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<jats:title>Abstract</jats:title> <jats:p>We investigate the dependence of the gamma-ray burst (GRB) jet structure and its evolution on the properties of the accreting torus in the central engine. Our models numerically evolve the accretion disk around a Kerr black hole using three-dimensional general relativistic magnetohydrodynamic simulations. We use two different analytical hydrodynamical models of the accretion disk, based on the Fishbone–Moncrief and Chakrabarti solutions, as our initial states for the structure of the collapsar disk and the remnant after a binary neutron star (BNS) merger, respectively. We impose poloidal magnetic fields of two different geometries upon the initial stable solutions. We study the formation and evolution of the magnetically arrested disk state and its effect on the properties of the emitted jet. The jets produced in our models are structured and have a relatively hollow core and reach higher Lorentz factors at an angle ≳9° from the axis. The jet in our short GRB model has an opening angle of up to ∼25° while our long GRB engine produces a narrower jet, of up to ∼11°. We also study the time variability of the jets and provide an estimate of the minimum variability timescale in our models. The application of our models to the GRB jets in the BNS postmerger system and to the ultrarelativistic jets launched from collapsing stars are briefly discussed.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Coronal mass ejections (CMEs) are the most geoeffective space weather phenomena, being associated with large geomagnetic storms, and having the potential to cause disturbances to telecommunications, satellite network disruptions, and power grid damage and failures. Thus, considering these storms’ potential effects on human activities, accurate forecasts of the geoeffectiveness of CMEs are paramount. This work focuses on experimenting with different machine-learning methods trained on white-light coronagraph data sets of close-to-Sun CMEs, to estimate whether such a newly erupting ejection has the potential to induce geomagnetic activity. We developed binary classification models using logistic regression, k-nearest neighbors, support vector machines, feed-forward artificial neural networks, and ensemble models. At this time, we limited our forecast to exclusively use solar onset parameters, to ensure extended warning times. We discuss the main challenges of this task, namely, the extreme imbalance between the number of geoeffective and ineffective events in our data set, along with their numerous similarities and the limited number of available variables. We show that even in such conditions adequate hit rates can be achieved with these models.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We present the radio properties of 66 spectroscopically confirmed normal star-forming galaxies (SFGs) at 4.4 &lt; <jats:italic>z</jats:italic> &lt; 5.9 in the COSMOS field that were [C <jats:sc>ii</jats:sc>]-detected in the Atacama Large Millimeter/submillimeter Array Large Program to INvestigate [C <jats:sc>ii</jats:sc>] at Early times (ALPINE). We separate these galaxies (“C <jats:sc>ii</jats:sc>-detected-all”) into lower-redshift (“C <jats:sc>ii</jats:sc>-detected-lz”; 〈<jats:italic>z</jats:italic>〉 = 4.5) and higher-redshift (“C <jats:sc>ii</jats:sc>-detected-hz”; 〈<jats:italic>z</jats:italic>〉 = 5.6) subsamples, and stack multiwavelength imaging for each subsample from X-ray to radio bands. A radio signal is detected in the stacked 3 GHz images of the C <jats:sc>ii</jats:sc>-detected-all and lz samples at ≳3<jats:italic>σ</jats:italic>. We find that the infrared–radio correlation of our sample, quantified by <jats:italic>q</jats:italic> <jats:sub>TIR</jats:sub>, is lower than the local relation for normal SFGs at a ∼3<jats:italic>σ</jats:italic> significance level, and is instead broadly consistent with that of bright submillimeter galaxies at 2 &lt; <jats:italic>z</jats:italic> &lt; 5. Neither of these samples show evidence of dominant active galactic nucleus activity in their stacked spectral energy distributions (SEDs), UV spectra, or stacked X-ray images. Although we cannot rule out the possible effects of the assumed spectral index and applied infrared SED templates in causing these differences, at least partially, the lower obscured fraction of star formation than at lower redshift can alleviate the tension between our stacked <jats:italic>q</jats:italic> <jats:sub>TIR</jats:sub>s and those of local normal SFGs. It is possible that the dust buildup, which primarily governs the infrared emission, in addition to older stellar populations, has not had enough time to occur fully in these galaxies, whereas the radio emission can respond on a more rapid timescale. Therefore, we might expect a lower <jats:italic>q</jats:italic> <jats:sub>TIR</jats:sub> to be a general property of high-redshift SFGs.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Using stellar population synthesis models to infer star formation histories (SFHs), we analyze photometry and spectroscopy of a large sample of quiescent galaxies that are members of Sunyaev–Zel’dovich (SZ)-selected galaxy clusters across a wide range of redshifts. We calculate stellar masses and mass-weighted ages for 837 quiescent cluster members at 0.3 &lt; <jats:italic>z</jats:italic> &lt; 1.4 using rest-frame optical spectra and the Python-based <jats:monospace>Prospector</jats:monospace> framework, from 61 clusters in the SPT-GMOS Spectroscopic Survey (0.3 &lt; <jats:italic>z</jats:italic> &lt; 0.9) and three clusters in the SPT Hi-z cluster sample (1.25 &lt; <jats:italic>z</jats:italic> &lt; 1.4). We analyze spectra of subpopulations divided into bins of redshift, stellar mass, cluster mass, and velocity-radius phase-space location, as well as by creating composite spectra of quiescent member galaxies. We find that quiescent galaxies in our data set sample a diversity of SFHs, with a median formation redshift (corresponding to the lookback time from the redshift of observation to when a galaxy forms 50% of its mass, <jats:italic>t</jats:italic> <jats:sub>50</jats:sub>) of <jats:italic>z</jats:italic> = 2.8 ± 0.5, which is similar to or marginally higher than that of massive quiescent field and cluster galaxy studies. We also report median age–stellar mass relations for the full sample (age of the universe at <jats:italic>t</jats:italic> <jats:sub>50</jats:sub> (Gyr) = 2.52 (±0.04)–1.66 (±0.12) log<jats:sub>10</jats:sub>(<jats:italic>M</jats:italic>/10<jats:sup>11</jats:sup> <jats:italic>M</jats:italic> <jats:sub>⊙</jats:sub>)) and recover downsizing trends across stellar mass; we find that massive galaxies in our cluster sample form on aggregate ∼0.75 Gyr earlier than lower-mass galaxies. We also find marginally steeper age–mass relations at high redshifts, and report a bigger difference in formation redshifts across stellar mass for fixed environment, relative to formation redshifts across environment for fixed stellar mass.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>When studying transiting exoplanets it is common to assume a spherical planet shape. However, short rotational periods can cause a planet to bulge at its equator, as is the case with Saturn, whose equatorial radius is almost 10% larger than its polar radius. As a new generation of instruments comes online, it is important to continually assess the underlying assumptions of models to ensure robust and accurate inferences. We analyze bulk samples of known transiting planets and calculate their expected signal strength if they were to be oblate. We find that for noise levels below 100 ppm, as many as 100 planets could have detectable oblateness. We also investigate the effects of fitting spherical planet models to synthetic oblate lightcurves. We find that this biases the retrieved parameters by several standard deviations for oblateness values &gt;0.1–0.2. When attempting to fit an oblateness model to both spherical and oblate lightcurves, we find that the sensitivity of such fits is correlated with both the signal-to-noise ratio as well as the time sampling of the data, which can mask the oblateness signal. For typical values of these quantities for Kepler observations, it is difficult to rule out oblateness values less than ∼0.25. This results in an accuracy wall of 10%–15% for the density of planets which may be oblate. Finally, we find that a precessing oblate planet has the ability to mimic the signature of a long-period companion via transit-timing variations, inducing offsets at the level of tens of seconds.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We present a technique to identify spectrophotometrically variable L7−T3 brown dwarfs with single-epoch, low-resolution, near-infrared SpeX spectra. We calculated spectral indices on known variable brown dwarfs and used them to select 11 index–index parameter spaces where known variables can be distinguished from the rest of the general population of brown dwarfs. We find 62 candidate variables, 12 of which show significant variability amplitude in independent photometric monitoring surveys. This technique constitutes the first formal method to identify a time-dependent effect such as variability from peculiarities in their integrated light spectra. This technique will be a useful tool to prioritize targets for future photometric and spectroscopic monitoring in the era of the James Webb Space Telescope and 30 m-class telescopes.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>Gamma-ray bursts (GRBs) are divided into short gamma-ray bursts (SGRBs) and long gamma-ray bursts (LGRBs) based on the bimodal distribution of their durations. LGRBs and SGRBs are typically characterized by different statistical characteristics. Nevertheless, there are some samples that challenge such a framework, such as GRB 060614, a long-duration burst with short-burst characteristics. Furthermore, GRBs are generally considered to be an event with no periodic or repetitive behavior, since the progenitors usually undergo destructive events, such as massive explosions or binary compact star mergers. In this work, we investigated Fermi data for possible quasiperiodic oscillations and repetitive behaviors of GRBs using timing analysis methods and report a special event GRB 201104A, which is a long-duration burst with the characteristics of an SGRB, and it exhibits a “repetitive” behavior. We propose that such a situation may arise from lensed SGRBs and attempt to verify it by Bayesian inference. In addition, we extend the spectral analysis to Bayesian inference. In spite of the existence of at least two distinct time periods with a nearly identical spectrum, there is no strong evidence that they result from a lensing GRB. Taking the gravitational-lensing scenario out of consideration, a long burst would resemble a short burst in its repetitive behavior, which presents a challenge for the current classification scheme.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>We report on a particular example of noise and data representation interacting to introduce systematic error into scientific measurements. Many instruments collect integer digitized values and apply nonlinear coding, in particular square root coding, to compress the data for transfer or downlink; this can introduce surprising systematic errors when they are decoded for analysis. Square root coding and subsequent decoding typically introduces a variable ±1 count value-dependent systematic bias in the data after reconstitution. This is significant when large numbers of measurements (e.g., image pixels) are averaged together. Using direct modeling of the probability distribution of particular coded values in the presence of instrument noise, one may apply Bayes’ theorem to construct a decoding table that reduces this error source to a very small fraction of a digitizer step; in our example, systematic error from square root coding is reduced by a factor of 20 from 0.23 to 0.012 count rms. The method is suitable both for new experiments such as the upcoming PUNCH mission, and also for post facto application to existing data sets—even if the instrument noise properties are only loosely known. Further, the method does not depend on the specifics of the coding formula, and may be applied to other forms of nonlinear coding or representation of data values.</jats:p>

<jats:title>Abstract</jats:title> <jats:p>The origin of astrophysical high-energy neutrinos detected by the IceCube Neutrino Observatory remains a mystery to be solved. In this paper we search for neutrino source candidates within the 90% containment area of 70 track-type neutrino events recorded by the IceCube Neutrino Observatory. By employing the Fermi-LAT 4FGL-DR2, the Swift-XRT 2SXPS, and the CRATES catalogs, we identify possible gamma-ray, X-ray, and flat-spectrum radio candidate sources of track-type neutrinos. We find that based on the brightness of sources and their spatial correlation with the track-type IceCube neutrinos, the constructed neutrino samples represent special populations of sources taken from the full Fermi-LAT 4FGL-DR2/Swift-XRT 2SXPS/CRATES catalogs with similar significance (2.1<jats:italic>σ</jats:italic>, 1.2<jats:italic>σ</jats:italic>, 2<jats:italic>σ</jats:italic> at 4.8 GHz, 2.1<jats:italic>σ</jats:italic> at 8.4 GHz, respectively, assuming 50% astrophysical signalness). After collecting redshifts and deriving subsamples of the CRATES catalog complete in the redshift–luminosity plane, we find that the 4.8 GHz (8.4 GHz) subsample can explain between 4% and 53% (3% and 42%) of the neutrinos (90% C.L.), when the probability of detecting a neutrino is proportional to the (<jats:italic>k</jats:italic>-corrected) radio flux. The overfluctuations indicate that a part of the sample is likely to contribute and that more sophisticated schemes in the source catalog selection are necessary to identify the neutrino sources at the 5<jats:italic>σ</jats:italic> level. Our selection serves as a starting point to further select the correct sources.</jats:p>