Catálogo de publicaciones - revistas

<jats:title>Abstract</jats:title> <jats:p>Kinetic turbulence in magnetized space plasmas has been extensively studied via in situ observations, numerical simulations, and theoretical models. In this context, a key point concerns the formation of coherent current structures and their disruption through magnetic reconnection. We present automatic techniques aimed at detecting reconnection events in a large data set of numerical simulations. We make use of clustering techniques known as <jats:italic>K</jats:italic>-means and DBscan (usually referred to in literature as unsupervised machine-learning approaches), and other methods based on thresholds of standard reconnection proxies. All our techniques also use a threshold on the aspect ratio of the regions selected. We test the performance of our algorithms. We propose an optimal aspect ratio to be used in the automated machine-learning algorithm: AR = 18. The performance of the unsupervised approach results in it being strongly competitive with respect to those of other methods based on thresholds of standard reconnection proxies.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Submillimeter spectral line and continuum emission from the protoplanetary disks and envelopes of protostars is a powerful probe of their structure, chemistry, and dynamics. Here we present a benchmark study of our modeling code, RadChemT, that for the first time uses a chemical model to reproduce ALMA C<jats:sup>18</jats:sup>O (2–1), and CARMA <jats:sup>12</jats:sup>CO (1–0) and N<jats:sub>2</jats:sub>H<jats:sup>+</jats:sup> (1–0) observations of L1527; this allows us to distinguish the disk, the infalling envelope, and outflow of this Class 0/I protostar. RadChemT combines dynamics, radiative transfer, gas chemistry, and gas–grain reactions to generate models that can be directly compared with observations for individual protostars. Rather than individually fit abundances to a large number of free parameters, we aim to best match the spectral line maps by (i) adopting a physical model based on density structure and luminosity derived primarily from previous work that fit spectral energy distribution and 2D imaging data, updating it to include a narrow jet detected in CARMA and ALMA data near (≤75 au) the protostar, and then (ii) computing the resulting astrochemical abundances for 292 chemical species. Our model reproduces the C<jats:sup>18</jats:sup>O and N<jats:sub>2</jats:sub>H<jats:sup>+</jats:sup> line strengths within a factor of 3.0; this is encouraging considering the pronounced abundance variation (factor &gt;10<jats:sup>3</jats:sup>) between the outflow shell and CO snowline region near the midplane. Further, our modeling confirms suggestions regarding the anticorrelation between N<jats:sub>2</jats:sub>H<jats:sup>+</jats:sup> and the CO snowline between 400 au and 2000 au from the central star. Our modeling tools represent a new and powerful capability with which to exploit the richness of spectral line imaging provided by modern submillimeter interferometers.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Low-mass satellites around Milky Way (MW)-like galaxies are important probes of small-scale structure and galaxy formation. However, confirmation of satellite candidates with distance measurements remains a key barrier to fast progress in the Local Volume (LV). We measure the surface brightness fluctuation distances to recently cataloged candidate dwarf satellites around 10 massive hosts within <jats:italic>D</jats:italic> &lt; 12 Mpc to confirm association. The satellite systems of these hosts are complete and mostly cleaned of contaminants down to <jats:italic>M</jats:italic> <jats:sub> <jats:italic>g</jats:italic> </jats:sub> ∼ −9 to −10, within the area of the search footprints. Joining this sample with hosts surveyed to comparable or better completeness in the literature, we explore how well cosmological simulations combined with common stellar to halo mass relations (SHMR) match observed satellite luminosity functions in the classical satellite luminosity regime. Adopting an SHMR that matches hydrodynamic simulations, we find that the predicted overall satellite abundance agrees well with the observations. The MW is remarkably typical in its luminosity function among LV hosts. We find that the host-to-host scatter predicted by the model is in close agreement with the scatter between the observed systems, once the different masses of the observed systems are taken into account. However, we find significant evidence that the observed systems have more bright and fewer faint satellites than the SHMR model predicts, possibly necessitating a higher normalization of the SHMR around halo masses of 10<jats:sup>11</jats:sup> <jats:italic>M</jats:italic> <jats:sub>⊙</jats:sub> or significantly greater scatter than present in common SHMRs. These results demonstrate the utility of nearby satellite systems in inferring the galaxy–subhalo connection in the low-mass regime.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>In this paper, we study the impact of different galaxy statistics and empirical metallicity scaling relations on the merging rates and properties of compact object binaries. Firstly, we analyze the similarities and differences of using the star formation rate functions versus stellar mass functions as galaxy statistics for the computation of cosmic star formation rate density. We then investigate the effects of adopting the Fundamental Metallicity Relation versus a classic Mass Metallicity Relation to assign metallicity to galaxies with given properties. We find that when the Fundamental Metallicity Relation is exploited, the bulk of the star formation occurs at relatively high metallicities, even at high redshift; the opposite holds when the Mass Metallicity Relation is employed, since in this case the metallicity at which most of the star formation takes place strongly decreases with redshift. We discuss the various reasons and possible biases giving rise to this discrepancy. Finally, we show the impact of these different astrophysical prescriptions on the merging rates and properties of compact object binaries; specifically, we present results for the redshift-dependent merging rates and for the chirp mass and time delay distributions of the merging binaries.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The study of the luminosity contribution from thermally pulsing asymptotic giant branch (TP-AGB) stars to the stellar populations of galaxies is crucial to determine their physical parameters (e.g., stellar mass and age). We use a sample of 84 nearby disk galaxies to explore diverse stellar population synthesis models with different luminosity contributions from TP-AGB stars. We fit the models to optical and near-infrared (NIR) photometry, on a pixel-by-pixel basis. The statistics of the fits show a preference for a low-luminosity contribution (i.e., high mass-to-light ratio in the NIR) from TP-AGB stars. Nevertheless, for 30%–40% of the pixels in our sample a high-luminosity contribution (hence low mass-to-light ratio in the NIR) from TP-AGB stars is favored. According to our findings, the mean TP-AGB star luminosity contribution in nearby disk galaxies may vary with Hubble type. This may be a consequence of the variation of the TP-AGB mass-loss rate with metallicity, if metal-poor stars begin losing mass earlier than metal-rich stars, because of a pre-dust wind that precedes the dust-driven wind.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Energy cutoffs in electron distribution define the lower and upper limits on the energy range of energetic electrons accelerated in solar flares. They are crucial parameters for understanding particle acceleration processes and energy budgets. Their signatures have been reported in studies of flattened flare X-ray spectra, i.e., the impulsive emission of nonthermal bremsstrahlung from energetic electrons impacting ambient, thermal plasma. However, these observations have not provided unambiguous constraints on the cutoffs. Moreover, other processes may result in similar spectral features. Even the existence and necessity of cutoffs as physical parameters of energetic electrons have been under debate. Here we report a search for their signatures in flare-accelerated electrons with two approaches, i.e., in both X-ray spectra and solar energetic particle (SEP) events. These represent two different electron populations, but may contain information of the same acceleration process. By studying a special group of late impulsive flares, and a group of selected SEP events, we found evidence of cutoffs revealed in both X-ray spectra and SEP electron distributions. In particular, we found for the first time consistent low- and high-energy cutoffs in both hard X-ray-producing and escaping electrons in two events. We also showed the importance of high-energy cutoff in studies of spectral shapes. These results provide evidence of cutoffs in flare-accelerated energetic electrons and new clues for constraining electron distribution parameters and particle acceleration models.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The local determination of the Hubble constant sits at a crossroad. Current estimates of the local expansion rate of the universe differ by about 1.7<jats:italic>σ</jats:italic>, derived from the Cepheid- and TRGB-based calibrations, applied to Type Ia supernovae. To help elucidate possible sources of systematic error causing the tension, we show in this study the recently developed distance indicator, the J-region Asymptotic Giant Branch (JAGB) method, can serve as an independent cross-check and comparison with other local distance indicators. Furthermore, we make the case that the JAGB method has substantial potential as an independent, precise, and accurate calibrator of Type Ia supernovae for the determination of <jats:italic>H</jats:italic> <jats:sub>0</jats:sub>. Using the Local Group galaxy Wolf–Lundmark–Melotte (WLM), we present distance comparisons between the JAGB method, a TRGB measurement at near-infrared (<jats:italic>JHK</jats:italic>) wavelengths, a TRGB measurement in the optical <jats:italic>I</jats:italic> band, and a multiwavelength Cepheid period–luminosity relation determination. We find</jats:p> <jats:p> <jats:inline-formula id="apjabd253ueqn1"> <jats:tex-math> <?CDATA \begin{eqnarray*}\begin{array}{rcl}{\mu }_{0}\,(\mathrm{JAGB}) & = & 24.97\pm 0.02\ (\mathrm{stat})\pm 0.04\ (\mathrm{sys})\ \mathrm{mag}\\ {\mu }_{0}\,({\mathrm{TRGB}}_{\mathrm{NIR}}) & = & 24.98\pm 0.04\ (\mathrm{stat})\pm 0.07\ (\mathrm{sys})\ \mathrm{mag}\\ {\mu }_{0}\,({\mathrm{TRGB}}_{{\rm{F}}814{\rm{W}}}) & = & 24.93\pm 0.02\ (\mathrm{stat})\pm 0.06\ (\mathrm{sys})\ \mathrm{mag}\\ {\mu }_{0}\,(\mathrm{Cepheids}) & = & 24.98\pm 0.03\ (\mathrm{stat})\pm 0.04\ (\mathrm{sys})\ \mathrm{mag}.\end{array}\end{eqnarray*}?> </jats:tex-math> <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mtable> <mml:mtr> <mml:mtd columnalign="right"> <mml:msub> <mml:mrow> <mml:mi>μ</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:msub> <mml:mspace width="0.25em" /> <mml:mo stretchy="false">(</mml:mo> <mml:mi>JAGB</mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:mtd> <mml:mtd columnalign="center"> <mml:mo>=</mml:mo> </mml:mtd> <mml:mtd columnalign="left"> <mml:mn>24.97</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.02</mml:mn> <mml:mspace width="0.33em" /> <mml:mo stretchy="false">(</mml:mo> <mml:mi>stat</mml:mi> <mml:mo stretchy="false">)</mml:mo> <mml:mo>±</mml:mo> <mml:mn>0.04</mml:mn> <mml:mspace width="0.33em" /> <mml:mo stretchy="false">(</mml:mo> <mml:mi>sys</mml:mi> <mml:mo stretchy="false">)</mml:mo> <mml:mspace width="0.33em" /> <mml:mi>mag</mml:mi> </mml:mtd> </mml:mtr> <mml:mtr> <mml:mtd columnalign="right"> <mml:msub> <mml:mrow> <mml:mi>μ</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:msub> <mml:mspace width="0.25em" /> <mml:mo stretchy="false">(</mml:mo> <mml:msub> <mml:mrow> <mml:mi>TRGB</mml:mi> </mml:mrow> <mml:mrow> <mml:mi>NIR</mml:mi> </mml:mrow> </mml:msub> <mml:mo stretchy="false">)</mml:mo> </mml:mtd> <mml:mtd columnalign="center"> <mml:mo>=</mml:mo> </mml:mtd> <mml:mtd columnalign="left"> <mml:mn>24.98</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.04</mml:mn> <mml:mspace width="0.33em" /> <mml:mo stretchy="false">(</mml:mo> <mml:mi>stat</mml:mi> <mml:mo stretchy="false">)</mml:mo> <mml:mo>±</mml:mo> <mml:mn>0.07</mml:mn> <mml:mspace width="0.33em" /> <mml:mo stretchy="false">(</mml:mo> <mml:mi>sys</mml:mi> <mml:mo stretchy="false">)</mml:mo> <mml:mspace width="0.33em" /> <mml:mi>mag</mml:mi> </mml:mtd> </mml:mtr> <mml:mtr> <mml:mtd columnalign="right"> <mml:msub> <mml:mrow> <mml:mi>μ</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:msub> <mml:mspace width="0.25em" /> <mml:mo stretchy="false">(</mml:mo> <mml:msub> <mml:mrow> <mml:mi>TRGB</mml:mi> </mml:mrow> <mml:mrow> <mml:mi mathvariant="normal">F</mml:mi> <mml:mn>814</mml:mn> <mml:mi mathvariant="normal">W</mml:mi> </mml:mrow> </mml:msub> <mml:mo stretchy="false">)</mml:mo> </mml:mtd> <mml:mtd columnalign="center"> <mml:mo>=</mml:mo> </mml:mtd> <mml:mtd columnalign="left"> <mml:mn>24.93</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.02</mml:mn> <mml:mspace width="0.33em" /> <mml:mo stretchy="false">(</mml:mo> <mml:mi>stat</mml:mi> <mml:mo stretchy="false">)</mml:mo> <mml:mo>±</mml:mo> <mml:mn>0.06</mml:mn> <mml:mspace width="0.33em" /> <mml:mo stretchy="false">(</mml:mo> <mml:mi>sys</mml:mi> <mml:mo stretchy="false">)</mml:mo> <mml:mspace width="0.33em" /> <mml:mi>mag</mml:mi> </mml:mtd> </mml:mtr> <mml:mtr> <mml:mtd columnalign="right"> <mml:msub> <mml:mrow> <mml:mi>μ</mml:mi> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> </mml:mrow> </mml:msub> <mml:mspace width="0.25em" /> <mml:mo stretchy="false">(</mml:mo> <mml:mi>Cepheids</mml:mi> <mml:mo stretchy="false">)</mml:mo> </mml:mtd> <mml:mtd columnalign="center"> <mml:mo>=</mml:mo> </mml:mtd> <mml:mtd columnalign="left"> <mml:mn>24.98</mml:mn> <mml:mo>±</mml:mo> <mml:mn>0.03</mml:mn> <mml:mspace width="0.33em" /> <mml:mo stretchy="false">(</mml:mo> <mml:mi>stat</mml:mi> <mml:mo stretchy="false">)</mml:mo> <mml:mo>±</mml:mo> <mml:mn>0.04</mml:mn> <mml:mspace width="0.33em" /> <mml:mo stretchy="false">(</mml:mo> <mml:mi>sys</mml:mi> <mml:mo stretchy="false">)</mml:mo> <mml:mspace width="0.33em" /> <mml:mi>mag</mml:mi> <mml:mi>.</mml:mi> </mml:mtd> </mml:mtr> </mml:mtable> </mml:math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabd253ueqn1.gif" xlink:type="simple" /> </jats:inline-formula> </jats:p> <jats:p>All four methods are in good agreement, confirming the local self-consistency of the four distance scales at the 3% level and adding confidence that the JAGB method is as accurate and as precise a distance indicator as either of the other three astrophysically based methods.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The path to understanding star formation processes begins with the study of the formation of molecular clouds. The outskirts of these clouds are characterized by low column densities that allow the penetration of ultraviolet radiation, resulting in a nonnegligible ionization fraction and the charging of the small dust grains that are mixed with the gas; this diffuse phase is then coupled to the ambient magnetic field. Despite the general assumption that dust and gas are tightly correlated, several observational and theoretical studies have reported variations in the dust-to-gas ratio toward diffuse and cold clouds. In this work, we present the implementation of a new charged particles module for analyzing the dust dynamics in molecular cloud envelopes. We study the evolution of a single population of small charged grains (0.05 <jats:italic>μ</jats:italic>m) in the turbulent, magnetized molecular cloud envelope using this module. We show that variations in the dust-to-gas ratio arise due to the coupling of the grains with the magnetic field, forming elongated dust structures decoupled from the gas. This emphasizes the importance of considering the dynamics of charged dust when simulating the different phases of the interstellar medium, especially for star formation studies.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>TXS 0506+056 is a blazar that has been recently identified as the counterpart of the neutrino event IceCube-170922A. Understanding the blazar type of TXS 0506+056 is important to constrain the neutrino emission mechanism, but the blazar nature of TXS 0506+056 is still uncertain. As an attempt to understand the nature of TXS 0506+056, we report the medium-band observation results of TXS 0506+056, covering the wavelength range of 0.575–1.025 <jats:italic>μ</jats:italic>m. The use of the medium-band filters allows us to examine if there were any significant changes in its spectral shapes over the course of one month and give a better constraint on the peak frequency of synchrotron radiation with quasi-simultaneous data sets. The peak frequency is found to be 10<jats:sup>14.28</jats:sup> Hz, and our analysis shows that TXS 0506+056 is not an outlier from the blazar sequence. As a way to determine the blazar type, we also analyzed if TXS 0506+056 is bluer-when-brighter (BL Lac type and some flat spectrum radio quasars, FSRQs) or redder-when-brighter (found only in some FSRQs). Even though we detect no significant variability in the spectral shape larger than observational error during our medium-band observation period, the comparison with a data set taken in 2012 shows a possible redder-when-brighter behavior of FSRQs. Our results demonstrate that medium-band observations with small to moderate-sized telescopes can be an effective way to trace the spectral evolution of transients such as TXS 0506+056.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Inferring planetary parameters from transit timing variations (TTVs) is challenging for small exoplanets because their transits may be so weak that determination of individual transit timing is difficult or impossible. We implement a useful combination of tools that together provide a numerically fast global photodynamical model. This is used to fit the TTV-bearing light curve, in order to constrain the masses of transiting exoplanets in low-eccentricity, multiplanet systems—and small planets in particular. We present inferred dynamical masses and orbital eccentricities in four multi-planet systems from Kepler's complete long-cadence data set. We test our model against Kepler-36/KOI-277, a system with some of the most precisely determined planetary masses through TTV inversion methods, and find masses of 5.56<jats:sup>+0.41</jats:sup> <jats:sub>−0.45</jats:sub> and 9.76<jats:sup>+0.79</jats:sup> <jats:sub>−0.89</jats:sub> <jats:inline-formula> <jats:tex-math> <?CDATA ${m}_{\oplus }$?> </jats:tex-math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabc87aieqn1.gif" xlink:type="simple" /> </jats:inline-formula> for Kepler-36 b and c, respectively—consistent with literature in both value and error. We then improve the mass determination of the four planets in Kepler-79/KOI-152, where literature values were physically problematic to 12.5<jats:sup>+4.5</jats:sup> <jats:sub>−3.6</jats:sub>, 9.5<jats:sup>+2.3</jats:sup> <jats:sub>−2.1</jats:sub>, 11.3<jats:sup>+2.2</jats:sup> <jats:sub>−2.2</jats:sub> and 6.3<jats:sup>+1.0</jats:sup> <jats:sub>−1.0</jats:sub> <jats:inline-formula> <jats:tex-math> <?CDATA ${m}_{\oplus }$?> </jats:tex-math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabc87aieqn2.gif" xlink:type="simple" /> </jats:inline-formula> for Kepler-79 b, c, d, and e, respectively. We provide new mass constraints where none existed before for two systems. These are 12.5<jats:sup>+3.2</jats:sup> <jats:sub>−2.6</jats:sub> <jats:inline-formula> <jats:tex-math> <?CDATA ${m}_{\oplus }$?> </jats:tex-math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabc87aieqn3.gif" xlink:type="simple" /> </jats:inline-formula> for Kepler-450 c, and 3.3<jats:sup>+1.7</jats:sup> <jats:sub>−1.0</jats:sub> and 17.4<jats:sup>+7.1</jats:sup> <jats:sub>−3.8</jats:sub> <jats:inline-formula> <jats:tex-math> <?CDATA ${m}_{\oplus }$?> </jats:tex-math> <jats:inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="apjabc87aieqn4.gif" xlink:type="simple" /> </jats:inline-formula> for Kepler-595 c (previously KOI-547.03) and b, respectively. The photodynamical code used here, called <jats:monospace>PyDynamicaLC</jats:monospace>, is made publicly available.</jats:p>