PHANGS-JWST: Data-processing Pipeline and First Full Public Data Release

The exquisite angular resolution and sensitivity of JWST are opening a new window for our understanding of the Universe. In nearby galaxies, JWST observations are revolutionizing our understanding of the first phases of star formation and the dusty interstellar medium. Nineteen local galaxies spanning a range of properties and morphologies across the star-forming main sequence have been observed as part of the PHANGS-JWST Cycle 1 Treasury program at spatial scales of ∼5–50 pc. Here, we describe pjpipe, an image-processing pipeline developed for the PHANGS-JWST program that wraps around and extends the official JWST pipeline. We release this pipeline to the community as it contains a number of tools generally useful for JWST NIRCam and MIRI observations. Particularly for extended sources, pjpipe products provide significant improvements over mosaics from the MAST archive in terms of removing instrumental noise in NIRCam data, background flux matching, and calibration of relative and absolute astrometry. We show that slightly smoothing F2100W MIRI data to 0.″9 (degrading the resolution by about 30%) reduces the noise by a factor of ≈3. We also present the first public release (DR1.1.0) of the pjpipe processed eight-band 2–21 μm imaging for all 19 galaxies in the PHANGS-JWST Cycle 1 Treasury program. An additional 55 galaxies will soon follow from a new PHANGS-JWST Cycle 2 Treasury program

PHANGS-ML: dissecting multiphase gas and dust in nearby galaxies using machine learning

The PHANGS survey uses ALMA, HST, VLT, and JWST to obtain an unprecedented high-resolution view of nearby galaxies, covering millions of spatially independent regions. The high dimensionality of such a diverse multi-wavelength dataset makes it challenging to identify new trends, particularly when they connect observables from different wavelengths. Here we use unsupervised machine learning algorithms to mine this information-rich dataset to identify novel patterns. We focus on three of the PHANGS-JWST galaxies, for which we extract properties pertaining to their stellar populations; warm ionized and cold molecular gas; and Polycyclic Aromatic Hydrocarbons (PAHs), as measured over 150 pc-scale regions. We show that we can divide the regions into groups with distinct multiphase gas and PAH properties. In the process, we identify previously-unknown galaxy-wide correlations between PAH band and optical line ratios and use our identified groups to interpret them. The correlations we measure can be naturally explained in a scenario where the PAHs and the ionized gas are exposed to different parts of the same radiation field that varies spatially across the galaxies. This scenario has several implications for nearby galaxies: (i) The uniform PAH ionized fraction on 150 pc scales suggests significant self-regulation in the ISM, (ii) the PAH 11.3/7.7 \mic~ band ratio may be used to constrain the shape of the non-ionizing far-ultraviolet to optical part of the radiation field, and (iii) the varying radiation field affects line ratios that are commonly used as PAH size diagnostics. Neglecting this effect leads to incorrect or biased PAH sizes.Comment: Main results in figures 6 and 12. Submitted to ApJ, and comments are welcome

PHANGS-ML: Dissecting Multiphase Gas and Dust in Nearby Galaxies Using Machine Learning

The PHANGS survey uses Atacama Large Millimeter/submillimeter Array, Hubble Space Telescope, Very Large Telescope, and JWST to obtain an unprecedented high-resolution view of nearby galaxies, covering millions of spatially independent regions. The high dimensionality of such a diverse multiwavelength data set makes it challenging to identify new trends, particularly when they connect observables from different wavelengths. Here, we use unsupervised machine-learning algorithms to mine this information-rich data set to identify novel patterns. We focus on three of the PHANGS-JWST galaxies, for which we extract properties pertaining to their stellar populations; warm ionized and cold molecular gas; and polycyclic aromatic hydrocarbons (PAHs), as measured over 150 pc scale regions. We show that we can divide the regions into groups with distinct multiphase gas and PAH properties. In the process, we identify previously unknown galaxy-wide correlations between PAH band and optical line ratios and use our identified groups to interpret them. The correlations we measure can be naturally explained in a scenario where the PAHs and the ionized gas are exposed to different parts of the same radiation field that varies spatially across the galaxies. This scenario has several implications for nearby galaxies: (i) The uniform PAH ionized fraction on 150 pc scales suggests significant self-regulation in the interstellar medium, (ii) the PAH 11.3/7.7 μm band ratio may be used to constrain the shape of the non-ionizing far-ultraviolet to optical part of the radiation field, and (iii) the varying radiation field affects line ratios that are commonly used as PAH size diagnostics. Neglecting this effect leads to incorrect or biased PAH sizes

Hidden Gems on a Ring: Infant Massive Clusters and Their Formation Timeline Unveiled by ALMA, HST, and JWST in NGC 3351

We use 0.1″ observations from the Atacama Large Millimeter Array (ALMA), Hubble Space Telescope (HST), and JWST to study young massive clusters (YMCs) in their embedded “infant” phase across the central starburst ring in NGC 3351. Our new ALMA data reveal 18 bright and compact (sub-)millimeter continuum sources, of which 8 have counterparts in JWST images and only 6 have counterparts in HST images. Based on the ALMA continuum and molecular line data, as well as ancillary measurements for the HST and JWST counterparts, we identify 14 sources as infant star clusters with high stellar and/or gas masses (∼105 M ⊙), small radii (≲ 5 pc), large escape velocities (6–10 km s−1), and short freefall times (0.5–1 Myr). Their multiwavelength properties motivate us to divide them into four categories, likely corresponding to four evolutionary stages from starless clumps to exposed H ii region–cluster complexes. Leveraging age estimates for HST-identified clusters in the same region, we infer an evolutionary timeline, ranging from ∼1–2 Myr before cluster formation as starless clumps, to ∼4–6 Myr after as exposed H ii region–cluster complexes. Finally, we show that the YMCs make up a substantial fraction of recent star formation across the ring, exhibit a nonuniform azimuthal distribution without a very coherent evolutionary trend along the ring, and are capable of driving large-scale gas outflows

A constant N2_2H+^+(1-0)-to-HCN(1-0) ratio on kiloparsec scales

Nitrogen hydrides such as NH$_3$ and N$_2$H$^+$ are widely used by Galactic observers to trace the cold dense regions of the interstellar medium. In external galaxies, because of limited sensitivity, HCN has become the most common tracer of dense gas over large parts of galaxies. We provide the first systematic measurements of N$_2$H$^+$(1-0) across different environments of an external spiral galaxy, NGC6946. We find a strong correlation ($r>0.98,p<0.01$) between the HCN(1-0) and N$_2$H$^+$(1-0) intensities across the inner $\sim8\mathrm{kpc}$ of the galaxy, at kiloparsec scales. This correlation is equally strong between the ratios N$_2$H$^+$(1-0)/CO(1-0) and HCN(1-0)/CO(1-0), tracers of dense gas fractions ($f_\mathrm{dense}$). We measure an average intensity ratio of N$_2$H$^+$(1-0)/HCN(1-0)$=0.15\pm0.02$ over our set of five IRAM-30m pointings. These trends are further supported by existing measurements for Galactic and extragalactic sources. This narrow distribution in the average ratio suggests that the observed systematic trends found in kiloparsec-scale extragalactic studies of $f_\mathrm{dense}$ and the efficiency of dense gas (SFE$_\mathrm{dense}$) would not change if we employed N$_2$H$^+$(1-0) as a more direct tracer of dense gas. At kiloparsec scales our results indicate that the HCN(1-0) emission can be used to predict the expected N$_2$H$^+$(1-0) over those regions. Our results suggest that, even if HCN(1-0) and N$_2$H$^+$(1-0) trace different density regimes within molecular clouds, subcloud differences average out at kiloparsec scales, yielding the two tracers proportional to each other.Comment: Accepted for publication in Astronomy & Astrophysic

Quantifying the energetics of molecular superbubbles in PHANGS galaxies

Star formation and stellar feedback are interlinked processes that redistribute energy and matter throughout galaxies. When young, massive stars form in spatially clustered environments, they create pockets of expanding gas termed superbubbles. As these processes play a critical role in shaping galaxy discs and regulating the baryon cycle, measuring the properties of superbubbles provides important input for galaxy evolution models. With wide coverage and high angular resolution (50-150 pc) of the PHANGS-ALMA $^{12}$CO (2-1) survey, we can now resolve and identify a statistically representative number of superbubbles with molecular gas in nearby galaxies. We identify superbubbles by requiring spatial correspondence between shells in CO with stellar populations identified in PHANGS-HST, and combine the properties of the stellar populations with CO to constrain feedback models and quantify their energetics. We visually identify 325 cavities across 18 PHANGS-ALMA galaxies, 88 of which have clear superbubble signatures (unbroken shells, central clusters, kinematic signatures of expansion). We measure their radii and expansion velocities using CO to dynamically derive their ages and the mechanical power driving the bubbles, which we use to compute the expected properties of the parent stellar populations driving the bubbles. We find consistency between the predicted and derived stellar ages and masses of the stellar populations if we use a supernova blast wave model that injects energy with a coupling efficiency of 10%, whereas continuous models fail to explain stellar ages we measure. Not only does this confirm molecular gas accurately traces superbubble properties, but it also provides key observational constraints for superbubble models. We also find evidence that the bubbles sweep up gas as they expand and speculate that these sites have the potential to host new generations of stars.Comment: 21 pages, 15 figures, 3 tables. Accepted to A&A. Abstract abridged for arXi

A Two-Component Probability Distribution Function Describes the mid-IR Emission from the Disks of Star-Forming Galaxies

High-resolution JWST-MIRI images of nearby spiral galaxies reveal emission with complex substructures that trace dust heated both by massive young stars and the diffuse interstellar radiation field. We present high angular (0."85) and physical resolution (20-80 pc) measurements of the probability distribution function (PDF) of mid-infrared (mid-IR) emission (7.7-21 $\mu$m) from 19 nearby star-forming galaxies from the PHANGS-JWST Cycle-1 Treasury. The PDFs of mid-IR emission from the disks of all 19 galaxies consistently show two distinct components: an approximately log-normal distribution at lower intensities and a high-intensity power-law component. These two components only emerge once individual star-forming regions are resolved. Comparing with locations of HII regions identified from VLT/MUSE H$\alpha$-mapping, we infer that the power-law component arises from star-forming regions and thus primarily traces dust heated by young stars. In the continuum-dominated 21 $\mu$m band, the power-law is more prominent and contains roughly half of the total flux. At 7.7-11.3 $\mu$m, the power-law is suppressed by the destruction of small grains (including PAHs) close to HII regions while the log-normal component tracing the dust column in diffuse regions appears more prominent. The width and shape of the log-normal diffuse emission PDFs in galactic disks remain consistent across our sample, implying a log-normal gas column density $N$(H)$\approx10^{21}$cm$^{-2}$ shaped by supersonic turbulence with typical (isothermal) turbulent Mach numbers $\approx5-15$. Finally, we describe how the PDFs of galactic disks are assembled from dusty HII regions and diffuse gas, and discuss how the measured PDF parameters correlate with global properties such as star-formation rate and gas surface density.Comment: 30 pages without appendix, 17 figures, (with appendix images of full sample: 56 pages, 39 figures), accepted in A

Pseudomonas Evades Immune Recognition of Flagellin in Both Mammals and Plants

The building blocks of bacterial flagella, flagellin monomers, are potent stimulators of host innate immune systems. Recognition of flagellin monomers occurs by flagellin-specific pattern-recognition receptors, such as Toll-like receptor 5 (TLR5) in mammals and flagellin-sensitive 2 (FLS2) in plants. Activation of these immune systems via flagellin leads eventually to elimination of the bacterium from the host. In order to prevent immune activation and thus favor survival in the host, bacteria secrete many proteins that hamper such recognition. In our search for Toll like receptor (TLR) antagonists, we screened bacterial supernatants and identified alkaline protease (AprA) of Pseudomonas aeruginosa as a TLR5 signaling inhibitor as evidenced by a marked reduction in IL-8 production and NF-κB activation. AprA effectively degrades the TLR5 ligand monomeric flagellin, while polymeric flagellin (involved in bacterial motility) and TLR5 itself resist degradation. The natural occurring alkaline protease inhibitor AprI of P. aeruginosa blocked flagellin degradation by AprA. P. aeruginosa aprA mutants induced an over 100-fold enhanced activation of TLR5 signaling, because they fail to degrade excess monomeric flagellin in their environment. Interestingly, AprA also prevents flagellin-mediated immune responses (such as growth inhibition and callose deposition) in Arabidopsis thaliana plants. This was due to decreased activation of the receptor FLS2 and clearly demonstrated by delayed stomatal closure with live bacteria in plants. Thus, by degrading the ligand for TLR5 and FLS2, P. aeruginosa escapes recognition by the innate immune systems of both mammals and plants