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Guillermo Blanc

Publications and source records attributed to Guillermo Blanc.

At least 19 recordsLinked to original sources

There is no single density: star-forming regions and galaxies hold more dense ionized gas than long assumed

Ionized gas fills star-forming regions and galaxies, and nearly everything we know about its temperature, pressure, mass, and composition is inferred from its emission lines [1-3]. The electron density is needed for all of these, yet a longstanding puzzle has resisted explanation: different density-sensitive lines, applied to the same gas, return values that disagree by up to two orders of magnitude. This is usually attributed either to each line tracing a physically distinct ionization zone or to imperfect atomic data [4-7]. Here we show that the disagreement is neither a flaw in the atomic data nor an ionization-stratification effect, but something more fundamental. Each diagnostic is tuned to a particular density, and when a nebula contains gas across a wide range of densities, as real nebulae do, each line reports the part of that range it is most sensitive to. The diagnostics do not measure a representative average density; they respond to different parts of a broad density distribution. This resolves the discrepancy with a simple relation between the density each line returns and the density it is most sensitive to, a relation that holds from individual H II regions to whole galaxies, near and far, and reveals that ionized nebulae contain far more dense gas than any one diagnostic implies. A nebula has no single electron density to measure, but a broad density distribution, and the masses, pressures, abundances and energetics built on the single-density assumption must be reconsidered, from nearby star-forming regions to galaxies across cosmic time.

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LATIS: Galaxy-Environment Relations at Cosmic Noon and the Role of Sample Selection

We investigate the environmental dependence of galaxy properties at $z\sim2.5$ using the Ly$\alpha$ Tomography IMACS Survey (LATIS), which provides high-resolution three-dimensional maps of intergalactic medium (IGM) overdensity via Ly$\alpha$ forest tomography. Our analysis focuses on a UV-selected spectroscopic sample of 2185 galaxies from LATIS and a complementary set of 1157 galaxies from heterogeneous spectroscopic surveys in the COSMOS field. We compare these datasets to forward-modeled mock catalogs constructed from the IllustrisTNG300-1 simulation, incorporating realistic selection functions to match both LATIS and the literature sample. While the mass-complete simulation predicts strong environmental trends--more massive and quiescent galaxies preferentially occupy overdense regions--we find that such trends are significantly weaker or absent in the observed samples. The LATIS galaxies show no measurable correlation between specific star formation rate (sSFR) and IGM overdensity, a result reproduced by LATIS-like mock catalogs, confirming that UV selection systematically excludes passive and dusty galaxies in dense environments. The literature compilation, despite improved high-mass coverage, remains incomplete and affected by similar biases. We also analyze a mass-complete photometric sample from the COSMOS-Web catalog at $z\sim2.5$ and find no detectable sSFR-environment relation, a null result that our simulations indicate can be explained by photometric redshift uncertainties. In particular, we find no evidence for a reversal of the sSFR-density relation at cosmic noon. These results demonstrate that observed correlations can be heavily shaped by selection effects, and caution against inferring physical trends from incomplete spectroscopic samples. Deeper, more representative spectroscopic surveys are needed to robustly characterize environmental effects at this epoch.

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The Nineteenth Data Release of the Sloan Digital Sky Survey

Mapping the local and distant Universe is key to our understanding of it. For decades, the Sloan Digital Sky Survey (SDSS) has made a concerted effort to map millions of celestial objects to constrain the physical processes that govern our Universe. The most recent and fifth generation of SDSS (SDSS-V) is organized into three scientific ``mappers". Milky Way Mapper (MWM) that aims to chart the various components of the Milky Way and constrain its formation and assembly, Black Hole Mapper (BHM), which focuses on understanding supermassive black holes in distant galaxies across the Universe, and Local Volume Mapper (LVM), which uses integral field spectroscopy to map the ionized interstellar medium in the local group. This paper describes and outlines the scope and content for the nineteenth data release (DR19) of SDSS and the most substantial to date in SDSS-V. DR19 is the first to contain data from all three mappers. Additionally, we also describe nine value added catalogs (VACs) that enhance the science that can be conducted with the SDSS-V data. Finally, we discuss how to access SDSS DR19 and provide illustrative examples and tutorials.

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Physical properties of HII regions at sub-kpc scales using integral field spectroscopy on IC 342

In this study we use Integral Field Spectroscopic (IFS) observations for one of the closest galaxy to us, the grand design spiral IC 342, to derive physical properties of HII regions at sub-kpc scales. This IFS data represents, to our knowledge, the most comprehensive observational effort in the optical for this galaxy. The final IFS datacube consists of 349 individual pointings using the IFS instrumentation from the SDSS-IV MaNGA survey. Using a prototype of the data analysis pipeline that will be devoted to the SDSS-V Local Volume Mapper (LVM) survey, we measure different observables from the emission line in the optical. In particular, using the flux map of the H$\alpha$ emission line, we derive the location and sizes of H ii region candidates for IC 342. Using the integrated flux for different emission lines within each region, we derived the radial distribution of different physical properties from the ionized gas (e.g., optical extinction, H$\alpha$ luminosity, oxygen abundance, etc). Comparing with larger samples of galaxies with IFS data, our results suggest that physical properties of the ionized gas of IC 342 are similar to galaxies with similar stellar mass in the nearby universe.

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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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Call to Protect the Dark and Quiet Sky from Harmful Interference by Satellite Constellations

The growing number of satellite constellations in low Earth orbit (LEO) enhances global communications and Earth observation, and support of space commerce is a high priority of many governments. At the same time, the proliferation of satellites in LEO has negative effects on astronomical observations and research, and the preservation of the dark and quiet sky. These satellite constellations reflect sunlight onto optical telescopes, and their radio emission impacts radio observatories, jeopardising our access to essential scientific discoveries through astronomy. The changing visual appearance of the sky also impacts our cultural heritage and environment. Both ground-based observatories and space-based telescopes in LEO are affected, and there are no places on Earth that can escape the effects of satellite constellations given their global nature. The minimally disturbed dark and radio-quiet sky is crucial for conducting fundamental research in astronomy and important public services such as planetary defence, technology development, and high-precision geolocation. Some aspects of satellite deployment and operation are regulated by States and intergovernmental organisations. While regulatory agencies in some States have started to require operators to coordinate with their national astronomy agencies over impacts, mitigation of the impact of space objects on astronomical activities is not sufficiently regulated. To address this issue, the CPS urges States and the international community to take steps to protect the dark and quiet sky as specified in this paper.

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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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PHANGS-JWST First Results: A statistical view on bubble evolution in NGC628

The first JWST observations of nearby galaxies have unveiled a rich population of bubbles that trace the stellar feedback mechanisms responsible for their creation. Studying these bubbles therefore allows us to chart the interaction between stellar feedback and the interstellar medium, and the larger galactic flows needed to regulate star formation processes globally. We present the first catalog of bubbles in NGC628, visually identified using MIRI F770W PHANGS-JWST observations, and use them to statistically evaluate bubble characteristics. We classify 1694 structures as bubbles with radii between 6-552 pc. Of these, 31% contain at least one smaller bubble at their edge, indicating that previous generations of star formation have a local impact on where new stars form. On large scales, most bubbles lie near a spiral arm, and their radii increase downstream compared to upstream. Furthermore, bubbles are elongated in a similar direction to the spiral arm ridge-line. These azimuthal trends demonstrate that star formation is intimately connected to the spiral arm passage. Finally, the bubble size distribution follows a power-law of index $p=-2.2\pm0.1$, which is slightly shallower than the theoretical value by 1-3.5$σ$ that did not include bubble mergers. The fraction of bubbles identified within the shells of larger bubbles suggests that bubble merging is a common process. Our analysis therefore allows us to quantify the number of star-forming regions that are influenced by an earlier generation, and the role feedback processes have in setting the global star formation rate. With the full PHANGS-JWST sample, we can do this for more galaxies.

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PHANGS-JWST First Results: Multi-wavelength view of feedback-driven bubbles (The Phantom Voids) across NGC 628

We present a high-resolution view of bubbles within The Phantom Galaxy (NGC 628); a nearby (~10Mpc), star-forming (~2Msun/yr), face-on (i~9deg) grand-design spiral galaxy. With new data obtained as part of the PHANGS-JWST treasury program, we perform a detailed case-study of two regions of interest, one of which contains the largest and most prominent bubble in the galaxy (The Phantom Void; over 1kpc in diameter), and the other being a smaller region that may be the precursor to such a large bubble (The Precursor Phantom Void). When comparing to matched resolution Halpha observations from the Hubble Space Telescope (HST), we see that the ionized gas is brightest in the shells of both bubbles, and is coincident with the youngest (~1Myr) and most massive (~100,000Msun) stellar associations. We also find an older generation (~20Myr) of stellar associations is present within the bubble of The Phantom Void. From our kinematic analysis of the HI, H2 (CO) and HII gas across The Phantom Void, we infer a high expansion speed of around 15 to 50km/s. The large size and high expansion speed of The Phantom Void suggest that the driving mechanism is sustained stellar feedback due to multiple mechanisms, where early feedback first cleared a bubble (as we observe now in The Precursor Phantom Void), and since then SNe have been exploding within the cavity, and have accelerated the shell. Finally, comparison to simulations shows a striking resemblance to our JWST observations, and suggests that such large-scale stellar feedback-driven bubbles should be common within other galaxies.

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PHANGS-JWST First Results: Dust embedded star clusters in NGC 7496 selected via 3.3 $μ$m PAH emission

The earliest stages of star formation occur enshrouded in dust and are not observable in the optical. Here we leverage the extraordinary new high-resolution infrared imaging from JWST to begin the study of dust-embedded star clusters in nearby galaxies throughout the local volume. We present a technique for identifying dust-embedded clusters in NGC 7496 (18.7 Mpc), the first galaxy to be observed by the PHANGS-JWST Cycle 1 Treasury Survey. We select sources that have strong 3.3$μ$m PAH emission based on a $\rm F300M-F335M$ color excess, and identify 67 candidate embedded clusters. Only eight of these are found in the PHANGS-HST optically-selected cluster catalog and all are young (six have SED-fit ages of $\sim1$ Myr). We find that this sample of embedded cluster candidates may significantly increase the census of young clusters in NGC 7496 from the PHANGS-HST catalog -- the number of clusters younger than $\sim$2 Myr could be increased by a factor of two. Candidates are preferentially located in dust lanes, and are coincident with peaks in PHANGS-ALMA CO (2-1) maps. We take a first look at concentration indices, luminosity functions, SEDs spanning from 2700A to 21$μ$m, and stellar masses (estimated to be between $\sim10^4-10^5 M_{\odot}$). The methods tested here provide a basis for future work to derive accurate constraints on the physical properties of embedded clusters, characterize the completeness of cluster samples, and expand analysis to all 19 galaxies in the PHANGS-JWST sample, which will enable basic unsolved problems in star formation and cluster evolution to be addressed.

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The MegaMapper: A Stage-5 Spectroscopic Instrument Concept for the Study of Inflation and Dark Energy

In this white paper, we present the MegaMapper concept. The MegaMapper is a proposed ground-based experiment to measure Inflation parameters and Dark Energy from galaxy redshifts at $2<z<5$. In order to achieve path-breaking results with a mid-scale investment, the MegaMapper combines existing technologies for critical path elements and pushes innovative development in other design areas. To this aim, we envision a 6.5-m Magellan-like telescope, with a newly designed wide field, coupled with DESI spectrographs, and small-pitch robots to achieve multiplexing of at least 26,000. This will match the expected achievable target density in the redshift range of interest and provide a 10x capability over the existing state-of the art, without a 10x increase in project budget.

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Validating the Local Volume Mapper acquisition and guiding hardware

The Local Volume Mapper (LVM) project is one of three surveys that form the Sloan Digital Sky Survey V. It will map the interstellar gas emission in a large fraction of the southern sky using wide-field integral field spectroscopy. Four 16-cm telescopes in siderostat configuration feed the integral field units (IFUs). A reliable acquisition and guiding (A&G) strategy will help ensure that we meet our science goals. Each of the telescopes hosts commercial CMOS cameras used for A&G. In this work, we present our validation of the camera performance. Our tests show that the cameras have a readout noise of around 5.6e- and a dark current of 21e-/s, when operated at the ideal gain setting and at an ambient temperature of 20°C. To ensure their performance at a high-altitude observing site, such as the Las Campanas Observatory, we studied the thermal behaviour of the cameras at different ambient pressures and with different passive cooling solutions. Using the measured properties, we calculated the brightness limit for guiding exposures. With a 5 s exposure time, we reach a depth of around 16.5 Gaia gmag with a signal-to-noise ratio (SNR)>5. Using Gaia Early Data Release 3, we verified that there are sufficient guide stars for each of the around 25000 survey pointings. For accurate acquisition, we also need to know the focal plane geometry. We present an approach that combines on-chip astrometry and using a point source microscope to measure the relative positions of the IFU lenslets and the individual CMOS pixels to around 2 $μ$m accuracy.

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Frequency and nature of central molecular outflows in nearby star-forming disk galaxies

Central molecular outflows in spiral galaxies are assumed to modulate their host galaxy's star formation rate by removing gas from the inner region of the galaxy. Outflows consisting of different gas phases appear to be a common feature in local galaxies, yet, little is known about the frequency of molecular outflows in main sequence galaxies in the nearby universe. We develop a rigorous set of selection criteria, which allow the reliable identification of outflows in large samples of galaxies. Our criteria make use of central spectra, position-velocity diagrams and velocity-integrated intensity maps (line-wing maps). We use this method on high-angular resolution CO(2-1) observations from the PHANGS-ALMA survey, which provides observations of the molecular gas for a homogeneous sample of 90 nearby main sequence galaxies at a resolution of ${\sim}100\,$pc. We find correlations between the assigned outflow confidence and stellar mass or global star formation rate (SFR). We determine the frequency of central molecular outflows to be $25\pm2$% considering all outflow candidates, or $20\pm2$% for secure outflows only. Our resulting outflow candidate sample of $16{-}20$ galaxies shows an overall enhanced fraction of active galactic nuclei (AGN) (50%) and bars (89%) compared to the full sample (galaxies with AGN: 24%, with bar: 61%). We extend the trend between mass outflow rates and SFR known for high outflow rates down to lower values ($\log_{10}{\dot{\rm M}_{\rm out}}\,[\mathrm{M}_\odot~\mathrm{yr}^{-1}]<0$). Mass loading factors are of order unity, indicating that these outflows are not efficient in quenching the SFR in main sequence galaxies.

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Giant Molecular Cloud Catalogues for PHANGS-ALMA: Methods and Initial Results

We present improved methods for segmenting CO emission from galaxies into individual molecular clouds, providing an update to the CPROPS algorithms presented by Rosolowsky & Leroy (2006; arXiv:astro-ph/0601706 ). The new code enables both homogenization of the noise and spatial resolution among data, which allows for rigorous comparative analysis. The code also models the completeness of the data via false source injection and includes an updated segmentation approach to better deal with blended emission. These improved algorithms are implemented in a publicly available python package, PYCPROPS. We apply these methods to ten of the nearest galaxies in the PHANGS-ALMA survey, cataloguing CO emission at a common 90 pc resolution and a matched noise level. We measure the properties of 4986 individual clouds identified in these targets. We investigate the scaling relations among cloud properties and the cloud mass distributions in each galaxy. The physical properties of clouds vary among galaxies, both as a function of galactocentric radius and as a function of dynamical environment. Overall, the clouds in our target galaxies are well-described by approximate energy equipartition, although clouds in stellar bars and galaxy centres show elevated line widths and virial parameters. The mass distribution of clouds in spiral arms has a typical mass scale that is 2.5x larger than interarm clouds and spiral arms clouds show slightly lower median virial parameters compared to interarm clouds (1.2 versus 1.4).

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Deep Transfer Learning for Star Cluster Classification: I. Application to the PHANGS-HST Survey

We present the results of a proof-of-concept experiment which demonstrates that deep learning can successfully be used for production-scale classification of compact star clusters detected in HST UV-optical imaging of nearby spiral galaxies (D < 20 Mpc) in the PHANGS-HST survey. Given the relatively small nature of existing, human-labelled star cluster samples, we transfer the knowledge of state-of-the-art neural network models for real-object recognition to classify star clusters candidates into four morphological classes. We perform a series of experiments to determine the dependence of classification performance on: neural network architecture (ResNet18 and VGG19-BN); training data sets curated by either a single expert or three astronomers; and the size of the images used for training. We find that the overall classification accuracies are not significantly affected by these choices. The networks are used to classify star cluster candidates in the PHANGS-HST galaxy NGC 1559, which was not included in the training samples. The resulting prediction accuracies are 70%, 40%, 40-50%, 50-70% for class 1, 2, 3 star clusters, and class 4 non-clusters respectively. This performance is competitive with consistency achieved in previously published human and automated quantitative classification of star cluster candidate samples (70-80%, 40-50%, 40-50%, and 60-70%). The methods introduced herein lay the foundations to automate classification for star clusters at scale, and exhibit the need to prepare a standardized dataset of human-labelled star cluster classifications, agreed upon by a full range of experts in the field, to further improve the performance of the networks introduced in this study.

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The VIRUS-P Exploration of Nearby Galaxies (VENGA): The stellar populations and assembly of NGC 2903's bulge, bar, and outer disc

We study the stellar populations and assembly of the nearby spiral galaxy NGC 2903's bulge, bar, and outer disc using the VIRUS-P Exploration of Nearby Galaxies IFS survey. We observe NGC 2903 with a spatial resolution of 185 pc using the Mitchell Spectrograph's 4.25 arcsec fibres at the 2.7 Harlan J. Smith telescope. Bulge-bar-disc decomposition on the 2MASS Ks-band image of NGC 2903 shows that it has ~6%, 6%, and 88%, of its stellar mass in the bulge, bar, and outer disc, respectively, and its bulge has a low Sersic index of ~0.27, suggestive of a disky bulge. We perform stellar population synthesis and find that the outer disc has 46% of its mass in stars >5 Gyr, 48% in stars between 1 and 5 Gyr, and <10% in younger stars. Its stellar bar has 65% of its mass in ages 1-5 Gyr and has metallicities similar to the outer disc, suggestive of the evolutionary picture where the bar forms from disc material. Its bulge is mainly composed of old high-metallicity stars though it also has a small fraction of young stars. We find enhanced metallicity in the spiral arms and central region, tracing areas of high star formation as seen in the Halpha map. These results are consistent with the idea that galaxies of low bulge-to-total mass ratio and low bulge Sersic index like NGC 2903 has not had a recent major merger event, but has instead grown mostly through minor mergers and secular processes.

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A model for the onset of self-gravitation and star formation in molecular gas governed by galactic forces: II. the bottleneck to collapse set by cloud-environment decoupling

In Meidt et al. (2018), we showed that gas kinematics on the scale of individual molecular clouds are not dominated by self-gravity but also track a component that originates with orbital motion in the potential of the host galaxy. This agrees with observed cloud line widths, which show systematic variations from virial motions with environment, pointing at the influence of the galaxy potential. In this paper, we hypothesize that these motions act to slow down the collapse of gas and so help regulate star formation. Extending the results of Meidt et al. (2018), we derive a dynamical collapse timescale that approaches the free-fall time only once the gas has fully decoupled from the galactic potential. Using this timescale we make predictions for how the fraction of free-falling, strongly self-gravitating gas varies throughout the disks of star-forming galaxies. We also use this collapse timescale to predict variations in the molecular gas star formation efficiency, which is lowered from a maximum, feedback-regulated level in the presence of strong coupling to the galactic potential. Our model implies that gas can only decouple from the galaxy to collapse and efficiently form stars deep within clouds. We show that this naturally explains the observed drop in star formation rate per unit gas mass in the Milky Way's CMZ and other galaxy centers. The model for a galactic bottleneck to star formation also agrees well with resolved observations of dense gas and star formation in galaxy disks and the properties of local clouds.

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