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Filip Huško

Publications and source records attributed to Filip Huško.

At least 37 records · Page 2Linked to original sources

The COLIBRE-SKIRT pipeline: Calibration-free dust radiative transfer postprocessing for cosmological simulations

Context. Three-dimensional dust radiative transfer provides a powerful framework to connect cosmological galaxy simulations to multiwavelength observations. Until recently, in large-volume simulations, the formation of a cold ISM phase was prevented and dust was not evolved self-consistently. This required calibration of dust-to-metal ratios and extra subgrid dust attenuation in birth clouds, thereby reducing the predictive power. Aims. We present the COLIBRE-SKIRT pipeline, a calibration-free dust radiative transfer framework for the novel COLIBRE suite of large-volume cosmological simulations, which include a live dust model and directly simulate the multiphase ISM. Our primary aim is to establish a reference pipeline for generating multiwavelength mock observables from these simulations. As a first application, we produce far-ultraviolet (FUV) to far-infrared (FIR) spatially integrated spectra and assess them by comparison with the observed low-redshift cosmic spectral energy distribution (CSED). Methods. We apply the SKIRT dust radiative transfer code to the COLIBRE simulations. Dust masses and species fractions are taken directly from the simulation, and no birth cloud model is added in postprocessing. We introduce a "split & scale" approach that maps the simulated two-size, multi-species dust distribution onto continuous grain size distributions without introducing free parameters. Results. We find that, for the first time, a large-volume cosmological simulation directly reproduces the local Universe CSED without calibrating the postprocessing routine a priori. Residual tensions in the mid-infrared (~0.2 dex) point towards insufficient heating of the hottest dust components and uncertainties in the modelling of the PAH-emission carriers. This framework can be readily applied at low and high redshift to create synthetic spectra and images from the FUV to the FIR.

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Cosmological Galaxy Formation Modelling in the Era of the Square Kilometre Array

Over the past decade, galaxy formation simulations have advanced dramatically, transforming our ability to model the interstellar medium (ISM) and predict galaxies' radio emission. Yet the challenge of bridging physical scales--from sub-parsec star formation to gigaparsec cosmic structure--remains. The Square Kilometre Array (SKA) will map the cold gas and radio continuum of galaxies across cosmic time, demanding models that couple physical realism with cosmological reach. This chapter reviews the state-of-the-art in cosmological galaxy formation modelling in preparation for the SKA. We outline progress in simulating atomic hydrogen (HI), molecular gas, and radio continuum emission from both star formation and active galactic nuclei, highlighting how cosmological hydrodynamical simulations and semi-analytic models now jointly reproduce many observed gas properties. We emphasise the need for a coordinated, ``wedding-cake'' strategy that unites simulations of different scales, for forward modelling of observables to ensure fair comparison with data, and for the integration of new technologies such as AI-driven emulators to accelerate progress. Together, these efforts will enable theoretical models to both interpret and guide SKA science, turning simulations from passive interpreters into active engines for discovery.

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The evolution of the galaxy gas-phase mass-metallicity relation from $z=15$ to $z=0$ in the COLIBRE cosmological simulations

We present the evolution of the galaxy gas-phase mass-metallicity relation (MZR) from $z=15$ to $z=0$ in the COLIBRE cosmological hydrodynamical simulations. Amongst other novel features, COLIBRE follows the multiphase interstellar medium with gas allowed to cool to $\sim 10\,\mathrm{K}$, and includes a new chemistry model in which hydrogen and helium are tracked in non-equilibrium, metals are allowed to mix and diffuse, and the chemical network is coupled to a self-consistent live dust model. Using fiducial COLIBRE runs spanning particle masses from $10^5\,\mathrm{M_{\odot}}$ to $10^7\,\mathrm{M_{\odot}}$ and box sizes $25 - 400\,\mathrm{cMpc}$, we derive the median, mass-weighted MZRs for star-forming galaxies and compare them with a comprehensive compilation of observational data and other simulations. COLIBRE reproduces the observed MZR across cosmic time, notwithstanding the systematic uncertainties in observational measurements of the gas-phase oxygen abundances. The simulations show excellent numerical convergence and uniquely probe the full stellar mass range sampled by current observations across all redshifts. We find that the MZR is already in place at cosmic dawn ($z \approx 10$), and shows no evolution until $z \approx 5$. The slope of the MZR becomes shallower at low redshifts. The turnover at the high-mass end is largely governed by feedback from active galactic nuclei (AGN), whereas the low-mass end of the MZR sensitively depends on the strength of feedback from core collapse supernovae. Variations in the star formation efficiency or depletion of oxygen on dust grains have a more minor impact on the MZR. We identify key physical processes that shape the MZR across cosmic time and highlight where future observations can further constrain galaxy formation models.

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The importance of super-Eddington black hole accretion for the emergence of massive quiescent galaxies at high redshift

Recent JWST observations indicate that massive quiescent galaxies (stellar mass $M_{*}\gtrsim 10^{10}~\mathrm{M_\odot}$) at high redshift ($z\gtrsim 6$) are more abundant than predicted by most existing galaxy formation simulations and semi-analytic models. Notably, the new COLIBRE simulations have succeeded in reconciling this tension, though the precise reason for their improved agreement with JWST data remains unclear. We demonstrate that the improved agreement is largely due to super-Eddington growth of supermassive black holes (BHs) at high redshift. We run a series of $(100~\mathrm{cMpc})^{3}$ simulations with the COLIBRE subgrid physics at m7 COLIBRE resolution (gas and dark matter particle masses $m_{\rm gas}\approx m_{\rm dm}\sim 10^7~\mathrm{M_\odot}$), varying the maximum allowed BH accretion rate in units of the Eddington rate. We show that only the fiducial COLIBRE model, which permits super-Eddington accretion, is consistent with the JWST constraints at $z \gtrsim 6$. Moreover, we find that in COLIBRE about $50$ per cent of BH mass growth at high redshift occurs in the super-Eddington regime, even though such events are extremely rare in time. Our work highlights the important role of super-Eddington accretion in simulations of galaxy formation for reproducing the observed early emergence of quenching of massive galaxies.

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The evolution of the galaxy stellar mass function and star formation rates in the COLIBRE simulations from redshift 17 to 0

We investigate the evolution of the galaxy stellar mass function (GSMF) and star formation rates (SFRs) across cosmic time in the COLIBRE simulations of galaxy formation. COLIBRE includes a multiphase interstellar medium, radiative cooling rates coupled to a model for the evolution of dust grains, and employs prescriptions for stellar and AGN feedback calibrated to reproduce the $z=0$ observed GSMF and stellar mass - size relation. We present the evolution of the GSMF from simulations at three resolutions: $m_{\rm gas}\approx m_{\rm dm}\sim 10^7$, $10^6$, and $10^5~\mathrm{M_\odot}$, in cosmological volumes of up to $400^3$, $200^3$, and $100^3$ cMpc$^3$, respectively. We demonstrate that COLIBRE is consistent with the observed GSMF over the full redshift range for which there are observations to compare with ($0<z<12$), with maximum systematic deviations of $\approx 0.3$ dex reached at $2<z<4$. We also examine the evolution of the star-forming main sequence, cosmic SFR density, stellar mass density, and galaxy quenched fraction, making predictions for both the fiducial COLIBRE model with thermally-driven AGN feedback and its variant with hybrid (thermal + kinetic jet) AGN feedback, and finding good agreement with observations. Notably, we show that COLIBRE matches the number density of massive quiescent galaxies at high redshifts reported by JWST, while predicting a stellar-to-halo mass relation that evolves little with redshift. We conclude that neither a redshift-dependent star formation efficiency, nor a variable stellar initial mass function, nor a deviation from $Λ\mathrm{CDM}$ is necessary to reproduce the high-redshift JWST stellar masses and SFRs.

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Dynamical disequilibrium in dwarf galaxies: rethinking gas dynamics, rotation curves, and dark matter inference

We quantify departures from hydrodynamical and centrifugal equilibrium in the gas discs of low-mass ($10^{10.75}<M_\mathrm{200c}/\mathrm{M}_\odot<10^{11}$) galaxies from the COLIBRE cosmological hydrodynamical simulations. We evaluate the full Eulerian acceleration balance in the midplane and show that disequilibrium is widespread: equilibrium-based circular velocity estimates typically have errors of $\geq 10$ per cent ($\approx 75$ per cent of midplane gas by mass). Disequilibrium is strongest and the largest associated errors occur in the inner few kiloparsecs that are crucial for constraining the dark matter density profile. Correcting the circular velocity to account for pressure and convective terms does not reliably improve its recovery in strongly perturbed systems where time-dependent forces dominate the residual acceleration budget. Stellar feedback, self-gravitating gas clumps and AGN energy injection account for most strong local perturbations, and large-scale gravitational asymmetries act as a scaffold for disequilibrium. We classify gas discs into coherent, perturbed, and slow/erratic rotators and show that this classification correlates with galaxy properties like mass, morphology and tracers of recent feedback. A majority of galaxies in our sample would be unsuitable for standard rotation curve analysis. Much of the observed diversity in the shapes of dwarf galaxy rotation curves may stem from non-equilibrium gas motions rather than diversity in mass profiles - resolving the discrepancy is then first and foremost a problem in gas dynamics.

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Simulating AGN wind feedback with variable feedback efficiencies in idealised disc galaxies

Active Galactic Nucleus (AGN) feedback plays a critical role in galaxy formation and evolution. AGN-driven winds can significantly influence their host galaxies, although the details of their impact remain unclear. In this study, we investigate the feedback effects of AGN winds on idealized disc galaxies using the SWIFT hydrodynamical code with COLIBRE subgrid physics. We implement a new thermal AGN feedback model in which the energy injection coupling efficiency has a power-law dependence on the Eddington ratio of the black hole (BH) accretion rate, motivated by scaling relations for AGN winds from numerical models and observations. We simulate idealised Milky Way-mass galaxies, incorporating a BH, cold gas disc, stellar disc, and hot circumgalactic medium, within a static dark matter halo. We vary the BH mass and the slope and normalisation of the new coupling efficiency model. For a fixed BH mass, we find that while systematic trends with coupling efficiency exist, most galaxy and BH properties show only modest variations. This likely reflects BH self-regulation in the COLIBRE model, which modulates the effects of changes in the feedback efficiency, provided the BH mass is sufficiently high. Key exceptions are the BH accretion rate and mass growth history, and outflow behaviour, where lower coupling efficiencies lead to faster BH growth and weaker outflows, potentially helping to explain the presence of overmassive BHs at high redshifts. Varying the BH mass, however, has a much larger impact, confirming that BH mass remains the primary factor shaping galaxy and BH evolution in our simulations.

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COLIBRE: calibrating subgrid feedback in cosmological simulations that include a cold gas phase

We present the calibration of stellar and active galactic nucleus (AGN) feedback in the subgrid model for the new COLIBRE hydrodynamical simulations of galaxy formation. COLIBRE directly simulates the multi-phase interstellar medium and the evolution of dust grains, which is coupled to the chemistry. COLIBRE is calibrated at three resolutions: particle masses of $m_{\rm gas} \approx m_{\rm dm} \sim 10^7$ (m7), $10^6$ (m6), and $10^5~\mathrm{M_\odot}$ (m5). To calibrate the COLIBRE feedback at m7 resolution, we run Latin hypercubes of $\approx 200$ simulations that vary up to four subgrid parameters in cosmological volumes of ($50~\mathrm{cMpc}$)$^{3}$. We train Gaussian process emulators on these simulations to predict the $z=0$ galaxy stellar mass function (GSMF) and size - stellar mass relation (SSMR) as functions of the model parameters, which we then fit to observations. The trained emulators not only provide the best-fitting parameter values but also enable us to investigate how different aspects of the prescriptions for supernova and AGN feedback affect the predictions. In particular, we demonstrate that while the observed $z=0$ GSMF and SSMR can be matched individually with a relatively simple supernova feedback model, simultaneously reproducing both necessitates a more sophisticated prescription. We show that the calibrated m7 COLIBRE model not only reproduces the calibration target observables, but also matches various other galaxy properties to which the model was not calibrated. Finally, we apply the calibrated m7 model to the m6 and m5 resolutions and, after slight manual adjustments of the subgrid parameters, achieve a similar level of agreement with the observed $z=0$ GSMF and SSMR.

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The COLIBRE project: cosmological hydrodynamical simulations of galaxy formation and evolution

We present the COLIBRE galaxy formation model and the COLIBRE suite of cosmological hydrodynamical simulations. COLIBRE includes new models for radiative cooling, dust grains, star formation, stellar mass loss, turbulent diffusion, pre-supernova stellar feedback, supernova feedback, supermassive black holes and active galactic nucleus (AGN) feedback. The multiphase interstellar medium is explicitly modelled without a pressure floor. Hydrogen and helium are tracked in non-equilibrium, with their contributions to the free electron density included in metal-line cooling calculations. The chemical network is coupled to a dust model that tracks three grain species and two grain sizes. In addition to the fiducial thermally-driven AGN feedback, a subset of simulations uses black hole spin-dependent hybrid jet/thermal AGN feedback. To suppress spurious transfer of energy from dark matter to stars, dark matter is supersampled by a factor 4, yielding similar dark matter and baryonic particle masses. The subgrid feedback model is calibrated to match the observed $z \approx 0$ galaxy stellar mass function, galaxy sizes, and black hole masses in massive galaxies. The COLIBRE suite includes three resolutions, with particle masses of $\sim 10^5$, $10^6$, and $10^7\,\text{M}_\odot$ in cubic volumes of up to 100, 200, and 400 cMpc on a side, respectively. The largest runs use 136 billion ($5 \times 3008^3$) particles. We describe the model, assess its strengths and limitations, and present both visual impressions and quantitative results. Comparisons with various low-redshift galaxy observations generally show very good numerical convergence and excellent agreement with the data.

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A hybrid active galactic nucleus feedback model with spinning black holes, winds and jets

We present a hybrid active galactic nucleus (AGN) feedback model that features three accretion disc states (the thick, thin, and slim discs at low, moderate, and super-Eddington accretion rates, respectively), and two feedback modes: thermal isotropic and kinetic jets. The model includes black hole (BH) spin evolution due to gas accretion, BH mergers, jet spindown, and Lense-Thirring torques. The BH spin determines the jet directions and affects the feedback efficiencies. The model is implemented in the SWIFT code and coupled with the COLIBRE galaxy formation model. We present the first results from hybrid AGN feedback simulations run as part of the COLIBRE suite, focusing on the impact of new parameters and calibration efforts. Using the new hybrid AGN feedback model, we find that AGN feedback affects not just massive galaxies, but all galaxies down to $M_*\approx10^8$ $\mathrm{M}_\odot$. BH spins are predicted to be near-maximal for intermediate-mass BHs ($M_\mathrm{BH}\in[10^6,10^8]$ $\mathrm{M}_\odot$), and lower for other BH masses. These trends are in good agreement with observations. The intergalactic medium is hotter and impacted on larger scales in the hybrid AGN feedback simulations compared to those using purely thermal feedback. In the hybrid AGN simulations, we predict that half of the cumulative injected AGN energy is in thermal and the other half in jet form, broadly independent of BH mass and redshift. Jet feedback is important at all redshifts and dominates over thermal feedback at $z<0.5$ and $z>1.5$, but only mildly.

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Non-explosive pre-supernova feedback in the COLIBRE model of galaxy formation

We present the implementation and testing of a subgrid non-explosive pre-supernova (NEPS) feedback module for the COLIBRE model of galaxy formation. The NEPS module incorporates three key physical processes sourced by young, massive stars that act immediately following star formation: momentum injection from stellar winds and radiation pressure, and thermal energy from photoheating in HII regions. The age- and metallicity-dependent energy and momentum budgets are derived from BPASS stellar population models and are coupled self-consistently to the local gas properties. We test the model using a suite of smoothed particle hydrodynamics simulations of isolated, unstable gaseous disks at various numerical resolutions (gas particle masses in the range $10^4-10^6$ $\rm M_{\odot}$). We find that the NEPS module successfully regulates star formation by providing pressure support that prevents catastrophic gas collapse. This regulation improves the numerical convergence of star formation rates and disk structure. In our model, feedback from HII regions is the dominant regulatory mechanism. Furthermore, we demonstrate a crucial synergy with subsequent supernova feedback; NEPS feedback pre-processes the interstellar medium, creating a more homogeneous environment that moderates the effect of explosive feedback from supernova events. Our NEPS module thus provides a physically motivated and numerically robust framework that mitigates resolution-dependent artefacts and promotes self-regulated galaxy growth.

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The effects of super-Eddington accretion and feedback on the growth of early supermassive black holes and galaxies

We present results of cosmological zoom-in simulations of a massive protocluster down to redshift $z\approx4$ (when the halo mass is $\approx10^{13}$ M$_\odot$) using the SWIFT code and the EAGLE galaxy formation model, focusing on supermassive black hole (BH) physics. The BH was seeded with a mass of $10^4$ M$_\odot$ at redshift $z\approx17$. We compare the base model that uses an Eddington limit on the BH accretion rate and thermal isotropic feedback by the AGN, with one where super-Eddington accretion is allowed, as well as two other models with BH spin and jets. In the base model, the BH grows at the Eddington limit from $z=9$ to $z=5.5$, when it becomes massive enough to halt its own and its host galaxy's growth through feedback. We find that allowing super-Eddington accretion leads to drastic differences, with the BH going through an intense but short super-Eddington growth burst around $z\approx7.5$, during which it increases its mass by orders of magnitude, before feedback stops further growth (of both the BH and the galaxy). By $z\approx4$ the galaxy is only half as massive in the super-Eddington cases, and an order of magnitude more extended, with the half-mass radius reaching values of a few physical kpc instead of a few hundred pc. The BH masses in our simulations are consistent with the intrinsic BH mass$-$stellar mass relation inferred from high-redshift observations by JWST. This shows that galaxy formation models using the $Λ$CDM cosmology are capable of reproducing the observed massive BHs at high redshift. Allowing jets, either at super- or sub-Eddington rates, has little impact on the host galaxy properties, but leads to lower BH masses as a consequence of higher feedback efficiencies.

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SWIFT: A modern highly-parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and algorithms is thus crucial. In this paper, we introduce the fully open-source highly-parallel, versatile, and modular coupled hydrodynamics, gravity, cosmology, and galaxy-formation code SWIFT. The software package exploits hybrid shared- and distributed-memory task-based parallelism, asynchronous communications, and domain-decomposition algorithms based on balancing the workload, rather than the data, to efficiently exploit modern high-performance computing cluster architectures. Gravity is solved for using a fast-multipole-method, optionally coupled to a particle mesh solver in Fourier space to handle periodic volumes. For gas evolution, multiple modern flavours of Smoothed Particle Hydrodynamics are implemented. SWIFT also evolves neutrinos using a state-of-the-art particle-based method. Two complementary networks of sub-grid models for galaxy formation as well as extensions to simulate planetary physics are also released as part of the code. An extensive set of output options, including snapshots, light-cones, power spectra, and a coupling to structure finders are also included. We describe the overall code architecture, summarise the consistency and accuracy tests that were performed, and demonstrate the excellent weak-scaling performance of the code using a representative cosmological hydrodynamical problem with $\approx$$300$ billion particles. The code is released to the community alongside extensive documentation for both users and developers, a large selection of example test problems, and a suite of tools to aid in the analysis of large simulations run with SWIFT.

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Winds versus jets: a comparison between black hole feedback modes in simulations of idealized galaxy groups and clusters

Using the SWIFT simulation code we study different forms of active galactic nuclei (AGN) feedback in idealized galaxy groups and clusters. We first present a physically motivated model of black hole (BH) spin evolution and a numerical implementation of thermal isotropic feedback (representing the effects of energy-driven winds) and collimated kinetic jets that they launch at different accretion rates. We find that kinetic jet feedback is more efficient at quenching star formation in the brightest cluster galaxies (BCGs) than thermal isotropic feedback, while simultaneously yielding cooler cores in the intracluster medium (ICM). A hybrid model with both types of AGN feedback yields moderate star formation rates, while having the coolest cores. We then consider a simplified implementation of AGN feedback by fixing the feedback efficiencies and the jet direction, finding that the same general conclusions hold. We vary the feedback energetics (the kick velocity and the heating temperature), the fixed efficiencies and the type of energy (kinetic versus thermal) in both the isotropic and the jet case. The isotropic case is largely insensitive to these variations. In particular, we highlight that kinetic isotropic feedback (used e.g. in IllustrisTNG) is similar in its effects to its thermal counterpart (used e.g. in EAGLE). On the other hand, jet feedback must be kinetic in order to be efficient at quenching. We also find that it is much more sensitive to the choice of energy per feedback event (the jet velocity), as well as the efficiency. The former indicates that jet velocities need to be carefully chosen in cosmological simulations, while the latter motivates the use of BH spin evolution models.

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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 complex interplay of AGN jet-inflated bubbles and the intracluster medium

We use SWIFT, a smoothed particle hydrodynamics code, to simulate the evolution of bubbles inflated by active galactic nuclei (AGN) jets, as well as their interactions with the ambient intracluster medium (ICM). These jets inflate lobes that turn into bubbles after the jets are turned off (at $t=50$ Myr). Almost all of the energy injected into the jets is transferred to the ICM very quickly after they are turned off, with roughly $70$ per cent of it in thermal form and the rest in kinetic. At late times ($t>500$ Myr) we find the following: 1) the bubbles draw out trailing filaments of low-entropy gas, similar to those recently observed, 2) the action of buoyancy and the uplift of the filaments dominates the energetics of both the bubbles and the ICM and 3) almost all of the originally injected energy is in the form of gravitational potential energy, with the bubbles containing $15$ per cent of it, and the rest contained in the ICM. These findings indicate that feedback proceeds mainly through the displacement of gas to larger radii. We find that the uplift of these filaments permanently changes the thermodynamic properties of the ICM by reducing the central density and increasing the central temperature (within $30$ kpc). We propose that jet feedback proceeds not only through the heating of the ICM (which can delay cooling), but also through the uplift-related reduction of the central gas density. The latter also delays cooling, on top of reducing the amount of gas available to cool.

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Active galactic nuclei jets simulated with smoothed particle hydrodynamics

Simulations of active galactic nuclei (AGN) jets have thus far been performed almost exclusively using grid-based codes. We present the first results from hydrodynamical tests of AGN jets, and their interaction with the intracluster medium (ICM), using smoothed particle hydrodynamics (SPH) as implemented in the SWIFT code. We launch these jets into a constant-density ICM, as well as ones with a power-law density profile. We also vary the jet power, velocity, opening angle and numerical resolution. In all cases we find broad agreement between our jets and theoretical predictions for the lengths of the jets and the lobes they inflate, as well as the radii of the lobes. The jets first evolve ballistically, and then transition to a self-similar phase, during which the lobes expand in a self-similar fashion (keeping a constant shape). In this phase the kinetic and thermal energies in the lobes and in the shocked ICM are constant fractions of the total injected energy. In our standard simulation, two thirds of the initially injected energy is transferred to the ICM by the time the jets are turned off, mainly through a bow shock. Of that, $70\%$ is in kinetic form, indicating that the bow shock does not fully and efficiently thermalise while the jet is active. At resolutions typical of large cosmological simulations ($m_\mathrm{gas}\approx10^7$ $\mathrm{M}_\odot$), the shape of the lobes is close to self-similar predictions to an accuracy of $15\%$. This indicates that the basic physics of jet-inflated lobes can be correctly simulated even at such resolutions ($\approx500$ particles per jet).

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