arXiv subjects

Nicholas Battaglia

Publications and source records attributed to Nicholas Battaglia.

At least 73 records · Page 4Linked to original sources

arXiv2021

The Atacama Cosmology Telescope: Probing the Baryon Content of SDSS DR15 Galaxies with the Thermal and Kinematic Sunyaev-Zel'dovich Effects

We present high signal-to-noise measurements (up to 12$σ$) of the average thermal Sunyaev Zel'dovich (tSZ) effect from optically selected galaxy groups and clusters and estimate their baryon content within a 2.1$^\prime$ radius aperture. Sources from the Sloan Digital Sky Survey (SDSS) Baryon Oscillation Spectroscopic Survey (BOSS) DR15 catalog overlap with 3,700 sq. deg. of sky observed by the Atacama Cosmology Telescope (ACT) from 2008 to 2018 at 150 and 98 GHz (ACT DR5), and 2,089 sq. deg. of internal linear combination component-separated maps combining ACT and $\it{Planck}$ data (ACT DR4). The corresponding optical depths, $\barτ$, which depend on the baryon content of the halos, are estimated using results from cosmological hydrodynamic simulations assuming an AGN feedback radiative cooling model. We estimate the mean mass of the halos in multiple luminosity bins, and compare the tSZ-based $\barτ$ estimates to theoretical predictions of the baryon content for a Navarro-Frenk-White profile. We do the same for $\barτ$ estimates extracted from fits to pairwise baryon momentum measurements of the kinematic Sunyaev-Zel'dovich effect (kSZ) for the same data set obtained in a companion paper. We find that the $\barτ$ estimates from the tSZ measurements in this work and the kSZ measurements in the companion paper agree within $1σ$ for two out of the three disjoint luminosity bins studied, while they differ by 2-3$σ$ in the highest luminosity bin. The optical depth estimates account for one third to all of the theoretically predicted baryon content in the halos across luminosity bins. Potential systematic uncertainties are discussed. The tSZ and kSZ measurements provide a step towards empirical Compton-$\bar{y}$-$\barτ$ relationships to provide new tests of cluster formation and evolution models.

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arXiv2021

The CAMELS project: Cosmology and Astrophysics with MachinE Learning Simulations

We present the Cosmology and Astrophysics with MachinE Learning Simulations --CAMELS-- project. CAMELS is a suite of 4,233 cosmological simulations of $(25~h^{-1}{\rm Mpc})^3$ volume each: 2,184 state-of-the-art (magneto-)hydrodynamic simulations run with the AREPO and GIZMO codes, employing the same baryonic subgrid physics as the IllustrisTNG and SIMBA simulations, and 2,049 N-body simulations. The goal of the CAMELS project is to provide theory predictions for different observables as a function of cosmology and astrophysics, and it is the largest suite of cosmological (magneto-)hydrodynamic simulations designed to train machine learning algorithms. CAMELS contains thousands of different cosmological and astrophysical models by way of varying $Ω_m$, $σ_8$, and four parameters controlling stellar and AGN feedback, following the evolution of more than 100 billion particles and fluid elements over a combined volume of $(400~h^{-1}{\rm Mpc})^3$. We describe the simulations in detail and characterize the large range of conditions represented in terms of the matter power spectrum, cosmic star formation rate density, galaxy stellar mass function, halo baryon fractions, and several galaxy scaling relations. We show that the IllustrisTNG and SIMBA suites produce roughly similar distributions of galaxy properties over the full parameter space but significantly different halo baryon fractions and baryonic effects on the matter power spectrum. This emphasizes the need for marginalizing over baryonic effects to extract the maximum amount of information from cosmological surveys. We illustrate the unique potential of CAMELS using several machine learning applications, including non-linear interpolation, parameter estimation, symbolic regression, data generation with Generative Adversarial Networks (GANs), dimensionality reduction, and anomaly detection.

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arXiv2021

Debiased Galaxy Cluster Pressure Profiles from X-ray Observations and Simulations

We present an updated model for the average cluster pressure profile, adjusted for hydrostatic mass bias by combining results from X-ray observations with cosmological simulations. Our model estimates this bias by fitting a power-law to the relation between the "true" halo mass and X-ray cluster mass in hydrodynamic simulations (IllustrisTNG, BAHAMAS, and MACSIS). As an example application, we consider the REXCESS X-ray cluster sample and the Universal Pressure Profile (UPP) derived from scaled and stacked pressure profiles. We find adjusted masses, $M_\mathrm{500c},$ that are $\lesssim$15% higher and scaled pressures $P/P_\mathrm{500c}$ that have $\lesssim$35% lower normalization than previously inferred. Our Debiased Pressure Profile (DPP) is well-fit by a Generalized Navarro-Frenk-White (GNFW) function, with parameters $[P_0,c_{500},α,β,γ]=[5.048,1.217,1.192,5.490,0.433]$ and does not require a mass-dependent correction term. When the DPP is used to model the Sunyaev-Zel'dovich (SZ) effect, we find that the integrated Compton $Y-M$ relation has only minor deviations from self-similar scaling. The thermal SZ angular power spectrum is lower in amplitude by approximately 30%, assuming nominal cosmological parameters (e.g. $Ω_\text{m}=0.3$, $σ_8 = 0.8$), and is broadly consistent with recent Planck results without requiring additional bias corrections.

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arXiv2021

Towards 1% accurate galaxy cluster masses: Including baryons in weak-lensing mass inference

Galaxy clusters are a promising probe of late-time structure growth, but constraints on cosmology from cluster abundances are currently limited by systematics in their inferred masses. One unmitigated systematic effect in weak-lensing mass inference is ignoring the presence of baryons and treating the entire cluster as a dark matter halo. In this work we present a new flexible model for cluster densities that captures both the baryonic and dark matter profiles, a new general technique for calculating the lensing signal of an arbitrary density profile, and a methodology for stacking those lensing signal to appropriately model stacked weak-lensing measurements of galaxy cluster catalogues. We test this model on 1400 simulated clusters. Similarly to previous studies, we find that a dark matter-only model overestimates the average mass by $7.5\%$, but including our baryonic term reduces that to $0.7\%$. Additionally, to mitigate the computational complexity of our model, we construct an emulator (surrogate model) which accurately interpolates our model for parameter inference, while being much faster to use than the raw model. We also provide an open-source software framework for our model and emulator, called maszcal, which will serve as a platform for continued efforts to improve these mass-calibration techniques. In this work, we detail our model, the construction of the emulator, and the tests which we used to validate that our model does mitigate bias. Lastly, we describe tests of the emulator's accuracy

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arXiv2021

A Machine Learning Approach for Dynamical Mass Measurements of Galaxy Clusters

We present a modern machine learning approach for cluster dynamical mass measurements that is a factor of two improvement over using a conventional scaling relation. Different methods are tested against a mock cluster catalog constructed using halos with mass >= 10^14 Msolar/h from Multidark's publicly-available N-body MDPL halo catalog. In the conventional method, we use a standard M(sigma_v) power law scaling relation to infer cluster mass, M, from line-of-sight (LOS) galaxy velocity dispersion, sigma_v. The resulting fractional mass error distribution is broad, with width=0.87 (68% scatter), and has extended high-error tails. The standard scaling relation can be simply enhanced by including higher-order moments of the LOS velocity distribution. Applying the kurtosis as a correction term to log(sigma_v) reduces the width of the error distribution to 0.74 (16% improvement). Machine learning can be used to take full advantage of all the information in the velocity distribution. We employ the Support Distribution Machines (SDMs) algorithm that learns from distributions of data to predict single values. SDMs trained and tested on the distribution of LOS velocities yield width=0.46 (47% improvement). Furthermore, the problematic tails of the mass error distribution are effectively eliminated. Decreasing cluster mass errors will improve measurements of the growth of structure and lead to tighter constraints on cosmological parameters.

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arXiv2020

The Atacama Cosmology Telescope: Delensed Power Spectra and Parameters

We present LCDM cosmological parameter constraints obtained from delensed microwave background power spectra. Lensing maps from a subset of DR4 data from the Atacama Cosmology Telescope (ACT) are used to undo the lensing effect in ACT spectra observed at 150 and 98 GHz. At 150 GHz, we remove the lensing distortion with an effective efficiency of 30% (TT), 30% (EE), 26% (TE) and 20% (BB); this results in detections of the delensing effect at 8.7 sigma (TT), 5.1 sigma (EE), 2.6 sigma (TE), and 2.4 sigma (BB) significance. The combination of 150 and 98 GHz TT, EE, and TE delensed spectra is well fit by a standard LCDM model. We also measure the shift in best-fit parameters when fitting delensed versus lensed spectra; while this shift does not inform our ability to measure cosmological parameters, it does provide a three-way consistency check among the lensing inferred from the best-fit parameters, the lensing in the CMB power spectrum, and the reconstructed lensing map. This shift is predicted to be zero when fitting with the correct model since both lensed and delensed spectra originate from the same region of sky. Fitting with a LCDM model and marginalizing over foregrounds, we find that the shift in cosmological parameters is consistent with zero. Our results show that gravitational lensing of the microwave background is internally consistent within the framework of the standard cosmological model.

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arXiv2020

The Atacama Cosmology Telescope: Weighing distant clusters with the most ancient light

We use gravitational lensing of the cosmic microwave background (CMB) to measure the mass of the most distant blindly-selected sample of galaxy clusters on which a lensing measurement has been performed to date. In CMB data from the the Atacama Cosmology Telescope (ACT) and the Planck satellite, we detect the stacked lensing effect from 677 near-infrared-selected galaxy clusters from the Massive and Distant Clusters of WISE Survey (MaDCoWS), which have a mean redshift of $ \langle z \rangle = 1.08$. There are no current optical weak lensing measurements of clusters that match the distance and average mass of this sample. We detect the lensing signal with a significance of $4.2 σ$. We model the signal with a halo model framework to find the mean mass of the population from which these clusters are drawn. Assuming that the clusters follow Navarro-Frenk-White density profiles, we infer a mean mass of $\langle M_{500c}\rangle = \left(1.7 \pm 0.4 \right)\times10^{14}\,\mathrm{M}_\odot$. We consider systematic uncertainties from cluster redshift errors, centering errors, and the shape of the NFW profile. These are all smaller than 30% of our reported uncertainty. This work highlights the potential of CMB lensing to enable cosmological constraints from the abundance of distant clusters populating ever larger volumes of the observable Universe, beyond the capabilities of optical weak lensing measurements.

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arXiv2020

CMB-S4: Forecasting Constraints on Primordial Gravitational Waves

CMB-S4---the next-generation ground-based cosmic microwave background (CMB) experiment---is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the Universe, from the highest energies at the dawn of time through the growth of structure to the present day. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semi-analytic projection tool, targeted explicitly towards optimizing constraints on the tensor-to-scalar ratio, $r$, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2--3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments given a desired scientific goal. To form a closed-loop process, we couple this semi-analytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for $r > 0.003$ at greater than $5σ$, or, in the absence of a detection, of reaching an upper limit of $r < 0.001$ at $95\%$ CL.

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arXiv2020

Cosmology with Rayleigh Scattering of the Cosmic Microwave Background

The cosmic microwave background (CMB) has been a treasure trove for cosmology. Over the next decade, current and planned CMB experiments are expected to exhaust nearly all primary CMB information. To further constrain cosmological models, there is a great benefit to measuring signals beyond the primary modes. Rayleigh scattering of the CMB is one source of additional cosmological information. It is caused by the additional scattering of CMB photons by neutral species formed during recombination and exhibits a strong and unique frequency scaling ($\propto ν^4$). We will show that with sufficient sensitivity across frequency channels, the Rayleigh scattering signal should not only be detectable but can significantly improve constraining power for cosmological parameters, with limited or no additional modifications to planned experiments. We will provide heuristic explanations for why certain cosmological parameters benefit from measurement of the Rayleigh scattering signal, and confirm these intuitions using the Fisher formalism. In particular, observation of Rayleigh scattering allows significant improvements on measurements of $N_{\rm eff}$ and $\sum m_ν$.

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arXiv2020

The Atacama Cosmology Telescope: Component-separated maps of CMB temperature and the thermal Sunyaev-Zel'dovich effect

Optimal analyses of many signals in the cosmic microwave background (CMB) require map-level extraction of individual components in the microwave sky, rather than measurements at the power spectrum level alone. To date, nearly all map-level component separation in CMB analyses has been performed exclusively using satellite data. In this paper, we implement a component separation method based on the internal linear combination (ILC) approach which we have designed to optimally account for the anisotropic noise (in the 2D Fourier domain) often found in ground-based CMB experiments. Using this method, we combine multi-frequency data from the Planck satellite and the Atacama Cosmology Telescope Polarimeter (ACTPol) to construct the first wide-area, arcminute-resolution component-separated maps (covering approximately 2100 sq. deg.) of the CMB temperature anisotropy and the thermal Sunyaev-Zel'dovich (tSZ) effect sourced by the inverse-Compton scattering of CMB photons off hot, ionized gas. Our ILC pipeline allows for explicit deprojection of various contaminating signals, including a modified blackbody approximation of the cosmic infrared background (CIB) spectral energy distribution. The cleaned CMB maps will be a useful resource for CMB lensing reconstruction, kinematic SZ cross-correlations, and primordial non-Gaussianity studies. The tSZ maps will be used to study the pressure profiles of galaxies, groups, and clusters through cross-correlations with halo catalogs, with dust contamination controlled via CIB deprojection. The data products described in this paper are available on LAMBDA.

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arXiv2020

First results from SMAUG: Uncovering the Origin of the Multiphase Circumgalactic Medium with a Comparative Analysis of Idealized and Cosmological Simulations

We examine the properties of the circumgalactic medium (CGM) at low redshift in a range of simulated Milky Way mass halos. The sample is comprised of seven idealized simulations, an adaptive mesh refinement cosmological zoom-in simulation, and two groups of 50 halos with star forming or quiescent galaxies taken from the IllustrisTNG100 simulation. The simulations have very different setups, resolution, and feedback models, but are analyzed in a uniform manner. By comparing median radial profiles and mass distributions of CGM properties, we isolate key similarities and differences. In doing so, we advance the efforts of the SMAUG (Simulating Multiscale Astrophysics to Understand Galaxies) project that aims to understand the inherently multiscale galaxy formation process. In the cosmological simulations, the CGM exhibits nearly flat temperature distributions, and broad pressure and radial velocity distributions. In the idealized simulations, similar distributions are found in the inner CGM ($\lesssim 0.5 \, r_{\rm 200c}$) when strong galactic feedback models are employed, but the outer CGM ($\gtrsim 0.5 \, r_{\rm 200c}$) has a much less prominent cold phase, and narrower pressure and velocity distributions even in models with strong feedback. This comparative analysis demonstrates the dominant role feedback plays in shaping the inner CGM and the increased importance of cosmological effects, such as nonspherical accretion and satellite galaxies, in the outer CGM. Furthermore, our findings highlight that while cosmological simulations are required to capture the multiphase structure of the CGM at large radii, idealized simulations provide a robust framework to study how galactic feedback interacts with the inner CGM and thereby provide a reliable avenue to constrain feedback prescriptions.

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arXiv2020

The Atacama Cosmology Telescope: Constraints on Cosmic Birefringence

We present new constraints on anisotropic birefringence of the cosmic microwave background polarization using two seasons of data from the Atacama Cosmology Telescope covering $456$ square degrees of sky. The birefringence power spectrum, measured using a curved-sky quadratic estimator, is consistent with zero. Our results provide the tightest current constraint on birefringence over a range of angular scales between $5$ arcminutes and $9$ degrees. We improve previous upper limits on the amplitude of a scale-invariant birefringence power spectrum by a factor of between $2$ and $3$. Assuming a nearly-massless axion field during inflation, our result is equivalent to a $2\,σ$ upper limit on the Chern-Simons coupling constant between axions and photons of $g_{αγ}<4.0\times 10^{-2}/H_I$ where $H_I$ is the inflationary Hubble scale.

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arXiv2020

The Atacama Cosmology Telescope: A CMB lensing mass map over 2100 square degrees of sky and its cross-correlation with BOSS-CMASS galaxies

We construct cosmic microwave background lensing mass maps using data from the 2014 and 2015 seasons of observations with the Atacama Cosmology Telescope (ACT). These maps cover 2100 square degrees of sky and overlap with a wide variety of optical surveys. The maps are signal dominated on large scales and have fidelity such that their correlation with the cosmic infrared background is clearly visible by eye. We also create lensing maps with thermal Sunyaev-Zel'dovich contamination removed using a novel cleaning procedure that only slightly degrades the lensing signal-to-noise ratio. The cross-spectrum between the cleaned lensing map and the BOSS CMASS galaxy sample is detected at $10$-$σ$ significance, with an amplitude of $A=1.02 \pm 0.10$ relative to the Planck best-fit LCDM cosmological model with fiducial linear galaxy bias. Our measurement lays the foundation for lensing cross-correlation science with current ACT data and beyond.

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arXiv2020

Sensitivity of the Prime-Cam Instrument on the CCAT-prime Telescope

CCAT-prime is a new 6 m crossed Dragone telescope designed to characterize the Cosmic Microwave Background (CMB) polarization and foregrounds, measure the Sunyaev-Zel'dovich effects of galaxy clusters, map the [CII] emission intensity from the Epoch of Reionization (EoR), and monitor accretion luminosity over multi-year timescales of hundreds of protostars in the Milky Way. CCAT-prime will make observations from a 5,600 m altitude site on Cerro Chajnantor in the Atacama Desert of northern Chile. The novel optical design of the telescope combined with high surface accuracy ($<$10 $μ$m) mirrors and the exceptional atmospheric conditions of the site will enable sensitive broadband, polarimetric, and spectroscopic surveys at sub-mm to mm wavelengths. Prime-Cam, the first light instrument for CCAT-prime, consists of a 1.8 m diameter cryostat that can house seven individual instrument modules. Each instrument module, optimized for a specific science goal, will use state-of-the-art kinetic inductance detector (KID) arrays operated at $\sim$100 mK, and Fabry-Perot interferometers (FPI) for the EoR science. Prime-Cam will be commissioned with staged deployments to populate the seven instrument modules. The full instrument will consist of 60,000 polarimetric KIDs at a combination of 220/280/350/410 GHz, 31,000 KIDS at 250/360 GHz coupled with FPIs, and 21,000 polarimetric KIDs at 850 GHz. Prime-Cam is currently being built, and the CCAT-prime telescope is designed and under construction by Vertex Antennentechnik GmbH to achieve first light in 2021. CCAT-prime is also a potential telescope platform for the future CMB Stage-IV observations.

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arXiv2020

The Atacama Cosmology Telescope: SZ-based masses and dust emission from IR-selected cluster candidates in the SHELA survey

We examine the stacked thermal Sunyaev-Zel\text{'}dovich (SZ) signals for a sample of galaxy cluster candidates from the Spitzer-HETDEX Exploratory Large Area (SHELA) Survey, which are identified in combined optical and infrared SHELA data using the redMaPPer algorithm. We separate the clusters into three richness bins, with average photometric redshifts ranging from 0.70 to 0.80. The richest bin shows a clear temperature decrement at 148 GHz in the Atacama Cosmology Telescope data, which we attribute to the SZ effect. All richness bins show an increment at 220 GHz, which we attribute to dust emission from cluster galaxies. We correct for dust emission using stacked profiles from Herschel Stripe 82 data, and allow for synchrotron emission using stacked profiles created by binning source fluxes from NVSS data. We see dust emission in all three richness bins, but can only confidently detect the SZ decrement in the highest richness bin, finding $M_{500}$ = $8.7^{+1.7}_{-1.3} \times 10^{13} M_\odot$. Neglecting the correction for dust depresses the inferred mass by 26 percent, indicating a partial fill-in of the SZ decrement from thermal dust and synchrotron emission by the cluster member galaxies. We compare our corrected SZ masses to two redMaPPer mass--richness scaling relations and find that the SZ mass is lower than predicted by the richness. We discuss possible explanations for this discrepancy, and note that the SHELA richnesses may differ from previous richness measurements due to the inclusion of IR data in redMaPPer.

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arXiv2020

The Websky Extragalactic CMB Simulations

We present a new pipeline for the efficient generation of synthetic observations of the extragalactic microwave sky, tailored to large ground-based CMB experiments such as the Simons Observatory, Advanced ACTPol, SPT-3G, and CMB-S4. Such simulated observations are a key technical challenge in cosmology because of the dynamic range and accuracy required. The first part of the pipeline generates a random cosmological realization in the form of a dark matter halo catalog and matter displacement field, as seen from a given position. The halo catalog and displacement field are modeled with ellipsoidal collapse dynamics and Lagrangian perturbation theory, respectively. In the second part, the cosmological realization is converted into a set of intensity maps over the range 10 - 10^3 GHz using models based on existing observations and hydrodynamical simulations. These maps include infrared emission from dusty star forming galaxies (CIB), Comptonization of CMB photons by hot gas in groups and clusters through the thermal Sunyaev-Zel'dovich effect (tSZ), Doppler boosting by Thomson scattering of the CMB by bulk flows through the kinetic Sunyaev-Zel'dovich effect (kSZ), and weak gravitational lensing of primary CMB anisotropies by the large-scale distribution of matter in the universe. After describing the pipeline and its implementation, we present the Websky maps, created from a realization of the cosmic web on our past light cone in the redshift interval 0<z<4.6 over the full-sky and a volume of ~(600 Gpc/h)^3 resolved with ~10^12 resolution elements. The Websky maps and halo catalog are publicly available at mocks.cita.utoronto.ca/websky.

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arXiv2019

Cosmology with kSZ: breaking the optical depth degeneracy with Fast Radio Bursts

The small-scale cosmic microwave background (CMB) is dominated by anisotropies from the kinematic Sunyaev-Zeldovich (kSZ) effect, and upcoming experiments will measure it very precisely, but the optical depth degeneracy limits the cosmological information that can be extracted. At the same time, fast radio bursts (FRBs) are an exciting new frontier for astrophysics, but their usefulness as cosmological probes is currently unclear. We show that FRBs are uniquely suited for breaking the kSZ optical depth degeneracy. This opens up new possibilities for constraining cosmology with the kSZ effect, and new cosmological applications for FRBs.

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arXiv2019

Multiwavelength cluster mass estimates and machine learning

One emerging application of machine learning methods is the inference of galaxy cluster masses. In this note, machine learning is used to directly combine five simulated multiwavelength measurements in order to find cluster masses. This is in contrast to finding mass estimates for each observable, normally by using a scaling relation, and then combining these scaling law based mass estimates using a likelihood. We also illustrate how the contributions of each observable to the accuracy of the resulting mass measurement can be compared via model-agnostic Importance Permutation values. Thirdly, as machine learning relies upon the accuracy of the training set in capturing observables, their correlations, and the observational selection function, and as the machine learning training set originates from simulations, two tests of whether a simulation's correlations are consistent with observations are suggested and explored as well.

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