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Francesco Belfiore

Publications and source records attributed to Francesco Belfiore.

At least 37 records · Page 2Linked to original sources

Masses, Star-Formation Efficiencies, and Dynamical Evolution of 18,000 HII Regions

We present measurements of the masses associated with $\sim18,000$ HII regions across 19 nearby star-forming galaxies by combining data from JWST, HST, MUSE, ALMA, VLA, and MeerKAT from the multi-wavelength PHANGS survey. We report 10 pc-scale measurements of the mass of young stars, ionized gas, and older disk stars coincident with each HII region, as well as the initial and current mass of molecular gas, atomic gas, and swept-up shell material, estimated from lower resolution data. We find that the mass of older stars dominates over young stars at $\gtrsim10\rm\,pc$ scales, and ionized gas exceeds the stellar mass in most optically bright HII regions. Combining our mass measurements for a statistically large sample of HII regions, we derive 10 pc scale star-formation efficiencies $\approx6{-}17\%$ for individual HII regions. Comparing each region's self-gravity with the ambient ISM pressure and total pressure from pre-supernova stellar feedback, we show that most optically bright HII regions are over-pressured relative to their own self-gravity and the ambient ISM pressure, and that they are hence likely expanding into their surroundings. Larger HII regions in galaxy centers approach dynamical equilibrium. The self-gravity of regions is expected to dominate over pre-supernova stellar feedback pressure at $\gtrsim130\rm\,pc$ and $60\rm\,pc$ scales in galaxy disks and centers, respectively, but is always sub-dominant to the ambient ISM pressure on HII region scales. Our measurements have direct implications for the dynamical evolution of star-forming regions and the efficiency of stellar feedback in ionizing and clearing cold gas.

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Polycyclic aromatic hydrocarbons destruction in star-forming regions across 42 nearby galaxies

Polycyclic aromatic hydrocarbons (PAHs) are widespread in the interstellar medium (ISM) of Solar metallicity galaxies, where they play a critical role in ISM heating, cooling, and reprocessing stellar radiation. The PAH fraction, the abundance of PAHs relative to total dust mass, is a key parameter in ISM physics. Using JWST and MUSE observations of 42 galaxies from the PHANGS survey, we analyze the PAH fraction in over 17 000 H II regions spanning a gas-phase oxygen abundance of 12+log(O/H) = 8.0-8.8 (Z ~ 0.2-1.3 Zsun), and ~400 isolated supernova remnants (SNRs). We find a significantly lower PAH fraction toward H II regions compared to a reference sample of diffuse ISM areas at matched metallicity. At 12+log(O/H) > 8.2, the PAH fraction toward H II regions is strongly anti-correlated with the local ionization parameter, suggesting that PAH destruction is correlated with ionized gas and/or hydrogen-ionizing UV radiation. At lower metallicities, the PAH fraction declines steeply in both H II regions and the diffuse ISM, likely reflecting less efficient PAH formation in metal-poor environments. Carefully isolating dust emission from the vicinity of optically-identified supernova remnants, we see evidence for selective PAH destruction from measurements of lower PAH fractions, which is, however, indistinguishable at ~50 pc scales. Overall, our results point to ionizing radiation as the dominant agent of PAH destruction within H II regions, with metallicity playing a key role in their global abundance in galaxies.

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Element nucleosynthetic origins from abundance spatial distributions beyond the Milky Way

An element's astrophysical origin should be reflected in the spatial distribution of its abundance, yielding measurably different spatial distributions for elements with different nucleosynthetic sites. However, most extragalactic multi-element analyses of gas-phase abundances to date have been limited to small numbers of sightlines, making statistical characterization of differences in spatial distributions of elements impossible. Here we use integrated field spectroscopic data covering the full face of the nearby dwarf galaxy NGC 5253 sampled at 3.5-pc resolution to produce maps of the abundances of oxygen, nitrogen, and sulfur using independent direct methods. We find strong evidence for differences in the elements' spatial statistics that mirror their predicted nucleosynthetic origins: the spatial distributions of oxygen and sulfur, both predominantly produced in core-collapse supernovae, indicate that initial injection occurs on larger scales than for nitrogen, which is predominantly produced by asymptotic giant branch stars. All elements are well-correlated but oxygen and sulfur are much better correlated with each other than with nitrogen, consistent with recent results for stellar abundances in the Milky Way. These findings both open a new avenue to test nucleosynthetic models, and make predictions for the structure of stellar chemical abundance distributions.

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Time-scales of polycyclic aromatic hydrocarbon and dust continuum emission from gas clouds compared to molecular gas cloud lifetimes in PHANGS-JWST galaxies

Recent JWST mid-infrared (mid-IR) images, tracing polycyclic aromatic hydrocarbons (PAHs) and dust continuum emission, provide detailed views of the interstellar medium (ISM) in nearby galaxies. Leveraging PHANGS-JWST Cycle 1 and PHANGS-MUSE data, we measure the PAH and dust continuum emission lifetimes of gas clouds across 17 nearby star-forming galaxies by analyzing the relative spatial distributions of mid-IR (7.7-11.3$μ$m) and H$α$ emission at various scales. We find that the mid-IR emitting time-scale of gas clouds in galaxy disks (excluding centers) ranges from 10 to 30Myr. After star formation is detected in H$α$, mid-IR emission persists for 3-7Myr during the stellar feedback phase, covering 70-80% of the H$α$ emission. This significant overlap is due to intense radiation from star-forming regions, illuminating the surrounding PAHs and dust grains. In most galaxies, the mid-IR time-scale closely matches the molecular cloud lifetime measured with CO. Although mid-IR emission is complex as influenced by ISM distribution, radiation, and abundances of dust and PAHs, the similarity between the two time-scales suggests that once gas clouds form with compact mid-IR emission, they quickly provide sufficient shielding for stable CO formation. This is likely due to our focus on molecular gas-rich regions of galaxies with near-solar metallicity. Finally, we find that the mid-IR emitting time-scale is longer in galaxies with well-defined HII regions and less structured backgrounds, allowing photons to more efficiently heat the ambient ISM surrounding the HII regions, rather than contributing to diffuse emission. This suggests that the shape of the ISM also influences mid-IR emission.

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Classifying spectra of emission-line regions with neural networks -- An application to integral field spectroscopic data of M33

Emission-line regions are key to understanding the properties of galaxies, as they trace the exchange of matter and energy between stars and the interstellar medium (ISM). In nearby galaxies, individual nebulae can be identified as HII regions, planetary nebulae (PNe), supernova remnants (SNR), and diffuse ionised gas (DIG) with criteria on single or multiple emission-line ratios. However, these methods are limited by rigid classification boundaries, the narrow scope of information they are based upon, and the inability to account for line-of-sight nebular superpositions. In this work, we use artificial neural networks to classify these regions using their optical spectra. Our training set consists of simulated spectra, obtained from photoionisation and shock models, and processed to match observations obtained with MUSE. We evaluate the performance of the network on simulated spectra for a range of signal-to-noise (S/N) levels and dust extinction, and the superposition of different nebulae along the line of sight. At infinite S/N the network achieves perfect predictive performance, while as the S/N decreases, the classification accuracy declines, reaching an average of ~80% at S/N(H$α$)=20. We apply our model to real spectra from MUSE observations of the galaxy M33, where it provides a robust classification of individual spaxels, even at low S/N, identifying HII regions and PNe and distinguishing them from SNRs and diffuse ionized gas, while identifying overlapping nebulae. We then compare the network's classification with traditional diagnostics and find satisfactory agreement. Using activation maximisation maps, we find that at high S/N the model mainly relies on weak lines (e.g. auroral lines of metal ions and He recombination lines), while at the S/N level typical of our dataset the model effectively emulates traditional diagnostic methods by leveraging strong nebular lines.

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Unveiling the Fast Acceleration of AGN-Driven Winds at Kiloparsec Scales

Supermassive black holes at the centre of galaxies gain mass through accretion disks. Models predict that quasi-spherical winds, expelled by the black hole during active accretion phases, have a key role in shaping galaxy evolution by regulating star formation, the distribution of metals over kiloparsec scales, and by sweeping ambient gas to the outskirts and beyond of galaxies. Nonetheless, the mechanism driving these outflows and the amount of energy exchanged between the wind and the galaxy's interstellar medium remain unclear. Here, we present a detailed analysis of the kinematical properties of winds in a sample of nearby active galaxies using the novel kinematic tool MOKA3D, which takes into account the clumpy nature of the ISM. We find remarkable similarities among the properties of the outflows in all the galaxies examined. In particular, we provide the first evidence that outflows exhibit a regular trend in radial velocity, initially constant or slightly decreasing, followed by rapid acceleration starting at approximately 1 kpc from the nucleus, despite the seemingly complex kinematics observed. The observed behavior aligns with our current theoretical understanding of Active Galactic Nuclei outflows, where a momentum-driven phase transitions to an energy-conserving phase just beyond approximately 1 kpc. The constant velocity of the momentum-driven wind is then rapidly accelerated following the inefficient Compton cooling of post-shock material and the transition to energy conservation. The measured radial terminal velocities of the outflows are always larger than the escape velocities from the host galaxies, confirming the key role of outflows in shaping the galaxy properties and evolution, as a manifestation of AGN feedback. Our results, only made possible by our novel kinematic analysis tool, are crucial to understand the origin and the powering mechanism of these winds.

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The resolved star-formation efficiency of early-type galaxies

Understanding how and why star formation varies between galaxies is fundamental to our comprehension of galaxy evolution. In particular, the star-formation efficiency (SFE; star-formation rate or SFR per unit cold gas mass) has been shown to vary substantially both across and within galaxies. Early-type galaxies (ETGs) constitute an extreme case, as about a quarter have detectable molecular gas reservoirs but little to no detectable star formation. In this work, we present a spatially-resolved view of the SFE in ten ETGs, combining state-of-the-art Atacama Large Millimeter/submillimeter Array (ALMA) and Multi Unit Spectroscopic Explorer (MUSE) observations. Optical spectroscopic line diagnostics are used to identify the ionized emission regions dominated by star-formation, and reject regions where the ionization arises primarily from other sources. We identify very few regions where the ionization is consistent with pure star formation. Using ${\rm H}α$ as our SFR tracer, we find that previous integrated measurements of the star-formation rate based on UV and 22$μ$m emission are systematically higher than the SFR measured from ${\rm H}α$. However, for the small number of regions where ionization is primarily associated with star formation, the SFEs are around 0.4 dex higher than those measured in star-forming galaxies at a similar spatial resolution (with depletion times ranging from $10^8$ to $10^{10}$ yr). Whilst the SFE of ETGs is overall low, we find that the SFEs of individual regions within ETGs can be similar to, or higher than, similar sized regions within star-forming galaxies.

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Linking stellar populations to HII regions across nearby galaxies. II. Infrared Reprocessed and UV Direct Radiation Pressure in HII Regions

Radiation pressure is a key mechanism by which stellar feedback disrupts molecular clouds and drives HII region expansion. This includes direct radiation pressure exerted by UV photons on dust grains, pressure associated with photoionization, and infrared (IR) radiation pressure on grains due to dust-reprocessed IR photons. We present a new method that combines high resolution mid-IR luminosities from JWST-MIRI, optical attenuation and nebular line measurements from VLT-MUSE, and HST H$α$-based region sizes to estimate the strength of radiation pressure in $\approx 18,000$ HII regions across 19 nearby star-forming galaxies. This is the most extensive and direct estimate of these terms beyond the Local Group to date. In the disks of galaxies, we find that the total reprocessed IR pressure is on average 5% of the direct UV radiation pressure. This fraction rises to 10% in galaxy centers. We expect reprocessed IR radiation pressure to dominate over UV radiation pressure in regions where $L_{\rm F2100W}/L_{\rm Hα}^{\rm corr} \gtrsim 75$. Radiation pressure due to H ionizations is lower than pressure on dust in our sample, but appears likely to dominate the radiation pressure budget in dwarf galaxies similar to the Small Magellanic Cloud. The contribution from all radiation pressure terms appears to be subdominant compared to thermal pressure from ionized gas, reinforcing the view that radiation pressure is most important in compact, heavily embedded, and young regions.

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The PHANGS-HST-Halpha Survey: Warm Ionized Gas Physics at High Angular resolution in Nearby GalaxieS with the Hubble Space Telescope

The PHANGS project is assembling a comprehensive, multi-wavelength dataset of nearby (~5-20 Mpc), massive star-forming galaxies to enable multi-phase, multi-scale investigations into the processes that drive star formation and galaxy evolution. To date, large survey programs have provided molecular gas (CO) cubes with ALMA, optical IFU spectroscopy with VLT/MUSE, high-resolution NUV--optical imaging in five broad-band filters with HST, and infrared imaging in NIRCAM+MIRI filters with JWST. Here, we present PHANGS-HST-Halpha, which has obtained high-resolution (~2-10 pc), narrow-band imaging in the F658N or F657N filters with the HST/WFC3 camera of the warm ionized gas in the first 19 nearby galaxies observed in common by all four of the PHANGS large programs. We summarize our data reduction process, with a detailed discussion of the production of flux-calibrated, Milky Way extinction corrected, continuum-subtracted Halpha maps. PHANGS-MUSE IFU spectroscopy data are used to background subtract the HST-Halpha maps, and to determine the [NII] correction factors for each galaxy. We describe our public data products and highlight a few key science cases enabled by the PHANGS-HST-Halpha observations.

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Polycyclic Aromatic Hydrocarbon and CO(2-1) Emission at 50-150 pc Scales in 70 Nearby Galaxies

Combining Atacama Large Millimeter/sub-millimeter Array CO(2-1) mapping and JWST near- and mid-infrared imaging, we characterize the relationship between CO(2-1) and polycyclic aromatic hydrocarbon (PAH) emission at ~100 pc resolution in 70 nearby star-forming galaxies. Leveraging a new Cycle 2 JWST treasury program targeting nearby galaxies, we expand the sample size by more than an order of magnitude compared to previous ~100 pc resolution CO-PAH comparisons. Focusing on regions of galaxies where most of the gas is likely to be molecular, we find strong correlations between CO(2-1) and 3.3 um, 7.7 um, and 11.3 um PAH emission, estimated from JWST's F335M, F770W, and F1130W filters. We derive power law relations between CO(2-1) and PAH emission, which have indices in the range 0.8-1.3, implying relatively weak variations in the observed CO-to-PAH ratios across the regions that we study. We find that CO-to-PAH ratios and scaling relationships near HII regions are similar to those in diffuse sight lines. The main difference between the two types of regions is that sight lines near HII regions show higher intensities in all tracers. Galaxy centers, on the other hand, show higher overall intensities and enhanced CO-to-PAH ratios compared to galaxy disks. Individual galaxies show 0.19 dex scatter in the normalization of CO at fixed I_PAH, and this normalization anti-correlates with specific star formation rate (sSFR) and correlates with stellar mass. We provide a prescription that accounts for these galaxy-to-galaxy variations and represents our best current empirical predictor to estimate CO(2-1) intensity from PAH emission, which allows one to take advantage of JWST's excellent sensitivity and resolution to trace cold gas.

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The Impact of Bars, Spirals and Bulge-Size on Gas-Phase Metallicity Gradients in MaNGA Galaxies

As galaxies evolve over time, the orbits of their constituent stars are expected to change in size and shape, moving stars away from their birth radius. Radial gas flows are also expected. Spiral arms and bars in galaxies are predicted to help drive this radial relocation, which may be possible to trace observationally via a flattening of metallicity gradients. We use data from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey, part of the fourth phase of the Sloan Digital Sky Surveys (SDSS-IV), to look for correlations of the steepness of gas-phase metallicity gradients with various galaxy morphological features (e.g. presence and pitch angle of spiral arms, presence of a large scale bar, bulge size). We select from MaNGA a sample of star forming galaxies for which gas phase metallicity trends can be measured, and use morphologies from Galaxy Zoo. We observe that at fixed galaxy mass (1) the presence of spiral structure correlates with steeper gas phase metallicity gradients; (2) spiral galaxies with larger bulges have both higher gas-phase metallicities and shallower gradients; (3) there is no observable difference with azimuthally averaged radial gradients between barred and unbarred spirals and (4) there is no observable difference in gradient between tight and loosely wound spirals, but looser wound spirals have lower average gas-phase metallicity values at fixed mass. We discuss the possible implications of these observational results.

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Machine learning the gap between real and simulated nebulae: A domain-adaptation approach to classify ionised nebulae in nearby galaxies

Classifying ionised nebulae in nearby galaxies is crucial to studying stellar feedback mechanisms and understanding the physical conditions of the interstellar medium. This classification task is generally performed by comparing observed line ratios with photoionisation simulations of different types of nebulae (HII regions, planetary nebulae, and supernova remnants). However, due to simplifying assumptions, such simulations are generally unable to fully reproduce the line ratios in observed nebulae. This discrepancy limits the performance of the classical machine-learning approach, where a model is trained on the simulated data and then used to classify real nebulae. For this study, we used a domain-adversarial neural network (DANN) to bridge the gap between photoionisation models (source domain) and observed ionised nebulae from the PHANGS-MUSE survey (target domain). The DANN is an example of a domain-adaptation algorithm, whose goal is to maximise the performance of a model trained on labelled data in the source domain on an unlabelled target domain by extracting domain-invariant features. Our results indicate a significant improvement in classification performance in the target domain when employing the DANN framework compared to a classical neural network (NN) classifier. Additionally, we investigated the impact of adding noise to the source dataset, finding that noise injection acts as a form of regularisation, further enhancing the performances of both the NN and DANN models on the observational data. The combined use of domain adaptation and noise injection improved the classification accuracy in the target domain by 23%. This study highlights the potential of domain adaptation methods in tackling the domain-shift challenge when using theoretical models to train machine-learning pipelines in astronomy.

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Inferring redshift and galaxy properties via a multi-task neural net with probabilistic outputs: An application to simulated MOONS spectra

The era of large-scale astronomical surveys demands innovative approaches for rapid and accurate analysis of extensive spectral data, and a promising direction in which to address this challenge is offered by machine learning. Here, we introduce a new pipeline, M-TOPnet (Multi-Task network Outputting Probabilities), which employs a convolutional neural network with residual learning to simultaneously derive redshift and other key physical properties of galaxies from their spectra. Our tool efficiently encodes spectral information into a latent space, employing distinct downstream branches for each physical quantity, thereby benefiting from multi-task learning. Notably, our method handles the redshift output as a probability distribution, allowing for a more refined and robust estimation of this critical parameter. We demonstrate preliminary results using simulated data from the MOONS instrument, which will soon be operating at the ESO/VLT. We highlight the effectiveness of our tool in accurately predicting the redshift, stellar mass, and star formation rate of galaxies at z>~1-3, even for faint sources (m_H ~ 24) for which traditional methods often struggle. Through analysis of the output probability distributions, we demonstrate that our pipeline enables robust quality screening of the results, achieving accuracy rates of up to 99% in redshift determination (defined as predictions within |Delta_z| < 0.01 relative to the true redshift) with 8h exposure spectra, while automatically identifying potentially problematic cases. Our pipeline thus emerges as a powerful solution for the upcoming challenges in observational astronomy, combining precision, interpretability, and efficiency, all aspects that are crucial for analysing the massive datasets expected from next-generation instruments.

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Direct-method metallicity gradients derived from spectral stacking with SDSS-IV MaNGA

Chemical abundances are key tracers of the cycle of baryons driving the evolution of galaxies. Most measurements of interstellar medium (ISM) abundance and metallicity gradients in galaxies are based, however, on model-dependent strong-line methods. Direct chemical abundances can be obtained via the detection of weak auroral lines, but such lines are too faint to be detected across large spectroscopic surveys of the local Universe. In this work we overcome this limitation and obtain metallicity gradients from direct method abundances by stacking spectra from the MaNGA integral field spectroscopy survey. In particular we stack 4140 star-forming galaxies across the star formation rate-stellar mass (SFR-M$_\star$) plane and across six radial bins. We calculate electron temperatures for [OII], [SII], [NII], [SIII] and [OIII] across the majority of stacks. We find that the T[OII] $\sim$ T[SII] $\sim$ T[OII], as expected since these ions all trace the low-ionization zone of nebulae. The [OIII] temperatures become substantially larger than those of other ions at high metallicity, indicating potentially unaccounted for spectral contamination or additional physics. In light of this uncertainty we base our abundance calculation on the temperatures of [SIII] and the low-ionization ions. We recover a mass-metallicity relation (MZR) similar to that obtained with different empirical calibrations. We do not find evidence, however, for a secondary dependence on SFR using direct metallicities. Finally, we derive metallicity gradients that becomes steeper with stellar mass for $\log(M_\star/M_\odot) < 10.5$. At higher masses, the gradients flatten again, confirming with auroral line determinations the trends previously defined with strong-line calibrators.

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Inferring stellar parameters and their uncertainties from high-resolution spectroscopy using invertible neural networks

Context: New spectroscopic surveys will increase the number of astronomical objects requiring characterization by over tenfold.. Machine learning tools are required to address this data deluge in a fast and accurate fashion. Most machine learning algorithms can not estimate error directly, making them unsuitable for reliable science. Aims: We aim to train a supervised deep-learning algorithm tailored for high-resolution observational stellar spectra. This algorithm accurately infer precise estimates while providing coherent estimates of uncertainties by leveraging information from both the neural network and the spectra. Methods: We train a conditional Invertible Neural Network (cINN) on observational spectroscopic data obtained from the GIRAFFE spectrograph (HR10 and HR21 setups) within the Gaia-ESO survey. A key features of cINN is its ability to produce the Bayesian posterior distribution of parameters for each spectrum. By analyzing this distribution, we inferred parameters and their uncertainties. Several tests have been applied to study how parameters and errors are estimated. Results: We achieved an accuracy of 28K in $T_{\text{eff}}$, 0.06 dex in $\log g$, 0.03 dex in $[\text{Fe/H}]$, and between 0.05 dex and 0.17 dex for the other abundances for high quality spectra. Accuracy remains stable with low signal-to-noise ratio spectra. The uncertainties obtained are well within the same order of magnitude. The network accurately reproduces astrophysical relationships both on the scale of the Milky Way and within smaller star clusters. We created a table containing the new parameters generated by our cINN. Conclusion: This neural network represents a compelling proposition for future astronomical surveys. These coherent derived uncertainties make it possible to reuse these estimates in other works as Bayesian priors and thus present a solid basis for future work.

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Metallicity calibrations based on auroral lines from PHANGS-MUSE data

We present a chemical analysis of selected HII regions from the PHANGS-MUSE nebular catalogue. Our intent is to empirically re-calibrate strong-line diagnostics of gas-phase metallicity, applicable across a wide range of metallicities within nearby star-forming galaxies. To ensure reliable measurements of auroral line fluxes, we carried out a new spectral fitting procedure whereby only restricted wavelength regions around the emission lines of interest are taken into account: this assures a better fit for the stellar continuum. No prior cuts to nebulae luminosity were applied to limit biases in auroral line detections. Ionic abundances of O+, O++, N+, S+, and S++ were estimated by applying the direct method. We integrated the selected PHANGS-MUSE sample with other existing auroral line catalogues, appropriately re-analysed to obtain a homogeneous dataset. This was used to derive strong-line diagnostic calibrations that span from 12+log(O/H) = 7.5 to 8.8. We investigate their dependence on the ionisation parameter and conclude that it is likely the primary cause of the significant scatter observed in these diagnostics. We apply our newly calibrated strong-line diagnostics to the total sample of HII regions from the PHANGS-MUSE nebular catalogue, and we exploit these indirect metallicity estimates to study the radial metallicity gradient within each of the 19 galaxies of the sample. We compare our results with the literature and find good agreement, validating our procedure and findings. With this paper, we release the full catalogue of auroral and nebular line fluxes for the selected HII regions from the PHANGS-MUSE nebular catalogue. This is the first catalogue of direct chemical abundance measurements carried out with PHANGS-MUSE data.

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Different regulation of stellar metallicities between star-forming and quiescent galaxies -- Insights into galaxy quenching

One of the most important questions in astrophysics is what causes galaxies to stop forming stars. Previous studies have shown a tight link between quiescence and black hole mass. Other studies have revealed that quiescence is also associated with 'starvation', the halting of gas inflows, which results in the remaining gas being used up by star formation and in rapid chemical enrichment. In this work, we find the missing link between these two findings. Using a large sample of galaxies, we uncover the intrinsic dependencies of the stellar metallicity on galaxy properties. In the case of star-forming galaxies, stellar metallicity is primarily driven by stellar mass. However, for passive galaxies, the stellar metallicity is primarily driven by the stellar velocity dispersion. The latter is known to be tightly correlated with black hole mass. This result can be seen as connecting previous studies, where the integrated effect of black hole feedback (i.e. black hole mass, traced by the velocity dispersion) prevents gas inflows, starving the galaxy, which is seen by the rapid increase in the stellar metallicity, and leading to the galaxy becoming passive.

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Ionized gas in quiescent galaxies: Temperature measurement and constraint on the ionization source

In non-star-forming, passively evolving galaxies, regions with emission lines dominated by low-ionization species are classified as Low-Ionization Emission Regions (LIERs). The ionization mechanism behind such regions has long been a mystery. Active Galactic Nuclei (AGNs), which were once believed to be the source, have been found not to be the dominant mechanism, especially in regions distant from the galaxy nuclei. The remaining candidates, photoionization by post-Asymtopic Giant Branch (pAGB) stars and interstellar shocks can only be distinguished with in-depth analysis. As the temperature predictions of these two models differ, temperature measurements can provide strong constraints on this puzzle. We selected a sample of 2795 quiescent red-sequence galaxies from the Sloan Digital Sky Survey IV (SDSS-IV) Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. We divided the sample spectra into three groups based on their [N II]/H$α$ flux ratio and utilized stacking techniques to improve the signal-to-noise ratio of the observed spectra. We determined the temperature of [O III], [N II], [S II], and [O II] through their temperature-sensitive emission line ratios. Subsequently, we compared the measured temperatures with predictions from different models. The results demonstrate consistency with the interstellar shock model with preshock density n = 1 cm$^{-3}$ and solar metallicity, thus supporting shocks as the dominant ionization source of LIERs. Additionally, we also find that the interstellar dust extinction value measured through the Balmer decrement appears to be larger than that implied by the forbidden line ratios of low-ionization lines.

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