arXiv subjects

Nico Hamaus

Publications and source records attributed to Nico Hamaus.

At least 19 recordsLinked to original sources

arXiv2026

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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arXiv2025

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.

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arXiv2025

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.

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arXiv2025

Cosmological Inference with Cosmic Voids and Neural Network Emulators

Cosmic Voids are a promising probe of cosmology for spectroscopic galaxy surveys due to their unique response to cosmological parameters. Their combination with other probes promises to break parameter degeneracies. Due to simplifying assumptions, analytical models for void statistics are only representative of a subset of the full void population. We present a set of neural-based emulators for void summary statistics of watershed voids, which retain more information about the full void population than simplified analytical models. We build emulators for the void size function and void density profiles traced by the halo number density using the Quijote suite of simulations for a broad range of the $\Lambda\mathrm{CDM}$ parameter space. The emulators replace the computation of these statistics from computationally expensive cosmological simulations. We demonstrate the cosmological constraining power of voids using our emulators, which offer orders-of-magnitude acceleration in parameter estimation, capture more cosmological information compared to analytic models, and produce more realistic posteriors compared to Fisher forecasts. We find that the parameters $\Omega_m$ and $\sigma_8$ in this Quijote setup can be recovered to $14.4\%$ and $8.4\%$ accuracy respectively using void density profiles; including the additional information in the void size function improves the accuracy on $\sigma_8$ to $6.8\%$. We demonstrate the robustness of our approach to two important variables in the underlying simulations, the resolution, and the inclusion of baryons. We find that our pipeline is robust to variations in resolution, and we show that the posteriors derived from the emulated void statistics are unaffected by the inclusion of baryons with the Magneticum hydrodynamic simulations. This opens up the possibility of a baryon-independent probe of the large-scale structure.

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arXiv2024

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.

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arXiv2024

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.

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arXiv2024

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 $S_8\equiv σ_8\sqrt{Ω_{\rm m}/0.3}$ 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 $Ω_{\rm m}$-$σ_8$ and $Ω_{\rm m}$-$H_0$ 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.

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arXiv2023

Why Cosmic Voids Matter: Mitigation of Baryonic Physics

We utilize the Magneticum suite of state-of-the-art hydrodynamical, as well as dark-matter-only simulations to investigate the effects of baryonic physics on cosmic voids in the highest-resolution study of its kind. This includes the size, shape and inner density distributions of voids, as well as their radial density and velocity profiles traced by halos, baryonic and cold dark matter particles. Our results reveal observationally insignificant effects that slightly increase with the inner densities of voids and are exclusively relevant on scales of only a few Mpc. Most notably, we identify deviations in the distributions of baryons and cold dark matter around halo-defined voids, relevant for weak lensing studies. In contrast, we find that voids identified in cold dark matter, as well as in halos of fixed tracer density exhibit nearly indistinguishable distributions and profiles between hydrodynamical and dark-matter-only simulations, consolidating the universality and robustness of the latter for comparisons of void statistics with observations in upcoming surveys. This corroborates that voids are the components of the cosmic web that are least affected by baryonic physics, further enhancing their use as cosmological probes.

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arXiv2023

Cosmological constraints from the BOSS DR12 void size function

We present the first cosmological constraints derived from the analysis of the void size function. This work relies on the final BOSS DR12 data set, a large spectroscopic galaxy catalog, ideal for the identification of cosmic voids. We extract a sample of voids from the distribution of galaxies and we apply a cleaning procedure aimed at reaching high levels of purity and completeness. We model the void size function by means of an extension of the popular volume-conserving model, based on two additional nuisance parameters. Relying on mock catalogs specifically designed to reproduce the BOSS DR12 galaxy sample, we calibrate the extended size function model parameters and validate the methodology. We then apply a Bayesian analysis to constrain the $Λ$CDM model and one of its simplest extensions, featuring a constant dark energy equation of state parameter, $w$. Following a conservative approach, we put constraints on the total matter density parameter and the amplitude of density fluctuations, finding $Ω_{\rm m}=0.29 \pm 0.06$ and $σ_8=0.79^{+0.09}_{-0.08}$. Testing the alternative scenario, we derive $w=-1.1\pm 0.2$, in agreement with the $Λ$CDM model. These results are independent and complementary to those derived from standard cosmological probes, opening up new ways to identify the origin of potential tensions in the current cosmological paradigm.

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arXiv2023

Why Cosmic Voids Matter: Nonlinear Structure & Linear Dynamics

We use the Magneticum suite of state-of-the-art hydrodynamical simulations to identify cosmic voids based on the watershed technique and investigate their most fundamental properties across different resolutions in mass and scale. This encompasses the distributions of void sizes, shapes, and content, as well as their radial density and velocity profiles traced by the distribution of cold dark matter particles and halos. We also study the impact of various tracer properties, such as their sparsity and mass, and the influence of void merging on these summary statistics. Our results reveal that all of the analyzed void properties are physically related to each other and describe universal characteristics that are largely independent of tracer type and resolution. Most notably, we find that the motion of tracers around void centers is perfectly consistent with linear dynamics, both for individual, as well as stacked voids. Despite the large range of scales accessible in our simulations, we are unable to identify the occurrence of nonlinear dynamics even inside voids of only a few Mpc in size. This suggests voids to be among the most pristine probes of cosmology down to scales that are commonly referred to as highly nonlinear in the field of large-scale structure.

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arXiv2022

Unveiling the Universe with Emerging Cosmological Probes

The detection of the accelerated expansion of the Universe has been one of the major breakthroughs in modern cosmology. Several cosmological probes (CMB, SNe Ia, BAO) have been studied in depth to better understand the nature of the mechanism driving this acceleration, and they are being currently pushed to their limits, obtaining remarkable constraints that allowed us to shape the standard cosmological model. In parallel to that, however, the percent precision achieved has recently revealed apparent tensions between measurements obtained from different methods. These are either indicating some unaccounted systematic effects, or are pointing toward new physics. Following the development of CMB, SNe, and BAO cosmology, it is critical to extend our selection of cosmological probes. Novel probes can be exploited to validate results, control or mitigate systematic effects, and, most importantly, to increase the accuracy and robustness of our results. This review is meant to provide a state-of-art benchmark of the latest advances in emerging beyond-standard cosmological probes. We present how several different methods can become a key resource for observational cosmology. In particular, we review cosmic chronometers, quasars, gamma-ray bursts, standard sirens, lensing time-delay with galaxies and clusters, cosmic voids, neutral hydrogen intensity mapping, surface brightness fluctuations, stellar ages of the oldest objects, secular redshift drift, and clustering of standard candles. The review describes the method, systematics, and results of each probe in a homogeneous way, giving the reader a clear picture of the available innovative methods that have been introduced in recent years and how to apply them. The review also discusses the potential synergies and complementarities between the various probes, exploring how they will contribute to the future of modern cosmology.

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arXiv2021

Intrinsic alignments of galaxies around cosmic voids

The intrinsic alignments of galaxies, i.e., the correlation between galaxy shapes and their environment, are a major source of contamination for weak gravitational lensing surveys. Most studies of intrinsic alignments have so far focused on measuring and modelling the correlations of luminous red galaxies with galaxy positions or the filaments of the cosmic web. In this work, we investigate alignments around cosmic voids. We measure the intrinsic alignments of luminous red galaxies detected by the Sloan Digital Sky Survey around a sample of voids constructed from those same tracers and with radii in the ranges: $[20-30; 30-40; 40-50]$ $h^{-1}$ Mpc and in the redshift range $z=0.4-0.8$. We present fits to the measurements based on a linear model at large scales, and on a new model based on the void density profile inside the void and in its neighbourhood. We constrain the free scaling amplitude of our model at small scales, finding no significant alignment at $1σ$ for either sample. We observe a deviation from the null hypothesis, at large scales, of 2$σ$ for voids with radii between 20 and 30 $h^{-1}$ Mpc, and 1.5 $σ$ for voids with radii between 30 and 40 $h^{-1}$ Mpc and constrain the amplitude of the model on these scales. We find no significant deviation at 1$σ$ for larger voids. Our work is a first attempt at detecting intrinsic alignments of galaxy shapes around voids and provides a useful framework for their mitigation in future void lensing studies.

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arXiv2021

The GIGANTES dataset: precision cosmology from voids in the machine learning era

We present GIGANTES, the most extensive and realistic void catalog suite ever released -- containing over 1 billion cosmic voids covering a volume larger than the observable Universe, more than 20 TB of data, and created by running the void finder VIDE on QUIJOTE's halo simulations. The expansive and detailed GIGANTES suite, spanning thousands of cosmological models, opens up the study of voids, answering compelling questions: Do voids carry unique cosmological information? How is this information correlated with galaxy information? Leveraging the large number of voids in the GIGANTES suite, our Fisher constraints demonstrate voids contain additional information, critically tightening constraints on cosmological parameters. We use traditional void summary statistics (void size function, void density profile) and the void auto-correlation function, which independently yields an error of $0.13\,\mathrm{eV}$ on $\sum\,m_ν$ for a 1 $h^{-3}\mathrm{Gpc}^3$ simulation, without CMB priors. Combining halos and voids we forecast an error of $0.09\,\mathrm{eV}$ from the same volume. Extrapolating to next generation multi-Gpc$^3$ surveys such as DESI, Euclid, SPHEREx, and the Roman Space Telescope, we expect voids should yield an independent determination of neutrino mass. Crucially, GIGANTES is the first void catalog suite expressly built for intensive machine learning exploration. We illustrate this by training a neural network to perform likelihood-free inference on the void size function. Cosmology problems provide an impetus to develop novel deep learning techniques, leveraging the symmetries embedded throughout the universe from physical laws, interpreting models, and accurately predicting errors. With GIGANTES, machine learning gains an impressive dataset, offering unique problems that will stimulate new techniques.

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arXiv2021

Volume Statistics as a Probe of Large-Scale Structure

We investigate the application of volume statistics to probe the distribution of underdense regions in the large-scale structure of the Universe. This statistic measures the distortion of Eulerian volume elements relative to Lagrangian ones and can be built from tracer particles using tessellation methods. We apply Voronoi and Delaunay tessellation to study the clustering properties of density and volume statistics. Their level of shot-noise contamination is similar, as both methods take into account all available tracer particles in the field estimator. The tessellation causes a smoothing effect in the power spectrum, which can be approximated by a constant window function on large scales. The clustering bias of the volume statistic with respect to the dark matter density field is determined and found to be negative. We further identify the Baryon Acoustic Oscillation (BAO) feature in the volume statistic. Apart from being smoothed out on small scales, the BAO is present in the volume power spectrum as well, without any systematic bias. These observations suggest that the exploitation of volume statistics as a complementary probe of cosmology is very promising.

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arXiv2020

Precision cosmology with voids in the final BOSS data

We report novel cosmological constraints obtained from cosmic voids in the final BOSS DR12 dataset. They arise from the joint analysis of geometric and dynamic distortions of average void shapes (i.e., the stacked void-galaxy cross-correlation function) in redshift space. Our model uses tomographic deprojection to infer real-space void profiles and self-consistently accounts for the Alcock-Paczynski (AP) effect and redshift-space distortions (RSD) without any prior assumptions on cosmology or structure formation. It is derived from first physical principles and provides an extremely good description of the data at linear perturbation order. We validate this model with the help of mock catalogs and apply it to the final BOSS data to constrain the RSD and AP parameters $f/b$ and $D_AH/c$, where $f$ is the linear growth rate, $b$ the linear galaxy bias, $D_A$ the comoving angular diameter distance, $H$ the Hubble rate, and $c$ the speed of light. In addition, we include two nuisance parameters in our analysis to marginalize over potential systematics. We obtain $f/b=0.540\pm0.091$ and $D_AH/c=0.588\pm0.004$ from the full void sample at a mean redshift of $z=0.51$. In a flat $Λ$CDM cosmology, this implies $Ω_\mathrm{m}=0.312\pm0.020$ for the present-day matter density parameter. When we use additional information from the survey mocks to calibrate our model, these constraints improve to $f/b=0.347\pm0.023$, $D_AH/c=0.588\pm0.003$, and $Ω_\mathrm{m}=0.310\pm0.017$. However, we emphasize that the calibration depends on the specific model of cosmology and structure formation assumed in the mocks, so the calibrated results should be considered less robust. Nevertheless, our calibration-independent constraints are among the tightest of their kind to date, demonstrating the immense potential of using cosmic voids for cosmology in current and future data.

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arXiv2020

Measurement of Void Bias Using Separate Universe Simulations

Cosmic voids are biased tracers of the large-scale structure of the universe. Separate universe simulations (SUS) enable accurate measurements of this biasing relation by implementing the peak-background split (PBS). In this work, we apply the SUS technique to measure the void bias parameters. We confirm that the PBS argument works well for underdense tracers. The response of the void size distribution depends on the void radius. For voids larger (smaller) than the size at the peak of the distribution, the void abundance responds negatively (positively) to a long wavelength mode. The linear bias from the SUS is in good agreement with the cross power spectrum measurement on large scales. Using the SUS, we have detected the quadratic void bias for the first time in simulations. We find that $ b_2 $ is negative when the magnitude of $ b_1 $ is small, and that it becomes positive and increases rapidly when $ |b_1| $ increases. We compare the results from voids identified in the halo density field with those from the dark matter distribution, and find that the results are qualitatively similar, but the biases generally shift to the larger voids sizes.

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arXiv2020

The bias of cosmic voids in the presence of massive neutrinos

Cosmic voids offer an extraordinary opportunity to study the effects of massive neutrinos on cosmological scales. Because they are freely streaming, neutrinos can penetrate the interior of voids more easily than cold dark matter or baryons, which makes their relative contribution to the mass budget in voids much higher than elsewhere in the Universe. In simulations it has recently been shown how various characteristics of voids in the matter distribution are affected by neutrinos, such as their abundance, density profiles, dynamics, and clustering properties. However, the tracers used to identify voids in observations (e.g., galaxies or halos) are affected by neutrinos as well, and isolating the unique neutrino signatures inherent to voids becomes more difficult. In this paper we make use of the DEMNUni suite of simulations to investigate the clustering bias of voids in Fourier space as a function of their core density and compensation. We find a clear dependence on the sum of neutrino masses that remains significant even for void statistics extracted from halos. In particular, we observe that the amplitude of the linear void bias increases with neutrino mass for voids defined in dark matter, whereas this trend gets reversed and slightly attenuated when measuring the relative void-halo bias using voids identified in the halo distribution. Finally, we argue how the original behaviour can be restored when considering observations of the total matter distribution (e.g. via weak lensing), and comment on scale-dependent effects in the void bias that may provide additional information on neutrinos in the future.

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arXiv2019

The Void Size Function in Dynamical Dark Energy Cosmologies

We test a theoretical description of the void size distribution function against direct estimates from halo catalogues of the DEMNUni suite of large cosmological simulations. Besides standard $Λ$CDM, we consider deviations of the dark energy equation of state from $w=-1$, corresponding to four combinations in the popular Chevallier-Polarski-Linder parametrisation: $w_0=-0.9;-1.1$, $w_a=-0.3;0.3$. The theoretical void size function model, relying on the Sheth & van de Weygaert double barrier excursion set formalism, provides an accurate description of the simulation measurements for the different dark energy models considered, within the statistical errors. The model remains accurate for any value of the threshold for void formation $δ_\mathrm{v}$. Its robust consistency with simulations demonstrates that the theoretical void size function can be applied to real data as a sensitive tool to constrain dark energy.

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