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Marcel P. van Daalen

Publications and source records attributed to Marcel P. van Daalen.

At least 19 recordsLinked to original sources

The FLAMINGO simulations data release

We describe the public release of $>2.3$ petabytes of data from the FLAMINGO cosmological simulations. The suite consists of hydrodynamical simulations that include radiative cooling, star formation, stellar mass loss and the resulting chemical enrichment, supernova feedback, and two implementations of AGN feedback. Neutrinos are simulated explicitly using particles. Data products include snapshots, halo and galaxy catalogues, HEALPix all-sky lightcone maps, particle data for lightcone maps, and power spectra. The FLAMINGO set includes 22 hydrodynamical simulations. In addition, there are 16 gravity-only simulations, including the $10080^3$ particles FLAMINGO-10k run, with initial conditions that match those of the corresponding hydrodynamical runs. The fiducial hydrodynamical simulations span three numerical resolutions that have each been calibrated to reproduce the present-day galaxy stellar mass function and gas fractions in low-redshift clusters. Other simulations systematically vary the galaxy stellar mass function, cluster gas fractions, cosmology (including neutrino masses), and/or the nature of dark matter, in volumes of 1Gpc$^3$. The release includes hitherto unpublished simulations that use extra dark matter particles. While we provide a facility for downloading complete simulation outputs, we recognise that for many users this will not be possible due to limited local storage or network bandwidth. We implement a web service that enables users to explore available outputs and selectively download datasets or parts of datasets.

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Choosing the right MCMC sampler: a systematic benchmark of gradient-free methods

We present a set of metrics and methods for testing and comparing a range of modern gradient-free Markov Chain Monte Carlo (MCMC) samplers against the commonly used Metropolis-Hastings (MH) algorithm. The goal is to quantify key performance metrics, including sampler ergodicity, robustness and overall likelihood performance. To provide a controlled and interpretable testbed, we use the Rosenbrock function and Neal's funnel as representative unimodal cases, while Gaussian random likelihood landscapes in three, five, and eight dimensions serve as multimodal test scenarios. The samplers considered include affine-invariant moves from the literature, such as the stretch and walk moves, the differential evolution move, and the snooker move. We additionally introduce two novel variations: a modified stretch move that incorporates a Principal Component Analysis (PCA) transformation, and a hybrid blend move that combines features of both differential evolution and stretch dynamics. Beyond sampler evaluation, we demonstrate reconstructing likelihood landscapes from sampled points using a quadtree algorithm. Additionally, we explore the use of optimisation algorithms to refine the best parameter set in terms of its likelihood, and find consistent improvements in log-likelihood values, with the post-sampling gain becoming more significant in higher-dimensional problems. Our comparative results of sampler testing show that the differential evolution algorithm, when tuned to a target acceptance fraction of 25%, consistently outperforms all other samplers in terms of ergodicity, robustness, and likelihood performance.

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FLAMINGO: The thermal history of the Universe from tSZ effect cross-correlations and its dependencies on cosmology and baryon physics

The cross-correlation between tracers of large-scale structure, such as galaxies or quasars, and the thermal Sunyaev-Zel'dovich (tSZ) signal yields a measure of the bias-weighted mean electron pressure, $\langle b_\mathrm{h} P_\mathrm{e} \rangle$, where $b_\mathrm{h}$ is the halo bias and $P_\mathrm{e}$ is the electron pressure. With a model for the bias, one can derive the thermal history, $\mathrm{d}y/\mathrm{d}z$, where $y$ is the Compton parameter and $z$ is redshift. We explore how these quantities depend on redshift, cosmology, and the physics of galaxy formation using the FLAMINGO suite of cosmological hydrodynamical simulations, which spans a range of cosmological parameters and baryonic feedback implementations in volumes of up to $(2.8\,\text{Gpc})^3$. We find that $\langle b_\mathrm{h} P_\mathrm{e} \rangle$ depends steeply on $S_8 \equiv σ_8\sqrt{Ω_\mathrm{m}/0.3}$, with an effective scaling $\langle b_\mathrm{h} P_\mathrm{e} \rangle \propto S_8^{ε(z)}$, where the exponent $ε(z) \approx 3$ over the redshift range $0.1 \leq z \leq 1$. Compared with existing cross-correlation measurements using tracer samples from SDSS, BOSS, eBOSS, DES, and DESI cross-correlated with tSZ measurements from Planck, we find that models with a low-$S_8$ cosmology and strong feedback are preferred, with a joint fit yielding $S_8 = 0.72^{+0.03}_{-0.03}$ and a normalised group-mass halo baryon fraction $f_b(10^{13}\,M_\odot, z=0.1)/(Ω_b/Ω_m) = 0.10^{+0.09}_{-0.05}$ . Contrary to most probes of feedback which sample smaller scales (e.g., X-ray measurements), we show that feedback boosts $\langle b_\mathrm{h} P_\mathrm{e} \rangle$, thus providing a novel test of feedback models. Overall, our results show the thermal history provides a route to jointly constrain cosmological parameters and test models of galaxy formation.

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The Connection between Dusty Star-Forming Galaxies and the First Massive Quenched Galaxies

High-redshift (z > 2) massive quiescent (MQ) galaxies provide an opportunity to probe the key physical processes driving the fuelling and quenching of star formation in the early Universe. Observational evidence suggests a possible evolutionary link between MQs and dusty star-forming galaxies (DSFGs; or submillimetre galaxies), another extreme high-redshift population. However, galaxy formation models have historically struggled to reproduce these populations - especially simultaneously - limiting our understanding of their formation and connection, particularly in light of recent JWST findings. In previous work, we presented a re-calibrated version of the L-Galaxies semi-analytic model that provides an improved match to observationally-inferred number densities of both DSFG and MQ populations. In this work, we use this new model to investigate the progenitors of MQs at z > 2 and the physical mechanisms that lead to their quenching. We find that most MQs at z > 2 were sub-millimetre-bright ($S_{870}$ > 1 mJy) at some point in their cosmic past. The stellar mass of MQs is strongly correlated with the maximum submillimetre flux density attained over their history, and this relation appears to be independent of redshift. However, only a minority of high-redshift DSFGs evolve into MQs by z = 2. The key distinction between typical DSFGs and MQ progenitors lies in their merger histories: MQ progenitors experience an early major merger that triggers a brief, intense starburst and rapid black hole growth, depleting their cold gas reservoirs. In our model, AGN feedback subsequently prevents further gas cooling, resulting in quenching. In contrast, the broader DSFG population remains sub-millimetre-bright, with star formation proceeding primarily via secular processes, becoming quenched later.

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The resummation model in FLAMINGO: precisely predicting matter power suppression from observed halo baryon fractions

In order to derive unbiased cosmological parameters from Stage-IV surveys, we need models that can predict the matter power spectrum for at least $k\,\lesssim\,10\,h\mathrm{\,Mpc^{-1}}$ with percent-level accuracy. The main challenge in this endeavour is that baryonic feedback significantly redistributes matter on large scales, but to an unknown degree. Here, we present an improved version of the "resummation" model, which maps observed halo baryon fractions of massive haloes ($M_{\mathrm{500c}}\gtrsim 10^{12.5}\, \mathrm{M_\odot}$) to a flexible suppression signal - i.e. the ratio of baryonic to dark-matter-only (DMO) matter power spectra - using zero free parameters. We calibrate this model to the FLAMINGO hydrodynamical simulations, obtaining a typical accuracy of $\lesssim 1\%$ for $k\,\leq\,10\,h\mathrm{\,Mpc^{-1}}$ given mean halo baryon fractions within the spherical overdensity radii $R_{\mathrm{500c}}$ and $R_{\mathrm{200m}}$. When only those within $R_{\mathrm{500c}}$ are available, we still obtain $\lesssim 2\%$ accuracy. We show that given small-scale stellar mass fractions, the model can be extended to yield $\lesssim 3\%$ accurate suppression signals for all scales measured ($k\,\leq\,25\,h\mathrm{\,Mpc^{-1}}$). We also extend the model to redshifts $z>0$. Central to the model is a seemingly mass-independent and feedback-independent relation that allows observed halo masses to be mapped to equivalent DMO halo masses using only observed mean halo baryon fractions, to $\lesssim 1\%$ accuracy. This relation can also be used to retrieve the DMO halo mass function from observed halo masses and baryon fractions with percent-level accuracy, without any assumptions on the strength of feedback. A Python package implementing the resummation model is made publicly available.

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FLAMINGO: Baryonic effects on the weak lensing scattering transform

The scattering transform is a wavelet-based statistic capable of capturing non-Gaussian features in weak lensing (WL) convergence maps and has been proven to tighten cosmological parameter constraints by accessing information beyond two-point functions. However, its application in cosmological inference requires a clear understanding of its sensitivity to astrophysical systematics, the most significant of which are baryonic effects. These processes substantially modify the matter distribution on small to intermediate scales ($k\gtrsim 0.1\,h\,\mathrm{Mpc}^{-1}$), leaving scale-dependent imprints on the WL convergence field. We systematically examine the impact of baryonic feedback on scattering coefficients using full-sky WL convergence maps with Stage IV survey characteristics, generated from the FLAMINGO simulation suite. These simulations include a broad range of feedback models, calibrated to match the observed cluster gas fraction and galaxy stellar mass function, including systematically shifted variations, and incorporating either thermal or jet-mode AGN feedback. We characterise baryonic effects using a baryonic transfer function defined as the ratio of hydrodynamical to dark-matter-only scattering coefficients. While the coefficients themselves are sensitive to both cosmology and feedback, the transfer function remains largely insensitive to cosmology and shows a strong response to feedback, with suppression reaching up to $10\%$ on scales of $k\gtrsim 0.1\,h\,\mathrm{Mpc}^{-1}$. We also demonstrate that shape noise significantly diminishes the sensitivity of the scattering coefficients to baryonic effects, reducing the suppression from $\sim 2 - 10 \;\%$ to $\sim 1\;\%$, even with 1.5 arcmin Gaussian smoothing. This highlights the need for noise mitigation strategies and high-resolution data in future WL surveys.

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FLAMINGO: combining kinetic SZ effect and galaxy-galaxy lensing measurements to gauge the impact of feedback on large-scale structure

Energetic feedback processes associated with accreting supermassive black holes can expel gas from massive haloes and significantly alter various measures of clustering on ~Mpc scales, potentially biasing the values of cosmological parameters inferred from analyses of large-scale structure (LSS) if not modelled accurately. Here we use the state-of-the-art FLAMINGO suite of cosmological hydrodynamical simulations to gauge the impact of feedback on large-scale structure by comparing to Planck + ACT stacking measurements of the kinetic Sunyaev-Zel'dovich (kSZ) effect of SDSS BOSS galaxies. We make careful like-with-like comparisons to the observations, aided by high precision KiDS and DES galaxy-galaxy lensing measurements of the BOSS galaxies to inform the selection of the simulated galaxies. In qualitative agreement with several recent studies using dark matter only simulations corrected for baryonic effects, we find that the kSZ effect measurements prefer stronger feedback than predicted by simulations which have been calibrated to reproduce the gas fractions of low redshift X-ray-selected groups and clusters. We find that the increased feedback can help to reduce the so-called S8 tension between the observed and CMB-predicted clustering on small scales as probed by cosmic shear (although at the expense of agreement with the X-ray group measurements). However, the increased feedback is only marginally effective at reducing the reported offsets between the predicted and observed clustering as probed by the thermal SZ (tSZ) effect power spectrum and tSZ effect--weak lensing cross-spectrum, both of which are sensitive to higher halo masses than cosmic shear.

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The FLAMINGO project: Baryon effects on the matter power spectrum

The effect of baryon physics associated with galaxy formation onto the large-scale matter distribution of the Universe is a key uncertainty in the theoretical modelling required for the interpretation of Stage IV surveys. We use the FLAMINGO simulations to study the baryon response due to galaxy formation of the total matter power spectrum. We find that it is only well converged for simulation volumes in excess of $200^3$ Mpc$^3$. We report results for simulations of varying feedback intensity, which either match the X-ray inferred gas fractions in clusters and the $z=0$ stellar mass function, or shifted versions of the data, as well as for different implementations of AGN feedback. We package our results in the form of a Gaussian process emulator which can rapidly reproduce all the simulations' predictions to better than one per cent up to the comoving wavenumber $k = 10~h$ Mpc$^{-1}$ and up to $z=3$ for all the feedback models present in the FLAMINGO suite. We find that the response becomes stronger, the range of scales affected increases, and the position of the minimum of the response moves to smaller scales as the redshift decreases. We find that lower gas fractions in groups and clusters lead to a stronger response and that the use of collimated jets instead of thermally driven winds for AGN feedback enhances the effect. Lowering the stellar masses at fixed cluster gas fractions also increases the magnitude of the response. We find only a small (1% at $k<10~h$ Mpc$^{-1}$) dependence of our results on the background cosmology, but a wider range of cosmology variations will be needed to confirm this result. The response we obtain for our strongest feedback models is compatible with some of the recent analyses combining weak lensing with external data. Such a response is, however, in strong tension with the X-ray inferred gas fractions in clusters used to calibrate the FLAMINGO model.

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Simultaneously Modelling Dusty Star Forming Galaxies and Massive Quiescents: A Calibration Framework for Galaxy Formation Models

Galaxy formation models, particularly semi-analytic models (SAMs), rely on differential equations with free parameters to describe the physical mechanisms governing galaxy formation and evolution. Traditionally, most SAMs calibrate these parameters manually to match observational data. However, this approach fails to fully explore the multidimensional parameter space, resulting in limited robustness and inconsistency with some observations. In contrast, the L-Galaxies SAM features a unique Markov Chain Monte Carlo (MCMC) mode, enabling robust model calibration. Using this functionality, we address a long-standing tension in galaxy formation models: simultaneously reproducing the number densities of dusty star-forming galaxies (DSFGs) and high-redshift massive quiescent galaxies (MQs). We test nine combinations of observational constraints - including stellar mass functions, quiescent fractions, neutral hydrogen mass functions, and DSFG number densities - across different redshifts. We then analyze the resulting galaxy property predictions and discuss the underlying physical mechanisms. Our results identify a model that reasonably matches the number density of DSFGs while remaining consistent with observationally-derived lower limits on the number density of high-redshift MQs. This model requires high star formation efficiencies in mergers and a null dependency of supermassive black hole (SMBH) cold gas accretion on halo mass, facilitating rapid stellar mass and SMBH growth. Additionally, our findings highlight the importance of robust calibration procedures to address the significant degeneracies inherent to multidimensional galaxy formation models.

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The FLAMINGO project: the coupling between baryonic feedback and cosmology in light of the $S_8$ tension

Large-scale structure surveys have reported measurements of the density of matter, $Ω_\mathrm{m}$, and the amplitude of clustering, $σ_8$, that are in tension with the values inferred from observations of the cosmic microwave background. While this may be a sign of new physics that slows the growth of structure at late times, strong astrophysical feedback processes could also be responsible. In this work, we argue that astrophysical processes are not independent of cosmology and that their coupling naturally leads to stronger baryonic feedback in cosmological models with suppressed structure formation or when combined with a mechanism that removes dark matter from halos. We illustrate this with two well-motivated extensions of the Standard Model known to suppress structure formation: massive neutrinos and decaying dark matter. Our results, based on the FLAMINGO suite of hydrodynamical simulations, show that the combined effect of baryonic and non-baryonic suppression mechanisms is greater than the sum of its parts, particularly for decaying dark matter. We also show that the dependence of baryonic feedback on cosmology can be modelled as a function of the ratio $f_\mathrm{b}/c^2_\mathrm{v}\sim f_\mathrm{b}/(Ω_\mathrm{m}σ_8)^{1/4}$ of the universal baryon fraction, $f_\mathrm{b}$, to a velocity-based definition of halo concentration, $c^2_\mathrm{v}$, giving an accurate fitting formula for the baryonic suppression of the matter power spectrum. Although the combination of baryonic and non-baryonic suppression mechanisms can resolve the tension, the models with neutrinos and decaying dark matter are challenged by constraints on the expansion history.

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The FLAMINGO Project: Galaxy clusters in comparison to X-ray observations

Galaxy clusters are important probes for both cosmology and galaxy formation physics. We test the cosmological, hydrodynamical FLAMINGO simulations by comparing to observations of the gaseous properties of clusters measured from X-ray observations. FLAMINGO contains unprecedented numbers of massive galaxy groups ($>10^6$) and clusters ($>10^5$) and includes variations in both cosmology and galaxy formation physics. We predict the evolution of cluster scaling relations as well as radial profiles of the temperature, density, pressure, entropy, and metallicity for different masses and redshifts. We show that the differences between volume-, and X-ray-weighting of particles in the simulations, and between cool-core non cool-core samples, are similar in size as the differences between simulations for which the stellar and AGN feedback has been calibrated to produce significantly different gas fractions. Compared to thermally-driven AGN feedback, kinetic jet feedback calibrated to produce the same gas fraction at $R_{\rm 500c}$ yields a hotter core with higher entropies and lower densities, which translates into a smaller fraction of cool-core clusters. Stronger feedback, calibrated to produce lower gas fractions and hence lower gas densities, results in higher temperatures, entropies, and metallicities, but lower pressures. The scaling relations and thermodynamic profiles show almost no evolution with respect to self-similar expectations, except for the metallicity decreasing with redshift. We find that the temperature, density, pressure, and entropy profiles of clusters in the fiducial FLAMINGO simulation are in excellent agreement with observations, while the metallicities in the core are too high.

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Inferring the dark matter splashback radius from cluster gas and observable profiles in the FLAMINGO simulations

The splashback radius, coinciding with the minimum in the dark matter radial density gradient, is thought to be a universal definition of the edge of a dark matter halo. Observational methods to detect it have traced the dark matter using weak gravitational lensing or galaxy number counts. Recent attempts have also claimed the detection of a similar feature in Sunyaev-Zel'dovich (SZ) observations of the hot intracluster gas. Here, we use the FLAMINGO simulations to investigate whether an extremum gradient in a similar position to the splashback radius is predicted to occur in the cluster gas profiles. We find that the minimum in the gradient of the stacked 3D gas density and pressure profiles, and the maximum in the gradient of the entropy profile, broadly align with the splashback feature though there are significant differences. While the dark matter splashback radius varies with specific mass accretion rate, in agreement with previous work, the radial position of the deepest minimum in the log-slope of the gas density is more sensitive to halo mass. In addition, we show that a similar minimum is also present in projected 2D pseudo-observable profiles: emission measure (X-ray); Compton-$y$ (SZ) and surface mass density (weak lensing). We find that the latter traces the dark matter results reasonably well albeit the minimum occurs at a slightly smaller radius. While results for the gas profiles are largely insensitive to accretion rate and various observable proxies for dynamical state, they do depend on the strength of the feedback processes.

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The FLAMINGO project: Baryonic impact on weak gravitational lensing convergence peak counts

Weak gravitational lensing convergence peaks, the local maxima in weak lensing convergence maps, have been shown to contain valuable cosmological information complementary to commonly used two-point statistics. To exploit the full power of weak lensing for cosmology, we must model baryonic feedback processes because these reshape the matter distribution on non-linear and mildly non-linear scales. We study the impact of baryonic physics on the number density of weak lensing peaks using the FLAMINGO cosmological hydrodynamical simulation suite. We generate ray-traced full-sky convergence maps mimicking the characteristics of a Stage IV weak lensing survey. We compare the number densities of peaks in simulations that have been calibrated to reproduce the observed galaxy mass function and cluster gas fraction or to match a shifted version of these, and that use either thermally driven or jet AGN feedback. We show that the differences induced by realistic baryonic feedback prescriptions (typically $5 - 30\%$ for $κ= 0.1 - 0.4$) are smaller than those induced by reasonable variations in cosmological parameters ($20 - 60\%$ for $κ= 0.1 - 0.4$) but must be modeled carefully to obtain unbiased results. The reasons behind these differences can be understood by considering the impact of feedback on halo masses, or by considering the impact of different cosmological parameters on the halo mass function. Our analysis demonstrates that, for the range of models we investigated, the baryonic suppression is insensitive to changes in cosmology up to $κ\approx 0.4$ and that the higher $κ$ regime is dominated by Poisson noise and cosmic variance.

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FLAMINGO: Calibrating large cosmological hydrodynamical simulations with machine learning

To fully take advantage of the data provided by large-scale structure surveys, we need to quantify the potential impact of baryonic effects, such as feedback from active galactic nuclei (AGN) and star formation, on cosmological observables. In simulations, feedback processes originate on scales that remain unresolved. Therefore, they need to be sourced via subgrid models that contain free parameters. We use machine learning to calibrate the AGN and stellar feedback models for the FLAMINGO cosmological hydrodynamical simulations. Using Gaussian process emulators trained on Latin hypercubes of 32 smaller-volume simulations, we model how the galaxy stellar mass function and cluster gas fractions change as a function of the subgrid parameters. The emulators are then fit to observational data, allowing for the inclusion of potential observational biases. We apply our method to the three different FLAMINGO resolutions, spanning a factor of 64 in particle mass, recovering the observed relations within the respective resolved mass ranges. We also use the emulators, which link changes in subgrid parameters to changes in observables, to find models that skirt or exceed the observationally allowed range for cluster gas fractions and the stellar mass function. Our method enables us to define model variations in terms of the data that they are calibrated to rather than the values of specific subgrid parameters. This approach is useful, because subgrid parameters are typically not directly linked to particular observables, and predictions for a specific observable are influenced by multiple subgrid parameters.

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The FLAMINGO project: cosmological hydrodynamical simulations for large-scale structure and galaxy cluster surveys

We introduce the Virgo Consortium's FLAMINGO suite of hydrodynamical simulations for cosmology and galaxy cluster physics. To ensure the simulations are sufficiently realistic for studies of large-scale structure, the subgrid prescriptions for stellar and AGN feedback are calibrated to the observed low-redshift galaxy stellar mass function and cluster gas fractions. The calibration is performed using machine learning, separately for three resolutions. This approach enables specification of the model by the observables to which they are calibrated. The calibration accounts for a number of potential observational biases and for random errors in the observed stellar masses. The two most demanding simulations have box sizes of 1.0 and 2.8 Gpc and baryonic particle masses of $1\times10^8$ and $1\times10^9 \text{M}_\odot$, respectively. For the latter resolution the suite includes 12 model variations in a 1 Gpc box. There are 8 variations at fixed cosmology, including shifts in the stellar mass function and/or the cluster gas fractions to which we calibrate, and two alternative implementations of AGN feedback (thermal or jets). The remaining 4 variations use the unmodified calibration data but different cosmologies, including different neutrino masses. The 2.8 Gpc simulation follows $3\times10^{11}$ particles, making it the largest ever hydrodynamical simulation run to $z=0$. Lightcone output is produced on-the-fly for up to 8 different observers. We investigate numerical convergence, show that the simulations reproduce the calibration data, and compare with a number of galaxy, cluster, and large-scale structure observations, finding very good agreement with the data for converged predictions. Finally, by comparing hydrodynamical and `dark-matter-only' simulations, we confirm that baryonic effects can suppress the halo mass function and the matter power spectrum by up to $\approx20$ per cent.

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The FLAMINGO project: revisiting the $S_8$ tension and the role of baryonic physics

A number of recent studies have found evidence for a tension between observations of large-scale structure (LSS) and the predictions of the standard model of cosmology with the cosmological parameters fit to the cosmic microwave background (CMB). The origin of this '$S_8$ tension' remains unclear, but possibilities include new physics beyond the standard model, unaccounted for systematic errors in the observational measurements and/or uncertainties in the role that baryons play. Here we carefully examine the latter possibility using the new FLAMINGO suite of large-volume cosmological hydrodynamical simulations. We project the simulations onto observable harmonic space and compare with observational measurements of the power and cross-power spectra of cosmic shear, CMB lensing, and the thermal Sunyaev-Zel'dovich (tSZ) effect. We explore the dependence of the predictions on box size and resolution, cosmological parameters including the neutrino mass, and the efficiency and nature of baryonic 'feedback'. Despite the wide range of astrophysical behaviours simulated, we find that baryonic effects are not sufficiently large to remove the $S_8$ tension. Consistent with recent studies, we find the CMB lensing power spectrum is in excellent agreement with the standard model, whilst the cosmic shear power spectrum, tSZ effect power spectrum, and the cross-spectra between shear, CMB lensing, and the tSZ effect are all in varying degrees of tension with the CMB-specified standard model. These results suggest that some mechanism is required to slow the growth of fluctuations at late times and/or on non-linear scales, but that it is unlikely that baryon physics is driving this modification.

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The contribution of massive haloes to the matter power spectrum in the presence of AGN feedback

The clustering of matter, as measured by the matter power spectrum, informs us about dark matter and cosmology, as well as baryonic effects on the distribution of matter in the universe. Using cosmological hydrodynamical simulations from the cosmo-OWLS and BAHAMAS simulation projects, we investigate the contribution of power in haloes with various masses, defined by particles within some overdensity region, to the full power spectrum, as well as the power ratio between baryonic and dark matter only (DMO) simulations for a matched (between simulations) and an unmatched set of haloes. We find that the presence of AGN feedback suppresses the power on all scales for haloes of all masses examined ($10^{11.25}\leq M_{500,\mathrm{crit}}\leq 10^{14.75}\,\mathrm{M_\odot}/h$), by ejecting matter from within $r_{500,\mathrm{c}}$ to $r_{200,\mathrm{m}}$ and potentially beyond in massive haloes ($M_{500,\mathrm{crit}}\gtrsim 10^{13}\,\mathrm{M_\odot}/h$), and likely impeding the growth of lower-mass haloes as a consequence. A lower AGN feedback temperature drastically changes the behaviour of high-mass haloes ($M_{500,\mathrm{crit}}\geq 10^{13.25}\,\mathrm{M_\odot}/h$), damping the effects of AGN feedback at small scales, $k\,\gtrsim\,4\,h\mathrm{\,Mpc^{-1}}$. For $k\,\lesssim\,3\,h\mathrm{\,Mpc^{-1}}$, group-sized haloes ($10^{14\pm0.25}\, \mathrm{M_\odot}/h$) dominate the power spectrum, while on smaller scales the combined contributions of lower-mass haloes to the full power spectrum rise above that of the group-sized haloes. Finally, we present a model for the power suppression due to feedback, which combines observed mean halo baryon fractions with halo mass fractions and halo-matter cross-spectra extracted from dark matter only simulations to predict the power suppression to percent-level accuracy down to $k\,\approx\,10\,h\mathrm{\,Mpc^{-1}}$ without any free parameters.

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Non-linear CMB lensing with neutrinos and baryons: FLAMINGO simulations vs. fast approximations

Weak lensing of the cosmic microwave background is rapidly emerging as a powerful probe of neutrinos, dark energy, and new physics. We present a fast computation of the non-linear CMB lensing power spectrum which combines non-linear perturbation theory at early times with power spectrum emulation using cosmological simulations at late times. Comparing our calculation with lightcones from the FLAMINGO 5.6 Gpc cube dark-matter-only simulation, we confirm its accuracy to 1% (2%) up to multipoles L = 3000 (L = 5000) for a nuLambdaCDM cosmology consistent with current data. Clustering suppression due to small-scale baryonic phenomena such as feedback from active galactic nuclei can reduce the lensing power by of order 10%. To our perturbation theory and emulator-based calculation we add SP(k), a new fitting function for this suppression, and confirm its accuracy compared to the FLAMINGO hydrodynamic simulations to 4% at L = 5000, with similar accuracy for massive neutrino models. We further demonstrate that scale-dependent suppression due to neutrinos and baryons approximately factorize, implying that a careful treatment of baryonic feedback can limit biasing neutrino mass constraints.

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