic galaxy alignments in the KiDS-1000 bright sample: dependence on colour, luminosity, morphology, and galaxy scale

The intrinsic alignment (IA) of galaxies is a major astrophysical contaminant to weak gravitational lensing measurements, and the study of its dependence on galaxy properties helps provide meaningful physical priors that aid cosmological analyses. This work studied for the first time the dependence of IA on galaxy structural parameters. We measured the IA of bright galaxies, selected on apparent r-band magnitude r<20, in the Kilo-Degree Survey (KiDS). Machine-learning-based photometric redshift estimates are available for this galaxy sample that helped us obtain a clean measurement of its IA signal. We supplemented this sample with a catalogue of structural parameters from Sersic profile fits to the surface-brightness profiles of the galaxies. We split the sample on galaxy intrinsic colour, luminosity, and Sersic index, and we fitted the non-linear linear alignment model to galaxy position-shape projected correlation function measurements on large scales. We observe a power-law luminosity dependence of the large-scale IA amplitude, $A_{IA}$, for both the red and high-Sersic-index ($n_s>2.5$) samples, and find no significant difference between the two. We measure an $\sim1.5σ$ lower $A_{IA}$ for red galaxies that also have a Sersic index of $n_s<4$ compared to the expected amplitude predicted using the sample's luminosity. We also probe the IA of red galaxies as a function of galaxy scale by varying the radial weight employed in the shape measurement. On large scales (above 6 Mpc/$h$), we do not detect a significant difference in the alignment. On smaller scales, we observe that IA increase with galaxy scale, with outer galaxy regions showing stronger alignments than inner regions. Finally, for intrinsically blue galaxies, we find $A_{IA}=-0.67\pm1.00$, which is consistent with previous works, and we find IA to be consistent with zero for the low-Sersic-index ($n_s<2.5$) sample.

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COBRA: Optimal Factorization of Cosmological Observables

We introduce COBRA (Cosmology with Optimally factorized Bases of Radial Approximants), a novel framework for rapid computation of large-scale structure observables. COBRA separates scale dependence from cosmological parameters in the linear matter power spectrum while also minimising the number of necessary basis terms $N_b$, thus enabling direct and efficient computation of derived and nonlinear observables. Moreover, the dependence on cosmological parameters is efficiently approximated using radial basis function interpolation. We apply our framework to decompose the linear matter power spectrum in the standard $Λ$CDM scenario, as well as by adding curvature, dynamical dark energy and massive neutrinos, covering all redshifts relevant for Stage IV surveys. With only a dozen basis terms $N_b$, COBRA reproduces exact Boltzmann solver calculations to $\sim 0.1\%$ precision, which improves further to $0.02\%$ in the pure $Λ$CDM scenario. Using our decomposition, we recast the one-loop redshift space galaxy power spectrum in a separable minimal-basis form, enabling $\sim 4000$ model evaluations per second at $0.02\%$ precision on a single thread. This constitutes a considerable improvement over previously existing methods (e.g., FFTLog) opening a window for efficient computations of higher loop and higher order correlators involving multiple powers of the linear matter power spectra. The resulting factorisation can also be utilised in clustering, weak lensing and CMB analyses. Our implementation will be made public upon publication.

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