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Alice Pisani

Publications and source records attributed to Alice Pisani.

At least 19 recordsLinked to original sources

Towards precision cosmology with Void x CMB correlations (II): Impact of mock catalogs on the Void x CMB lensing signal

Gravitational lensing by large-scale structure imprints secondary anisotropies on the Cosmic Microwave Background (CMB) that can be exploited to probe cosmology. In particular, cosmic voids produce a characteristic lensing signature detectable through Void x CMB cross-correlations. This signal has been robustly measured in the past but its cosmological constraining power remains limited by the incomplete knowledge of how methodological choices affect its measurement and by its uncertain dependence on cosmological parameters. Using a set of validated Roman mock catalogs, we first quantify how mock construction impacts the measured signal and then forecast the capabilities of Roman, in combination with current and upcoming CMB surveys such as Planck, SO and CMB-S4-like experiments. We analyze the signal-to-noise ratio (S/N) for different void definitions (2D and 3D), stacking approaches (rescaled versus non-rescaled profiles), CMB map filtering schemes and noise levels. In contrast to galaxy and void statistics, we find that the Void x CMB lensing signal is less sensitive to the choice of mock catalog, indicating that future tensions with data are unlikely to stem from mock inaccuracies alone. The highest S/N is achieved for 2D voids with rescaled profiles. We forecast S/N ~13$\sigma$ (8$\sigma$) for 2D (3D) Roman voids combined with Planck, increasing to 22$\sigma$ (13$\sigma$) for SO and 31$\sigma$ (18$\sigma$) for CMB-S4-like surveys. While the cosmological dependence of this observable remains to be quantified, Roman together with next-generation of LSS and CMB surveys opens a path toward the first direct cosmological constraints from Void x CMB lensing.

astro-ph.CO

Baryons in the Darkest Sites of the Universe

The pristine underdense patches of the Universe, cosmic voids, are powerful cosmological laboratories, uniquely sensitive to dark energy, modified gravity, and neutrino masses, yet their baryonic content remains uncharacterized. We present the first observational constraint on baryon underdensity in void interiors, exploiting the dispersion measures (DMs) of Fast Radio Bursts (FRBs) as tracers of the free electron column, independent of gas phase, temperature, and metallicity. By stacking 3,455 sightlines from CHIME/FRB on 1,288 SDSS BOSS voids over redshifts $0.2 < z < 0.7$, we measure a DM deficit toward void centers at $3.2\sigma$ significance, establishing that diffuse baryons inhabit the emptiest corners of the cosmic web at a suppressed level. The measured signal amplitude is consistent with an effective Universe model built directly from the observed galaxy underdensity in these voids, and a baryonic model calibrated to the FRB DM-redshift relation ($\alpha_v = 1.80 \pm 0.87$). A uniform-density void model yields an electron density contrast of $\delta_\mathrm{e,v} = -0.58 \pm 0.30$, implying a $\sim 60$% underdensity of baryons in void interiors relative to the cosmic mean. Jointly interpreting our FRB measurement with existing stacks of the thermal Sunyaev-Zel'dovich effect on voids further constrains the mean void gas temperature to $T_\mathrm{e} \lesssim (1.1 \pm 0.7) \times 10^6$ K, pointing to a warm-hot diffuse phase, consistent with hydrodynamical simulation predictions. With forthcoming FRB (CHORD, DSA, SKA) and galaxy (DESI, LSST, Euclid, PFS-Subaru, SPHEREx, Roman) surveys, set to expand both samples by orders of magnitude, this approach opens a new window onto tomographic baryon mapping, with direct implications for feedback models governing gas expulsion into low-density environments, and for the use of cosmic voids to extract cosmological constraints.

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Setting SAIL: Leveraging Scientist-AI-Loops for Rigorous Visualization Tools

Scientists across all disciplines share a common challenge: the divide between their theoretical knowledge and the specialized skills and time needed to build interactive tools to communicate this expertise. While large language models (LLMs) offer unparalleled acceleration in code generation, they frequently prioritize functional syntax over scientific accuracy, risking visually convincing but scientifically invalid results. This work advocates the Scientist-AI-Loop (SAIL), a framework designed to harness this speed without compromising rigor. By separating domain logic from code syntax, SAIL enables researchers to maintain strict oversight of scientific concepts and constraints while delegating code implementation to AI. We illustrate this approach through two open-source, browser-based astrophysics tools: an interactive gravitational lensing visualization and a large-scale structure formation sandbox, both publicly available. Our methodology condensed development to mere days while maintaining scientific integrity. We specifically address failure modes where AI-generated code neglects phenomenological boundaries or scientific validity. While cautioning that research-grade code requires stringent protocols, we demonstrate through two examples that SAIL provides an effective code generation workflow for outreach, teaching, professional presentations, and early-stage research prototyping. This framework contributes to a foundation for the further development of AI-assisted scientific software.

astro-ph.IM

The era of precision cosmology with voids

Cosmic voids, the large underdense regions of our Universe, have emerged over the past decade as powerful cosmological laboratories: their simple dynamics, sensitivity to local gravitational effects and cosmic expansion, and ability to span large volumes, make them uniquely suited to test fundamental physics. Fueled by advances in theory, simulations, and observations, void science has matured into a precision tool for constraining the parameters of the standard cosmological model and its possible extensions. In this review, we provide a comprehensive description of the statistical tools developed to characterize voids, the theoretical models that link them to cosmological parameters, and the methodologies used to extract information from survey data. We highlight the growing synergy between void-based observables and other cosmological probes, and showcase the increasingly stringent constraints derived from voids measured from current survey data and expected from future missions. With the advent of the next generation of galaxy surveys, voids are poised to play a central role in the future of cosmology, turning what was once regarded as emptiness into one of the most promising frontiers of fundamental science.

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Towards precision cosmology with Voids x CMB correlations (I): Roman-Agora mock catalogs and pipeline validation

We construct and validate a set of multi-purpose mock galaxy catalogs designed to capture, to different degrees of accuracy, the main characteristics of the Nancy Grace Roman Space Telescope survey. These catalogs provide a foundation for void statistics and various CMB cross-correlation analyses. Our approach differs from traditional halo occupation or abundance matching methods by directly translating a reference mock catalog -- containing basic properties of the host halos -- into a new simulation (in our case Agora). This technique, which we call analog matching, assigns a halo counterpart in the new simulation to each reference galaxy through a nearest-neighbor search in a multi-dimensional parameter space. This space can include halo mass, environmental measures and other galaxy-specific attributes. By varying the composition of this parameter vector, we can generate catalogs of differing complexity and test how galaxy-halo prescriptions influence LSS statistics and CMB-related observables. We find that analog matching based on halo mass alone, or halo mass and galaxy-type indicators, successfully reproduces the expected Roman emission-line galaxy statistics. We also show that reproducing two-dimensional galaxy clustering does not guarantee consistent void properties. Our results highlight the importance of matching void statistics for improved mock accuracy, and demonstrate that measuring voids provides independent and sensitive constraints on galaxy-halo connections beyond the matter power spectrum. An important by-product of our setup is that it is fully general and can be applied to any combination of simulation and reference catalog, provided that the desired parameter space for both is specified. The resulting Roman-Agora mock catalogs offer a versatile resource for LSS x CMB studies and a benchmark for assessing the impact of mock accuracy on cosmological observables.

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Why Cosmic Voids Matter: Pristine Evolution

We utilize the Magneticum suite of hydrodynamical simulations to investigate the formation and evolution of cosmic voids from $z = 5.04$ to present day, using cold dark matter and (sub-) halo tracers in high-density samples. This includes the evolution of their global properties, such as size, shape, inner density, and average density, as well as their radial density profiles. Our results provide several key conclusions for void analyses in modern surveys. We demonstrate that a relative size framework is required, mitigating methodological selection effects and revealing the true physical evolution of densities around halo-defined voids. This necessity arises from our findings that a void's properties are more fundamentally tied to its rank within its contemporary population than to its absolute size. Using this framework, we show that the evolution of halo voids stabilizes at redshifts below $z \simeq 1$, driven primarily by cosmic expansion rather than ongoing halo formation. We further find that the matter evolution around these stable voids is remarkably well-described by linear growth theory, with deviations appearing as non-linear growth on small scales and suppressed growth in the largest voids, potentially driven by the influence of dark energy. This late-time stability and the predictable evolution confirm voids as pristine laboratories for probing the nature of dark energy with upcoming surveys.

astro-ph.CO

Multiprobe cosmology forecasts from halo-occupation-distribution-based forward modeling of galaxy and void statistics

The large under-dense regions in the cosmological matter density field, known as cosmic voids, are powerful probes of cosmology but their potential is currently under-exploited. Observationally, voids are identified within the large scale distribution of galaxies and are therefore sensitive to certain features of the galaxy-halo connection. This sensitivity makes the combination of void and galaxy summary statistics particularly powerful probes of both cosmology and the galaxy-halo connection through self-calibration of the void-galaxy relation. In particular the combination of void and galaxy summary statistics breaks degeneracies in the galaxy-halo connection and cosmology relative to the case of galaxy clustering alone. To demonstrate this we forecast cosmological constraints attainable from the combination of the void size function $n_v$, projected void-galaxy cross-correlation function $w_{p,vg}$ and projected galaxy auto-correlation function $w_{p,gg}$ measured in Dark Energy Spectroscopic Instrument (DESI) Year 5 data. We use a grid of cosmological N-body simulations to model this datavector as a function of $\sigma_8$, $\Omega_m$ and a flexible halo occupation distribution (HOD) model that includes central and satellite galaxy assembly bias. For our fiducial scenario combining $n_v$, $w_{p,vg}$ and $w_{p,gg}$ we forecast $1.5\%$ and $0.8\%$ constraints on $\Omega_m$ and $\sigma_8$ from DESI-Y5 data. We also forecast constraints from the combination of the void size function and stacked weak lensing signal of voids.

astro-ph.CO

The CosmoVerse White Paper: Addressing observational tensions in cosmology with systematics and fundamental physics

The standard model of cosmology has provided a good phenomenological description of a wide range of observations both at astrophysical and cosmological scales for several decades. This concordance model is constructed by a universal cosmological constant and supported by a matter sector described by the standard model of particle physics and a cold dark matter contribution, as well as very early-time inflationary physics, and underpinned by gravitation through general relativity. There have always been open questions about the soundness of the foundations of the standard model. However, recent years have shown that there may also be questions from the observational sector with the emergence of differences between certain cosmological probes. In this White Paper, we identify the key objectives that need to be addressed over the coming decade together with the core science projects that aim to meet these challenges. These discordances primarily rest on the divergence in the measurement of core cosmological parameters with varying levels of statistical confidence. These possible statistical tensions may be partially accounted for by systematics in various measurements or cosmological probes but there is also a growing indication of potential new physics beyond the standard model. After reviewing the principal probes used in the measurement of cosmological parameters, as well as potential systematics, we discuss the most promising array of potential new physics that may be observable in upcoming surveys. We also discuss the growing set of novel data analysis approaches that go beyond traditional methods to test physical models. [Abridged]

astro-ph.CO

Much Ado About Nothing: Galaxy Formation and Galactic Outflows in Cosmic Voids

We present a theoretical framework for calculating the volume filling fraction of galactic outflows in cosmic voids by integrating analytical models for the halo mass function (HMF), the halo occupation fraction, the stellar mass-halo mass relation, and outflow sizes. Using RAMSES, we perform a hydrodynamical zoom-in simulation of the central 25 cMpc/h region of a spherical void, identified as the lowest-density region among 1,000 random spheres in a parent 1 Gpc box simulation. This void has a diameter of 120 cMpc/h and a density contrast of $\delta \simeq -0.8$. We find that the properties of void galaxies remain stable when expanding the zoom-in region to 50 cMpc/h, though our relatively low mass resolution impacts the results. Our higher-resolution simulation aligns with the analytical HMF that accounts for the void's underdensity and size. While higher resolution improves stellar mass estimates for low-mass halos, computational constraints necessitate a theoretical framework that enables extrapolation to infinite resolution. Our analytical model, calibrated to our simulations, enables extrapolation down to the filtering mass of star-forming halos. To compare galaxy properties in this void with those in the field, we conduct a companion field simulation of the same box size. At infinite resolution, we predict wind volume filling fractions of $18.6\%$ in the field and $3.1\%$ in our void, with values dependent on cosmic variance, void size, and underdensity. Dwarf galaxies contribute minimally, and resolving halos to $M_{\rm h}=10^{10} M_\odot$ suffices for robust estimates. Applying our framework to the Local Group void ($\delta \simeq -0.5$, $R=20\ \mathrm{cMpc}$), we predict a wind volume filling fraction of $9.6\%\pm3.3\%$.

astro-ph.GA

Cosmology with voids from the Nancy Grace Roman Space Telescope

We provide an accurate forecast of the expected constraining power from the main void statistics -- the void size function and the void-galaxy cross-correlation function -- to be measured by the Roman reference High Latitude Spectroscopic Survey from the Nancy Grace Roman Space Telescope. Relying on a realistic galaxy mock lightcone, covering 2000 square degrees, we find more than $8\times 10^4 $ voids and explore their constraining power in the framework of three different cosmological models: $\Lambda$CDM, $w$CDM, and $w_0 w_{\rm a}$CDM. This work confirms the strong complementarity of different void statistics and showcases the constraining power to be expected from Roman voids thanks to the combination of its high tracer density and large observed volume.

astro-ph.CO

Significance of void shape: Neutrino mass from Voronoi void halos?

Massive neutrinos suppress the growth of cosmic structure on nonlinear scales, motivating the use of information beyond the power spectrum to tighten constraints on the neutrino mass, for example by considering cosmic voids. It was recently proposed that constraints on neutrino mass from the halo mass function (HMF) can be improved by considering only the halos that reside within voids -- the void-halo mass function (VHMF). We extend this analysis, which made spherical assumptions about the shape of voids, to take into account the non-spherical nature of voids as defined by the Voronoi-tessellation-based void finder, VIDE. In turn, after accounting for one spurious non-spherical void, we find no evidence that the VHMF contains information beyond the HMF. Given this finding, we then introduce a novel summary statistic by splitting halos according to the emptiness of their individual environments, defined by the Voronoi cell volume each halo resides in, and combining the mass functions from each split. We name the corresponding statistic the VorHMF and find that it could provide information regarding neutrino mass beyond the HMF. Our work thus motivates the importance of accounting for the full shape of voids in future analyses, both in terms of removing outliers to achieve robust results and as an additional source of cosmological information.

astro-ph.CO

Cosmology from one galaxy in a void?

Understanding galaxy properties may be the key to unlocking some of the most intriguing mysteries of modern cosmology. Recent work relied on machine learning to extract cosmological constraints on $\Omega_\mathrm{m}$ using only one galaxy. But if this is true, how should we select the galaxy to use for cosmology inference? In this paper, we consider selecting a galaxy that lies in cosmic voids, the underdense regions of the cosmic web, and compare the constraints obtained with the ones obtained when randomly selecting a galaxy in the whole sample. We use the IllustrisTNG galaxy catalog from the CAMELS project and the VIDE void finder to identify galaxies inside voids. We show that void galaxies provide stronger constraints on $\Omega_\mathrm{m}$ compared to randomly selected galaxies. This result suggests that the distinctive characteristics of void galaxies may provide a cleaner and more effective environment for extracting cosmological information.

astro-ph.CO

A Parameter-Masked Mock Data Challenge for Beyond-Two-Point Galaxy Clustering Statistics

The last few years have seen the emergence of a wide array of novel techniques for analyzing high-precision data from upcoming galaxy surveys, which aim to extend the statistical analysis of galaxy clustering data beyond the linear regime and the canonical two-point (2pt) statistics. We test and benchmark some of these new techniques in a community data challenge "Beyond-2pt", initiated during the Aspen 2022 Summer Program "Large-Scale Structure Cosmology beyond 2-Point Statistics," whose first round of results we present here. The challenge dataset consists of high-precision mock galaxy catalogs for clustering in real space, redshift space, and on a light cone. Participants in the challenge have developed end-to-end pipelines to analyze mock catalogs and extract unknown ("masked") cosmological parameters of the underlying $\Lambda$CDM models with their methods. The methods represented are density-split clustering, nearest neighbor statistics, BACCO power spectrum emulator, void statistics, LEFTfield field-level inference using effective field theory (EFT), and joint power spectrum and bispectrum analyses using both EFT and simulation-based inference. In this work, we review the results of the challenge, focusing on problems solved, lessons learned, and future research needed to perfect the emerging beyond-2pt approaches. The unbiased parameter recovery demonstrated in this challenge by multiple statistics and the associated modeling and inference frameworks supports the credibility of cosmology constraints from these methods. The challenge data set is publicly available and we welcome future submissions from methods that are not yet represented.

astro-ph.CO

The universal multiplicity function: counting halos and voids

We present a novel combination of the excursion-set approach with the peak theory formalism in Lagrangian space and provide accurate predictions for halo and void statistics over a wide range of scales. The set-up is based on an effective moving barrier. Besides deriving the corresponding numerical multiplicity function, we introduce a new analytical formula reaching the percent level agreement with the exact numerical solution obtained via Monte Carlo realizations down to small scales, $\sim 10^{12} h^{-1}\mathrm{M_\odot}$. In the void case, we derive the dependence of the effective moving barrier on the void formation threshold, $\delta_{\rm v}$, by comparison against the Lagrangian void size function measured in the Dark Energy and Massive Neutrinos Universe simulations. We discuss the mapping from Lagrangian to Eulerian space for both halos and voids; adopting the spherical symmetry approximation, we obtain a strong agreement at intermediate and large scales. Finally, using the effective moving barrier, we derive Lagrangian void density profiles accurately matching measurements from cosmological simulations, a major achievement towards using void profiles for precision cosmology with the next generation of galaxy surveys.

astro-ph.CO

Neutrino mass constraint from an Implicit Likelihood Analysis of BOSS voids

Cosmic voids identified in the spatial distribution of galaxies provide complementary information to two-point statistics. In particular, constraints on the neutrino mass sum, $\sum m_\nu$, promise to benefit from the inclusion of void statistics. We perform inference on the CMASS NGC sample of SDSS-III/BOSS with the aim of constraining $\sum m_\nu$. We utilize the void size function, the void galaxy cross power spectrum, and the galaxy auto power spectrum. To extract constraints from these summary statistics we use a simulation-based approach, specifically implicit likelihood inference. We populate approximate gravity-only, particle neutrino cosmological simulations with an expressive halo occupation distribution model. With a conservative scale cut of kmax=0.15 h/Mpc and a Planck-inspired LCDM prior, we find upper bounds on $\sum m_\nu$ of 0.43 and 0.35 eV from the galaxy auto power spectrum and the full data vector, respectively (95% credible interval). We observe hints that the void statistics may be most effective at constraining $\sum m_\nu$ from below. We also substantiate the usual assumption that the void size function is Poisson distributed.

astro-ph.CO

DEMNUni: disentangling dark energy from massive neutrinos with the void size function

Cosmic voids, the underdense regions in the Universe, are impacted by dark energy and massive neutrinos. In this work, relying on the DEMNUni suite of cosmological simulations, we explore the void size function in cosmologies with both dynamical dark energy and massive neutrinos. We investigate the impact of different choices of dark matter tracers on the void size function and study its sensitivity to the joint effect of modifying the dark energy equation of state and the sum of neutrino masses. We show that dark energy and massive neutrinos produce separable effects on the void size function. This statistic therefore allows us to distinguish among a wide range of combinations of dark energy equations of state and total neutrino masses, and its exploitation in forthcoming large galaxy surveys will be extremely useful in breaking degeneracies among these cosmological parameters.

astro-ph.CO

The perspective of voids on rising cosmology tensions

We investigate the main tensions within the current standard model of cosmology from the perspective of the main statistics of cosmic voids, using the final BOSS DR12 data set. For this purpose, we present the first estimate of the $S_8\equiv \sigma_8\sqrt{\Omega_{\rm m}/0.3}$ and $H_0$ parameters obtained from void number counts and shape distortions. To analyze void counts we relied on an extension of the popular volume-conserving model for the void size function, tailored to the application on data, including geometric and dynamic distortions. We calibrated the two nuisance parameters of this model with the official BOSS collaboration mock catalogs and propagated their uncertainty through the statistical analysis of the BOSS void number counts. The constraints from void shapes come from the study of the geometric distortions of the stacked void-galaxy cross-correlation function. In this work we focus our analysis on the $\Omega_{\rm m}$-$\sigma_8$ and $\Omega_{\rm m}$-$H_0$ parameter planes and derive the marginalized constraints $S_8 = 0.813^{+0.093}_{-0.068}$ and $H_0 = 67.3^{+10.0}_{-9.1} \ \mathrm{km} \ \mathrm{s}^{-1} \ \mathrm{Mpc}^{-1}$, which are fully compatible with constraints from the literature. These results are expected to notably improve in precision when analyzed jointly with independent probes and will open a new viewing angle on the rising cosmological tensions in the near future.

astro-ph.CO

Machine-learning cosmology from void properties

Cosmic voids are the largest and most underdense structures in the Universe. Their properties have been shown to encode precious information about the laws and constituents of the Universe. We show that machine learning techniques can unlock the information in void features for cosmological parameter inference. We rely on thousands of void catalogs from the GIGANTES dataset, where every catalog contains an average of 11,000 voids from a volume of $1~(h^{-1}{\rm Gpc})^3$. We focus on three properties of cosmic voids: ellipticity, density contrast, and radius. We train 1) fully connected neural networks on histograms from individual void properties and 2) deep sets from void catalogs, to perform likelihood-free inference on the value of cosmological parameters. We find that our best models are able to constrain the value of $\Omega_{\rm m}$, $\sigma_8$, and $n_s$ with mean relative errors of $10\%$, $4\%$, and $3\%$, respectively, without using any spatial information from the void catalogs. Our results provide an illustration for the use of machine learning to constrain cosmology with voids.

astro-ph.CO