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Wojciech A. Hellwing

Publications and source records attributed to Wojciech A. Hellwing.

At least 19 recordsLinked to original sources

Non-linear Pairwise Velocities as a Cosmological Probe

Peculiar velocities trace gravitational dynamics directly, complementing density-based clustering as wide-field spectroscopic surveys (DESI, Euclid, PFS) and kinetic Sunyaev-Zel'dovich (kSZ) measurements enter the precision era. Observational analyses of pairwise velocities and the pairwise kSZ signal remain largely restricted to linear and quasi-linear scales ($\gtrsim20-30$ $h^{-1}Mpc$), despite substantial cosmological information available at smaller separations. We present a simulation-calibrated likelihood for $v_{12}(r,a)$, built on the exact pair conservation equation and PyCAMB HMcode-2020 non-linear clustering, and validate it against the QUIJOTE and TNG300-3 suites across resolution, particle sampling, box size, and redshift. Using QUIJOTE, we show that extending the fit to non-linear scales tightens the $1σ$ uncertainty on $Ω_\mathrm{m}$ and $σ_8$ by $74\%$ and $81\%$ at $z=0.5$ ($r_{\rm min}=4$ $h^{-1}Mpc$), and by $70\%$ and $74\%$ at $z=0$ ($r_{\rm min}=8$ $h^{-1}Mpc$), relative to the linear-regime baseline ($r_{\rm min}=50$ $h^{-1}Mpc$) (all at fixed $r_{max}=140$ $h^{-1}Mpc$); $σ(fσ_8)$ tightens by up to $86\%$, and the joint $Ω_\mathrm{m}$-$fσ_8$ Figure-of-Merit improves by up to $9.1\times$ relative to the same baseline. These constraints are conditional on $h$ fixed at its QUIJOTE fiducial value, due to a near-degenerate response with $σ_8$; jointly sampling $h$ shifts and widens them substantially. This framework provides a validated route to exploiting that information in upcoming direct peculiar-velocity, redshift-space, and kSZ analyses.

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Angular clustering and bias of photometric quasars in the Kilo-Degree Survey Data Release 4

We investigate the angular clustering and effective bias of photometrically selected quasars in the Kilo-Degree Survey Data Release 4 (KiDS DR4). We update the previous photometric redshifts (photo-$z$s) of the KiDS quasars using Hybrid-z, a deep learning framework combining four-band KiDS images and nine-band KiDS+VIKING magnitudes. Hybrid-z is trained on the latest Dark Energy Spectroscopic Instrument (DESI) DR1 and Sloan Digital Sky Survey (SDSS) DR17 quasars matching with KiDS, and achieves average bias $\langle δz \rangle < 0.01$ and scatter $\sim 0.04(1 + z)$ on a test sample. The updated catalog of $\sim 157k$ quasars over $777~\mathrm{deg}^2$ is divided into four tomographic bins spanning $0.1 \leq z_{\mathrm{phot}} \leq 2.7$. In each bin, we measure the angular two-point correlation function and compare it with theoretical predictions for dark matter clustering. We estimate the best-fit scale-independent quasar bias, which increases from $b \approx 1.6$ at $z \approx 0.6$ to $b \approx 4.0$ at $z \approx 2.2$, and is well matched by a quadratic relation in redshift. Our clustering analysis indicates that KiDS quasars reside in dark matter halos of mass $\log_{10}(M_{\mathrm{eff}}/h^{-1}M_\odot)$ in the range $\sim 12.7$--$12.9$ and effective peak heights $ν_{\mathrm{eff}}$ rising from $\sim 1.5$ to $2.9$ over our redshift span. We study two systematics that could affect the bias derivation: stellar contamination and the redshift distribution assumed in the theoretical modeling. The former has a negligible effect, whereas the latter significantly impacts the derived $b(z)$, emphasizing the importance of redshift calibration. Our work is the first cosmological application of quasars selected from KiDS and paves the way for future extensions in the final KiDS DR5, the Legacy Survey of Space and Time, or the 4-metre Multi-Object Spectroscopic Telescope.

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Skewness as a Probe of Gravity: Real and Redshift Space Counts-In-Cells

We study the counts-in-cells reduced skewness $s_3$ for dark matter, halo, and galaxy distributions in both real and redshift space, using the ELEPHANT ($\textit{Extended LEnsing PHysics with ANalytical ray Tracing}$) suite of $N$-body simulations. We compare General Relativity (GR) with two extended (EG) gravity models: $f(R)$ gravity with chameleon screening and the normal-branch Dvali-Gabadadze-Porrati (nDGP) model with Vainshtein screening. We quantify the suppression of $s_3$ by redshift-space distortions (RSD), finding that while small-scale skewness is strongly reduced, the $F5$ model retains a $\sim 4\%$ deviation from GR in galaxy samples, corresponding to a $2σ$ significance. We show that the ratio $s_3^{\mathrm{RSD}}/s_3^{\mathrm{real}}$ is approximately independent of the gravity model across tracers and redshifts. Our results demonstrate that real-space predictions can help reliably infer redshift-space skewness in both GR and extended gravity, providing a new tool for testing gravity with current and forthcoming galaxy redshift surveys.

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Anisotropic Counts-in-Cells in Redshift Space: A New Route to Cosmological Constraints from Galaxy Surveys

We introduce a novel extension of the volume-averaged correlation function (VACF) framework by replacing the traditional spherical smoothing kernels with anisotropic, ellipsoidal windows. This generalized approach enables the study of shape-dependent clustering statistics and captures directional information encoded in large-scale structure, particularly in redshift space where galaxy distribution is distorted by peculiar velocities. We define and compute ellipsoidal VACFs $\barξ_J (r_{\parallel}, r_{\perp})$ and the corresponding reduced cumulants $s_J (r_{\parallel}, r_{\perp})$, allowing for joint sensitivity to both scale and anisotropy across arbitrary statistical order J. Using a suite of COLA N-body simulations spanning a grid of cosmologies with varying $Ω_M$ and $σ_8$, we analyze the behavior of ellipsoidal VACFs and cumulants in both real and redshift space. We find that the shape of the smoothing kernel that maximizes the clustering signal depends strongly on the redshift-space distortion regime: spherical in real space, prolate in the Fingers-of-God-dominated regime, and oblate in the Kaiser squashing-dominated regime. While the standard VACF amplitude is mainly sensitive to $σ_8$, the shape-dependence of redshift-space skewness shows a coherent response to the combined growth parameter $f σ_8$, with a typical sensitivity at the 1-3 $σ$ level between neighboring models. Our results demonstrate that ellipsoidal VACFs offer a computationally efficient and information-rich generalization of counts-in-cells analysis, with promising applications to galaxy survey data, halo catalogs, and cosmological tests of gravity beyond $ΛCDM$.

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Galaxy and halo angular clustering in LCDM and Modified Gravity cosmologies

Using a suite of $N$-body simulations we study the angular clustering of galaxies, halos, and dark matter in $\mathrm{Λ\text{CDM}}$ and Modified Gravity (MG) scenarios. We consider two general categories of such MG models, one is the $f(R)$ gravity, and the other is the normal branch of the Dvali-Gabadadze-Porrati brane world (nDGP). To measure angular clustering we construct a set of observer-frame lightcones and resulting mock sky catalogs. We focus on the area-averaged angular correlation functions, $W_J$, and the associated reduced cumulants, $S_J\equiv W_J/W_2^{(J-1)}$, and robustly measure them up to the 9th order using counts-in-cells (CIC). We find that $0.15 < z < 0.3$ is the optimal redshift range to maximize the MG signal in our lightcones. Analyzing various scales for the two types of statistics, we identify up to 20\% relative departures in MG measurements from general relativity (GR), with varying signal significance. For the case of halos and galaxies, we find that $3$rd order statistics offer the most sensitive probe of the different structure formation scenarios, with both $W_3$ and the reduced skewness, $S_3$, reaching from $2σ$ to $4σ$ significance at angular scales $θ\sim 0.13 ^\circ$. The MG clustering of the smooth dark matter field is characterized by even stronger deviations ($\stackrel{>}{{}_\sim} 5σ$) from GR, albeit at a bit smaller scales of $θ\sim0.08^\circ$, where baryonic physics is already important. Finally, we stress out that our mock halo and galaxy catalogs are characterized by rather low surface number densities when compared to existing and forthcoming state-of-the-art photometric surveys. This opens up exciting potential for testing GR and MG using angular clustering in future applications, with even higher precision and significance than reported here.

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Caught in the Cosmic Web: Environmental Impacts on the Halo Substructure Boosts to Dark Matter Annihilation Signals

The annihilation of dark matter (DM) particles is expected to produce Standard Model particles, providing a potential indirect signature of DM. The clumpy substructure of DM haloes amplifies the expected annihilation signal, an effect commonly quantified by the subhalo boost factor. Standard semi-analytic models usually treat this boost as a universal function of host-halo mass, neglecting systematic variations induced by the large-scale environment. In this work, we extend this framework by incorporating the influence of the cosmic web on subhalo populations. Using simulation-calibrated, environment-dependent ratios for host-halo concentrations, the subhalo mass function, and internal-structure proxies of subhalos based on the $V_{\max}$--$R_{\max}$ relation, we compute environment-conditioned boost predictions for haloes residing in filaments, walls, and voids. Our main result is the boost factor at fixed host-halo mass, expressed relative to the cosmic-mean prediction, $B(M,\mathrm{env})/B_{\mathrm{CM}}(M)$. We find a clear environmental modulation: in the fiducial distance-dependent model, filament haloes show a mass-dependent transition from a $\sim 15\%$ suppression at the low-mass end to a modest enhancement of $\sim 12\%$ for massive hosts, wall haloes remain intermediate, while void haloes stay suppressed by roughly $30$--$33\%$ across the explored host-mass range. These results should be interpreted as deterministic model predictions obtained by propagating environment-dependent ingredient ratios through two standard semi-analytic boost frameworks. We provide an environment-aware prescription for subhalo boosts, together with modular environmental corrections that may also be useful in indirect-detection forecasts, strong-lensing mass modeling, and related halo-population applications.

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Large Scale Structure and Environmental Effects on Dwarf Galaxy Growth

Dwarf galaxies serve as key models for understanding galaxy assembly in the early universe, with their final properties influenced by environmental factors. Using the dark matter-only simulation "Copernicus Complexio" (COCO) and the semi-analytic model GALFORM, we examine the stellar mass assembly of dwarf galaxies across different cosmic web regions, defined by the NEXUS+/CACTUS algorithm. We identify significant variations in stellar mass assembly based on final mass, with the largest dwarf galaxies assembling, on average, 50% of their mass 7.7 Gyrs later than the smallest ones. Central galaxies also differ in their assembly from satellites of comparable final mass, forming 50% of their mass 2.5 Gyrs later. The location within the cosmic web further influences assembly, with satellite galaxies showing greater differences than centrals. Satellites in the densest regions assemble their mass 1.5 Gyrs earlier than those in the least dense regions, compared to 0.69 Gyrs for central galaxies. This disparity arises from varying infall times, with satellites in dense environments infalling 5.2 Gyrs earlier than those in voids. Additionally, we investigate the impact of reionisation parameters, specifically the timing ($z_{cut}$) and filtering scale ($v_{cut}$) of reionisation. The stellar-to-halo-mass relation shows a power law break between $10^8~\mathrm{M}_\odot < M_{200} < 10^{10}~\mathrm{M}_\odot$, with earlier $z_{cut}$ or higher $v_{cut}$ leading to more star formation suppression in lower-mass haloes. The halo occupation fraction is also affected, with later $z_{cut}$ or lower $v_{cut}$ resulting in fewer lower-mass haloes being occupied at $z=0$. Our investigation provides a valuable theoretical framework for interpreting upcoming observational data in this mass regime.

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Hybrid-z: Enhancing Kilo-Degree Survey bright galaxy sample photometric redshifts with deep learning

We employ deep learning (DL) to improve photometric redshifts (photo-$z$s) in the Kilo-Degree Survey Data Release 4 Bright galaxy sample (KiDS-Bright DR4). This dataset, used as a foreground for KiDS lensing and clustering studies, is flux-limited to $r<20$ mag with mean $z=0.23$ and covers 1000 deg$^2$. Its photo-$z$s were previously derived with artificial neural networks from the ANNz2 package, trained on the Galaxy And Mass Assembly (GAMA) spectroscopy. Here we considerably improve over these previous redshift estimations by building a DL model, Hybrid-z, which combines four-band KiDS images with nine-band magnitudes from KiDS+VIKING. The Hybrid-z framework provides photo-$z$s for KiDS-Bright, with negligible mean residuals of O($10^{-4}$) and scatter at the level of $0.014(1+z)$ -- reduction by 20% over the previous nine-band derivations with ANNz2. We check our photo-$z$ model performance on test data drawn from GAMA, as well as from other KiDS-overlapping wide-angle spectroscopic surveys, namely SDSS, 2dFLenS, and 2dFGRS. We find stable behavior and consistent improvement over ANNz2 throughout. We finally apply Hybrid-z trained on GAMA to the entire KiDS-Bright DR4 sample of 1.2 million galaxies. For these final predictions, we design a method of smoothing the input redshift distribution of the training set, to avoid propagation of features present in GAMA, related to its small sky area and large-scale structure imprint in its fields. Our work paves the way towards the best-possible photo-$z$s achievable with machine learning for any galaxy type both for the final KiDS-Bright DR5 data and for future deeper imaging, such as from the Legacy Survey of Space and Time.

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Caught in the cosmic web: environmental effects on subhalo abundance and internal density profiles

Using the high-resolution $N$-body cosmological simulation COLOR, we explore the cosmic web (CW) environmental effects on subhalo populations and their internal properties. We use CaCTus, which incorporates an implementation of the state-of-the-art segmentation method NEXUS+, to delineate the simulation volume into nodes, filaments, walls, and voids. We group host haloes by virial mass and segment each mass bin into consecutive CW elements. This reveals that subhalo populations in hosts within specific environments differ on average from the cosmic mean. The subhalo mass function is affected strongly, where hosts in filaments typically contain more subhaloes ($5$ to $20\%$), while hosts in voids are subhalo-poor, with $25\%$ fewer subhaloes. We find that the abundance of the most massive subhaloes, with reduced masses of $μ\equiv M_\mathrm{sub}/M_{200}$ is most sensitive to the CW environment. A corresponding picture emerges when looking at subhalo mass fractions, $f_\mathrm{sub}$, where the filament hosts are significantly more `granular' (having higher $f_\mathrm{sub}$) than the cosmic mean, while the void hosts have much smoother density distributions (with $f_\mathrm{sub}$ lower by $2$ - $20\%$ than the mean). Finally, when we look at the subhalo internal kinematic $V_{\rm max}$-$R_{\rm max}$ relations, we find that subhaloes located in the void and wall hosts exhibit density profiles with lower concentrations than the mean, while the filament hosts demonstrate much more concentrated mass profiles. Across all our samples, the effect of the CW environment generally strengthens with decreasing host halo virial mass. Our results show that host location in the large-scale CW introduces significant systematic effects on internal subhalo properties and population statistics.

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Simulations of the accreted stellar halos of low-mass field galaxies

We predict the properties of stellar halos in galaxies of present-day virial mass $10^8 < M_{200} < 10^{12} {\rm M_\odot}$ by combining the GALFORM semi-analytic model of galaxy formation, the COCO cosmological N-body simulation, and the STINGS particle tagging technique. Galaxies in low mass halos have a wide range of stellar halo properties. Their diversity is much greater at fixed stellar mass than fixed virial mass. In the least massive DM halos capable of supporting galaxy formation, accreted mass fractions are < 10 per cent, and the typical density profile of accreted stars is similar to that of stars formed in situ. In low mass galaxies, the radial scale lengths of accreted stellar halos are smaller than those of stellar disks formed in situ, but the accreted component is still diffuse, not bulge-like. At the scale of galaxies like M33, the surface density of accreted stars exceeds that of the in situ component at ~15kpc; the accreted surface density at this radius is $3.5\lesssim \log_{10} M_\star/{\rm M_\odot} \mathrm{kpc^{-2}} \lesssim 6$, varying systematically with virial mass. We compare our predictions to observations and other cosmological simulations. A small but significant number of $\sim 10^{12} {\rm M_\odot}$ halos with exceptionally inefficient star formation -- "failed Milky Ways" -- are more prominent in our model than others; the true abundance of this population is a potential constraint on galaxy formation physics and could be measured by low surface brightness surveys targeting field galaxies with M33-like stellar mass. The stellar particle data for our simulation is publicly available.

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Hierarchical structure of the cosmic web and galaxy properties

Voids possess a very complex internal structure and dynamics. Using $N$-body simulations we study the hierarchical nature of sub-structures present in the cosmic web (CW). We use the SpineWeb method which provides a complete characterization of the CW into its primary constituents: voids, walls, filaments, and nodes. We aim to characterize the inner compositions of voids by detecting their internal filamentary structure and explore the impact of this on the properties of void galaxies. Using a semi-analytical galaxy evolution model we explore the impact of the CW on several galaxies' properties. We find the fraction of haloes living in various CW components to be a function of their mass, with the majority of the haloes of mass below $10^{12}M_{\odot}/h$, residing in voids and haloes of higher masses distributed mostly in walls. Similarly, in the Stellar-to-Halo mass relationship, we observe an environmental dependence for haloes of masses below $10^{12}M_{\odot}/h$, showing an increased stellar mass fraction for the densest environments. The spin is lower for galaxies in the densest environments for the mass range of $10^{10}-10^{12}M_{\odot}/h$. Finally, we found a strong trend of higher metallicity fractions for filaments and node galaxies, with respect to the full sample, in the range of $M_*<10^{10}M_{\odot}/h$. Our results show that cosmic voids possess an intricate internal network of substructures. This in turn makes them a complex environment for galaxy formation, impacting in an unique way the properties and evolution of the chosen few galaxies that form inside them.

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Dynamics of pairwise motions in the fully non-linear regime in LCDM and Modified Gravity cosmologies

In contrast to our understanding of density field tracers, the modelling of direct statistics pertaining to the cosmic velocity field remains open to significant opportunities for improvement. The lack of accurate modelling for the non-linear domain of pairwise velocities restricts our capacity to fully exploit the information encoded in this observable. We present a robust approach for modelling the mean infall velocities, $v_{12}(r,a)$, with broad applicability spanning sub-megaparsec scales and cosmologies extending beyond the standard LCDM paradigm. Our approach involves solving the full pair-conservation equation using accurate non-linear power spectrum descriptions. To assess the robustness of our model, we extend it to cosmologies beyond the standard LCDM, in particular, the Hu-Sawicki $f(R)$-gravity and Dvali-Gabadadze-Porrati (DGP) modified gravity models. Remarkably, our predictions for pairwise velocities of dark matter particles at kilo-parsec scales exhibit excellent agreement with N-body simulations throughout the entire dynamical range ($0.1 \lesssim ξ\lesssim 1000$, or $r\geq0.4$Mpc/h). Furthermore, we show that different gravity models leave distinct signatures in the shape and dynamics of the mean pairwise velocities, providing a potent test of cosmological gravity laws.

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Enhancing Photometric Redshift Catalogs Through Color-Space Analysis: Application to KiDS-Bright Galaxies

We present a method to refine photometric redshift galaxy catalogs by comparing their color-space matching with overlapping spectroscopic calibration data. We focus on cases where photometric redshifts (photo-$z$) are estimated empirically. Identifying galaxies that are poorly represented in spectroscopic data is crucial, as their photo-$z$ may be unreliable due to extrapolation beyond the training sample. Our approach uses a self-organizing map (SOM) to project a multi-dimensional parameter space of magnitudes and colors onto a 2-D manifold, allowing us to analyze the resulting patterns as a function of various galaxy properties. Using SOM, we compare the Kilo-Degree Survey bright galaxy sample (KiDS-Bright), limited to $r<20$ mag, with various spectroscopic samples, including the Galaxy And Mass Assembly (GAMA). Our analysis reveals that GAMA under-represents KiDS-Bright at its faintest ($r\gtrsim19.5$) and highest-redshift ($z\gtrsim0.4$) ranges, however no strong trends in color or stellar mass. By incorporating additional spectroscopic data from the SDSS, 2dF, and early DESI, we identify SOM cells where photo-$z$ are estimated suboptimally. We derive a set of SOM-based criteria to refine the photometric sample and improve photo-$z$ statistics. For the KiDS-Bright sample, this improvement is modest: exclusion of the least represented 20% of the sample reduces photo-$z$ scatter by less than 10%. We conclude that GAMA, used for KiDS-Bright photo-$z$ training, is sufficiently representative for reliable redshift estimation across most of the color space. Future spectroscopic data from surveys such as DESI should be better suited for exploiting the full improvement potential of our method.

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A universal and physically motivated threshold for Hessian-based cosmic web identification: V-Web case

The study of large-scale structure can benefit from accurate and robust identification of the cosmic web. Having such classification can facilitate a more complete extraction of cosmological information encoded therein. Classification methods like T-web and V-web, based on the Hessian matrix, are widely used to signal-out voids, sheets, filaments, and knots. However, these techniques depend on a threshold parameter which value is chosen without physical justification, usually relying on a user visual impression, thus limiting the universality of results. In this paper we focus on the V-web method. Our aim is to find a physical motivation for deriving an universal threshold that can be applied across different cosmic scales and epochs. V-web classify the large-scale structure using the eigenvalues of the velocity shear tensor. Using a set of gravity-only simulations we introduce a normalization that incorporates the standard deviation of the velocity divergence field, isolating the beyond Gaussian evolution of cosmic web elements. In the Zeldovich's approximation, the probability presence of each cosmic web element remains constant at a threshold equal to 0. For the first time, we reveal that this behavior also holds in the non-linear regime for a normalized positive 'constant volume threshold' that depends on both the redshift and the applied smoothing scale. The conservation of volume fractions is valid for the studied redshifts between 0 and 2, regardless of cosmic variance, and is most precise for intermediate smoothing scales around 3 Mpc/h. The properties of the cosmic web derived using this approach in the V-web align with expectations from other methods, including visual impressions. We provide a general fit formula to compute the constant volume threshold for any standard cosmological simulation, regardless of its specific properties.

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Extragalactic Stellar Tidal Streams: Observations meet Simulation

According to the well established hierarchical framework for galaxy evolution, galaxies grow through mergers with other galaxies and the LambdaCDM cosmological model predicts that the stellar halos of massive galaxies are rich in remnants from minor mergers. The Stellar Streams Legacy Survey (SSLS) has provided a first release of a catalogue with a statistically significant sample of stellar streams in the Local Universe, detected in deep images from DESI Legacy Surveys and the Dark Energy Survey (DES). The main objective is to compare the results of the observations of stellar tidal streams with predictions from state-of-the-art cosmological simulations regarding their abundance, up to a redshift z < 0.02, according to the LambdaCDM model. We use the predictions of the cosmological simulations Copernicus Complexio, TNG50 of the IllustrisTNG project, and Auriga to generate mock-images of nearby halos and search for stellar streams. We compare the stream frequency, characteristics and photometry in these images with DES observations. We find generally good agreement between the real images and the simulated ones regarding frequency, characteristics and photometry of the streams, while the stream morphology is somewhat different between observations and simulations, and between simulations themselves. By varying the sky background of the synthetic images to emulate different surface brightness limit levels, we also obtain predictions for the detection rate of stellar tidal streams up to a surface brightness limit of 35 mag arcsec^-2. The cosmological simulations predict that with an instrument such as the one used in the DES, it would be necessary to reach a surface brightness limit of 32 mag arcsec^-2 in the r-band to achieve a frequency of up to around 70% in the detection of stellar tidal streams around galaxies in the redshift range considered here.

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Bending the web: exploring the impact of modified gravity on the density field and halo properties within the cosmic web

This work investigates the impact of different Modified Gravity (MG) models on the large-scale structures (LSS) properties in relation to the cosmic web (CW), using N-body simulations of f(R) and nDGP models. We analyse the impact of the MG effect on the density field through density distribution and clustering statistics, and assess its influence on halo properties by examining the halo mass function and spin. We find that the PDF of dark matter density fields shift towards lower densities for stronger variants of f(R) and nDGP. Additionally, when segregated into CW environments, the stronger variants show a higher mean density in knots, and a lower mean density in voids compared to LCDM. For higher-order clustering statistics relative to LCDM, the scale-dependent f(R) variants exhibit a greater non-monotonic deviation as a function of scale when segregated into environments, compared to nDGP. Additionally, the halo mass function separated into CW environments shows a similar behaviour, introducing complex trends as a function of mass for f(R) and nDGP models. We also report up to a 15% enhancement in the angular momentum of halos in f(R) gravity models compared to LCDM, with similar differences when considering environmental segregation. We demonstrate that this difference in the spin arises largely due to different tidal torquing across the various MG models. Therefore, studying higher-order statistics of the cosmological fields and halo properties separated into CW components probes the additional physics contained within the MG models. We conclude that considering the effect of CW in MG studies increases the constraining power of these LSS statistics, and can further aid the distinction between the cosmologies that have an identical expansion history to the standard LCDM but differing underlying physics, such as the MG models presented in this work.

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Improved analytical modeling of the non-linear power spectrum in modified gravity cosmologies

Reliable analytical modeling of the non-linear power spectrum (PS) of matter perturbations is among the chief pre-requisites for cosmological analyses from the largest sky surveys. This is especially true for the models that extend the standard general-relativity paradigm by adding the fifth force, where numerical simulations can be prohibitively expensive. Here we present a method for building accurate PS models for two modified gravity (MG) variants: namely the Hu-Sawicki $f(R)$, and the normal branch of the Dvali-Gabadadze-Porrati (nDGP) braneworld. We start by modifying the standard halo model (HM) with respect to the baseline Lambda-Cold-Dark-Matter ($Λ$CDM) scenario, by using the HM components with specific MG extensions. We find that our $P(k)_{\text{HM}}$ retains 5% accuracy only up to mildly non-linear scales ($k \lesssim 0.3$ $h/\,\mbox{Mpc}$) when compared to PS from numerical simulations. At the same time, our HM prescription much more accurately captures the ratio $Υ(k) = P(k)_{\text{MG}}/P(k)_{Λ\text{CDM}}$ up to non-linear scales. We show that using HM-derived $Υ(k)$ together with a viable non-linear $Λ$CDM $P(k)$ prescription (such as HALOFIT), we render a much better and more accurate PS predictions in MG. The new approach yields considerably improved performance, with modeled $P(k)_{\text{MG}}$ being now accurate to within 5% all the way to non-linear scales of $k \lesssim 2.5-3$ $h/\,\mbox{Mpc}$. The magnitude of deviations from GR as fostered by these MG models is typically $\mathcal{O}(10\%)$ in these regimes. Therefore reaching 5% PS modeling is enough for forecasting constraints on modern-era cosmological observables.

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Dark matter solution to the $H_{0}$ and $S_{8}$ tensions, and the integrated Sachs-Wolfe void anomaly

We consider a phenomenological model of dark matter with an equation-of-state $w$ that is negative and changing at late times. We show this couples the $H_{0}$ and $S_{8}$ tensions, alleviating them both simultaneously, reducing the $H_{0}$ tension from $\sim5σ$ to $\sim3σ$ and the $S_{8}$ tension from $\sim3σ$ to $\sim1σ$. Furthermore, the model provides an explanation for the anomalously large integrated Sachs-Wolfe (ISW) effect from cosmic voids, a unique consequence of the changing and negative equation-of-state. Observations of high ISW from cosmic voids may therefore be evidence that dark matter plays a significant role in both the $H_{0}$ and $S_{8}$ tensions. We predict the ISW from cosmic voids to be a factor of up to $\sim2$ greater in this model than what is expected from the standard model $Λ$CDM. These results extend to other degenerate models of dark matter, such as unified or interacting dark matter and dark energy models.

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