arXiv subjects

Mark Vogelsberger

Publications and source records attributed to Mark Vogelsberger.

At least 235 records · Page 13Linked to original sources

arXiv2021

Weighing the Milky Way and Andromeda with Artificial Intelligence

We present new constraints on the masses of the halos hosting the Milky Way and Andromeda galaxies derived using graph neural networks. Our models, trained on thousands of state-of-the-art hydrodynamic simulations of the CAMELS project, only make use of the positions, velocities and stellar masses of the galaxies belonging to the halos, and are able to perform likelihood-free inference on halo masses while accounting for both cosmological and astrophysical uncertainties. Our constraints are in agreement with estimates from other traditional methods.

astro-ph.GA↗

arXiv2021

Impact of gas based seeding on supermassive black hole populations at $z\geq7$

Deciphering the formation of supermassive black holes~(SMBHs) is a key science goal for upcoming observational facilities. In most theoretical channels proposed so far, the seed formation depends crucially on local gas conditions. We systematically characterize the impact of a range of gas based black hole seeding prescriptions on SMBH populations using cosmological simulations. Seeds of mass $M_{\mathrm{seed}}\sim 10^3-10^{6}~M_{\odot}/h$ are placed in halos that exceed critical thresholds for star-forming, metal-poor gas mass and halo mass (defined as $\tilde{M}_{\mathrm{sf,mp}}$ and $\tilde{M}_{\mathrm{h}}$, respectively, in units of $M_{\mathrm{seed}}$). We quantify the impact of these parameters on the properties of $z\geq7$ SMBHs. Lower seed masses produce much higher BH merger rates (by factors of $\sim10$ and $\sim1000$ at $z\sim7$ and $z\sim15$, respectively). For fixed seed mass, we find that $\tilde{M}_{\mathrm{h}}$ has the strongest impact on the BH population at high redshift ($z\gtrsim15$, where a factor of 10 increase in $\tilde{M}_{\mathrm{h}}$ suppresses merger rates by $\gtrsim 100$). At lower redshift ($z\lesssim15$), we find that $\tilde{M}_{\mathrm{sf,mp}}$ has a larger impact on the BH population. Increasing $\tilde{M}_{\mathrm{sf,mp}}$ from $5-150$ suppresses the merger rates by factors of $\sim8$ at $z\sim7-15$. This suggests that the seeding criteria explored here could leave distinct imprints on the redshift distribution of LISA merger rates. In contrast, AGN luminosity functions are much less sensitive to seeding criteria, varying by factors $\lesssim2-3$ within the seed parameters we have explored. Such variations will be challenging to probe even with future sensitive instruments such as Lynx or JWST. Overall, our systematic parameter study provides a useful benchmark for development of seed models for large-volume cosmological simulations.

astro-ph.GA↗

arXiv2021

Impact of gas spin and Lyman-Werner flux on black hole seed formation in cosmological simulations: implications for direct collapse

Direct collapse black holes~(BH) are promising candidates for producing massive $z\gtrsim 6$ quasars, but their formation requires fine-tuned conditions. In this work, we use cosmological zoom simulations to study systematically the impact of requiring: 1) low gas angular momentum, and 2) a minimum incident Lyman-Werner~(LW) flux in order to form BH seeds. We probe the formation of seeds (with initial masses of $M_{\rm seed} \sim 10^4$ - $10^6 M_{\odot}/h)$ in halos with a total mass $> 3000\times M_{\mathrm{seed}}$ and a dense, metal poor gas mass $> 5\times M_{\mathrm{seed}}$. We find that the seed-forming halos have a prior history of star formation and metal enrichment, but contain pockets of dense, metal poor gas. When seeding is further restricted to halos with low gas spins, the number of seeds formed is suppressed by factors of $\sim6$ compared to the baseline model, regardless of the seed mass. Seed formation is much more strongly impacted if the dense, metal poor gas is required to have a critical LW flux ($J_{\mathrm{crit}}$). Even for $J_{\mathrm{crit}}$ values as low as $50J_{21}$, no $8\times10^{5}M_{\odot}/h$ seeds are formed. While lower mass ($1.25\times10^{4},1\times10^{5} M_{\odot}/h$) seeds do form, they are strongly suppressed~(by factors of $\sim10-100$) compared to the baseline model at gas mass resolutions of $\sim10^4~M_{\odot}/h$ (with even stronger suppression at higher resolutions). As a result, BH merger rates are also similarly suppressed. Since early BH growth is dominated by mergers in our models, no seeds are able to grow to the supermassive regime~($\gtrsim10^6 M_{\odot}/h$) by $z=7$. Our results hint that producing the bulk of the $z\gtrsim6$ supermassive BH population may require alternate seeding scenarios that do not depend on the LW flux, early BH growth dominated by rapid or super-Eddington accretion, or a combination of these possibilities.

astro-ph.GA↗

arXiv2021

Quenched, bulge-dominated, but dynamically cold galaxies in IllustrisTNG and their real-world counterparts

Galaxy morphologies, kinematics, and stellar populations are thought to be linked to each other. However, both simulations and observations have pointed out mismatches therein. In this work, we study the nature and origin of the present-day quenched, bulge-dominated, but dynamically cold galaxies within a stellar mass range of $10.3\,\leqslant\,\log\,M_{\ast}/\mathrm{M_{\odot}}\,\leqslant\,11.2$ in the IllustrisTNG-100 Simulation. We compare these galaxies with a population of normal star-forming dynamically cold disc galaxies and a population of normal quenched dynamically hot elliptical galaxies within the same mass range. The populations of the present-day quenched and bulge-dominated galaxies (both being dynamically cold and hot) used to have significantly higher star-formation rates and flatter morphologies at redshift of $z\sim 2$. They have experienced more frequent larger mass-ratio mergers below $z \sim 0.7$ in comparison to their star-forming disc counterparts, which is responsible for the formation of their bulge-dominated morphologies. The dynamically cold populations (both being star-forming and quenched) have experienced more frequent prograde and tangential mergers especially below $z \sim 1$, in contrast to the dynamically hot ellipticals, which have had more retrograde and radial mergers. Such different merging histories can well explain the differences on the cold and hot dynamical status among these galaxies. We point out that the real-world counterparts of these dynamically cold and hot bulge-dominated quenched populations are the fast- and slow-rotating early-type galaxies, respectively, as seen in observations and hence reveal the different evolution paths of these two distinct populations of early-type galaxies.

astro-ph.GA↗

arXiv2021

Supermassive black holes in cosmological simulations II: the AGN population and predictions for upcoming X-ray missions

In large-scale hydrodynamical cosmological simulations, the fate of massive galaxies is mainly dictated by the modeling of feedback from active galactic nuclei (AGN). The amount of energy released by AGN feedback is proportional to the mass that has been accreted onto the BHs, but the exact sub-grid modeling of AGN feedback differs in all simulations. Whilst modern simulations reliably produce populations of quiescent massive galaxies at z<2, it is also crucial to assess the similarities and differences of the responsible AGN populations. Here, we compare the AGN population of the Illustris, TNG100, TNG300, Horizon-AGN, EAGLE, and SIMBA simulations. The AGN luminosity function (LF) varies significantly between simulations. Although in agreement with current observational constraints at z=0, at higher redshift the agreement of the LFs deteriorates with most simulations producing too many AGN of L_{x, 2-10 keV}~10^43-10^44 erg/s. AGN feedback in some simulations prevents the existence of any bright AGN with L_{x, 2-10 keV}>=10^45 erg/s (although this is sensitive to AGN variability), and leads to smaller fractions of AGN in massive galaxies than in the observations at z<=2. We find that all the simulations fail at producing a number density of AGN in good agreement with observational constraints for both luminous (L_{x, 2-10 keV}~10^43-10^45 erg/s) and fainter (L_{x, 2-10 keV}~10^42-10^43 erg/s) AGN, and at both low and high redshift. These differences can aid us in improving future BH and galaxy subgrid modeling in simulations. Upcoming X-ray missions (e.g., Athena, AXIS, and LynX) will bring faint AGN to light and new powerful constraints. After accounting for AGN obscuration, we find that the predicted number density of detectable AGN in future surveys spans at least one order of magnitude across the simulations, at any redshift.

astro-ph.GA↗

arXiv2021

The large-scale distribution of ionized metals in IllustrisTNG

We study the intrinsic large-scale distribution and evolution of seven ionized metals in the IllustrisTNG magneto-hydrodynamical cosmological simulation. We focus on the fractions of C\,\textsc{ii}, C\,\textsc{iv}, Mg\,\textsc{ii}, N\,\textsc{v}, Ne\,\textsc{viii}, O\,\textsc{vi}, and Si\,\textsc{iv} in different cosmic web structures (filaments, haloes, and voids) and gas phases (warm-hot intergalactic medium WHIM, hot, diffuse, and condensed gas) from $z=6$ to $z=0$. Our analysis provides a new perspective to the study of the distribution and evolution of baryons across cosmic time while offering new hints in the context of the well-known missing baryons problem. The cosmic web components are here identified using the local comoving dark matter density, which provides a simple but effective way of mapping baryons on large scales. Our results show that C\,\textsc{ii} and Mg\,\textsc{ii} are mostly located in condensed gas inside haloes in high-density and low-temperature star-forming regions ($ρ_{\rm gas}/\barρ_{\rm bar}\gtrsim10^3$, and ${\rm T}\lesssim10^{5}$~K). C\,\textsc{iv} and Si\,\textsc{iv} present similar evolution of their mass fractions in haloes and filaments across cosmic time. In particular, their mass budgets in haloes in condensed phase ($ρ_{\rm gas}/\barρ_{\rm bar}\gtrsim10^3$, and ${\rm T}\lesssim10^{5}$~K) are driven by gas cooling and star formation with a peak at $z\sim2$. Finally, our results confirm that O\,\textsc{vi}, Ne\,\textsc{viii}, and N\,\textsc{v} are good tracers of warm/hot and low-density gas at low redshift ($ρ_{\rm gas}/\barρ_{\rm bar}\lesssim10^3$, and ${\rm T}\gtrsim10^{5}$~K), regions that are likely to contain most of the missing baryons in the local Universe.

astro-ph.GA↗

arXiv2021

Supermassive black holes in cosmological simulations I: M_BH-M_star relation and black hole mass function

The past decade has seen significant progress in understanding galaxy formation and evolution using large-scale cosmological simulations. While these simulations produce galaxies in overall good agreement with observations, they employ different sub-grid models for galaxies and supermassive black holes (BHs). We investigate the impact of the sub-grid models on the BH mass properties of the Illustris, TNG100, TNG300, Horizon-AGN, EAGLE, and SIMBA simulations, focusing on the M_BH-M_star relation and the BH mass function. All simulations predict tight M_BH-M_star relations, and struggle to produce the lowest (M_BH< 10^7.5 Msun) in galaxies of M_star~10^10.5-10^11.5 Msun. While the time evolution of the mean M_BH-M_star relation is mild (<1 dex in BH mass for 0 10^9 Msun in most of the simulations. The BH mass function is dominated by efficiently accreting BHs (log10 f_Edd >-2$) at high redshifts, and transitions progressively from the high-mass to the low-mass end to be governed by inactive BHs. The transition time and the contribution of active BHs are different among the simulations, and can be used to evaluate models against observations.

astro-ph.GA↗

arXiv2021

Gas flows in galaxy mergers: supersonic turbulence in bridges, accretion from the circumgalactic medium, and metallicity dilution

In major galaxy mergers, the orbits of stars are violently perturbed, and gas is torqued to the centre, diluting the gas metallicity and igniting a starburst. In this paper, we study the gas dynamics in and around merging galaxies using a series of cosmological magneto-hydrodynamical (MHD) zoom-in simulations. We find that the gas bridge connecting the merging galaxies pre-coalescence is dominated by turbulent pressure, with turbulent Mach numbers peaking at values of 1.6-3.3. This implies that bridges are dominated by supersonic turbulence, and are thus ideal candidates for studying the impact of extreme environments on star formation. We also find that gas accreted from the circumgalactic medium (CGM) during the merger significantly contributes (27-51 per cent) to the star formation rate (SFR) at the time of coalescence and drives the subsequent reignition of star formation in the merger remnant. Indeed, 19-53 per cent of the SFR at z=0 originates from gas belonging to the CGM prior the merger. Finally, we investigate the origin of the metallicity-diluted gas at the centre of merging galaxies. We show that this gas is rapidly accreted onto the galactic centre with a time-scale much shorter than that of normal star-forming galaxies. This explains why coalescing galaxies are not well-captured by the fundamental metallicity relation.

astro-ph.GA↗

arXiv2021

The physical origins and dominant emission mechanisms of Lyman-alpha halos: results from the TNG50 simulation in comparison to MUSE observations

Extended Lyman-alpha emission is now commonly detected around high redshift galaxies through stacking and even on individual basis. Despite recent observational advances, the physical origin of these Lyman-alpha halos (LAHs), as well as their relationships to galaxies, quasars, circumgalactic gas, and other environmental factors remains unclear. We present results from our new Lyman-alpha full radiative transfer code voroILTIS which runs directly on the unstructured Voronoi tessellation of cosmological hydrodynamical simulations. We make use of the TNG50 simulation and simulate LAHs from redshift $z=2$ to $z=5$, focusing on star-forming galaxies with $8.0 < \log_{10}{(M_\star/\rm{M}_\odot)} < 10.5$. While TNG50 does not directly follow ionizing radiation, it includes an on-the-fly treatment for active galactic nuclei and ultraviolet background radiation with self-shielding, which are important processes impacting the cooling and ionization of the gas. Based on this model, we present the predictions for the stacked radial surface brightness profiles of Ly$α$ as a function of galaxy mass and redshift. Comparison with data from the MUSE UDF at $z>3$ reveals a promising level of agreement. We measure the correlations of LAH size and central brightness with galaxy properties, finding that at the masses of $8.5 \leq \log_{10} \left(M_\star/\rm{M}_\odot\right) \leq 9.5$, physical LAH sizes roughly double from $z=2$ to $z=5$. Finally, we decompose the profiles into contributions from diffuse emission and scattered photons from star-forming regions. In our simulations, we find rescattered photons from star-forming regions to be the major source in observed LAHs. Unexpectedly, we find that the flattening of LAH profiles at large radii becomes dominated by photons originating from other nearby halos rather than diffuse emission itself.

astro-ph.GA↗

arXiv2021

Real and counterfeit cores: how feedback expands halos and disrupts tracers of inner gravitational potential in dwarf galaxies

The tension between the diverging density profiles in Lambda Cold Dark Matter ($Λ$CDM) simulations and the constant-density inner regions of observed galaxies is a long-standing challenge known as the `core-cusp' problem. We demonstrate that the \texttt{SMUGGLE} galaxy formation model implemented in the \textsc{Arepo} moving mesh code forms constant-density cores in idealized dwarf galaxies of $M_\star \approx 8 \times 10^7$ M$_{\odot}$ with initially cuspy dark matter halos of $M_{200} \approx 10^{10}$ M$_{\odot}$. Identical initial conditions run with the Springel and Hernquist (2003; SH03) feedback model preserve cuspiness. Literature on the subject has pointed to the low density threshold for star formation, $ρ_\text{th}$, in SH03-like models as an obstacle to baryon-induced core formation. Using a \texttt{SMUGGLE} run with equal $ρ_\text{th}$ to SH03, we demonstrate that core formation can proceed at low density thresholds, indicating that $ρ_\text{th}$ is insufficient on its own to determine whether a galaxy develops a core. We suggest that the ability to resolve a multiphase interstellar medium at sufficiently high densities is a more reliable indicator of core formation than any individual model parameter. In \texttt{SMUGGLE}, core formation is accompanied by large degrees of non-circular motion, with gas rotational velocity profiles that consistently fall below the circular velocity $v_\text{circ} = \sqrt{GM/R}$ out to $\sim 2$ kpc. This may artificially mimic larger core sizes when derived from observable quantities compared to the size measured from the dark matter distribution ($\sim 0.5$ kpc), highlighting the need for careful modeling in the inner regions of dwarfs to infer the true distribution of dark matter.

astro-ph.GA↗

arXiv2021

The abundance of satellites around Milky Way- and M31-like galaxies with the TNG50 simulation: a matter of diversity

We study the abundance of satellite galaxies around 198 Milky Way- (MW) and M31-like hosts in TNG50, the final instalment in the IllustrisTNG suite of cosmological magnetohydrodynamical simulations. MW/M31-like analogues are defined as disky galaxies with stellar masses of Mstar = 10^10.5-11.2 Msun in relative isolation at z = 0. By defining satellites as galaxies with Mstar > 5*10^6 Msun within 300 kpc (3D) of their host, we find a remarkable level of diversity and host-to-host scatter across individual host galaxies. The median (16th - 84th percentiles) TNG50 MW/M31-like galaxy hosts a total of 5 (2-11) satellites with Mstar > 5*10^6 Msun, reaching up to Mstar ~ 10^8.5 Msun (10^7.4-9.4 Msun). The abundance of subhaloes with Mdyn > 5*10^7 Msun is larger by a factor of more than 10. The number of all satellites (subhaloes) ever accreted is larger by a factor of 4-5 (3-5) than those surviving to z = 0. Hosts with larger galaxy stellar mass, brighter K-band luminosity, larger total halo mass, and more recent halo assembly typically have a larger number of surviving satellites. The satellite abundances around TNG50 MW/M31-like galaxies are consistent with similar hosts from observational surveys (e.g. SAGA) and previous simulations (e.g. Latte). While the observed MW satellite system falls within the TNG50 scatter across all stellar masses considered, M31 is slightly more satellite-rich than our 1 sigma scatter, possibly due to volume and mass limitations. We find a handful of systems with both a Large and a Small Magellanic Cloud-like satellite. There is no missing satellites problem with TNG50.

astro-ph.GA↗

arXiv2021

AGN and Star Formation at Cosmic Noon: Comparison of Data to Theoretical Models

In theoretical models of galaxy evolution, AGN and star formation (SF) activity are closely linked and AGN feedback is routinely invoked to regulate galaxy growth. In order to constrain such models, we compare the hydrodynamical simulations IllustrisTNG and SIMBA, and the semi-analytical model SAG to the empirical results on AGN and SF at cosmic noon ($0.75 < z < 2.25$) reported in Florez et al. (2020). The empirical results are based on a large mass-complete sample drawn from 93,307 galaxies with and without high X-ray luminosity AGN ($L_X \gtrsim 10^{44}$ erg s$^{-1}$), selected from a 11.8 deg$^2$ area ($\sim 0.18$ Gpc$^3$ comoving volume at $z=0.75-2.25$). The main results of our comparisons are: (i) SAG and IllustrisTNG both qualitatively reproduce the empirical result that galaxies with high X-ray luminosity AGN have higher mean SFR, at a given stellar mass, than galaxies without such AGN. SAG, however, strongly over-produces the number density of high X-ray luminosity AGN by a factor of 10 to 100, while IllustrisTNG shows a lack of high X-ray luminosity AGN at high stellar mass ($M* > 10^{11} \ M_{\odot}$) at $z \sim 2$. (ii) In SIMBA, the mean SFR of galaxies with high X-ray luminosity AGN is lower than the SFR of galaxies without such AGN. Contrary to the data, many high X-ray luminosity AGN in SIMBA have quenched SF, suggesting that AGN feedback, or other feedback modes in galaxies with such AGN, might be too efficient in SIMBA.

astro-ph.GA↗

arXiv2021

The CAMELS Multifield Dataset: Learning the Universe's Fundamental Parameters with Artificial Intelligence

We present the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) Multifield Dataset, CMD, a collection of hundreds of thousands of 2D maps and 3D grids containing many different properties of cosmic gas, dark matter, and stars from 2,000 distinct simulated universes at several cosmic times. The 2D maps and 3D grids represent cosmic regions that span $\sim$100 million light years and have been generated from thousands of state-of-the-art hydrodynamic and gravity-only N-body simulations from the CAMELS project. Designed to train machine learning models, CMD is the largest dataset of its kind containing more than 70 Terabytes of data. In this paper we describe CMD in detail and outline a few of its applications. We focus our attention on one such task, parameter inference, formulating the problems we face as a challenge to the community. We release all data and provide further technical details at https://camels-multifield-dataset.readthedocs.io.

cs.LG↗

arXiv2021

Robust marginalization of baryonic effects for cosmological inference at the field level

We train neural networks to perform likelihood-free inference from $(25\,h^{-1}{\rm Mpc})^2$ 2D maps containing the total mass surface density from thousands of hydrodynamic simulations of the CAMELS project. We show that the networks can extract information beyond one-point functions and power spectra from all resolved scales ($\gtrsim 100\,h^{-1}{\rm kpc}$) while performing a robust marginalization over baryonic physics at the field level: the model can infer the value of $Ω_{\rm m} (\pm 4\%)$ and $σ_8 (\pm 2.5\%)$ from simulations completely different to the ones used to train it.

astro-ph.CO↗

arXiv2021

Multifield Cosmology with Artificial Intelligence

Astrophysical processes such as feedback from supernovae and active galactic nuclei modify the properties and spatial distribution of dark matter, gas, and galaxies in a poorly understood way. This uncertainty is one of the main theoretical obstacles to extract information from cosmological surveys. We use 2,000 state-of-the-art hydrodynamic simulations from the CAMELS project spanning a wide variety of cosmological and astrophysical models and generate hundreds of thousands of 2-dimensional maps for 13 different fields: from dark matter to gas and stellar properties. We use these maps to train convolutional neural networks to extract the maximum amount of cosmological information while marginalizing over astrophysical effects at the field level. Although our maps only cover a small area of $(25~h^{-1}{\rm Mpc})^2$, and the different fields are contaminated by astrophysical effects in very different ways, our networks can infer the values of $Ω_{\rm m}$ and $σ_8$ with a few percent level precision for most of the fields. We find that the marginalization performed by the network retains a wealth of cosmological information compared to a model trained on maps from gravity-only N-body simulations that are not contaminated by astrophysical effects. Finally, we train our networks on multifields -- 2D maps that contain several fields as different colors or channels -- and find that not only they can infer the value of all parameters with higher accuracy than networks trained on individual fields, but they can constrain the value of $Ω_{\rm m}$ with higher accuracy than the maps from the N-body simulations.

astro-ph.CO↗

arXiv2021

Inpainting hydrodynamical maps with deep learning

From 1,000 hydrodynamic simulations of the CAMELS project, each with a different value of the cosmological and astrophysical parameters, we generate 15,000 gas temperature maps. We use a state-of-the-art deep convolutional neural network to recover missing data from those maps. We mimic the missing data by applying regular and irregular binary masks that cover either $15\%$ or $30\%$ of the area of each map. We quantify the reliability of our results using two summary statistics: 1) the distance between the probability density functions (pdf), estimated using the Kolmogorov-Smirnov (KS) test, and 2) the 2D power spectrum. We find an excellent agreement between the model prediction and the unmasked maps when using the power spectrum: better than $1\%$ for $k<20 h/$Mpc for any irregular mask. For regular masks, we observe a systematic offset of $\sim5\%$ when covering $15\%$ of the maps while the results become unreliable when $30\%$ of the data is missing. The observed KS-test p-values favor the null hypothesis that the reconstructed and the ground-truth maps are drawn from the same underlying distribution when irregular masks are used. For regular-shaped masks on the other hand, we find a strong evidence that the two distributions do not match each other. Finally, we use the model, trained on gas temperature maps, to perform inpainting on maps from completely different fields such as gas mass, gas pressure, and electron density and also for gas temperature maps from simulations run with other codes. We find that visually, our model is able to reconstruct the missing pixels from the maps of those fields with great accuracy, although its performance using summary statistics depends strongly on the considered field.

astro-ph.CO↗

arXiv2021

Finding universal relations in subhalo properties with artificial intelligence

We use a generic formalism designed to search for relations in high-dimensional spaces to determine if the total mass of a subhalo can be predicted from other internal properties such as velocity dispersion, radius, or star-formation rate. We train neural networks using data from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project and show that the model can predict the total mass of a subhalo with high accuracy: more than 99% of the subhalos have a predicted mass within 0.2 dex of their true value. The networks exhibit surprising extrapolation properties, being able to accurately predict the total mass of any type of subhalo containing any kind of galaxy at any redshift from simulations with different cosmologies, astrophysics models, subgrid physics, volumes, and resolutions, indicating that the network may have found a universal relation. We then use different methods to find equations that approximate the relation found by the networks and derive new analytic expressions that predict the total mass of a subhalo from its radius, velocity dispersion, and maximum circular velocity. We show that in some regimes, the analytic expressions are more accurate than the neural networks. We interpret the relation found by the neural network and approximated by the analytic equation as being connected to the virial theorem.

astro-ph.CO↗

arXiv2021

Quiescent Ultra-diffuse galaxies in the field originating from backsplash orbits

Ultra-diffuse galaxies (UDGs) are the lowest-surface brightness galaxies known, with typical stellar masses of dwarf galaxies but sizes similar to larger galaxies like the Milky Way. The reason for their extended sizes is debated, with suggested internal processes like angular momentum, feedback or mergers versus external mechanisms or a combination of both. Observationally, we know that UDGs are red and quiescent in groups and clusters while their counterparts in the field are blue and star-forming. This dichotomy suggests environmental effects as main culprit. However, this scenario is challenged by recent observations of isolated quiescent UDGs in the field. Here we use $Λ$CDM cosmological hydrodynamical simulation to show that isolated quenched UDGs are formed as backsplash galaxies that were once satellites of another galactic, group or cluster halo but are today a few Mpc away from them. These interactions, albeit brief, remove the gas and tidally strip the outskirts of the dark matter haloes of the now quenched seemingly-isolated UDGs, which are born as star-forming field UDGs occupying dwarf-mass dark matter haloes. Quiescent UDGs may therefore be found in non-negligible numbers in filaments and voids, bearing the mark of past interactions as stripped outer haloes devoid of dark matter and gas compared to dwarfs with similar stellar content.

astro-ph.GA↗