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<jats:title>Abstract</jats:title> <jats:p>Using the Australian Square Kilometre Array Pathfinder to measure 21 cm absorption spectra toward continuum background sources, we study the cool phase of the neutral atomic gas in the far outer disk, and in the inner Galaxy near the end of the Galactic bar at longitude 340°. In the inner Galaxy, the cool atomic gas has a smaller scale height than in the solar neighborhood, similar to the molecular gas and the super-thin stellar population in the bar. In the outer Galaxy, the cool atomic gas is mixed with the warm, neutral medium, with the cool fraction staying roughly constant with the Galactic radius. The ratio of the emission brightness temperature to the absorption, i.e., 1 − <jats:italic>e</jats:italic> <jats:sup>−<jats:italic>τ</jats:italic> </jats:sup>, is roughly constant for velocities corresponding to Galactic radius greater than about twice the solar circle radius. The ratio has a value of about 300 K, but this does not correspond to a physical temperature in the gas. If the gas causing the absorption has kinetic temperature of about 100 K, as in the solar neighborhood, then the value 300 K indicates that the fraction of the gas mass in this phase is one-third of the total H <jats:sc>i</jats:sc> mass.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Supernovae classes have been defined phenomenologically, based on spectral features and time series data, since the specific details of the physics of the different explosions remain unrevealed. However, the number of these classes is increasing as objects with new features are observed, and the next generation of large surveys will only bring more variety to our attention. We apply the machine learning technique of multi-label classification to the spectra of supernovae. By measuring the probabilities of specific features or “tags” in the supernova spectra, we can compress the information from a specific object down to that suitable for a human or database scan, without the need to directly assign to a reductive “class”. We use logistic regression to assign tag probabilities, and then a feed-forward neural network to filter the objects into the standard set of classes, based solely on the tag probabilities. We present <jats:monospace>STag</jats:monospace>, a software package that can compute these tag probabilities and make spectral classifications.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>StrayCats, the catalog of NuSTAR stray light observations, contains data from bright X-ray sources that fall within crowded source regions. These observations offer unique additional data with which to monitor sources such as X-ray binaries that show variable timing behavior. In this work, we present a timing analysis of stray light data of the high-mass X-ray binary SMC X-1, the first scientific analysis of a single source from the StrayCats project. We describe the process of screening stray light data for scientific analysis, verify the orbital ephemeris, and create both time- and energy-resolved pulse profiles. We find that the orbital ephemeris of SMC X-1 is unchanged and confirm a long-term spin-up rate of <jats:inline-formula> <jats:tex-math> <?CDATA $\dot{\nu }=(2.52\pm 0.03)\times {10}^{-11}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mover accent="true"> <mml:mrow> <mml:mi>ν</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>̇</mml:mo> </mml:mrow> </mml:mover> <mml:mo>=</mml:mo> <mml:mo stretchy="false">(</mml:mo> <mml:mn>2.52</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.03</mml:mn> <mml:mo stretchy="false">)</mml:mo> <mml:mo>×</mml:mo> <mml:msup> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>11</mml:mn> </mml:mrow> </mml:msup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjac4d24ieqn1.gif" xlink:type="simple" /> </jats:inline-formula> Hz s<jats:sup>−1</jats:sup>. We also note that the shape of SMC X-1's pulse profile, while remaining double peaked, varies significantly with time and only slightly with energy.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We perform photoionization modeling of the dusty nova V1280 Scorpii (V1280 Sco) with the aim to study the changes in the physical and chemical parameters. We model the predust and postdust phase and optical and near-infrared spectra using the photoionization code <jats:sc>cloudy</jats:sc>, v.17.02, considering a two-component (low-density and high-density regions) model. From the best-fit model, we find that the temperature and luminosity of the central ionizing source in the predust phase is in the range 1.32–1.50 × 10<jats:sup>4</jats:sup> K and 2.95–3.16 × 10<jats:sup>36</jats:sup> ergs<jats:sup>−1</jats:sup>, respectively, which increase to 1.58–1.62 × 10<jats:sup>4</jats:sup> K and 3.23–3.31 × 10<jats:sup>36</jats:sup> ergs<jats:sup>−1</jats:sup>, respectively, in the postdust phase. It is found that a very high hydrogen density (∼10<jats:sup>13</jats:sup>–10<jats:sup>14</jats:sup> cm<jats:sup>−3</jats:sup>) is required for the proper generation of spectra. Dust condensation conditions are achieved at high ejecta density (∼3.16 × 10<jats:sup>8</jats:sup> cm<jats:sup>−3</jats:sup>) and low temperature (∼2000 K) in the outer region of the ejecta. It is found that a mixture of small (0.005–0.25 <jats:italic>μ</jats:italic>m) amorphous carbon dust grains and large (0.03–3.0 <jats:italic>μ</jats:italic>m) astrophysical silicate dust grains is present in the ejecta in the postdust phase. Our model yields very high elemental abundance values as C/H = 13.5–20, N/H = 250, O/H = 27–35, by number, relative to solar values, during the predust phase, which decrease in the postdust phase.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The local escape velocity provides valuable inputs to the mass profile of the galaxy, and requires understanding the tail of the stellar speed distribution. Following Leonard &amp; Tremaine, various works have since modeled the tail of the stellar speed distribution as <jats:inline-formula> <jats:tex-math> <?CDATA $\propto {({v}_{\mathrm{esc}}-v)}^{k}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mo>∝</mml:mo> <mml:msup> <mml:mrow> <mml:mo stretchy="false">(</mml:mo> <mml:msub> <mml:mrow> <mml:mi>v</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>esc</mml:mi> </mml:mrow> </mml:msub> <mml:mo>−</mml:mo> <mml:mi>v</mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:mrow> <mml:mrow> <mml:mi>k</mml:mi> </mml:mrow> </mml:msup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjac4243ieqn1.gif" xlink:type="simple" /> </jats:inline-formula>, where <jats:italic>v</jats:italic> <jats:sub>esc</jats:sub> is the escape velocity, and <jats:italic>k</jats:italic> is the slope of the distribution. In such studies, however, these two parameters were found to be largely degenerate and often a narrow prior is imposed on <jats:italic>k</jats:italic> in order to constrain <jats:italic>v</jats:italic> <jats:sub>esc</jats:sub>. Furthermore, the validity of the power-law form can breakdown in the presence of multiple kinematic substructures or other mis-modeled features in the data. In this paper, we introduce a strategy that for the first time takes into account the presence of kinematic substructure. We model the tail of the velocity distribution as a sum of multiple power laws as a way of introducing a more flexible fitting framework. Using mock data and data from FIRE simulations of Milky Way-like galaxies, we show the robustness of this method in the presence of kinematic structure that is similar to the recently discovered Gaia Sausage. In a companion paper, we present the new measurement of the escape velocity and subsequently the mass of the Milky Way using Gaia eDR3 data.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Small-scale internetwork (IN) magnetic fields are considered to be the main building blocks of quiet Sun magnetism. For this reason, it is crucial to understand how they appear on the solar surface. Here, we employ a high-resolution, high-sensitivity, long-duration Hinode/NFI magnetogram sequence to analyze the appearance modes and spatiotemporal evolution of individual IN magnetic elements inside a supergranular cell at the disk center. From identification of flux patches and magnetofrictional simulations, we show that there are two distinct populations of IN flux concentrations: unipolar and bipolar features. Bipolar features tend to be bigger and stronger than unipolar features. They also live longer and carry more flux per feature. Both types of flux concentrations appear uniformly over the solar surface. However, we argue that bipolar features truly represent the emergence of new flux on the solar surface, while unipolar features seem to be formed by the coalescence of background flux. Magnetic bipoles appear at a faster rate than unipolar features (68 as opposed to 55 Mx cm<jats:sup>−2</jats:sup> day<jats:sup>−1</jats:sup>), and provide about 70% of the total instantaneous IN flux detected in the interior of the supergranule.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Measuring the escape velocity of the Milky Way is critical in obtaining the mass of the Milky Way, understanding the dark matter velocity distribution, and building the dark matter density profile. In Necib &amp; Lin, we introduced a strategy to robustly measure the escape velocity. Our approach takes into account the presence of kinematic substructures by modeling the tail of the stellar distribution with multiple components, including the stellar halo and the debris flow called the Gaia Sausage (Enceladus). In doing so, we can test the robustness of the escape velocity measurement for different definitions of the “tail” of the velocity distribution and the consistency of the data with different underlying models. In this paper, we apply this method to the Gaia eDR3 data release and find that a model with two components is preferred, although results from a single-component fit are also consistent. Based on a fit to retrograde data with two bound components to account for the relaxed halo and the Gaia Sausage, we find the escape velocity of the Milky Way at the solar position to be <jats:inline-formula> <jats:tex-math> <?CDATA ${v}_{\mathrm{esc}}={445}_{-8}^{+25}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>v</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>esc</mml:mi> </mml:mrow> </mml:msub> <mml:mo>=</mml:mo> <mml:msubsup> <mml:mrow> <mml:mn>445</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>8</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>25</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjac4244ieqn1.gif" xlink:type="simple" /> </jats:inline-formula> km s<jats:sup>−1</jats:sup>. A fit with a single component to the same data gives <jats:inline-formula> <jats:tex-math> <?CDATA ${v}_{\mathrm{esc}}={472}_{-12}^{+17}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>v</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>esc</mml:mi> </mml:mrow> </mml:msub> <mml:mo>=</mml:mo> <mml:msubsup> <mml:mrow> <mml:mn>472</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>12</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>17</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjac4244ieqn2.gif" xlink:type="simple" /> </jats:inline-formula> km s<jats:sup>−1</jats:sup>. Assuming a Navarro−Frenck−White dark matter profile, we find a Milky Way concentration of <jats:inline-formula> <jats:tex-math> <?CDATA ${c}_{200}={19}_{-7}^{+11}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>c</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>200</mml:mn> </mml:mrow> </mml:msub> <mml:mo>=</mml:mo> <mml:msubsup> <mml:mrow> <mml:mn>19</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>7</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>11</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjac4244ieqn3.gif" xlink:type="simple" /> </jats:inline-formula> and a mass of <jats:inline-formula> <jats:tex-math> <?CDATA ${M}_{200}={4.6}_{-0.8}^{+1.5}\times {10}^{11}{M}_{\odot }$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>200</mml:mn> </mml:mrow> </mml:msub> <mml:mo>=</mml:mo> <mml:msubsup> <mml:mrow> <mml:mn>4.6</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>0.8</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>1.5</mml:mn> </mml:mrow> </mml:msubsup> <mml:mo>×</mml:mo> <mml:msup> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> <mml:mrow> <mml:mn>11</mml:mn> </mml:mrow> </mml:msup> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⊙</mml:mo> </mml:mrow> </mml:msub> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjac4244ieqn4.gif" xlink:type="simple" /> </jats:inline-formula>, which is considerably lighter than previous measurements.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We study the jet in the hard state of the accreting black hole (BH) binary MAXI J1820+070. From the available radio-to-optical spectral and variability data, we put strong constraints on the jet parameters. We find while it is not possible to uniquely determine the jet Lorentz factor from the spectral and variability properties alone, we can estimate the jet opening angle (≈1.°5 ± 1°), the distance at which the jet starts emitting synchrotron radiation (∼3 × 10<jats:sup>10</jats:sup> cm), and the magnetic field strength there (∼10<jats:sup>4</jats:sup> G), with relatively low uncertainty, as they depend weakly on the bulk Lorentz factor. We find the breaks in the variability power spectra from radio to submillimeter wavelength are consistent with variability damping over the timescale equal to the travel time along the jet at any Lorentz factor. This factor can still be constrained by the electron–positron pair-production rate within the jet base, which we calculate based on the observed X-ray/soft-gamma-ray spectrum, and the jet power, required to be less than the accretion power. The minimum (∼1.5) and maximum (∼4.5) Lorentz factors correspond to the dominance of pairs and ions, and the minimum and maximum jet power, respectively. We estimate the magnetic flux threading the BH and find the jet can be powered by the Blandford–Znajek mechanism in a magnetically arrested flow accretion flow. We point out the similarity of our derived formalism to that of core shifts, observed in extragalactic radio sources.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We compare observations of H <jats:sc>i</jats:sc> from the Very Large Array (VLA) and the Arecibo Observatory and observations of HCO<jats:sup>+</jats:sup> from the Atacama Large Millimeter/submillimeter Array (ALMA) and the Northern Extended Millimeter Array (NOEMA) in the diffuse (<jats:italic>A</jats:italic> <jats:sub> <jats:italic>V</jats:italic> </jats:sub> ≲ 1) interstellar medium (ISM) to predictions from a photodissociation region (PDR) chemical model and multiphase ISM simulations. Using a coarse grid of PDR models, we estimate the density, FUV radiation field, and cosmic-ray ionization rate (CRIR) for each structure identified in HCO<jats:sup>+</jats:sup> and H <jats:sc>i</jats:sc> absorption. These structures fall into two categories. Structures with <jats:italic>T</jats:italic> <jats:sub> <jats:italic>s</jats:italic> </jats:sub> &lt; 40 K, mostly with <jats:italic>N</jats:italic>(HCO<jats:sup>+</jats:sup>) ≲ 10<jats:sup>12</jats:sup> cm<jats:sup>−2</jats:sup>, are consistent with modest density, FUV radiation field, and CRIR models, typical of the diffuse molecular ISM. Structures with spin temperature <jats:italic>T</jats:italic> <jats:sub> <jats:italic>s</jats:italic> </jats:sub> &gt; 40 K, mostly with <jats:italic>N</jats:italic>(HCO<jats:sup>+</jats:sup>) ≳ 10<jats:sup>12</jats:sup> cm<jats:sup>−2</jats:sup>, are consistent with high density, FUV radiation field, and CRIR models, characteristic of environments close to massive star formation. The latter are also found in directions with a significant fraction of thermally unstable H <jats:sc>i</jats:sc>. In at least one case, we rule out the PDR model parameters, suggesting that alternative mechanisms (e.g., nonequilibrium processes like turbulent dissipation and/or shocks) are required to explain the observed HCO<jats:sup>+</jats:sup> in this direction. Similarly, while our observations and simulations of the turbulent, multiphase ISM agree that HCO<jats:sup>+</jats:sup> formation occurs along sight lines with <jats:italic>N</jats:italic>(H I) ≳ 10<jats:sup>21</jats:sup> cm<jats:sup>−2</jats:sup>, the simulated data fail to explain HCO<jats:sup>+</jats:sup> column densities ≳ few × 10<jats:sup>12</jats:sup> cm<jats:sup>−2</jats:sup>. Because a majority of our sight lines with HCO<jats:sup>+</jats:sup> had such high column densities, this likely indicates that nonequilibrium chemistry is important for these lines of sight.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We present hydrodynamic simulations of the Pegasus–Pisces Arch (PP Arch), an intermediate velocity cloud in our Galaxy. The PP Arch, also known as IVC 86-36, is unique among intermediate and high velocity clouds, because its twin tails are unusually long and narrow. Its −50 km s<jats:sup>−1</jats:sup> line-of-sight velocity qualifies it as an intermediate velocity cloud, but the tails’ orientations indicate that the cloud’s total three-dimensional speed is at least ∼100 km s<jats:sup>−1</jats:sup>. This speed is supersonic in the Reynold’s Layer and thick disk. We simulated the cloud as it travels supersonically through the Galactic thick and thin disks at an oblique angle relative to the midplane. Our simulated clouds grow long double tails and reasonably reproduce the H <jats:sc>I</jats:sc> 21 cm intensity and velocity of the head of the PP Arch. A bow shock protects each simulated cloud from excessive shear and lowers its Reynolds number. These factors may similarly protect the PP Arch and enable the survival of its unusually long tails. The simulations predict the future hydrodynamic behavior of the cloud when it collides with denser gas nearer to the Galactic midplane. It appears that the PP Arch’s fate is to deform, dissipate, and merge with the Galactic disk.</jats:p>