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<jats:title>Abstract</jats:title> <jats:p>We have examined the star formation history (SFH) of Andromeda VII (And VII), the brightest and most massive dwarf spheroidal (dSph) satellite of the Andromeda galaxy (M31). Although M31 is surrounded by several dSph companions with old stellar populations and low metallicity, it has a metal-rich stellar halo with an age of 6–8 Gyr. This indicates that any evolutionary association between the stellar halo of M31 and its dSph system is frail. Therefore, the question is whether And VII (a high-metallicity dSph located ∼220 kpc from M31) can be associated with M31's young, metal-rich halo. Here we perform the first reconstruction of the SFH of And VII employing long-period variable (LPV) stars. As the most evolved asymptotic giant branch and red supergiant stars, the birth mass of LPVs can be determined by connecting their near-infrared photometry to theoretical evolutionary tracks. We found 55 LPV candidates within two half-light radii, using multiepoch imaging with the Isaac Newton Telescope in the <jats:italic>i</jats:italic> and <jats:italic>V</jats:italic> bands. Based on their birth mass function, the star formation rate (SFR) of And VII was obtained as a function of cosmic time. The main epoch of star formation occurred ≃ 6.2 Gyr ago with an SFR of 0.006 ± 0.002 <jats:italic>M</jats:italic> <jats:sub>⊙</jats:sub> yr<jats:sup>−1</jats:sup>. Over the past 6 Gyr, we find slow star formation, which continued until 500 Myr ago with an SFR ∼ 0.0005 ± 0.0002 <jats:italic>M</jats:italic> <jats:sub>⊙</jats:sub> yr<jats:sup>−1</jats:sup>. We determined And VII’s stellar mass <jats:italic>M</jats:italic> = (13.3 ± 5.3) × 10<jats:sup>6</jats:sup> <jats:italic>M</jats:italic> <jats:sub>⊙</jats:sub> within a half-light radius <jats:inline-formula> <jats:tex-math> <?CDATA ${r}_{\tfrac{1}{2}}=3\buildrel{\,\prime}\over{.} 8\pm 0\buildrel{\,\prime}\over{.} 3$?> </jats:tex-math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabdec1ieqn1.gif" xlink:type="simple" /> </jats:inline-formula> and metallicity <jats:italic>Z</jats:italic> = 0.0007, and we also derived its distance modulus of <jats:italic>μ</jats:italic> = 24.38 mag.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Molecular clouds are supported by turbulence and magnetic fields, but quantifying their influence on cloud life cycle and star formation efficiency (SFE) remains an open question. We perform radiation magnetohydrodynamic simulations of star-forming giant molecular clouds (GMCs) with UV radiation feedback, in which the propagation of UV radiation via ray tracing is coupled to hydrogen photochemistry. We consider 10 GMC models that vary in either initial virial parameter (1 ≤ <jats:italic>α</jats:italic> <jats:sub>vir,0</jats:sub> ≤ 5) or dimensionless mass-to-magnetic flux ratio (0.5 ≤ <jats:italic>μ</jats:italic> <jats:sub>Φ,0</jats:sub> ≤ 8 and ∞ ); the initial mass 10<jats:sup>5</jats:sup> <jats:italic> M</jats:italic> <jats:sub>⊙</jats:sub> and radius 20 pc are fixed. Each model is run with five different initial turbulence realizations. In most models, the duration of star formation and the timescale for molecular gas removal (primarily by photoevaporation) are 4–8 Myr. Both the final SFE (<jats:italic>ε</jats:italic> <jats:sub>*</jats:sub>) and time-averaged SFE per freefall time (<jats:italic>ε</jats:italic> <jats:sub>ff</jats:sub>) are reduced by strong turbulence and magnetic fields. The median <jats:italic>ε</jats:italic> <jats:sub>*</jats:sub> ranges between 2.1% and 9.5%. The median <jats:italic>ε</jats:italic> <jats:sub>ff</jats:sub> ranges between 1.0% and 8.0%, and anticorrelates with <jats:italic>α</jats:italic> <jats:sub>vir,0</jats:sub>, in qualitative agreement with previous analytic theory and simulations. However, the time-dependent <jats:italic>α</jats:italic> <jats:sub>vir</jats:sub>(<jats:italic>t</jats:italic>) and <jats:italic>ε</jats:italic> <jats:sub>ff,obs</jats:sub>(<jats:italic>t</jats:italic>) based on instantaneous gas properties and cluster luminosity are positively correlated due to rapid evolution, making observational validation of star formation theory difficult. Our median <jats:italic>ε</jats:italic> <jats:sub>ff,obs</jats:sub>(<jats:italic>t</jats:italic>) ≈ 2% is similar to observed values. We show that the traditional virial parameter estimates the true gravitational boundedness within a factor of 2 on average, but neglect of magnetic support and velocity anisotropy can sometimes produce large departures from traditional virial parameter estimates. Magnetically subcritical GMCs are unlikely to represent sites of massive star formation given their unrealistic columnar outflows, prolonged lifetime, and low escape fraction of radiation.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Shock breakout (SBO), the first expected electromagnetic signature of a supernova (SN), can be an important probe of the progenitors of these explosions. Unfortunately, SBO is difficult to capture with current surveys due to its brief timescale (≲1 hr). However, SBO may be lengthened when dense circumstellar material (CSM) is present. Indeed, recent photometric modeling studies of SNe, as well as early spectroscopy, suggest that such dense CSM may be present more often than previously expected. If true, this should also affect the features of SBO. We present an exploration of the impact of such CSM interaction on the SBO width and luminosity using both analytic and numerical modeling, where we parameterize the CSM as a steady-state wind. We then compare this modeling to PS1-13arp, an SN that showed an early UV excess that has been argued to be SBO in dense CSM. We find PS1-13arp is well fit with a wind of mass ∼0.08 <jats:italic>M</jats:italic> <jats:sub>⊙</jats:sub> and radius ∼1900 <jats:italic>R</jats:italic> <jats:sub>⊙</jats:sub>, parameters which are similar to, if not slightly less massive than, what have been inferred for Type II SNe using photometric modeling. This similarity suggests that future SBO observations of SNe II may be easier to obtain than previously appreciated.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Molecular clouds (MCs) are exposed to Galactic and extragalactic cosmic rays (CR) that trigger several physical and physicochemical changes, including gas and grain heating and molecular destruction and formation. Here we present a theoretical model describing the energy delivered by CRs, composed of protons, alphas, and electrons taken from Voyager I measurements, into a typical MC with 5400 <jats:italic>M</jats:italic> <jats:sub>☉</jats:sub> (composed mainly of H with a density law of <jats:italic>r</jats:italic> <jats:sup>−1.2</jats:sup>) and size around 1 × 10<jats:sup>6</jats:sup> au. The calculation was performed employing the Monte Carlo toolkit GEANT4 to obtain the energy deposition per mass from several types of secondary particles (considering nuclear and hadron physics). The results indicate that incoming protons contribute to most of the energy delivered in the MC in all regions (maximum ∼230 MeV g<jats:sup>−1</jats:sup> s<jats:sup>−1</jats:sup> at outer regions of the cloud). Secondary electrons are the second most important component for energy deposition in almost all layers of the MC and can deliver an energy rate of ∼130 MeV g<jats:sup>−1</jats:sup> s<jats:sup>−1</jats:sup> in the outer region of the MC. Other cascade particles have their major energy delivery in the central and denser core of the MC. From a temperature model (considering CR data from Voyager I), we observed (i) a small bump in temperature at the distance of 3 × 10<jats:sup>3</jats:sup>–2 × 10<jats:sup>4</jats:sup> au from the center, (ii) a rapid temperature decrease (roughly 7 K) between the outer layer and the second most outer layer, and (iii) that, at a distance of 5 × 10<jats:sup>4</jats:sup> au (<jats:italic>Av</jats:italic> &gt; 10), the gas temperature of the MC is below 15 K.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In the first paper of this series, we demonstrated that neural networks can robustly and efficiently estimate kinematic parameters for optical emission-line spectra taken by SITELLE at the Canada–France–Hawaii Telescope. This paper expands upon this notion by developing an artificial neural network to estimate the line ratios of strong emission lines present in the SN1, SN2, and SN3 filters of SITELLE. We construct a set of 50,000 synthetic spectra using line ratios taken from the Mexican Million Model database replicating <jats:sc>H</jats:sc> <jats:sc>ii</jats:sc> regions. Residual analysis of the network on the test set reveals the network’s ability to apply tight constraints to the line ratios. We verified the network’s efficacy by constructing an activation map, checking the [<jats:sc>N</jats:sc> <jats:sc>ii</jats:sc>] doublet fixed ratio, and applying a standard k-fold cross-correlation. Additionally, we apply the network to SITELLE observations of M33; the residuals between the algorithm’s estimates and values calculated using standard fitting methods show general agreement. Moreover, the neural network reduces the computational costs by two orders of magnitude. Although standard fitting routines do consistently well depending on the signal-to-noise ratio of the spectral features, the neural network can also excels at predictions in the low signal-to-noise regime within the controlled environment of the training set as well as on observed data when the source spectral properties are well constrained by models. These results reinforce the power of machine learning in spectral analysis.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The Helioseismic and Magnetic Imager (HMI) on board NASA’s Solar Dynamics Observatory produces estimates of the photospheric magnetic field, which are a critical input to many space weather modeling and forecasting systems. The magnetogram products produced by HMI and its analysis pipeline are the result of a per-pixel optimization that estimates solar atmospheric parameters and minimizes disagreement between a synthesized and observed Stokes vector. In this paper, we introduce a deep-learning-based approach that can emulate the existing HMI pipeline results two orders of magnitude faster than the current pipeline algorithms. Our system is a U-Net trained on input Stokes vectors and their accompanying optimization-based Very Fast Inversion of the Stokes Vector (VFISV) inversions. We demonstrate that our system, once trained, can produce high-fidelity estimates of the magnetic field and kinematic and thermodynamic parameters while also producing meaningful confidence intervals. We additionally show that despite penalizing only per-pixel loss terms, our system is able to faithfully reproduce known systematic oscillations in full-disk statistics produced by the pipeline. This emulation system could serve as an initialization for the full Stokes inversion or as an ultrafast proxy inversion. This work is part of the NASA Heliophysics DRIVE Science Center (SOLSTICE) at the University of Michigan, under grant NASA 80NSSC20K0600E, and will be open sourced.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Laboratory experiments revealed that CO<jats:sub>2</jats:sub> ice particles stick less efficiently than H<jats:sub>2</jats:sub>O ice particles, and there is an order of magnitude difference in the threshold velocity for sticking. However, the surface energies and elastic moduli of CO<jats:sub>2</jats:sub> and H<jats:sub>2</jats:sub>O ices are comparable, and the reason why CO<jats:sub>2</jats:sub> ice particles were poorly sticky compared to H<jats:sub>2</jats:sub>O ice particles was unclear. Here we investigate the effects of viscoelastic dissipation on the threshold velocity for sticking of ice particles using the viscoelastic contact model derived by Krijt et al. We find that the threshold velocity for the sticking of CO<jats:sub>2</jats:sub> ice particles reported in experimental studies is comparable to that predicted for perfectly elastic spheres. In contrast, the threshold velocity for the sticking of H<jats:sub>2</jats:sub>O ice particles is an order of magnitude higher than that predicted for perfectly elastic spheres. Therefore, we conclude that the large difference in stickiness between CO<jats:sub>2</jats:sub> and H<jats:sub>2</jats:sub>O ice particles would mainly originate from the difference in the strength of viscoelastic dissipation, which is controlled by the viscoelastic relaxation time.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Resonant absorption is considered to be a crucial mechanism for the damping of the coronal loop oscillations and plasma heating. We study resonant absorption of the coronal loop kink oscillations excited by such external drivers as flares, assuming that there is an intermediate shear flow region surrounding the loop. We find that for long coronal loops resonant absorption can be highly enhanced or reduced depending sensitively on the magnitude and direction of the flow and the spatial extent of the flow region when the transitional layer is thin. For short coronal loops, high flow speed and a thick transitional layer are needed to have a substantial resonant absorption. We provide a potential picture to explain the results where the external Alfvén speed and phase speed of the wave are important parameters. These results imply that the transport of the external wave energy into the loop is significantly changed by the shear flow region, which may cause the selective excitation of the coronal loop oscillations.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We use the ∼370 deg<jats:sup>2</jats:sup> data from the MWISP CO survey to study the vertical distribution of the molecular clouds (MCs) toward the tangent points in the region of <jats:italic>l</jats:italic> = [+16°, +52°] and ∣<jats:italic>b</jats:italic>∣ &lt; 5.°1. We find that the molecular disk consists of two components with a layer thickness (FWHM) of ∼85 pc and ∼280 pc, respectively. In the inner Galaxy, the molecular mass in the thin disk is dominant, while the molecular mass traced by the discrete MCs with weak CO emission in the thick disk is probably ≲10% of the whole molecular disk. For the CO gas in the thick disk, we identified 1055 high-<jats:italic>z</jats:italic> MCs that are ≳100 pc from the Galactic plane. However, only a few samples (i.e., 32 MCs or 3%) are located in the ∣<jats:italic>z</jats:italic>∣ ≳ 360 pc region. Typically, the discrete MCs of the thick-disk population have a median peak temperature of 2.1 K, a median velocity dispersion of 0.8 km s<jats:sup>−1</jats:sup>, and a median effective radius of 2.5 pc. Assuming a constant value of <jats:italic>X</jats:italic> <jats:sub>CO</jats:sub> = 2 × 10<jats:sup>20</jats:sup> cm<jats:sup>−2</jats:sup>(K km s<jats:sup>−1</jats:sup>)<jats:sup>−1</jats:sup>, the median surface density of these MCs is 6.8 <jats:italic>M</jats:italic> <jats:sub>⊙</jats:sub> pc<jats:sup>−2</jats:sup>, indicating very faint CO emission for the high-<jats:italic>z</jats:italic> gas. The cloud–cloud velocity dispersion is 4.9 ± 1.3 km s<jats:sup>−1</jats:sup> and a linear variation with a slope of ∼−0.4 km s<jats:sup>−1</jats:sup> kpc<jats:sup>−1</jats:sup> is obtained in the region of <jats:italic>R</jats:italic> <jats:sub>GC</jats:sub> = 2.2–6.4 kpc. Assuming that these clouds are supported by their turbulent motions against the gravitational pull of the disk, a model of <jats:italic>ρ</jats:italic> <jats:sub>0</jats:sub>(<jats:italic>R</jats:italic>) = 1.28 <jats:italic>M</jats:italic> <jats:sub>⊙</jats:sub> pc<jats:sup>−3</jats:sup> <jats:inline-formula> <jats:tex-math> <?CDATA ${e}^{-\displaystyle \frac{R}{3.2\mathrm{kpc}}}$?> </jats:tex-math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabe5abieqn1.gif" xlink:type="simple" /> </jats:inline-formula> can be used to describe the distribution of the total mass density in the Galactic midplane.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Submillimeter emission lines are important tracers of the cold gas and ionized environments of galaxies and the targets for future line intensity mapping surveys. Physics-based simulations that predict multiple emission lines arising from different phases of the interstellar medium are crucial for constraining the global physical conditions of galaxies with upcoming line intensity mapping observations. In this work, we present a general framework for creating multitracer mock submillimeter line intensity maps based on physically grounded galaxy formation and submillimeter line emission models. We simulate a mock light cone of 2 deg<jats:sup>2</jats:sup> over a redshift range <jats:inline-formula> <jats:tex-math> <?CDATA $0\leqslant z\leqslant 10$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>0</mml:mn> <mml:mo>≤</mml:mo> <mml:mi>z</mml:mi> <mml:mo>≤</mml:mo> <mml:mn>10</mml:mn> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabec75ieqn1.gif" xlink:type="simple" /> </jats:inline-formula> comprising discrete galaxies and galaxy [C <jats:sc>ii</jats:sc>], CO, and [C <jats:sc>i</jats:sc>] emission. We present simulated line intensity maps for two fiducial surveys with resolution and observational frequency windows representative of COMAP and EXCLAIM. We show that the star formation rate and line emission scaling relations predicted by our simulation significantly differ at low halo masses from widely used empirical relations, which are often calibrated to observations of luminous galaxies at lower redshifts. We show that these differences lead to significant changes in key summary statistics used in intensity mapping, such as the one-point intensity probability density function and the power spectrum. It will be critical to use more realistic and complex models to forecast the ability of future line intensity mapping surveys to measure observables such as the cosmic star formation rate density.</jats:p>