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Adi Nusser

Publications and source records attributed to Adi Nusser.

At least 19 recordsLinked to original sources

Cosmicflows-4 and the Cosmological Consistency of Large-Scale Motions

We study coherent flows in Cosmicflows-4 (CF4) and its constituent catalogs. We fit monopole and dipole moments in nonoverlapping radial bins using a log-distance radial-velocity estimator. For each sample, the Planck 2018 $\Lambda$CDM prediction accounts for the actual positions, statistical weights, velocity covariance, and measurement covariance. Across six bins extending to $300,h^{-1},\mathrm{Mpc}$, the All Individual sample is broadly consistent with $\Lambda$CDM, with dipole and joint deviations of $2.29\sigma$ and $2.36\sigma$. The strongest localized feature occurs at $120$--$160,h^{-1},\mathrm{Mpc}$, where $|V_{\rm dip}|=628\pm82,\mathrm{km,s^{-1}}$ and the dipole deviation reaches $3.40\sigma$. The excess is concentrated toward negative supergalactic X and depends strongly on the survey window. TFR and 6dFGS favor larger dipoles, while SDSS and SN favor smaller ones. Removing 6dFGS reduces the upper-bin dipole deviation to $1.56\sigma$, while removing SN raises it to $3.77\sigma$. Nevertheless, the SN and 6dFGS dipoles remain mutually consistent when their covariance is included. SDSS is consistent with $\Lambda$CDM through $160,h^{-1},\mathrm{Mpc}$ but shows a separate rise at larger radii whose significance depends on the treatment of the monopole and shared distance-scale covariance. Overall, CF4 does not show uniformly anomalous motion across its full radial range. Instead, it contains localized and window-dependent features that should be tested with selection-matched mock catalogs and correlated calibration uncertainties.

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Bayesian Reconstruction of the Local Universe from 2MRS: Testing the Gravitational Flow with Cosmicflows-4

We present a Bayesian reconstruction of the local density and velocity fields traced by the 2MASS Redshift Survey (2MRS) and test the inferred gravitational flow against independent Cosmicflows-4 (CF4) galaxy-group peculiar velocities. The fiducial reconstruction is the maximum-a-posteriori (MAP) solution of a Zel'dovich-approximation forward model, constrained by the 2MRS redshift-space distribution through an unbinned Poisson point-process likelihood. The model assumes Gaussian initial conditions and includes the 2MRS selection function, the Zone of Avoidance, redshift-space distortions, and a distance-dependent galaxy-bias prescription. The MAP field is obtained by optimization of the posterior, while Hamiltonian Monte Carlo is used to draw posterior samples and constrained realizations within the same framework. The reconstructed velocity field agrees well with CF4 in object-by-object, density--velocity-correlation, and shell-by-shell reflex-dipole tests. These comparisons are made at the CF4 redshift-space positions and do not require smoothing the observed CF4 velocities to the MAP resolution. We also evolve constrained initial conditions with Gadget-4. The real-space density retains the large-scale Zel'dovich structure while developing additional nonlinear small-scale structure, and the redshift-space distribution develops nonlinear Fingers of God. The results show that the 2MRS field-level reconstruction captures the large-scale gravitational flow of the nearby Universe and provides initial conditions suitable for constrained simulations.

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On distance and velocity estimation in cosmology

Scatter in distance indicators introduces two conceptually distinct systematic biases when reconstructing peculiar velocity fields from redshifts and distances. The first is distance Malmquist bias (dMB) that affects individual distance estimates and can in principle be approximately corrected. The second is velocity Malmquist bias (vMB) that arises when constructing continuous velocity fields from scattered distance measurements: random scatter places galaxies at noisy spatial positions, introducing spurious velocity gradients that persist even when distances are corrected for dMB. Considering the Tully-Fisher relation as a concrete example, both inverse and forward formulations yield unbiased individual peculiar velocities for galaxies with the same true distance (the forward relation requires a selection-dependent correction), but neither eliminates vMB when galaxies are placed at their inferred distances. We develop a modified Wiener filter that properly encodes correlations between directly observed distance $d$ and true distance $r$ through the conditional probability $P(r|d)$, accounting for the distribution of true distances sampled by galaxies at observed distance $d$. Nonetheless, this modified filter yields suppressed amplitude estimates. Since machine learning autoencoders converge to the Wiener filter for Gaussian fields, they are unlikely to significantly improve velocity field estimation. We therefore argue that optimal reconstruction places galaxies at their observed redshifts rather than inferred distances; an approach effective when distance errors exceed $\sigma_v/H_0$, a condition satisfied for most galaxies in typical surveys beyond the nearby volume.

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Probing the Dark Sector using the Fornax Satellite

A long-range force acting only in the dark sector can displace the stellar component of satellite galaxies relative to their dark matter (DM) halos, thereby \emph{breaking} the weak equivalence principle (WEP) between DM and baryons. We investigate observational signatures of such WEP breaking using $N$-body simulations of a Fornax-like Milky Way (MW) satellite, implementing a fifth force between DM particles of amplitude $\beta$ relative to Newtonian gravity (with a screening length much larger than the MW halo size). We find that $\beta \gtrsim 0.6$ strips and unbinds the bulk of the stellar component, leaving at most a negligible bound remnant that fails to match the observed stellar content, surface-brightness, and line-of-sight velocity-dispersion profiles of Fornax. By contrast, $\beta \lesssim 0.2$ yields only mild stellar stripping and remains broadly consistent with current photometric and kinematic constraints within our modeling assumptions.

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Estimating cluster masses: a comparative study between machine learning and maximum likelihood

We compare an autoencoder convolutional neural network (AE-CNN) with a conventional maximum-likelihood estimator (MLE) for inferring cluster virial masses, $M_v$, directly from the galaxy distribution around clusters, without identifying members or interlopers. The AE-CNN is trained on mock galaxy catalogues, whereas the MLE assumes that clusters of similar mass share the same phase-space galaxy profile. Conceptually, the MLE returns an unbiased estimate of $\log M_v$ at fixed true mass, whereas the AE-CNN approximates the posterior mean, so the true $\log M_v$ is unbiased at fixed estimate. Using MDPL2 mock clusters with redshift space number density as input, the AE-CNN attains an rms scatter of $0.10\,\textrm{dex}$ between predicted and true $\log M_v$, compared with $0.16\,\textrm{dex}$ for the MLE. With inputs based on mean peculiar velocities, binned in redshift space or observed distance, the AE-CNN achieves scatters of $0.12\,\textrm{dex}$ and $0.16\,\textrm{dex}$, respectively, despite strong inhomogeneous Malmquist bias.

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High-redshift halo-galaxy connection via constrained simulations

The evolution of halos with masses around $M_\textrm{h} \approx 10^{11}\; \textrm{M}_\odot$ and $M_\textrm{h} \approx 10^{12}\; \textrm{M}_\odot$ at redshifts $z>9$ is examined using constrained N-body simulations. {The average specific mass accretion rates, $\dot{M}_\textrm{h} / M_\textrm{h}$, exhibit minimal mass dependence and generally agree with existing literature. Individual halo accretion histories, however, vary substantially. } About one-third of simulations reveal an increase in $\dot{M}_\textrm{h}$ around $z\approx 13$. Comparing simulated halos with observed galaxies having spectroscopic redshifts, we find that for galaxies at $z\gtrsim9$, the ratio between observed star formation rate (SFR) and $\dot{M}_\textrm{h}$ is approximately $2\%$. This ratio remains consistent for the stellar-to-halo mass ratio (SHMR) but only for $z\gtrsim 10$. At $z\simeq 9$, the SHMR is notably lower by a factor of a few. At $z\gtrsim10$, there is an agreement between specific star formation rates (sSFRs) and $\dot{M}_\textrm{h} / M_\textrm{h}$. However, at $z\simeq 9$, observed sSFRs exceed simulated values by a factor of two. It is argued that the mildly elevated SHMR in high-$z$ halos with $M_\textrm{h} \approx 10^{11} M_{\odot}$, can be achieved by assuming the applicability of the local Kennicutt-Schmidt law and a reduced effectiveness of stellar feedback due to deeper gravitational potential of high-$z$ halos of a fixed mass.

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Neural network reconstruction of density and velocity fields from the 2MASS Redshift Survey

We reconstruct the 3D matter density and peculiar velocity fields in the local Universe up to a distance of 200$\,h^{-1}\,$Mpc from the Two-Micron All-Sky Redshift Survey (2MRS), using a neural network (NN). We employed an NN with a U-net autoencoder architecture and a weighted mean squared error loss function trained separately to output either the density or velocity field for a given input grid of galaxy number counts. The NN was trained on mocks derived from the Quijote N-body simulations, incorporating redshift-space distortions (RSDs), galaxy bias, and selection effects closely mimicking the characteristics of 2MRS. The trained NN was benchmarked against a standard Wiener filter (WF) on a validation set of mocks before applying it to 2MRS. The NN reconstructions effectively approximate the mean posterior estimate of the true density and velocity fields conditioned on the observations. They consistently outperform the WF in terms of reconstruction accuracy and effectively capture the nonlinear relation between velocity and density. The NN-reconstructed bulk flow of the total survey volume exhibits a significant correlation with the true mock bulk flow, demonstrating that the NN is sensitive to information on super-survey scales encoded in the RSDs. When applied to 2MRS, the NN successfully recovers the main known clusters, some of which are partially in the Zone of Avoidance. The reconstructed bulk flows in spheres of different radii less than 100$\,h^{-1}\,$Mpc are in good agreement with a previous 2MRS analysis that required an additional external bulk flow component inferred from directly observed peculiar velocities. The NN-reconstructed peculiar velocity of the Local Group closely matches the observed Cosmic Microwave Background dipole in amplitude and Galactic latitude, and only deviates by 18${}^\circ$ in longitude. The NN-reconstructed fields are publicly available.

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Which came first: supermassive black holes or galaxies? Insights from JWST

Insights from JWST observations suggest that AGN feedback evolved from a short-lived, high redshift phase in which radiatively cooled turbulence and/or momentum-conserving outflows stimulated vigorous early star formation (``positive'' feedback), to late, energy-conserving outflows that depleted halo gas reservoirs and quenched star formation. The transition between these two regimes occurred at $z\sim 6$, independently of galaxy mass, for simple assumptions about the outflows and star formation process. Observational predictions provide circumstantial evidence for the prevalence of massive black holes at the highest redshifts hitherto observed, and we discuss their origins.

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Large-scale density and velocity field reconstructions with neural networks

We assess a neural network (NN) method for reconstructing 3D cosmological density and velocity fields (target) from discrete and incomplete galaxy distributions (input). We employ second-order Lagrangian Perturbation Theory to generate a large ensemble of mock data to train an autoencoder (AE) architecture with a Mean Squared Error (MSE) loss function. The AE successfully captures nonlinear features arising from gravitational dynamics and the discreteness of the galaxy distribution. It preserves the positivity of the reconstructed density field and exhibits a weaker suppression of the power on small scales than the traditional linear Wiener filter (WF), which we use as a benchmark. In the density reconstruction, the reduction of the AE MSE relative to the WF is $\sim 15 \%$, whereas, for the velocity reconstruction, a relative reduction of up to a factor of two can be achieved. The AE is advantageous to the WF at recovering the distribution of the target fields, especially at the tails. In fact, trained with an MSE loss, any NN estimate approaches the unbiased mean of the underlying target given the input. This implies a slope of unity in the linear regression of the true on the NN-reconstructed field. Only for the special case of Gaussian fields, the NN and WF estimates are equivalent. Nonetheless, we also recover a linear regression slope of unity for the WF with non-Gaussian fields.

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The clustering properties of AGNs/quasars in CatWISE2020 catalog

We study the clustering properties of 1,307,530 AGNs/quasars in the CatWISE2020 catalog prepared using the Wide-field Infrared Survey Explorer (WISE) and Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE) survey data. For angular moments $\ell \gtrapprox 10$ ($\lessapprox 18^\circ$) down to non-linear scales, the results are in agreement with the standard $Λ$CDM cosmology, with a galaxy bias roughly matching that of the NRAO VLA Sky Survey (NVSS) AGNs. We further explore the redshift dependence of the fraction of infrared bright AGNs on stellar mass, $f_{\rm IB} \sim M_*^{α_0 + α_1 z}$, and find $α_1=1.27^{+0.25}_{-0.30}$, ruling out a non-evolution hypothesis at $\approx 4.6σ$ confidence level. The results are consistent with the measurements obtained with NVSS AGNs, though considerably more precise thanks to the significantly higher number density of objects in CatWISE2020. The excess dipole and high clustering signal above angular scale $\approx 18^\circ$ remain anomalous.

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Analytic solution to the dynamical friction acting on circularly moving perturbers

We present an analytic approach to the dynamical friction (DF) acting on a circularly moving point mass perturber in a gaseous medium. We demonstrate that, when the perturber is turned on at $t=0$, steady-state (infinite time perturbation) is achieved after exactly one sound-crossing time. At low Mach number $\mathcal{M}~\ll~1$, the circular-motion steady-state DF converges to the linear-motion, finite time perturbation expression. The analytic results describe both the radial and tangential forces on the perturbers caused by the backreaction of the wake propagating in the medium. The radial force is directed inward, toward the motion centre, and is dominant at large Mach numbers. For subsonic motion, this component is negligible. For moderate and low Mach numbers, the tangential force is stronger and opposes the motion of the perturber. The analytic solution to the circular-orbit DF suffers from a logarithmic divergence in the supersonic regime. This divergence appears at short distances from the perturber solely (unlike the linear motion result which is also divergent at large distances) and can be encoded in a maximum multipole. This is helpful to assess the resolution dependence of numerical simulations implementing DF at the level of Liénard-Wiechert potentials. We also show how our approach can be generalised to calculate the DF acting on a compact circular binary.

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Regulation of star formation by large scale gravito-turbulence

A simple model for star formation based on supernova (SN) feedback and gravitational heating via the collapse of perturbations in gravitationally unstable disks reproduces the Schmidt-Kennicutt relation between the star formation rate (SFR) per unit area, $Σ_{SFR}$, and the gas surface density, $Σ_g$, remarkably well. The gas velocity dispersion, $σ_g$, is derived self-consistently in conjunction with $Σ_{SFR}$ and is found to match the observations. Gravitational instability triggers {"gravito-turbulence"} at the scale of the least stable perturbation mode, boosting $σ_g$ at $Σ_g> \, Σ_g^\textrm{thr}=50\, {\rm M}_\odot\, {\rm pc}^{-2}$, and contributing to the pressure needed to carry the disk weight vertically. $Σ_{SFR}$ is reduced to the observed level at $ Σ_g > Σ_g^\textrm{thr}$, whereas at lower surface densities, SN feedback is the prevailing energy source. Our proposed star formation recipes require efficiencies of order 1\%, and the Toomre parameter, $Q$, for the joint gaseous and stellar disk is predicted to be close to the critical value for marginal stability for $Σ_g< \, Σ_g^\textrm{thr}$, spreading to lower values and larger gas velocity dispersion at higher $Σ_g$.

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Constrained realizations of 2MRS density and peculiar velocity fields: growth rate and local flow

We generate constrained realizations (CRs) of the density and peculiar velocity fields within $200 \; h^{-1} \, \mathrm{Mpc}$ from the final release of the Two-Micron All-Sky Redshift Survey (2MRS) $-$ the densest all-sky redshift survey to date. The CRs are generated by combining a Wiener filter estimator in spherical Fourier-Bessel space with random realizations of log-normally distributed density fields and Poisson-sampled galaxy positions. The algorithm is tested and calibrated on a set of semi-analytic mock catalogs mimicking the environment of the Local Group (LG), to rigorously account for the statistical and systematic errors of the reconstruction method. By comparing our peculiar velocity CRs with the observed velocities from the Cosmicflows-3 catalog, we constrain the normalized linear growth rate to $f σ_8^\mathrm{lin} = 0.367 \pm 0.060$, which is consistent at the $1.1 σ$ level with the latest Planck results as well as other direct probes. Simultaneously, we estimate a bulk flow contribution from sources beyond the 2MRS reconstruction volume of $B^\mathrm{ext} = 199 \pm 68 \; \mathrm{km} \, \mathrm{s}^{-1}$ towards $l = 299 \pm 18^\circ$, $b = 8 \pm 19^\circ$. The total reconstructed velocity field at the position of the LG, smoothed with a $1 \; h^{-1} \, \mathrm{Mpc}$ Gaussian, is $685 \pm 75 \; \mathrm{km} \, \mathrm{s}^{-1}$ towards $l = 270.6 \pm 6.6^\circ$, $b = 35.5 \pm 7.2^\circ$, in good agreement with the observed CMB dipole. The total reconstructed bulk flow within different radii is compatible with other measurements. Within a $50 \; h^{-1} \, \mathrm{Mpc}$ Gaussian window we find a bulk flow of $274 \pm 50 \; \mathrm{km} \, \mathrm{s}^{-1}$ towards $l = 287 \pm 9^\circ$, $b = 11 \pm 10^\circ$. The code used to generate the CRs and obtain these results, dubbed CORAS, is made publicly available.

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From Cosmicflows distance moduli to unbiased distances and peculiar velocities

Surveys of galaxy distances and radial peculiar velocities can be used to reconstruct the large scale structure. Other than systematic errors in the zero-point calibration of the galaxy distances the main source of uncertainties of such data are errors on the distance moduli, assumed here to be Gaussian and thus turn into lognormal errors on distances and velocities. Naively treated, it leads to spurious nearby outflow and strong infall at larger distances. The lognormal bias is corrected here and tested against mock data extracted from a $Λ$CDM simulation, designed to statistically follow the grouped Cosmicflows-3 (CF3) data. Considering a subsample of data points, all of which have the same true distances or same redshifts, the lognormal bias arises because the means of the distributions of observed distances and velocities are skewed off the means of the true distances and velocities. Yet, the medians are invariant under the lognormal transformation. That invariance allows the Gaussianization of the distances and velocities and the removal of the lognormal bias. This Bias Gaussianization correction (BGc) algorithm is tested against mock CF3 catalogs. The test consists of a comparison of the BGC estimated with the simulated distances and velocities and of an examination of the Wiener filter reconstruction from the BGc data. Indeed, the BGc eliminates the lognormal bias. The estimation of Hubble's ($H_{0}$) constant is also tested. The residual of the BGc estimated $H_{0}$ from the simulated values is $0.6 \pm 0.7 {\rm kms}^{-1}{\rm Mpc}^{-1}$ and is dominated by the cosmic variance. The BGc correction of the actual CF3 data yields $H_{0} = 75.8 \pm 1.1 {\rm kms}^{-1}{\rm Mpc}^{-1}$ .

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Biasing relation, environmental dependencies and estimation of the growth rate from star forming galaxies

The connection between galaxy star formation rate (SFR) and dark matter (DM) is of paramount importance for the extraction of cosmological information from next generation spectroscopic surveys that will target emission line star forming galaxies. Using publicly available mock galaxy catalogs obtained from various semi-analytic models (SAMs) we explore the SFR-DM connection in relation to the speed-from-light method (Feix et al. 2016) for inferring the growth rate, $f$, from luminosity/SFR shifts. Emphasis is given to the dependence of the SFR distribution on the environment density on scales of 10s-100s Mpc. We show that the application of the speed-from-light method to an Euclid-like survey is not biased by environmental effects. In all models, the precision on the measured $β=f/b$ parameter is $σ_β< 0.17$ at $z=1$. This translates into errors of $σ_f \sim 0.22$ and $σ_{(fσ_8)}\sim 0.1$, without invoking assumptions on the mass power spectrum. These errors are in the same ballpark as recent analyses of the redshift space distortions in galaxy clustering. In agreement with previous studies, the bias factor, $b$ is roughly a scale-independent, constant function of the SFR for star forming galaxies. Its value at $z=1$ ranges from $1.2$ to $1.5$ depending on the SAM recipe. Although in all SAMs denser environments host galaxies with higher stellar masses, the dependence of the SFR on the environment is more involved. In most models the SFR probability distribution is skewed to larger values in denser regions. One model exhibits an inverted trend where high SFR is suppressed in dense environment.

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Axion core - halo mass and the black hole - halo mass relation: constraints on a few parsec scales

If the dark matter is made of ultra-light axions, stable solitonic cores form at the centers of virialized halos. In some range for the mass $m$ of the axion particle, these cores are sufficiently compact and can mimic supermassive black holes (SMBH) residing at galactic nuclei. We use the solitonic core--halo mass relation, validated in numerical simulations, to constrain a new range of allowed axion mass from measurements of the SMBH mass in (pseudo)bulge and bulgeless galaxies. These limits are based on observations of galactic nuclei on scales smaller than 10 pc. Our analysis suggests that $m < 10^{-18}$ eV is ruled out by the data. We briefly discuss whether an attractive self-interaction among axions could alleviate this constraint.

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A scenario for ultra-diffuse satellite galaxies with low velocity dispersions: the case of [KKS 2000]04

A scenario for achieving a low velocity dispersion for the galaxy [KKS 2000]04 (aka NGC 1052-DF2) and similar galaxies is presented. A progenitor halo corresponding to a $z=0$ halo of mass $\sim 5\times 10^{10}\; \textrm{M}_\odot$ and a low concentration parameter (but consistent with cosmological simulations) infalls onto a Milky Way-size host at early times. {Substantial removal of cold gas} from the inner regions by supernova feedback and ram pressure, assisted by tidal stripping of the dark matter in the outer regions, leads to a substantial reduction of the velocity dispersion of stars within one effective radius. In this framework, the observed stellar content of [KKS 2000]04 is associated with a progenitor mass close to that inferred from the global stellar-to-halo-mass ratio. As far as the implications of kinematics are concerned, even if at a $\sim 20 $ Mpc distance, it is argued that [KKS 2000]04 is no more peculiar than numerous early type galaxies with seemingly little total dark-matter content.

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Towards a higher mass for NGC1052-DF2: an analysis based on full distribution functions

It is demonstrated that the kinematics of the 10 star clusters in NGC2052-DF2 is compatible with a high dynamical mass close to those implied by the standard stellar-to-halo-mass ratio (SHMR). The analysis relies on a convenient form for the distribution function (DF) of projected phase space data, capturing non-gaussian features in the spread of true velocities of the mass tracers. A key ingredient is tidal stripping by the gravity of the apparently nearby larger galaxy, NGC 1052. Tidal stripping decreases the range of velocities of mass tracers, while only mildly lowering the total mass inside the trimming radius $r_{tr}$. The analysis is performed assuming halo profiles consistent with simulations of the $Λ$CDM model. For the fiducial value $r_{tr}=10$ kpc, we find that the virial mass of the pre-trimmed halo is $M<1.6\times 10^{10}M_\odot$ at $2σ$ ($95\%$) and $M<8.6\times 10^{9}M_\odot$ at $1.64σ$ ($90\%$). For the mass within 10 kpc we obtain, $M_\mathrm{10kpc}<3.9\times 10^{9}M_\odot$ and $<2.9\times 10^{9}M_\odot$ at $2σ$ and $1.64σ$, respectively. The $2σ$ upper limit on the virial mass is roughly a factor of 3-5 below the mean SHMR relation.Taking $r_{tr}=20$ kpc, lowers the $2σ$ virial mass limits by a factor of $\sim 4 $, bringing our results closer to those of Wasserman et al. (2018) without their SHMR prior.

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