K2-141 b is a transiting, small (1.5 RE) Ultra-Short-Period (USP) planet orbiting its star every 6.7 hours discovered by the Kepler space telescope. The planet’s high surface temperature of more than 2000 K makes it an excellent target for atmospheric studies by the observation of its thermal emission. We present 65 hours of continuous photometric observations of K2-141 b collected with Spitzer’s IRAC Channel 2 at 4.5 microns spanning 10 full phases of the orbit. Our best fit model of the Spitzer data shows no significant offset of the thermal hotspot and is inconsistent with the observed offset of the well-studied USP planet 55 Cnc e at a 3.7 sigma level. We measure an eclipse depth of 142 +/- 40 ppm and an amplitude variation of 120 +/- 40 ppm in the infrared. The joint analysis of the observations collected in the two photometric bands favors a non-zero geometric albedo with Ag = 0.26 +/- 0.07 and a tentative temperature gradient. With a dayside temperature of 2141 -361 +352 K and a night-side temperature of 1077 -623 +473 K we also find no evidence of heat redistribution on the planet. We compare the observations to a 1D rock vapor model and a 1D circulation toy model and argue that the data are best explained by a thin rock vapor atmosphere with a thermal inversion.

We present new high-spectral resolution observations (R = $\lambda/\Delta\lambda$ = 7000) of the filamentary nebula surrounding NGC 1275, the central galaxy of the Perseus cluster. These observations have been obtained with SITELLE, an imaging Fourier transform spectrometer installed on the Canada-France-Hawai Telescope (CFHT) with a field of view of $11\text{ arcmin }\times 11 \text{ arcmin}$ encapsulating the entire filamentary structure of ionised gas despite its large size of $80 \text{ kpc}\times50 \text{ kpc}$. Here, we present renewed flux, velocity and velocity dispersion maps that show in great detail the kinematics of the optical nebula at \sii$\lambda6716$, \sii$\lambda6731$, \nii$\lambda6584$, H$\alpha$(6563\AA), and \nii$\lambda6548$. These maps reveal the existence of a bright flattened disk-shaped structure in the core extending to r $\sim 10$ kpc and dominated by a chaotic velocity field. This structure is located in the wake of X-ray cavities and characterised by a high mean velocity dispersion of $134$ km/s. The disk-shaped structure is surrounded by an extended array of filaments spread out to $r\sim 50$ kpc that are 10 times fainter in flux, remarkably quiescent and has a uniform mean velocity dispersion of $44$ km/s. This stability is puzzling given that the cluster core exhibits several energetic phenomena. Based on these results, we argue that there are two mechanisms to form multiphase gas in clusters of galaxies: a first triggered in the wake of X-ray cavities leading to more turbulent multiphase gas and a second, distinct mechanism, that is gentle and leads to large-scale multiphase gas spread throughout the core.

BackgroundThe management of shoulder pain is challenging for primary care clinicians considering that 40% of affected individuals remain symptomatic one year after initial consultation. Developing tailored knowledge mobilization interventions founded on evidence-based recommendations while also considering patients’ expectations could improve primary care for shoulder pain. The aim of this qualitative study is to explore patients’ expectations and experiences of their primary care consultation for shoulder pain.MethodsIn this qualitative study, participants with shoulder pain and having consulted a primary care clinician in the past year were interviewed. All the semi-structured interviews were transcribed verbatim, and inductive thematic analysis was performed to identify themes related to the participants’ expectations and experiences of primary care consultations for shoulder pain.ResultsThirteen participants with shoulder pain were interviewed (8 women, 5 men; mean age 50 ± 12 years). Eleven of them initially consulted a family physician or an emergency physician, and two participants initially consulted a physiotherapist. Four overarching themes related to patients’ expectations and experiences were identified from our thematic analysis: 1) I can’t sleep because of my shoulder; 2) I need to know what is happening with my shoulder; 3) But… we need to really see what is going on to help me!; and 4) Please take some time with me so I can understand what to do!. Several participants waited until they experienced a high level of shoulder pain before making an appointment since they were not confident about what their family physician could do to manage their condition. Although some participants felt that their physician took the time to listen to their concerns, many were dissatisfied with the limited assessment and education provided by the clinician.ConclusionsImplementing evidence-based recommendations while considering patients’ expectations is important as it may improve patients’ satisfaction with healthcare. Several participants reported that their expectations were not met, especially when it came to the explanations provided. One unexpected finding that emerged from this study was the waiting period between the onset of shoulder pain and when patients decided to consult their primary care clinician.

ABSTRACT Turbulence plays a crucial role in shaping the structure of the interstellar medium. The ratio of the three-dimensional density contrast ($\sigma _{\rho /\rho _0}$) to the turbulent sonic Mach number ($\mathcal {M}$) of an isothermal, compressible gas describes the ratio of solenoidal to compressive modes in the turbulent acceleration field of the gas, and is parameterized by the turbulence driving parameter: $b=\sigma _{\rho /\rho _0}/\mathcal {M}$. The turbulence driving parameter ranges from b = 1/3 (purely solenoidal) to b = 1 (purely compressive), with b = 0.38 characterizing the natural mixture (1/3 compressive, 2/3 solenoidal) of the two driving modes. Here, we present a new method for recovering $\sigma _{\rho /\rho _0}$, $\mathcal {M}$, and b, from observations on galactic scales, using a roving kernel to produce maps of these quantities from column density and centroid velocity maps. We apply our method to high-resolution ${\rm H}\,\rm{\small I}$ emission observations of the Small Magellanic Cloud (SMC) from the GASKAP-HI survey. We find that the turbulence driving parameter varies between b ∼ 0.3 and 1.0 within the main body of the SMC, but the median value converges to b ∼ 0.51, suggesting that the turbulence is overall driven more compressively (b > 0.38). We observe no correlation between the b parameter and ${\rm H}\,\rm{\small I}$ or H α intensity, indicating that compressive driving of ${\rm H}\,\rm{\small I}$ turbulence cannot be determined solely by observing ${\rm H}\,\rm{\small I}$ or H α emission density, and that velocity information must also be considered. Further investigation is required to link our findings to potential driving mechanisms such as star-formation feedback, gravitational collapse, or cloud–cloud collisions.

Abstract Eta Carinae (η Car) exhibits a unique set of P Cygni profiles with both broad and narrow components. Over many decades, the spectrum has changed—there has been an increase in observed continuum fluxes and a decrease in Fe ii and H i emission-line equivalent widths. The spectrum is evolving toward that of a P Cygni star such as P Cygni itself and HDE 316285. The spectral evolution has been attributed to intrinsic variations such as a decrease in the mass-loss rate of the primary star or differential evolution in a latitudinal-dependent stellar wind. However, intrinsic wind changes conflict with three observational results: the steady long-term bolometric luminosity; the repeating X-ray light curve over the binary period; and the constancy of the dust-scattered spectrum from the Homunculus. We extend previous work that showed a secular strengthening of P Cygni absorptions by adding more orbital cycles to overcome temporary instabilities and by examining more atomic transitions. cmfgen modeling of the primary wind shows that a time-decreasing mass-loss rate is not the best explanation for the observations. However, models with a small dissipating absorber in our line of sight can explain both the increase in brightness and changes in the emission and P Cygni absorption profiles. If the spectral evolution is caused by the dissipating circumstellar medium, and not by intrinsic changes in the binary, the dynamical timescale to recover from the Great Eruption is much less than a century, different from previous suggestions.

ABSTRACT We present astrophot, a fast, powerful, and user-friendly python based astronomical image photometry solver. astrophot incorporates automatic differentiation and graphics processing unit (GPU), or parallel central processing unit (CPU), acceleration, powered by the machine learning library pytorch. Everything: astrophot can fit models for sky, stars, galaxies, point spread functions (PSFs), and more in a principled χ2 forward optimization, recovering Bayesian posterior information and covariance of all parameters. Everywhere: astrophot can optimize forward models on CPU or GPU; across images that are large, multiband, multi-epoch, rotated, dithered, and more. All at once: The models are optimized together, thus handling overlapping objects and including the covariance between parameters (including PSF and galaxy parameters). A number of optimization algorithms are available including Levenberg–Marquardt, Gradient descent, and No-U-Turn Markov chain Monte Carlo sampling. With an object-oriented user interface, astrophot makes it easy to quickly extract detailed information from complex astronomical data for individual images or large survey programs. This paper outlines novel features of the astrophot code and compares it to other popular astronomical image modelling software. astrophot is open-source, fully python based, and freely accessible at https://github.com/Autostronomy/AstroPhot .

ABSTRACT Using datacubes from the imaging Fourier transform spectrometer SITELLE at the Canada–France–Hawaii Telescope as part of the star formation, ionized gas, and nebular abundances legacy survey, we identify 15 new planetary nebulae (PNe) as well as five new supernova remnants (SNRs) in the outer parts of the nearby dwarf starburst galaxy NGC 4214. These data also allow us to study the morphology and kinematics of all 18 known SNRs in this galaxy. We highlight the use of a $\xi = \sigma \frac{\rm {[S{\small \,II}]}}{\rm {H\alpha }}$ diagnostic diagram (σ being the velocity dispersion) to separate SNRs from H ii regions and its advantage compared to classical BPT or Sabbadin diagrams. We provide the emission-line flux ([O iii] λ5007, H α, and H β) and radial velocities of all new PNe candidates, as well as those of 12 of the 17 PNe previously discovered in the central part of the galaxy with Hubble Space Telescope (HST) data. Finally, we use the [O iii] emission-line luminosity function of the PNe sample to establish a new velocity-independent distance for NGC 4214: $D = 3.23^{+0.18}_{-0.25}$ Mpc.

Wolf-Rayet (WR) 140 is the archetypal periodic dust-forming colliding-wind binary that hosts a carbon-rich WR (WC) star and an O-star companion with an orbital period of 7.93 yr and an orbital eccentricity of 0.9. Throughout the past few decades, multiple dust-formation episodes from WR 140 have been observed that are linked to the binary orbit and occur near the time of periastron passage. Given its predictable dust-formation episodes, WR 140 presents an ideal astrophysical laboratory to investigate the formation and evolution of dust in the hostile environment around a massive binary system. In this paper, we present near- and mid-infrared (IR) spectroscopic and imaging observations of WR 140 with Subaru/SCExAO+CHARIS, Keck/NIRC2+PyWFS, and Subaru/Cooled Mid-Infrared Camera and Spectrograph taken between 2020 June and September that resolve the circumstellar dust emission linked to its most recent dust-formation episode in 2016 December. Our spectral energy distribution analysis of WR 140's resolved circumstellar dust emission reveals the presence of a hot (T d ∼ 1000 K) near-IR dust component that is co-spatial with the previously known and cooler (T d ∼ 500 K) mid-IR dust component composed of 300–500 Å sized dust grains. We attribute the hot near-IR dust emission to the presence of nano-sized (nanodust) grains and suggest they were formed from grain–grain collisions or the rotational disruption of the larger grain size population by radiative torques in the strong radiation field from the central binary. Lastly, we speculate on the astrophysical implications of nanodust formation around colliding-wind WC binaries, which may present an early source of carbonaceous nanodust in the interstellar medium.

Galaxies in the Universe are distributed in a web-like structure characterized by different large-scale environments: dense clusters, elongated filaments, sheetlike walls and under-dense regions, called voids1-5. The low density in voids is expected to affect the properties of their galaxies. Indeed, previous studies6-14 have shown that galaxies in voids are, on average, bluerand less massive, andhave later morphologies and higher current star formation rates than galaxies in denser large-scale environments. However, it has never been observationally proved that the star formation histories (SFHs) in voids are substantially different from those infilaments, walls and clusters. Here we show that void galaxies have had, on average, slower SFHs than galaxies in denser large-scale environments. We also find two main SFH types present in all the environments: 'short-timescale' galaxies are not affected by their large-scale environment at early times but only later in their lives; 'long-timescale' galaxies have been continuously affected by their environment and stellar mass. Both types have evolved more slowly in voids than in filaments, walls and clusters.

Modeling strong gravitational lenses in order to quantify distortions in the images of background sources and to reconstruct the mass density in foreground lenses has been a difficult computational challenge. As the quality of gravitational lens images increases, the task of fully exploiting the information they contain becomes computationally and algorithmically more difficult. In this work, we use a neural network based on the recurrent inference machine to reconstruct simultaneously an undistorted image of the background source and the lens mass density distribution as pixelated maps. The method iteratively reconstructs the model parameters (the image of the source and a pixelated density map) by learning the process of optimizing the likelihood given the data using the physical model (a ray-tracing simulation), regularized by a prior implicitly learned by the neural network through its training data. When compared to more traditional parametric models, the proposed method is significantly more expressive and can reconstruct complex mass distributions, which we demonstrate by using realistic lensing galaxies taken from the IllustrisTNG cosmological hydrodynamic simulation.