arXiv subjects

Ana Maria Delgado

Publications and source records attributed to Ana Maria Delgado.

At least 19 recordsLinked to original sources

arXiv2026

How to Craft the Right Language AI Policy For Your Research Group (Some Assembly Required)

Language AI is rapidly becoming part of the astronomy research ecosystem, prompting research teams to develop policies governing its use. But resources and advice for AI adoption assume that all research groups share the same goals and values. This paper lays out an argument for why there is no single "correct" AI policy for astronomy research groups. Instead, we introduce four research laboratory archetypes with competing research priorities, and we use them to explore how a small laboratory or research group's priorities shape decisions about AI's impact on research productivity, scientist development, scientific integrity, and data governance. Rather than prescribing a universal set of rules, this paper provides a framework for aligning AI policies with a group's scientific values and mission. The objective is to help research leaders decide how Language AI should be used within their particular research environment.

astro-ph.IM↗

arXiv2026

Estimating the triaxiality of massive clusters from 2D observables in MillenniumTNG with machine learning

Properties of massive galaxy clusters, such as mass abundance and concentration, are sensitive to cosmology, making cluster statistics a powerful tool for cosmological studies. However, favoring a more simplified, spherically symmetric model for galaxy clusters can lead to biases in the estimates of cluster properties. In this work, we present a deep-learning approach for estimating the triaxiality and orientations of massive galaxy clusters (those with masses $\gtrsim 10^{14}\,M_\odot h^{-1}$) from 2D observables. We utilize the flagship hydrodynamical volume of the suite of cosmological-hydrodynamical MillenniumTNG (MTNG) simulations as our ground truth. Our model combines the feature extracting power of a convolutional neural network (CNN) and the message passing power of a graph neural network (GNN) in a multi-modal, fusion network. Our model is able to extract 3D geometry information from 2D idealized cluster multi-wavelength images (soft X-ray, medium X-ray, hard X-ray and tSZ effect) and mathematical graph representations of 2D cluster member observables (line-of-sight radial velocities, 2D projected positions and V-band luminosities). Our network improves cluster geometry estimation in MTNG by $30\%$ compared to assuming spherical symmetry. We report an $R^2 = 0.85$ regression score for estimating the major axis length of triaxial clusters and correctly classifying $71\%$ of prolate clusters with elongated orientations along our line-of-sight.

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arXiv2025

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters

The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.

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arXiv2025

Fully non-linear simulations of galaxy intrinsic alignments for weak lensing with the MillenniumTNG lightcone

We present a complete forward model of a realistic weak lensing galaxy catalogue based on the 740 Mpc hydrodynamical MillenniumTNG (MTNG) simulation. Starting with a complete particle and cell lightcone covering one octant of the sky with redshift range 0 < $z$ < 1.5, we apply a group and subhalo finder to generate the corresponding galaxy catalogue for a fiducial observer. For all galaxies, we compute both their intrinsic and lensing-induced shear. The intrinsic component is derived from the luminosity-weighted inertia tensor of stellar particles, while the extrinsic (gravitational) shear is obtained through full-sky ray-tracing on the same lightcone. This allows us to directly predict the impact of intrinsic alignment (IA) of galaxies on the shear correlation function and popular convergence statistics in a fully non-linear forward model. We find that IA modifies the convergence power spectrum at all angular scales by up to 20%, it significantly impacts the PDF, altering its tails by 10-20%, and distorts peak and minimum counts up to 30%, depending on redshift and scale. We also evaluate the impact of the IA signal on the shear correlation function finding that, along with a redshift dependence, the signal strongly increases for higher galaxy stellar mass cuts applied to the catalogue. Notably, with the highest stellar mass cut we apply, the intrinsic shear autocorrelation can become comparable to the gravitational shear component on small angular scales. Our results highlight the importance of accurately modeling IA for precision weak lensing cosmology with upcoming Stage IV surveys.

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arXiv2025

Ray-tracing vs. Born approximation in full-sky weak lensing simulations of the MillenniumTNG project

Weak gravitational lensing is a powerful tool for precision tests of cosmology. As the expected deflection angles are small, predictions based on non-linear N-body simulations are commonly computed with the Born approximation. Here we examine this assumption using ${\small DORIAN}$, a newly developed full-sky ray-tracing scheme applied to high-resolution mass-shell outputs of the two largest simulations in the MillenniumTNG suite, each with a 3000 Mpc box containing almost 1.1 trillion cold dark matter particles in addition to 16.7 billion particles representing massive neutrinos. We examine simple two-point statistics like the angular power spectrum of the convergence field, as well as statistics sensitive to higher order correlations such as peak and minimum statistics, void statistics, and Minkowski functionals of the convergence maps. Overall, we find only small differences between the Born approximation and a full ray-tracing treatment. While these are negligibly small at power-spectrum level, some higher order statistics show more sizable effects; ray-tracing is necessary to achieve percent level precision. At the resolution reached here, full-sky maps with 0.8 billion pixels and an angular resolution of 0.43 arcmin, we find that interpolation accuracy can introduce appreciable errors in ray-tracing results. We therefore implemented an interpolation method based on nonuniform fast Fourier transforms (NUFFT) along with more traditional methods. Bilinear interpolation introduces significant smoothing, while nearest grid point sampling agrees well with NUFFT, at least for our fiducial source redshift, $z_s=1.0$, and for the 1 arcmin smoothing we use for higher-order statistics.

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arXiv2024

A Multi-Wavelength Technique for Estimating Galaxy Cluster Mass Accretion Rates

The mass accretion rate of galaxy clusters is a key factor in determining their structure, but a reliable observational tracer has yet to be established. We present a state-of-the-art machine learning model for constraining the mass accretion rate of galaxy clusters from only X-ray and thermal Sunyaev-Zeldovich observations. Using idealized mock observations of galaxy clusters from the MillenniumTNG simulation, we train a machine learning model to estimate the mass accretion rate. The model constrains 68% of the mass accretion rates of the clusters in our dataset to within 33% of the true value without significant bias, a ~58% reduction in the scatter over existing constraints. We demonstrate that the model uses information from both radial surface brightness density profiles and asymmetries.

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arXiv2024

The MillenniumTNG Project: Impact of massive neutrinos on the cosmic large-scale structure and the distribution of galaxies

We discuss the cold dark matter plus massive neutrinos simulations of the MillenniumTNG (MTNG) project, which aim to improve understanding of how well ongoing and future large-scale galaxy surveys will measure neutrino masses. Our largest simulations, $3000\,{\rm Mpc}$ on a side, use $10240^3$ particles of mass $m_{p} = 6.66\times 10^{8}\,h^{-1}{\rm M}_\odot$ to represent cold dark matter, and $2560^3$ to represent a population of neutrinos with summed mass $M_ν= 100\,{\rm meV}$. Smaller volume runs with $\sim 630\,{\rm Mpc}$ also include cases with $M_ν= 0\,\textrm{and}\, 300\,{\rm meV}$. All simulations are carried out twice using the paired-and-fixed technique for cosmic variance reduction. We evolve the neutrino component using the particle-based $δf$ importance sampling method, which greatly reduces shot noise in the neutrino density field. In addition, we modify the GADGET-4 code to account both for the influence of relativistic and mildly relativistic components on the expansion rate and for non-Newtonian effects on the largest represented simulation scales. This allows us to quantify accurately the impact of neutrinos on basic statistical measures of nonlinear structure formation, such as the matter power spectrum and the halo mass function. We use semi-analytic models of galaxy formation to predict the galaxy population and its clustering properties as a function of summed neutrino mass, finding significant ($\sim 10\%$) impacts on the cosmic star formation rate history, the galaxy mass function, and the clustering strength. This offers the prospect of identifying combinations of summary statistics that are optimally sensitive to the neutrino mass.

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arXiv2024

The MillenniumTNG Project: The impact of baryons and massive neutrinos on high-resolution weak gravitational lensing convergence maps

We study weak gravitational lensing convergence maps produced from the MillenniumTNG (MTNG) simulations by direct projection of the mass distribution on the past backwards lightcone of a fiducial observer. We explore the lensing maps over a large dynamic range in simulation mass and angular resolution, allowing us to establish a clear assessment of numerical convergence. By comparing full physics hydrodynamical simulations with corresponding dark-matter-only runs we quantify the impact of baryonic physics on the most important weak lensing statistics. Likewise, we predict the impact of massive neutrinos reliably far into the non-linear regime. We also demonstrate that the "fixed & paired" variance suppression technique increases the statistical robustness of the simulation predictions on large scales not only for time slices but also for continuously output lightcone data. We find that both baryonic and neutrino effects substantially impact weak lensing shear measurements, with the latter dominating over the former on large angular scales. Thus, both effects must explicitly be included to obtain sufficiently accurate predictions for stage IV lensing surveys. Reassuringly, our results agree accurately with other simulation results where available, supporting the promise of simulation modelling for precision cosmology far into the non-linear regime.

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arXiv2024

Zooming by in the CARPoolGP lane: new CAMELS-TNG simulations of zoomed-in massive halos

Galaxy formation models within cosmological hydrodynamical simulations contain numerous parameters with non-trivial influences over the resulting properties of simulated cosmic structures and galaxy populations. It is computationally challenging to sample these high dimensional parameter spaces with simulations, particularly for halos in the high-mass end of the mass function. In this work, we develop a novel sampling and reduced variance regression method, CARPoolGP, which leverages built-in correlations between samples in different locations of high dimensional parameter spaces to provide an efficient way to explore parameter space and generate low variance emulations of summary statistics. We use this method to extend the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) to include a set of 768 zoom-in simulations of halos in the mass range of $10^{13} - 10^{14.5} M_\odot\,h^{-1}$ that span a 28-dimensional parameter space in the IllustrisTNG model. With these simulations and the CARPoolGP emulation method, we explore parameter trends in the Compton $Y-M$, black hole mass-halo mass, and metallicity-mass relations, as well as thermodynamic profiles and quenched fractions of satellite galaxies. We use these emulations to provide a physical picture of the complex interplay between supernova and active galactic nuclei feedback. We then use emulations of the $Y-M$ relation of massive halos to perform Fisher forecasts on astrophysical parameters for future Sunyaev-Zeldovich observations and find a significant improvement in forecasted constraints. We publicly release both the simulation suite and CARPoolGP software package.

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arXiv2024

Evolution of cosmic filaments in the MTNG simulation

We present a study of the evolution of cosmic filaments across redshift with an emphasis on some important properties: filament lengths, growth rates, and radial profiles of galaxy densities. Following an observation-driven approach, we build cosmic filament catalogues at z=0,1,2,3, and 4 from the galaxy distributions of the large hydro-dynamical run of the MilleniumTNG project. We employ the extensively used DisPerSE cosmic web finder code, for which we provide a user-friendly guide, including the details of a physics-driven calibration procedure, with the hope of helping future users. We perform the first statistical measurements of the evolution of connectivity in a large-scale simulation, finding that the connectivity of cosmic nodes (defined as the number of filaments attached) globally decreases from early to late times. The study of cosmic filaments in proper coordinates reveals that filaments grow in length and radial extent, as expected from large-scale structures in an expanding Universe. But the most interesting results arise once the Hubble flow is factored out. We find remarkably stable comoving filament length functions and over-density profiles, showing only little evolution of the total population of filaments in the past ~12.25 Gyrs. However, by tracking the spatial evolution of individual structures, we demonstrate that filaments of different lengths actually follow different evolutionary paths. While short filaments preferentially contract, long filaments expand along their longitudinal direction with growth rates that are the highest in the early, matter-dominated Universe. Filament diversity at fixed redshift is also shown by the different (~$5 σ$) density values between the shortest and longest filaments. Our results hint that cosmic filaments can be used as additional probes for dark energy, but further theoretical work is still needed.

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arXiv2023

The MillenniumTNG Project: Semi-analytic galaxy formation models on the past lightcone

Upcoming large galaxy surveys will subject the standard cosmological model, $Λ$CDM, to new precision tests. These can be tightened considerably if theoretical models of galaxy formation are available that can predict galaxy clustering and galaxy-galaxy lensing on the full range of measurable scales throughout volumes as large as those of the surveys and with sufficient flexibility that uncertain aspects of the underlying astrophysics can be marginalised over. This, in particular, requires mock galaxy catalogues in large cosmological volumes that can be directly compared to observation, and can be optimised empirically by Monte Carlo Markov Chains or other similar schemes to eliminate or estimate astrophysical parameters related to galaxy formation when constraining cosmology. Semi-analytic galaxy formation methods implemented on top of cosmological dark matter simulations offer a computationally efficient approach to construct physically based and flexibly parametrised galaxy formation models, and as such they are more potent than still faster, but purely empirical models. Here we introduce an updated methodology for the semi-analytic L-GALAXIES code, allowing it to be applied to simulations of the new MillenniumTNG project, producing galaxies directly on fully continuous past lightcones, potentially over the full sky, out to high redshift, and for all galaxies more massive than $\sim 10^8\,{\rm M}_\odot$. We investigate the numerical convergence of the resulting predictions, and study the projected galaxy clustering signals of different samples. The new methodology can be viewed as an important step towards more faithful forward-modelling of observational data, helping to reduce systematic distortions in the comparison of theory to observations.

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arXiv2023

Predicting the impact of feedback on matter clustering with machine learning in CAMELS

Extracting information from the total matter power spectrum with the precision needed for upcoming cosmological surveys requires unraveling the complex effects of galaxy formation processes on the distribution of matter. We investigate the impact of baryonic physics on matter clustering at $z=0$ using a library of power spectra from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project, containing thousands of $(25\,h^{-1}{\rm Mpc})^3$ volume realizations with varying cosmology, initial random field, stellar and AGN feedback strength and sub-grid model implementation methods. We show that baryonic physics affects matter clustering on scales $k \gtrsim 0.4\,h\,\mathrm{Mpc}^{-1}$ and the magnitude of this effect is dependent on the details of the galaxy formation implementation and variations of cosmological and astrophysical parameters. Increasing AGN feedback strength decreases halo baryon fractions and yields stronger suppression of power relative to N-body simulations, while stronger stellar feedback often results in weaker effects by suppressing black hole growth and therefore the impact of AGN feedback. We find a broad correlation between mean baryon fraction of massive halos ($M_{\rm 200c} > 10^{13.5}$\,\Msun) and suppression of matter clustering but with significant scatter compared to previous work owing to wider exploration of feedback parameters and cosmic variance effects. We show that a random forest regressor trained on the baryon content and abundance of halos across the full mass range $10^{10} \leq M_\mathrm{halo}/$\Msun$< 10^{15}$ can predict the effect of galaxy formation on the matter power spectrum on scales $k = 1.0$--20.0\,$h\,\mathrm{Mpc}^{-1}$.

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arXiv2023

The MillenniumTNG Project: Intrinsic alignments of galaxies and halos

The intrinsic alignment (IA) of observed galaxy shapes with the underlying cosmic web is a source of contamination in weak lensing surveys. Sensitive methods to identify the IA signal will therefore need to be included in the upcoming weak lensing analysis pipelines. Hydrodynamical cosmological simulations allow us to directly measure the intrinsic ellipticities of galaxies and thus provide a powerful approach to predict and understand the IA signal. Here we employ the novel, large-volume hydrodynamical simulation MTNG740, a product of the MillenniumTNG (MTNG) project, to study the IA of galaxies. We measure the projected correlation functions between the intrinsic shape/shear of galaxies and various tracers of large-scale structure, $w_{+g},\ w_{+m},\ w_{++}$ over the radial range $r_{\rm p} \in [0.02 , 200]\,h^{-1}{\rm Mpc}$ and at redshifts $z=0.0$, $0.5$ and $1.0$. We detect significant signal-to-noise IA signals with the density field for both elliptical and spiral galaxies. We also find significant intrinsic shear-shear correlations for ellipticals. We further examine correlations of the intrinsic shape of galaxies with the local tidal field. Here we find a significant IA signal for elliptical galaxies assuming a linear model. We also detect a weak IA signal for spiral galaxies under a quadratic tidal torquing model. Lastly, we measure the alignment between central galaxies and their host dark-matter halos, finding small to moderate misalignments between their principal axes that decline with halo mass.

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arXiv2023

Interpreting Sunyaev-Zel'dovich observations with MillenniumTNG: Mass and environment scaling relations

In the coming years, Sunyaev-Zel'dovich (SZ) measurements can dramatically improve our understanding of the Intergalactic Medium (IGM) and the role of feedback processes on galaxy formation, allowing us to calibrate important astrophysical systematics in cosmological constraints from weak lensing galaxy clustering surveys. However, the signal is only measured in a two-dimensional projection, and its correct interpretation relies on understanding the connection between observable quantities and the underlying intrinsic properties of the gas, in addition to the relation between the gas and the underlying matter distribution. One way to address these challenges is through the use of hydrodynamical simulations such as the high-resolution, large-volume MillenniumTNG suite. We find that measurements of the optical depth, $τ$, and the Compton-y parameter, $Y$, receive large line-of-sight contributions which can be removed effectively by applying a Compensated Aperture Photometry (CAP) filter. In contrast with other $τ$ probes (e.g., X-rays and Fast Radio Bursts), the kSZ-inferred $τ$ receives most of its signal from a confined cylindrical region around the halo due to the velocity decorrelation along the line-of-sight. Additionally, we perform fits to the $Y-M$ and $τ-M$ scaling relations and report best-fit parameters adopting the smoothly broken power law (SBPL) formalism. We note that subgrid physics modeling can broaden the error bar on these by 30\% for intermediate-mass halos ($\sim$$10^{13} \, {\rm M}_{\odot}$). The scatter of the scaling relations can be captured by an intrinsic dependence on concentration, and an extrinsic dependence on tidal shear. Finally, we comment on the effect of using galaxies rather than halos in real observations, which can bias the inferred SZ profiles by $\sim$20\% for $L_\ast$-galaxies.

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arXiv2023

The MillenniumTNG Project: The large-scale clustering of galaxies

Modern redshift surveys are tasked with mapping out the galaxy distribution over enormous distance scales. Existing hydrodynamical simulations, however, do not reach the volumes needed to match upcoming surveys. We present results for the clustering of galaxies using a new, large volume hydrodynamical simulation as part of the MillenniumTNG (MTNG) project. With a computational volume that is $\approx15$ times larger than the next largest such simulation currently available, we show that MTNG is able to accurately reproduce the observed clustering of galaxies as a function of stellar mass. When separated by colour, there are some discrepancies with respect to the observed population, which can be attributed to the quenching of satellite galaxies in our model. We combine MTNG galaxies with those generated using a semi-analytic model to emulate the sample selection of luminous red galaxies (LRGs) and emission line galaxies (ELGs), and show that although the bias of these populations is approximately (but not exactly) constant on scales larger than $\approx10$ Mpc, there is significant scale-dependent bias on smaller scales. The amplitude of this effect varies between the two galaxy types, and also between the semi-analytic model and MTNG. We show that this is related to the distribution of haloes hosting LRGs and ELGs. Using mock SDSS-like catalogues generated on MTNG lightcones, we demonstrate the existence of prominent baryonic acoustic features in the large-scale galaxy clustering. We also demonstrate the presence of realistic redshift space distortions in our mocks, finding excellent agreement with the multipoles of the redshift-space clustering measured in SDSS data.

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arXiv2023

The MillenniumTNG Project: High-precision predictions for matter clustering and halo statistics

Cosmological inference with large galaxy surveys requires theoretical models that combine precise predictions for large-scale structure with robust and flexible galaxy formation modelling throughout a sufficiently large cosmic volume. Here, we introduce the MillenniumTNG (MTNG) project which combines the hydrodynamical galaxy formation model of IllustrisTNG with the large volume of the Millennium simulation. Our largest hydrodynamic simulation, covering (500 Mpc/h)^3 = (740 Mpc)^3, is complemented by a suite of dark-matter-only simulations with up to 4320^3 dark matter particles (a mass resolution of 1.32 x 10^8 Msun/h) using the fixed-and-paired technique to reduce large-scale cosmic variance. The hydro simulation adds 4320^3 gas cells, achieving a baryonic mass resolution of 2 x 10^7 Msun/h. High time-resolution merger trees and direct lightcone outputs facilitate the construction of a new generation of semi-analytic galaxy formation models that can be calibrated against both the hydro simulation and observation, and then applied to even larger volumes - MTNG includes a flagship simulation with 1.1 trillion dark matter particles and massive neutrinos in a volume of (3000 Mpc)^3. In this introductory analysis we carry out convergence tests on basic measures of non-linear clustering such as the matter power spectrum, the halo mass function and halo clustering, and we compare simulation predictions to those from current cosmological emulators. We also use our simulations to study matter and halo statistics, such as halo bias and clustering at the baryonic acoustic oscillation scale. Finally we measure the impact of baryonic physics on the matter and halo distributions.

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arXiv2023

The MillenniumTNG Project: The galaxy population at $z\geq 8$

The early release science results from $\textit{JWST}$ have yielded an unexpected abundance of high-redshift luminous galaxies that seems to be in tension with current theories of galaxy formation. However, it is currently difficult to draw definitive conclusions form these results as the sources have not yet been spectroscopically confirmed. It is in any case important to establish baseline predictions from current state-of-the-art galaxy formation models that can be compared and contrasted with these new measurements. In this work, we use the new large-volume ($L_\mathrm{box}\sim 740 \, \mathrm{cMpc}$) hydrodynamic simulation of the MillenniumTNG project, suitably scaled to match results from higher resolution - smaller volume simulations, to make predictions for the high-redshift ($z\gtrsim8$) galaxy population and compare them to recent $\textit{JWST}$ observations. We show that the simulated galaxy population is broadly consistent with observations until $z\sim10$. From $z\approx10-12$, the observations indicate a preference for a galaxy population that is largely dust-free, but is still consistent with the simulations. Beyond $z\gtrsim12$, however, our simulation results underpredict the abundance of luminous galaxies and their star-formation rates by almost an order of magnitude. This indicates either an incomplete understanding of the new $\textit{JWST}$ data or a need for more sophisticated galaxy formation models that account for additional physical processes such as Population~III stars, variable stellar initial mass functions, or even deviations from the standard $Λ$CDM model. We emphasise that any new process invoked to explain this tension should only significantly influence the galaxy population beyond $z\gtrsim10$, while leaving the successful galaxy formation predictions of the fiducial model intact below this redshift.

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arXiv2023

Inferring the impact of feedback on the matter distribution using the Sunyaev Zel'dovich effect: Insights from CAMELS simulations and ACT+DES data

Feedback from active galactic nuclei and stellar processes changes the matter distribution on small scales, leading to significant systematic uncertainty in weak lensing constraints on cosmology. We investigate how the observable properties of group-scale halos can constrain feedback's impact on the matter distribution using Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS). Extending the results of previous work to smaller halo masses and higher wavenumber, $k$, we find that the baryon fraction in halos contains significant information about the impact of feedback on the matter power spectrum. We explore how the thermal Sunyaev Zel'dovich (tSZ) signal from group-scale halos contains similar information. Using recent Dark Energy Survey (DES) weak lensing and Atacama Cosmology Telescope (ACT) tSZ cross-correlation measurements and models trained on CAMELS, we obtain $10\%$ constraints on feedback effects on the power spectrum at $k \sim 5\, h/{\rm Mpc}$. We show that with future surveys, it will be possible to constrain baryonic effects on the power spectrum to $\mathcal{O}(<1\%)$ at $k = 1\, h/{\rm Mpc}$ and $\mathcal{O}(3\%)$ at $k = 5\, h/{\rm Mpc}$ using the methods that we introduce here. Finally, we investigate the impact of feedback on the matter bispectrum, finding that tSZ observables are highly informative in this case.

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