Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>We present a study of density fluctuations in coronal holes. We used a reduced magnetohydrodynamic (RMHD) model that incorporated observationally constrained density fluctuations to determine whether density fluctuations in coronal holes can enhance Alfvén wave reflection and dissipation, thereby heating coronal holes and driving the fast solar wind. We show results for two models of the background atmosphere. Each model is a solution of the momentum equation and includes the effects of wave pressure on the solar wind outflow. In the first model, the plasma density and Alfvén speed vary smoothly with height. Wave reflection is relatively weak in the smooth model, resulting in a low energy dissipation rate. In the second model, we include additional density fluctuations along the flux tube based on the observations. We find that density <jats:italic>ρ</jats:italic> fluctuations on the order of <jats:italic>δρ</jats:italic>/<jats:italic>ρ</jats:italic> ∼ 0.24 increase the Alfvén wave turbulence to levels sufficient to heat the open field regions in coronal holes.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We present the first results of a 4.5 yr monitoring campaign of the three bright images of multiply imaged <jats:italic>z</jats:italic> = 2.805 quasar SDSS J2222+2745 using the Gemini North Multi-Object Spectrograph and the Nordic Optical Telescope. We take advantage of gravitational time delays to construct light curves surpassing 6 yr in duration in the observed frame and achieve an average spectroscopic cadence of 10 days during the 8 months of visibility per season. Using multiple secondary calibrators and advanced reduction techniques, we achieve percent-level spectrophotometric precision and carry out an unprecedented reverberation mapping analysis, measuring both integrated and velocity-resolved time lags for the C <jats:sc>iv</jats:sc> emission line. The full line lags the continuum by <jats:inline-formula> <jats:tex-math> <?CDATA ${\tau }_{\mathrm{cen}}={36.5}_{-3.9}^{+2.9}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>τ</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>cen</mml:mi> </mml:mrow> </mml:msub> <mml:mo>=</mml:mo> <mml:msubsup> <mml:mrow> <mml:mn>36.5</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>3.9</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>2.9</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabe943ieqn1.gif" xlink:type="simple" /> </jats:inline-formula> rest-frame days. We combine our measurement with published C <jats:sc>iv</jats:sc> emission line lags and derive the <jats:italic>r</jats:italic> <jats:sub>BLR</jats:sub> − <jats:italic>L</jats:italic> relationship <jats:inline-formula> <jats:tex-math> <?CDATA ${\mathrm{log}}_{10}(\tau /{\rm{d}}{\rm{a}}{\rm{y}})=(0.99\,\pm 0.07)+(0.48\pm 0.03){\mathrm{log}}_{10}[\lambda {L}_{\lambda }(1350\,{\rm{A}}{\rm{A}})/{10}^{44}\,{{\rm{e}}{\rm{r}}{\rm{g}}{\rm{s}}}^{-1}]$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mi>log</mml:mi> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> </mml:msub> <mml:mo>​</mml:mo> <mml:mo stretchy="false">(</mml:mo> <mml:mi>τ</mml:mi> <mml:mrow> <mml:mo>/</mml:mo> </mml:mrow> <mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">d</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">a</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">y</mml:mi> </mml:mrow> </mml:mrow> <mml:mo stretchy="false">)</mml:mo> <mml:mo>=</mml:mo> <mml:mo stretchy="false">(</mml:mo> <mml:mn>0.99</mml:mn> <mml:mspace width="0.25em" /> <mml:mo>±</mml:mo> <mml:mn>0.07</mml:mn> <mml:mo stretchy="false">)</mml:mo> <mml:mo>+</mml:mo> <mml:mo stretchy="false">(</mml:mo> <mml:mn>0.48</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.03</mml:mn> <mml:mo stretchy="false">)</mml:mo> <mml:msub> <mml:mi>log</mml:mi> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> </mml:msub> <mml:mo>​</mml:mo> <mml:mo stretchy="false">[</mml:mo> <mml:mi>λ</mml:mi> <mml:msub> <mml:mi>L</mml:mi> <mml:mi>λ</mml:mi> </mml:msub> <mml:mo stretchy="false">(</mml:mo> <mml:mn>1350</mml:mn> <mml:mspace width="0.25em" /> <mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">A</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">A</mml:mi> </mml:mrow> </mml:mrow> <mml:mo stretchy="false">)</mml:mo> <mml:mrow> <mml:mo>/</mml:mo> </mml:mrow> <mml:msup> <mml:mn>10</mml:mn> <mml:mrow> <mml:mn>44</mml:mn> </mml:mrow> </mml:msup> <mml:mspace width="0.25em" /> <mml:msup> <mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">e</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">r</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">g</mml:mi> </mml:mrow> <mml:mspace width="0.25em" /> <mml:mrow> <mml:mi mathvariant="normal">s</mml:mi> </mml:mrow> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> <mml:mo stretchy="false">]</mml:mo> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabe943ieqn2.gif" xlink:type="simple" /> </jats:inline-formula> with 0.30 ± 0.06 dex intrinsic scatter. The velocity-resolved lags are consistent with circular Keplerian orbits, with <jats:inline-formula> <jats:tex-math> <?CDATA ${\tau }_{\mathrm{cen}}={86.2}_{-5.0}^{+4.5}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>τ</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>cen</mml:mi> </mml:mrow> </mml:msub> <mml:mo>=</mml:mo> <mml:msubsup> <mml:mrow> <mml:mn>86.2</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>5.0</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>4.5</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabe943ieqn3.gif" xlink:type="simple" /> </jats:inline-formula>, <jats:inline-formula> <jats:tex-math> <?CDATA ${25}_{-15}^{+11}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msubsup> <mml:mrow> <mml:mn>25</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>15</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="apjabe943ieqn4.gif" xlink:type="simple" /> </jats:inline-formula>, and <jats:inline-formula> <jats:tex-math> <?CDATA ${7.5}_{-3.5}^{+4.2}$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msubsup> <mml:mrow> <mml:mn>7.5</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>3.5</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>4.2</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabe943ieqn5.gif" xlink:type="simple" /> </jats:inline-formula> rest-frame days for the core, blue wing, and red wing, respectively. Using <jats:italic>σ</jats:italic> <jats:sub>line</jats:sub> with the mean spectrum and assuming <jats:inline-formula> <jats:tex-math> <?CDATA ${\mathrm{log}}_{10}({f}_{\mathrm{mean},\sigma })=0.52\pm 0.26$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>log</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> </mml:msub> <mml:mo stretchy="false">(</mml:mo> <mml:msub> <mml:mrow> <mml:mi>f</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>mean</mml:mi> <mml:mo>,</mml:mo> <mml:mi>σ</mml:mi> </mml:mrow> </mml:msub> <mml:mo stretchy="false">)</mml:mo> <mml:mo>=</mml:mo> <mml:mn>0.52</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.26</mml:mn> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabe943ieqn6.gif" xlink:type="simple" /> </jats:inline-formula>, we derive <jats:inline-formula> <jats:tex-math> <?CDATA ${\mathrm{log}}_{10}({M}_{\mathrm{BH}}/{M}_{\odot })=8.63\pm 0.27$?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msub> <mml:mrow> <mml:mi>log</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>10</mml:mn> </mml:mrow> </mml:msub> <mml:mo stretchy="false">(</mml:mo> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>BH</mml:mi> </mml:mrow> </mml:msub> <mml:mrow> <mml:mo stretchy="true">/</mml:mo> </mml:mrow> <mml:msub> <mml:mrow> <mml:mi>M</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>⊙</mml:mo> </mml:mrow> </mml:msub> <mml:mo stretchy="false">)</mml:mo> <mml:mo>=</mml:mo> <mml:mn>8.63</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.27</mml:mn> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabe943ieqn7.gif" xlink:type="simple" /> </jats:inline-formula>. Given the quality of the data, this system represents a unique benchmark for calibration of <jats:italic>M</jats:italic> <jats:sub>BH</jats:sub> estimators at high redshift. Future work will present dynamical modeling of the data to constrain the virial factor <jats:italic>f</jats:italic> and <jats:italic>M</jats:italic> <jats:sub>BH</jats:sub>.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We present a measurement of the Hubble constant <jats:italic>H</jats:italic> <jats:sub>0</jats:sub> from surface brightness fluctuation (SBF) distances for 63 bright, mainly early-type galaxies out to 100 Mpc observed with the WFC3/IR on the Hubble Space Telescope (HST). The sample is drawn from several independent HST imaging programs using the F110W bandpass, with the majority of the galaxies being selected from the MASSIVE survey. The distances reach the Hubble flow with a median statistical uncertainty per measurement of 4%. We construct the Hubble diagram with these IR SBF distances and constrain <jats:italic>H</jats:italic> <jats:sub>0</jats:sub> using four different treatments of the galaxy velocities. For the SBF zero-point calibration, we use both the existing tie to Cepheid variables, updated for consistency with the latest determination of the distance to the Large Magellanic Cloud from detached eclipsing binaries, and a new tie to the tip of the red giant branch (TRGB) calibrated from the maser distance to NGC 4258. These two SBF calibrations are consistent with each other and with theoretical predictions from stellar population models. From a weighted average of the Cepheid and TRGB calibrations, we derive <jats:italic>H</jats:italic> <jats:sub>0</jats:sub> = 73.3 ± 0.7 ± 2.4 km s<jats:sup>−1</jats:sup> Mpc<jats:sup>−1</jats:sup>, where the error bars reflect the statistical and systematic uncertainties. This result accords well with recent measurements of <jats:italic>H</jats:italic> <jats:sub>0</jats:sub> from Type Ia supernovae, time delays in multiply lensed quasars, and water masers. The systematic uncertainty could be reduced to below 2% by calibrating the SBF method with precision TRGB distances for a statistical sample of massive early-type galaxies out to the Virgo cluster measured with the James Webb Space Telescope.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We present a multiwavelength analysis of the cluster A1668, performed by means of new EVLA and Chandra observations and archival H<jats:italic>α</jats:italic> data. The radio images exhibit a small central source (∼14 kpc at 1.4 GHz) with <jats:italic>L</jats:italic> <jats:sub>1.4GHz</jats:sub> ∼ 6 · 10<jats:sup>23</jats:sup> W Hz<jats:sup>−1</jats:sup>. The mean spectral index between 1.4 GHz and 5 GHz is ∼−1, consistent with the usual indices found in BCGs. The cooling region extends for 40 kpc, with bolometric X-ray luminosity <jats:italic>L</jats:italic> <jats:sub>cool</jats:sub> = 1.9 ± 0.1 · 10<jats:sup>43</jats:sup> erg s<jats:sup>−1</jats:sup>. We detect an offset of ∼6 kpc between the cluster BCG and the X-ray peak, and another offset of ∼7.6 kpc between the H<jats:italic>α</jats:italic> and the X-ray peaks. We discuss possible causes for these offsets, which suggest that the coolest gas is not condensing directly from the lowest-entropy gas. In particular, we argue that the cool ICM was drawn out from the core by sloshing, whereas the H<jats:italic>α</jats:italic> filaments were pushed aside from the expanding radio galaxy lobes. We detect two putative X-ray cavities, spatially associated with the west radio lobe (cavity A) and the east radio lobe (cavity B). The cavity power and age of the system are <jats:italic>P</jats:italic> <jats:sub>cav</jats:sub> ∼ 9 × 10<jats:sup>42</jats:sup> erg s<jats:sup>−1</jats:sup> and <jats:italic>t</jats:italic> <jats:sub>age</jats:sub> ∼ 5.2 Myr, respectively. Evaluating the position of A1668 in the cooling luminosity–cavity power parameter space, we find that the AGN energy injection is currently consistent within the scatter of the relationship, suggesting that offset cooling is likely not breaking the AGN feedback cycle.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>High-energy neutrinos are unique messengers of the high-energy universe, tracing the processes of cosmic ray acceleration. This paper presents analyses focusing on time-dependent neutrino point-source searches. A scan of the whole sky, making no prior assumption about source candidates, is performed, looking for a space and time clustering of high-energy neutrinos in data collected by the IceCube Neutrino Observatory between 2012 and 2017. No statistically significant evidence for a time-dependent neutrino signal is found with this search during this period, as all results are consistent with the background expectation. Within this study period, the blazar 3C 279, showed strong variability, inducing a very prominent gamma-ray flare observed in 2015 June. This event motivated a dedicated study of the blazar, which consists of searching for a time-dependent neutrino signal correlated with the gamma-ray emission. No evidence for a time-dependent signal is found. Hence, an upper limit on the neutrino fluence is derived, allowing us to constrain a hadronic emission model.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Ram pressure stripping can remove gas from satellite galaxies in clusters via a direct interaction between the intracluster medium (ICM) and the interstellar medium. This interaction is generally thought of as a contact force per area; however, we point out that these gases must interact in a hydrodynamic fashion and argue that this will lead to the mixing of the galactic gas with the ICM wind. We develop an analytic framework for how mixing is related to the acceleration of stripped gas from a satellite galaxy. We then test this model using three “wind-tunnel” simulations of Milky Way–like galaxies interacting with a moving ICM and find excellent agreement with predictions using the analytic framework. Focusing on the dense clumps in the stripped tails, we find that they are nearly uniformly mixed with the ICM, indicating that all gas in the tail mixes with the surroundings and dense clumps are not separate entities to be modeled differently than diffuse gas. We find that while mixing drives the acceleration of stripped gas, the density and velocity of the surrounding wind will determine whether the mixing results in the heating of stripped gas into the ICM or the cooling of the ICM into dense clouds.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Massive star formation occurs in the interior of giant molecular clouds and proceeds through many stages. In this work, we focus on massive young stellar objects (MYSOs) and ultracompact H <jats:sc>ii</jats:sc> regions (UCH <jats:sc>ii</jats:sc>), where the former are enshrouded in dense envelopes of dust and gas, the latter of which has begun dispersing. By selecting a complete sample of MYSOs and UCH <jats:sc>ii</jats:sc> from the Red MSX Source (RMS) survey database, we combine Planck and IRAS data and build their spectral energy distributions. With these, we estimate the physical properties (dust temperatures, mass, luminosity) of the sample. Because the RMS database provides unique solar distances, it also allows the instantaneous star formation efficiency (SFE) to be investigated as a function of Galactocentric radius. We find that the SFE increases between 2 and 4.5 kpc, where it reaches a peak, likely in correspondence with the accumulation of molecular material at the end of the Galactic bar. It then stays approximately constant up to 9 kpc, after which it linearly declines, in agreement with predictions from extragalactic studies. This behavior suggests the presence of a significant amount of undetected molecular gas at <jats:italic>R</jats:italic> <jats:sub>G</jats:sub> &gt; 8 kpc. Finally, we present diagnostic colors that can be used to identify sites of massive star formation.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We have obtained Keck near-infrared spectroscopy of a sample of nine <jats:italic>M</jats:italic> <jats:sub>⋆</jats:sub> &lt; 10<jats:sup>10</jats:sup> <jats:italic>M</jats:italic> <jats:sub>⊙</jats:sub> dwarf galaxies to confirm active galactic nuclei (AGNs) activity and the presence of galaxy-wide, AGN-driven outflows through coronal line (CL) emission. We find strong CL detections in 5/9 galaxies (55%) with line ratios incompatible with shocks, confirming the presence of AGNs in these galaxies. Similar CL detection rates are found in larger samples of more massive galaxies hosting type 1 and 2 AGNs. We investigate the connection between the CLs and galaxy-wide outflows by analyzing the kinematics of the CL region as well as the scaling of gas velocity with ionization potential of different CLs. In addition, using complementary Keck Cosmic Web Imager observations of these objects, we find that the outflow velocities measured in [Si <jats:sc>vi</jats:sc>] are generally faster than those seen in [O <jats:sc>iii</jats:sc>]. The galaxies with the fastest outflows seen in [O <jats:sc>iii</jats:sc>] also have the highest [Si <jats:sc>vi</jats:sc>] luminosity. The lack of <jats:italic>J</jats:italic>-band CN absorption features, which are often associated with younger stellar populations, provides further evidence that these outflows are driven by AGNs in low-mass galaxies.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In the stellar chromospheres, radiative energy transport is dominated by only the strongest spectral lines. For these lines, the approximation of local thermodynamic equilibrium (LTE) is known to be very inaccurate, and a state of equilibrium cannot be assumed in general. To calculate the radiative energy transport under these conditions, the population evolution equation must be evaluated explicitly, including all time-dependent terms. We develop a numerical method to solve the evolution equation for the atomic-level populations in a time-implicit way, keeping all time-dependent terms to first order. We show that the linear approximation of the time dependence of the populations can handle very large time steps without losing accuracy. We reproduce the benchmark solutions from earlier, well-established works in terms of non-LTE kinetic equilibrium solutions and typical ionization/recombination timescales in the solar chromosphere.</jats:p>