Verifying the fully kinematic nature of the cosmic microwave background (CMB) dipole is of fundamental importance in cosmology. In the standard cosmological model with the Friedman-Lemaitre-Robertson-Walker (FLRW) metric from the inflationary expansion the CMB dipole should be entirely kinematic. Any non-kinematic CMB dipole component would thus reflect the preinflationary structure of spacetime probing the extent of the FLRW applicability. Cosmic backgrounds from galaxies after the matter-radiation decoupling, should have kinematic dipole component identical in velocity with the CMB kinematic dipole. Comparing the two can lead to isolating the CMB non-kinematic dipole. It was recently proposed that such measurement can be done using the near-IR cosmic infrared background (CIB) measured with the currently operating Euclid telescope, and later with Roman. The proposed method reconstructs the resolved CIB, the Integrated Galaxy Light (IGL), from Euclid's Wide Survey and probes its dipole, with a kinematic component amplified over that of the CMB by the Compton-Getting effect. The amplification coupled with the extensive galaxy samples forming the IGL would determine the CIB dipole with an overwhelming signal/noise, isolating its direction to sub-degree accuracy. We develop details of the method for Euclid's Wide Survey in 4 bands spanning 0.6 to 2 mic. We isolate the systematic and other uncertainties and present methodologies to minimize them, after confining the sample to the magnitude range with negligible IGL/CIB dipole from galaxy clustering. These include the required star-galaxy separation, accounting for the extinction correction dipole using the method newly developed here achieving total separation, accounting for the Earth's orbital motion and other systematic effects. (Abridged)

We present the first detection of weak gravitational lensing around spectroscopically confirmed dwarf galaxies, using the large overlap between DESI DR1 spectroscopic data and DECADE/DES weak lensing catalogs. A clean dwarf galaxy sample with well-defined redshift and stellar mass cuts enables excess surface mass density measurements in two stellar mass bins ($\log \rm{M}_*=[8.2, 9.2]~M_\odot$ and $\log \rm{M}_*=[9.2, 10.2]~M_\odot$), with signal-to-noise ratios of $5.6$ and $12.4$ respectively. This signal-to-noise drops to $4.5$ and $9.2$ respectively for measurements without applying individual inverse probability (IIP) weights, which mitigates fiber incompleteness from DESI's targeting. The measurements are robust against variations in stellar mass estimates, photometric shredding, and lensing calibration systematics. Using a simulation-based modeling framework with stellar mass function priors, we constrain the stellar mass-halo mass relation and find a satellite fraction of $\simeq 0.3$, which is higher than previous photometric studies but $1.5\sigma$ lower than $\Lambda$CDM predictions. We find that IIP weights have a significant impact on lensing measurements and can change the inferred $f_{\rm{sat}}$ by a factor of two, highlighting the need for accurate fiber incompleteness corrections for dwarf galaxy samples. Our results open a new observational window into the galaxy-halo connection at low masses, showing that future massively multiplexed spectroscopic observations and weak lensing data will enable stringent tests of galaxy formation models and $\Lambda$CDM predictions.

Forward models of the galaxy density field enable simulation based inference as well as field level inference of galaxy clustering. However, these analysis techniques require forward models that are both computationally fast and robust to modeling uncertainties in the relation between galaxies and matter. Both requirements can be addressed with the Effective Field Theory of Large Scale Structure. Here, we focus on the physical and numerical convergence of the LEFTfield model. Based on the perturbative nature of the forward model, we derive an analytic understanding of the leading numerical errors, and we compare our estimates to high-resolution and N-body references. This allows us to derive a set of best-practice recommendations for the numerical accuracy parameters, which are completely specified by the desired order of the perturbative solution and the cut-off scale. We verify these recommendations by an extended set of parameter recovery tests from fully nonlinear mock data and find very consistent results. A single evaluation of the forward model takes seconds, making cosmological analyses of galaxy clustering data based on forward models computationally feasible.

Small-scale winds driven from accretion discs surrounding active galactic nuclei (AGN) are expected to launch kpc-scale outflows into their host galaxies. However, the ways in which the structure of the interstellar medium (ISM) affects the multiphase content and impact of the outflow remains uncertain. We present a series of numerical experiments featuring a realistic small-scale AGN wind with velocity $5\times 10^3-10^4\ \rm{km/s}$ interacting with an isolated galaxy disc with a manually-controlled clumpy ISM, followed at sub-pc resolution. Our simulations are performed with AREPO and probe a wide range of AGN luminosities ($L=10^{43-47}\ \rm{erg/s}$) and ISM substructures. In homogeneous discs, the AGN wind sweeps up an outflowing, cooling shell, where the emerging cold phase dominates the mass and kinetic energy budgets, reaching a momentum flux $\dot{p} \approx 7\ L/c$. However, when the ISM is clumpy, outflow properties are profoundly different. They contain small, long-lived (> 5\ \rm{Myr}), cold (T<10^{4.5}\ \rm{K}) cloudlets entrained in the faster, hot outflow phase, which are only present in the outflow if radiative cooling is included in the simulation. While the cold phase dominates the mass of the outflow, most of the kinetic luminosity is now carried by a tenuous, hot phase with T > 10^7 \ \rm K. While the hot phases reaches momentum fluxes $\dot{p} \approx (1 - 5)\ L/c$, energy-driven bubbles couple to the cold phase inefficiently, producing modest momentum fluxes \dot{p} < L/c in the fast-outflowing cold gas. These low momentum fluxes could lead to the outflows being misclassified as momentum-driven using common observational diagnostics. We also show predictions for scaling relations between outflow properties and AGN luminosity and discuss the challenges in constraining outflow driving mechanisms and kinetic coupling efficiencies using observed quantities.

We present cosmic shear constraints from the completed Kilo-Degree Survey (KiDS), where the cosmological parameter $S_8\equiv\sigma_8\sqrt{\Omega_{\rm m}/0.3} = 0.815^{+0.016}_{-0.021}$, is found to be in agreement ($0.73\sigma$) 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 $\Sigma_8\equiv\sigma_8\left(\Omega_{\rm m}/0.3\right)^\alpha = 0.821^{+0.014}_{-0.016}$, where $\alpha = 0.58$ has been optimised to match the revised degeneracy direction of $\sigma_8$ and $\Omega_{\rm m}$. 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.

We develop a framework to study the relation between the stellar mass of a galaxy and the total mass of its host dark matter halo using galaxy clustering and galaxy-galaxy lensing measurements. We model a wide range of scales, roughly from $\sim 100 \; {\rm kpc}$ to $\sim 100 \; {\rm Mpc}$, using a theoretical framework based on the Halo Occupation Distribution and data from Year 3 of the Dark Energy Survey (DES) dataset. The new advances of this work include: 1) the generation and validation of a new stellar mass-selected galaxy sample in the range of $\log M_\star/M_\odot \sim 9.6$ to $\sim 11.5$; 2) the joint-modeling framework of galaxy clustering and galaxy-galaxy lensing that is able to describe our stellar mass-selected sample deep into the 1-halo regime; and 3) stellar-to-halo mass relation (SHMR) constraints from this dataset. In general, our SHMR constraints agree well with existing literature with various weak lensing measurements. We constrain the free parameters in the SHMR functional form $\log M_\star (M_h) = \log(\epsilon M_1) + f\left[ \log\left( M_h / M_1 \right) \right] - f(0)$, with $f(x) \equiv -\log(10^{\alpha x}+1) + \delta [\log(1+\exp(x))]^\gamma / [1+\exp(10^{-x})]$, to be $\log M_1 = 11.559^{+0.334}_{-0.415}$, $\log \epsilon = -1.689^{+0.333}_{-0.220}$, $\alpha = -1.637^{+0.107}_{-0.096}$, $\gamma = 0.588^{+0.265}_{-0.220}$ and $\delta = 4.227^{+2.223}_{-1.776}$. The inferred average satellite fraction is within $\sim 5-35\%$ for our fiducial results and we do not see any clear trends with redshift or stellar mass. Furthermore, we find that the inferred average galaxy bias values follow the generally expected trends with stellar mass and redshift. Our study is the first SHMR in DES in this mass range, and we expect the stellar mass sample to be of general interest for other science cases.

Forward modeling the galaxy density within the Effective Field Theory of Large Scale Structure (EFT of LSS) enables field-level analyses that are robust to theoretical uncertainties. At the same time, they can maximize the constraining power from galaxy clustering on the scales amenable to perturbation theory. In order to apply the method to galaxy surveys, the forward model must account for the full observational complexity of the data. In this context, a major challenge is the inclusion of redshift space distortions (RSDs) from the peculiar motion of galaxies. Here, we present improvements in the efficiency and accuracy of the RSD modeling in the perturbative LEFTfield forward model. We perform a detailed quantification of the perturbative and numerical error for the prediction of momentum, velocity and the redshift-space matter density. Further, we test the recovery of cosmological parameters at the field level, namely the growth rate $f$, from simulated halos in redshift space. For a rigorous test and to scan through a wide range of analysis choices, we fix the linear (initial) density field to the known ground truth but marginalize over all unknown bias coefficients and noise amplitudes. With a third-order model for gravity and bias, our results yield <1\,\% statistical and <1.5\,\% systematic error. The computational cost of the redshift-space forward model is only $\sim 1.5$ times of the rest frame equivalent, enabling future field-level inference that simultaneously targets cosmological parameters and the initial matter distribution.

We present reconstructed convergence maps, \textit{mass maps}, from the Dark Energy Survey (DES) third year (Y3) weak gravitational lensing data set. The mass maps are weighted projections of the density field (primarily dark matter) in the foreground of the observed galaxies. We use four reconstruction methods, each is a \textit{maximum a posteriori} estimate with a different model for the prior probability of the map: Kaiser-Squires, null B-mode prior, Gaussian prior, and a sparsity prior. All methods are implemented on the celestial sphere to accommodate the large sky coverage of the DES Y3 data. We compare the methods using realistic $\Lambda$CDM simulations with mock data that are closely matched to the DES Y3 data. We quantify the performance of the methods at the map level and then apply the reconstruction methods to the DES Y3 data, performing tests for systematic error effects. The maps are compared with optical foreground cosmic-web structures and are used to evaluate the lensing signal from cosmic-void profiles. The recovered dark matter map covers the largest sky fraction of any galaxy weak lensing map to date.

For decades, the boundary of cosmic filaments have been a subject of debate. In this work, we determine the physically-motivated radii of filaments by constructing stacked galaxy number density profiles around the filament spines. We find that the slope of the profile changes with distance to the filament spine, reaching its minimum at approximately 1 Mpc at z = 0 in both state-of-the-art hydrodynamical simulations and observational data. This can be taken as the average value of the filament radius. Furthermore, we note that the average filament radius rapidly decreases from z = 4 to z = 1, and then slightly increases. Moreover, we find that the filament radius depends on the filament length, the distance from connected clusters, and the masses of the clusters. These results suggest a two-phase formation scenario of cosmic filaments. The filaments experience rapid contraction before z = 1, but their density distribution has remained roughly stable since then. The subsequent mass transport along the filaments to the connected clusters is likely to have contributed to the formation of the clusters themselves.

Deep learning (DL) has been shown to outperform traditional, human-defined summary statistics of the Ly{\alpha} forest in constraining key astrophysical and cosmological parameters owing to its ability to tap into the realm of non-Gaussian information. An understanding of the impact of nuisance effects such as noise on such field-level frameworks, however, still remains elusive. In this work we conduct a systematic investigation into the efficacy of DL inference from noisy Ly{\alpha} forest spectra. Building upon our previous, proof-of-concept framework (Nayak et al. 2024) for pure spectra, we constructed and trained a ResNet neural network using labeled mock data from hydrodynamical simulations with a range of noise levels to optimally compress noisy spectra into a novel summary statistic that is exclusively sensitive to the power-law temperature-density relation of the intergalactic medium. We fit a Gaussian mixture surrogate with 23 components through our labels and summaries to estimate the joint data-parameter distribution for likelihood free inference, in addition to performing inference with a Gaussian likelihood. The posterior contours in the two cases agree well with each other. We compared the precision and accuracy of our posterior constraints with a combination of two human defined summaries (the 1D power spectrum and PDF of the Ly{\alpha} transmission) that have been corrected for noise, over a wide range of continuum-to-noise ratios (CNR) in the likelihood case. We found a gain in precision in terms of posterior contour area with our pipeline over the said combination of 65% (at a CNR of 20 per 6 km/s) to 112% (at 200 per 6 km/s). While the improvement in posterior precision is not as large as in the noiseless case, these results indicate that DL still remains a powerful tool for inference even with noisy, real-world datasets.

Supernovae are an important source of energy in the interstellar medium. Young remnants of supernovae have a peak emission in the X-ray region, making them interesting objects for X-ray observations. In particular, the supernova remnant SN1006 is of great interest due to its historical record, proximity and brightness. It has therefore been studied by several X-ray telescopes. Improving the X-ray imaging of this and other remnants is important but challenging as it requires to address a spatially varying instrument response in order to achieve a high signal-to-noise ratio. Here, we use Chandra observations to demonstrate the capabilities of Bayesian image reconstruction using information field theory. Our objective is to reconstruct denoised, deconvolved and spatio-spectral resolved images from X-ray observations and to decompose the emission into different morphologies, namely diffuse and point-like. Further, we aim to fuse data from different detectors and pointings into a mosaic and quantify the uncertainty of our result. Utilizing prior knowledge on the spatial and spectral correlation structure of the two components, diffuse emission and point sources, the presented method allows the effective decomposition of the signal into these. In order to accelerate the imaging process, we introduce a multi-step approach, in which the spatial reconstruction obtained for a single energy range is used to derive an informed starting point for the full spatio-spectral reconstruction. The method is applied to 11 Chandra observations of SN1006 from 2008 and 2012, providing a detailed, denoised and decomposed view of the remnant. In particular, the separated view of the diffuse emission should provide new insights into its complex small-scale structures in the center of the remnant and at the shock front profiles.

This work aims at assessing the impact of DM self-interactions on the properties of galaxy clusters. In particular, the goal is to study the angular dependence of the cross section by testing rare (large angle scattering) and frequent (small angle scattering) SIDM models with velocity-dependent cross sections. We re-simulate six galaxy cluster zoom-in initial conditions with a dark matter only run and with a full-physics setup simulations that includes a self-consistent treatment of baryon physics. We test the dark matter only setup and the full physics setup with either collisionless cold dark matter, rare self-interacting dark matter, and frequent self-interacting dark matter models. We then study their matter density profiles as well as their subhalo population. Our dark matter only SIDM simlations agree with theoretical models, and when baryons are included in simulations, our SIDM models substantially increase the central density of galaxy cluster cores compared to full-physics simulations using collisionless dark matter. SIDM subhalo suppression in full-physics simulations is milder compared to the one found in dark matter only simulations, because of the cuspier baryionic potential that prevent subhalo disruption. Moreover SIDM with small-angle scattering significantly suppress a larger number of subhaloes compared to large angle scattering SIDM models. Additionally, SIDM models generate a broader range of subhalo concentration values, including a tail of more diffuse subhaloes in the outskirts of galaxy clusters and a population of more compact subhaloes in the cluster cores.

Galaxies with high star-formation rate surface densities often host large-scale outflows that redistribute energy, momentum, and baryons between the interstellar medium and the halo, making them a key feedback channel regulating galaxy evolution. Despite their importance, the driving physics behind galactic outflows and their interaction with the surrounding halo is yet to be fully understood. In particular, the influence of a pre-existing reservoir of cosmic rays (CRs) in galaxy halos has not been clearly established. We determine the conditions required to launch outflows in the presence of halo CRs and investigate how CR pressure gradients modify outflow speeds. We find that CR halos suppress the development of large-scale, CR-driven winds and redirect CR feedback toward local recycling flows. Slow outflows are therefore more likely in young galaxies lacking extended CR halos, while fast winds in intense starbursts are dominated by momentum injection and largely unaffected by halo CRs.

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 $S_8\equiv \sigma_8\sqrt{\Omega_{\rm m}/0.3} = 0.814^{+0.011}_{-0.012}$ and $\sigma_8 = 0.802^{+0.022}_{-0.018}$.

We revisit the Quasar Main Sequence (QMS) by investigating the impact of the stellar component from the host galaxy (HG) on the emission line spectra of the active galactic nuclei (AGN). We first detect spectra with broad emission lines using a line ratio method for a sample of $\sim$3000 high SNR (>20) Black Hole Mapper objects (part of the fifth phase of the Sloan Digital Sky Survey). We then built the Index diagram, a novel diagnostic tool using the $z$-corrected spectra, model-free, designed to easily identify spectra with significant stellar HG contributions and to classify the AGN spectra into three categories based on AGN-HG dominance: HG-dominated (HGD), Intermediate (INT), and AGN-dominated (AGND) sources. A colour-$z$ diagram was used to refine the AGN-HG classification. We subtract the stellar contributions from the HGD and INT spectra before modeling the AGN spectrum to extract the QMS parameters. Our QMS reveals that HGD galaxies predominantly occupy the Population B region with no \rfe, %FWHM$\gtrsim$4000 \kms, with outliers exhibiting \rfe\ > 1, likely due to HG subtraction residuals and a faint contribution of \hbbc. INT and AGND spectra show similar distributions in the Population A %FWHM(\hbbc)<4000 \kms\ region, while in Population B, %For broader lines, a tail of AGND sources becomes apparent. Cross-matching with radio, infrared, and X-ray catalogs, we find that the strongest radio emitters are associated with HGD and INT groups. Strong X-ray emitters are found in INT and AGND sources, also occupying the AGN region in the WISE colour diagram.

Various so-called anomalies have been found in both the WMAP and Planck cosmic microwave background (CMB) temperature data that exert a mild tension against the highly successful best-fit 6 parameter cosmological model, potentially providing hints of new physics to be explored. That these are real features on the sky is uncontested. However, given their modest significance, whether they are indicative of true departures from the standard cosmology or simply statistical excursions, due to a mildly unusual configuration of temperature anisotropies on the sky which we refer to as the "fluke hypothesis", cannot be addressed further without new information. No theoretical model of primordial perturbations has to date been constructed that can explain all of the temperature anomalies. Therefore, we focus in this paper on testing the fluke hypothesis, based on the partial correlation between the temperature and $E$-mode CMB polarisation signal. In particular, we compare the properties of specific statistics in polarisation, built from unconstrained realisations of the $\Lambda$CDM cosmological model as might be observed by the LiteBIRD satellite, with those determined from constrained simulations, where the part of the $E$-mode anisotropy correlated with temperature is constrained by observations of the latter. Specifically, we use inpainted Planck 2018 SMICA temperature data to constrain the $E$-mode realisations. Subsequent analysis makes use of masks defined to minimise the impact of the inpainting procedure on the $E$-mode map statistics. We find that statistical assessments of the $E$-mode data alone do not provide any evidence for or against the fluke hypothesis. However, tests based on cross-statistical measures determined from temperature and $E$ modes can allow this hypothesis to be rejected with a moderate level of probability.

Observational cosmology in the next decade will rely on probes of the distribution of matter in the redshift range between $0

We identify a chain of galaxies along an almost straight line in the nearby Universe with a projected length of ~5 Mpc. The galaxies are distributed within projected distances of only 7-105 kpc from the axis of the identified filament. They have redshifts in a very small range of z=0.0361-0.0370 so that their radial velocities are consistent with galaxy proper motions. The filament galaxies are mainly star-forming and have stellar masses in a range of $\rm 10^{9.1}-10^{10.7}\,M_{\odot}$. We search for systems with similar geometrical properties in the full-sky mock galaxy catalogue of the MillenniumTNG simulations and find that although such straight filaments are unusual and rare, they are predicted by $\Lambda$CDM simulations (4% incidence). We study the cold HI gas in a 1.3 Mpc section of the filament through HI-21cm emission line observations and detect eleven HI sources, many more than expected from the HI mass function in a similar volume. They have HI masses $\rm 10^{8.5}-10^{9.5}\,M_{\odot}$ and are mostly within ~120 kpc projected distance from the filament axis. None of these HI sources has a confirmed optical counterpart. Their darkness together with their large HI-21cm line-widths indicate that they contain gas that might not yet be virialized. These clouds must be marking the peaks of the dark matter and HI distributions over large scales within the filament. The presence of such gas clouds around the filament spines is predicted by simulations, but this is the first time that the existence of such clouds in a filament is observationally confirmed.

Recent cosmological analyses measuring distances of Type Ia Supernovae (SNe Ia) and Baryon Acoustic Oscillations (BAO) have all given similar hints at time-evolving dark energy. To examine whether underestimated SN Ia systematics might be driving these results, Efstathiou (2024) compared overlapping SN events between Pantheon+ and DES-SN5YR (20% SNe are in common), and reported evidence for a $\sim$0.04 mag offset between the low and high-redshift distance measurements of this subsample of events. If these offsets are arbitrarily subtracted from the entire DES-SN5YR sample, the preference for evolving dark energy is reduced. In this paper, we reproduce this offset and show that it has two sources. First, 43% of the offset is due to DES-SN5YR improvements in the modelling of supernova intrinsic scatter and host galaxy properties. These are scientifically-motivated modelling updates implemented in DES-SN5YR and their associated uncertainties are captured within the DES-SN5YR systematic error budget. Even if the less accurate scatter model and host properties from Pantheon+ are used instead, the DES-SN5YR evidence for evolving dark energy is only reduced from 3.9$\sigma$ to 3.3$\sigma$. Second, 38% of the offset is due to a misleading comparison because different selection functions characterize the DES subsets included in Pantheon+ and DES-SN5YR and therefore individual SN distance measurements are expected to be different because of different bias corrections. In conclusion, we confirm the validity of the published DES-SN5YR results.

Halo occupation distribution (HOD) models describe the number of galaxies that reside in different haloes, and are widely used in galaxy-halo connection studies using the halo model (HM). Here, we introduce and study HOD response functions $R_\mathcal{O}^g$ that describe the response of the HODs to long-wavelength perturbations $\mathcal{O}$. The linear galaxy bias parameters $b_\mathcal{O}^g$ are a weighted version of $b_\mathcal{O}^h + R_\mathcal{O}^g$, where $b_\mathcal{O}^h$ is the halo bias, but the contribution from $R_\mathcal{O}^g$ is routinely ignored in the literature. We investigate the impact of this by measuring the $R_\mathcal{O}^g$ in separate universe simulations of the IllustrisTNG model for three types of perturbations: total matter perturbations, $\mathcal{O}=\delta_m$; baryon-CDM compensated isocurvature perturbations, $\mathcal{O}=\sigma$; and potential perturbations with local primordial non-Gaussianity, $\mathcal{O}\propto f_{\rm NL}\phi$. Our main takeaway message is that the $R_\mathcal{O}^g$ are not negligible in general and their size should be estimated on a case-by-case basis. For stellar-mass selected galaxies, the responses $R_\phi^g$ and $R_\sigma^g$ are sizeable and cannot be neglected in HM calculations of the bias parameters $b_\phi^g$ and $b_\sigma^g$; this is relevant to constrain inflation using galaxies. On the other hand, we do not detect a strong impact of the HOD response $R_1^g$ on the linear galaxy bias $b_1^g$. These results can be explained by the impact that the perturbations have on stellar-to-total-mass relations. We also look into the impact on the bias of the gas distribution and find similar conclusions. We show that a single extra parameter describing the overall amplitude of $R_\mathcal{O}^g$ recovers the measured $b_\mathcal{O}^g$ well, which indicates that $R_\mathcal{O}^g$ can be easily added to HM/HOD studies as a new ingredient.