adsabs/FOCAL huggingface dataset:
Radio searches for single pulses and average pulse emission by folding the data based on the ephemeris derived from the X-ray observations (e.g. Israel et al. 2016) were carried out using the NC, GMRT (Surnis et al. 2016), and Arecibo (Younes et al. 2017b), on time-scales of days to a few weeks after the outbursts in 2014–2016. Neither telescope reported a detection, and the GMRT quotes upper limits of 0.4 and 0.2 mJy at 326.5 and 610 MHz, respectively, assuming a 10 per cent duty cycle and an 8σ detection threshold. The Arecibo observations were at 6.7 and 1.4 GHz and they report upper limits of 14 and 7 μJy, respectively, having used a 10σ threshold and a 20 per cent duty cycle. However, regular monitoring is supported by the most recent detection of just three pulses with CHIME (Good & CHIME/FRB Collaboration 2020) and the subsequent detection of single pulses and average pulse emission with FAST (Zhu, Wang & Zhou 2020), which also appears to have been transient in nature. It is also unclear how long it takes before the radio emission turns on in these systems. Sometimes it is relatively rapid (e.g. Levin et al. 2019) and other times it can be quite some time after the X-ray outbursts (see Kaspi & Beloborodov 2017, for more details) and can apparently also vary for a given source too. Usually, when a magnetar turns on in the radio, it emits radio pulses during most rotations and stays on, with some significant variability in flux density and pulse shape, over a time-scale of months to years. In the case of SGR J1935+2154, the Kirsten et al. (2020a) campaign lasted for 2 months with a total observing time of 522 h, while our campaign lasted for 1.5 months for a total integration time of ∼110 h. Between these two overlapping campaigns, only two radio pulses were seen by Kirsten et al. (2020a). These results along with the the very recent detection of bright radio single pulses and pulsed radio emission from the magnetar (Good & CHIME/FRB Collaboration 2020; Zhu et al. 2020) suggest that the change in the magnetosphere configuration in SGR J1935+2154 to enable pulsed radio emission might be more gradual or sporadic than other magnetars like XTE J1810–197 and Swift J1818.0–1607 where bright radio pulses were seen in the immediate aftermath of the X-ray bursting behaviour. A possible change in the magnetosphere is also supported by X-ray pulsar variations (Younes et al. 2020b). This diversity of emission characteristics emphasizes the need to regularly monitor magnetars in their active states.
Citation: Kaspi & Beloborodov 2017
Citation function: Motivation; Motivation
Two additional interesting sources for a comparison are the radio galaxies M 87 (z = 0.0044) and 3C 84 (also called NGC 1275, z = 0.0176). Both sources have a viewing angle similar to NGC 3894: 15°  θ   25° (Mertens et al. 2016) and θ   18° (Giovannini et al. 2018), respectively. The velocities of the jet components are about 0.2c in 3C 84 (Suzuki et al. 2012) and in the inner part of M 87 (Mertens et al. 2016), similar to what we find for NGC 3894. The three sources have a comparable photon index (Γ ∼ 2.1). Although it is less distant and more extended (∼100 kpc), M 87 shows a γ-ray luminosity of 6−7 × 1041 erg s−1, similar to NGC 3894. Different is the case of 3C 84, which has two-sided compact (parsec scale) jets and a distance similar to NGC 3894, but it presents a γ-ray luminosity more than 200 times higher (2 × 1044 erg s−1). Unlike NGC 3894, for which no observations with Cherenkov telescopes have been performed, M 87 and 3C 84 are also detected at very high energy (VHE, E > 100 GeV; Aharonian et al. 2006; Aleksić et al. 2012). In particular, at VHE, M 87 displayed strong variability on timescales as short as one day, but no unique signature of the region responsible for the VHE flares has been identified (Abramowski et al. 2012). Despite the long-term monitoring of M 87 during 2012−2015 in a low-activity state, the production site of γ-rays remains unclear (MAGIC Collaboration 2020). However, the correlation observed between the radio and X-ray activities is a strong indication that most often the emitting region is close to the core in this source. In the case of 3C 84, several works on radio, X-ray, and γ-ray variability suggest that short-term and long-term variability may be produced in different regions of the source. In particular, short-term variability seems related to the injection of fresh particles that are accelerated in a shock in the core region, whereas long-term variability is more likely connected with the jet structure (e.g., Fukazawa et al. 2016; Hodgson et al. 2018). Similarly to M 87 and 3C 84, long-term radio and X-ray monitoring of NGC 3894 may provide important information about the origin of the γ-ray emission.
Citation: Aharonian et al. 2006
Citation function: Background
In comparison with studies focused on other T Tauri systems, the period analysis of the Hα lines for this target often do not exhibit a single and highly significant peak. As the Hα line is expected to form not only at the accretion spot, but also in the accretion funnel and in the stellar winds, the variability of this line is also influenced by the variations of the circumstellar environment. However, the rotation period might appear with varying strengths in the periodograms. It is instructive to compare our findings with similar analyses of individual targets. In the LkCa 15 system, the strength of the emission at the line center is modulated by stellar rotation, and this effect is clearly displayed in the periodogram (Alencar et al. 2018). On the other hand, the inverse P Cygni profile of the Hα line of the HQ Tau system displays modulation on the timescale of the stellar rotation not only in the line center, but all the way to the red wing (Pouilly et al. 2020). Another interesting system to mention is V2129 Oph. When analyzing this target, Sousa et al. (2021) compared their results with the periodograms for the same system as was analyzed by Alencar et al. (2012), and they found some differences on timescales of a decade, similarly to our results. Sousa et al. (2021) discussed a few possible explanations for the observed phenomena, such as variations in the magnetic field strength, which would result in variations in the magnetospheric truncation radius, or latitudinal differential rotation, or a more complex magnetic structure with two major funnel flows originating at different radii in the inner disk. However, in the case of V2129 Oph, a periodicity longer than the stellar rotation period is present at the line center for a time of almost a decade. The likely cause of the periodicity is a structure that is present beyond the corotation radius that is stable for almost a decade. In the case of CR Cha, the rotation period has been stable for decades, but the line profiles (and the photometry as well) also vary with longer periods, likely because of variations in the circumstellar environment.
Citation: Alencar et al. 2018
Citation function: Similarities
Observations of the polarized dust emission of nine low-mass protostars at 0.87 mm were obtained using the SMA (Projects 2013A-S034 and 2013B-S027, PI: A. Maury) in the compact and subcompact configuration. To increase our statistics, we also included SMA observations from three additional sources from Perseus (NGC 1333 IRAS4A and IRAS4B) and Ophiuchus (IRAS16293) observed in 2004 and 2006 (Projects 2004-142 and 2006-09-A026, PI: R. Rao; Project 2005-09-S061, PI: D.P. Marrone). The observations of NGC 1333 IRAS4A and IRAS16293 are presented in Girart et al. (2006) and Rao et al. (2009), respectively. Marrone (2006) and Marrone & Rao (2008) provide a detailed description of the SMA polarimeter system, but we provide a few details on the SMA and the polarization design below. The SMA has eight antennas. Each optical path is equipped with a quarter-wave plate (QWP), an optical element that adds a 90° phase delay between orthogonal linear polarizations and is used to convert the linear into circular polarization. The antennas are switched between polarizations (QWP are rotated at various angles) in a coordinated temporal sequence to sample the various combinations of circular polarizations on each baseline. The 230, 345, and 400 band receivers are installed in all eight SMA antennas. Polarization can be measured in single-receiver polarization mode and in dual-receiver mode when two receivers with orthogonal linear polarizations are tuned simultaneously. In this dual-receiver mode, all correlations (the parallel-polarized RR and LL and the cross-polarized RL and LR; with R and L for right circular and left circular, respectively) are measured at the same time. Both polarization modes were used in our observations. This campaign was used to partly commission the dual-receiver full polarization mode for the SMA. A fraction of the data was lost during this period owing to issues with the correlator software. Frequent observations of various calibrators were interspersed to ensure that such issues were detected as early as possible to minimize data loss.
Citation: Marrone & Rao (2008)
Citation function: Background
Since the 1960s, Venus has been investigated by various flyby missions (Mariner 2, 5 and 10, Galileo, and Cassini), landers (Venera 11–14), atmospheric probes, and orbiter missions (Pioneer Venus, Venus Express, and Akatsuki), out of these, Mariner 10 had the most similar flyby trajectory to Solar Orbiter and could study magnetic field fluctuations far downtail (Lepping & Behannon 1978). Nevertheless, the nature of the high frequency plasma waves at Venus has been mainly studied by the Pioneer Venus Orbiter (PVO), as it was the only orbiter that carried a plasma wave instrument, the Orbiter Electric Field Detector (OEFD; Scarf et al. 1980b). Various types of propagation modes have been identified in different regions around the planet: 30 kHz Langmuir oscillations were present in the foreshock, 5.4 kHz Doppler-shifted electrostatic ion-acoustic waves were observed in the bow shock and appeared to be a prominent feature of the magnetotail boundary, and electromagnetic 100 Hz whistler waves were thought to be generated at the bow shock, propagating through the magnetosheath and eventually absorbed within the ionosphere (Scarf et al. 1979, 1980a; Strangeway 1991). However, the identification of these waves was not well determined as they were also suspected to be lower hybrid waves (Szegö et al. 1991), or ion acoustic waves (Strangeway & Crawford 1993; Huba 1993). This ambiguity was a direct consequence of the absence of a wave magnetic field sensor on-board PVO and the limited frequency coverage of the OEFD instrument, that had only a 4 channel electric field receiver (E field wave power at 100 Hz, 730 Hz, 5.4 kHz, 30 kHz). Furthermore, after more than forty years long search for lightning on Venus, results obtained by the different spacecraft missions are still inconclusive. The most compelling indications of some kind of atmospheric electrical activity at Venus appear to be the Venera landers’ detections of electromagnetic pulses at frequencies from 10 to 80 kHz (Ksanfomaliti 1980). Their origin is questionable (Lorenz 2018); they might be assigned to interferences similarly as electric pulses found by Galileo (Gurnett et al. 1991). No lightning related signals were found during the Cassini Venus flyby in spite of the fact that the same instrument detected up to 70 sferics per second during the Earth flyby in 1999 (Gurnett et al. 2001). The whistler-mode waves at frequencies near 100 Hz recorded by Pioneer Venus and Venus Express were attributed to lightening (Russell et al. 2008). Nevertheless, a variety of other explanations were offered for these electromagnetic observations (Lorenz 2018). Up to now, not a single image from any spacecraft has been able to confirm the existence of lightning including an extensive a 5-years long search for lightning by the Akatsuki Venus orbiter (Takahashi et al. 2018). However, the modeling did not exclude electrical breakdown in the Venusian atmosphere and transient luminous events were forecasted to occur on Venus (Riousset et al. 2020).
Citation: Strangeway & Crawford 1993
Citation function: Compare/Contrast; Compare/Contrast; Compare/Contrast
The high temperatures of these filaments result in the matter being highly ionised so that it absorbs and emits far-UV and soft X-ray photons. However, these WHIM filaments are of low column density and, therefore, produce a low signal intensity which makes them difficult to detect with the current instrumentation. In spite of this, the search for the missing baryons has continued and detections of extragalactic O VII and O VIII have been claimed (Nicastro et al. 2005) but they are often disputed (Kaastra et al. 2006; Williams et al. 2006; Rasmussen et al. 2007), of a single-line or low statistical significance (Nicastro et al. 2010; Bonamente et al. 2016), misidentifications of the WHIM (Nicastro et al. 2016), or they are local to the background source (Johnson et al. 2019). More recently, Nicastro et al. (2018), later updated by Nicastro (2018), reported the detection of two O VII absorption features at redshifts z = 0.3551 and z = 0.4339 along the sight-line towards blazar 1ES 1553+113 after a 1.75 Ms observation with the XMM-Newton reflection grating spectrometer. Johnson et al. (2019) conducted additional studies towards 1ES 1553+113, suggesting that the feature located at z = 0.4339 may not originate from the WHIM and is associated, rather, with the local environment of the blazar. A study by Kovács et al. (2019) quotes a 3.3σ detection of O VII towards H1821+643 from a stacked spectrum of Chandra observations with an 8 Ms total exposure. Ahoranta et al. (2020) performed spectral analysis of Chandra and XMM-Newtown observations at previously determined FUV redshifts, yielding two X-ray line candidates of Ne IX[[Inline38]He and O VIII Lyα at a combined significance of 3.9σ. In spite of the large observational efforts, only these few marginal detections have been achieved so far. The small equivalent widths of ≈0.07−0.42 eV (Branchini et al. 2009; Nicastro et al. 2018) from WHIM absorption features mean that high signal-to-noise ratio observations are required for their detection. This calls for an observatory with a large effective area, high energy resolution, and a low energy threshold in the soft X-ray energy band.
Citation: Nicastro et al. 2016
Citation function: Background; Background; Background
Mid-infrared and millimeter polarimetric observation has so far been considered as the best method to probe the magnetic field. This is because if aspherical grains in disks become aligned with the magnetic field as is the case in the interstellar medium (ISM), the polarization vector arising from thermal emission of the aligned grains becomes perpendicular to the local magnetic field line (Cho & Lazarian 2007, henceforth CL07, Matsakos et al. 2016; Yang et al. 2016b; Bertrang et al. 2017). At mid-infrared wavelengths, Li et al. (2016) performed a polarimetric imaging observation of AB Aur using CanariCam. As a result, they detected a centrosymmetric polarization pattern, and the degree of polarization was as high as 1.5% at large radii. At millimeter wavelengths, polarimetric observations of disks have been performed (e.g., Hughes et al. 2009, 2013; Rao et al. 2014; Stephens et al. 2014; Cox et al. 2015; Kataoka et al. 2016b). Polarized emission from a circumstellar disk has been detected in the Class 0 phase (Rao et al. 2014; Cox et al. 2015). More evolved disks do not show a degree of linear polarization larger than 0.5% (Hughes et al. 2009, 2013). It should be mentioned that Stephens et al. (2014) detected polarized flux from HL Tau, which is classified as a Class I-II, with an average degree of linear polarization of 0.9%. More recently, Kataoka et al. (2016b) reported the first submillimeter polarization observation of a disk obtained with ALMA, and they clearly detected polarized flux from HD 142527. The polarization fraction at a peak position of polarized intensity was 3.26%, and the maximum polarization fraction was as high as 13.9%. The disk reveals radial polarization vectors; however, they flip by 90° in its northeast and northwest regions. In addition, the detected polarization fraction is much larger than the stringent limit set by Hughes et al. (2009, 2013), and further polarimetric observations by ALMA will reconcile this discrepancy.
Citation: Hughes et al.; 2013
Citation function: Differences; Future Work
Citation: Hughes et al.; 2013
Citation function: Background
In Sect. 4.2 we see that the Q.S. decreases with both the stellar mass and the local density. The Q.S. provides us with a glimpse of quenching in the past. It significantly decreases with stellar mass at the low-mass end (similarly for the cluster candidates and the field), showing that more massive galaxies are at a much later stage of quenching. This is consistent with the downsizing scenario (e.g. Cowie et al. 1996; Cattaneo et al. 2008; Webb et al. 2020) that massive galaxies form and quench earlier, and hence they are at a later, more advanced stage of evolution compared to low-mass galaxies. The mass dependence of the quenching stage is strongly affected by the local density. The trend is only significant in high-density environments. For sparse environments, the errorbars are too large for us to say anything. The scenario is consistent with Hatch et al. (2011), where faster evolution in protoclusters is found. This can also be due to the migration of galaxies from the low-density cluster outskirts to the high-density cluster cores where the quenching happens. The Q.S. also shows a stable decreasing trend with the local density, indicating that galaxies in denser environments (cluster cores) are at a later, more advanced stage of quenching. The earlier Q.S. of field galaxies also supports this scenario. This is consistent with the inside-out quenching in clusters, where galaxies in cluster cores quench early, while the galaxies in the outer parts quench progressively later, which is consistent with the scenario in Koyama et al. (2013) and Shimakawa et al. (2018). Another possibility is that during the in-falling process their gas will be stripped off, which directly leads to their quenching (Bekki et al. 2002). In this case the effect should be stronger for low-mass galaxies since their gas components are easier to strip. This environmental dependence is not strongly affected by the stellar mass, which supports the inside-out quenching that has an impact on low- and high-mass galaxies equally. In McNab et al. (2021) the authors use three types of transitional populations: green valley (GV) selected by rest-frame (NUV−V) and (V − J) colours; blue quiescent (BQ) selected by rest-frame (U − V) and (V − J) colours; and post-starburst (PSB) selected by galaxy spectra. They connect the quenching timescale to the transitional population fraction excess in clusters. They found that the lowest mass systems ( 1010.5 M⊙) have short quenching timescales ( 1 Gyr), which agrees with our result that low-mass galaxies are dominated by fast quenching ( 1 Gyr).
Citation: Hatch et al. (2011)
Citation function: Similarities; Similarities
A challenge with empirical methods is that with growing numbers of input parameters, it becomes prohibitive in terms of CPU time to use all of them. It can also be counterproductive to feed the machine learning tool with all of these parameters because some of them might either be too noisy or not bring any relevant information to the specific problem being tackled. Moreover, high-dimensional problems suffer from being overfit by machine learning methods (Cawley & Talbot 2010), thereby yielding high-dimensional nonoptimal solutions. This requires subselection of relevant variables from a large N-dimensional space (with N potentially close to 1000). This task itself can also be achieved using machine learning tools. Here we present, to our knowledge, the first application to astronomy of the combination of two machine learning techniques: genetic algorithms (GA; e.g., Steeb 2014) for selecting relevant features, followed by SVMs to build a decision–reward function. GAs alone have already been used in astronomy, for instance, in the study of orbits of exoplanets and the SEDs of young stellar objects (Cantó et al. 2009), the analysis of SN Ia data (Nesseris 2011), the study of star-formation and metal-enrichment histories of a resolved stellar system (Small et al. 2013), the detection of globular clusters from Hubble Space Telescope (HST) imaging (Cavuoti et al. 2014), and photometric redshift estimation (Hogan et al. 2015). At the same time, SVMs have been extensively used to solve a number of problems, such as object classification (Zhang & Zhao 2004), the identification of red variable sources (Woźniak et al. 2004), photometric redshift estimation (Wadadekar 2005), morphological classification (Huertas-Company et al. 2011), and parameter estimation for Gaia spectrophotometry (Liu et al. 2012). We note also that the combination of GA and SVM has already been used in a number of fields, such as cancer classification (e.g., Huerta et al. 2006; Albda et al. 2007), chemistry (e.g., Fatemi & Gharaghani 2007), and bankruptcy prediction (e.g., Min et al. 2006). We do not attempt here to provide the most optimized results from this combination of methods. Rather, we present a proof of concept that shows that GA and SVM yield remarkable results when combined, as opposed to using the SVM as a standalone tool.
Citation: Steeb 2014
Citation function: Uses; Uses
H2O ice on Pluto has long escaped spectroscopic detection, and based on initial New Horizons data appears to be exposed only in a number of specific locations, usually associated with red color, suggestive of water ice/tholin mix (Grundy et al. 2015; Cook et al. 2015). Nonetheless, water ice is likely to be ubiquitous in Pluto’s near subsurface, given its cosmogonical abundance, Pluto’s density, and its presence on Charon’s surface6. Absorption coefficients for pure water ice (kH2O) at sub-mm-to-cm wavelengths are discussed extensively by Mätzler (1998), who also provides several analytic formulations to estimate them as a function of frequency and temperature along with illustrative plots. We use the Mishima et al. (1983) formulation (see Appendix of Mätzler 1998). Its applicability is normally restricted to temperatures above 100 K, but Fig. 2 of Mätzler (1998) indicates the trend with temperature. Absorption coefficients extrapolated to 50 K (estimated as half the values at 100 K) are shown in Fig. 5. At 500 μm, our best estimate is kH2O = 0.25 cm-1, comparable to the above values for CH4 and N2 ices. The corresponding penetration length is therefore comparable to the diurnal skin depth but remains negligible compared to the seasonal skin depth, even for seasonal Γ = 25 MKS. According to these calculations, the seasonal layer would be probed only at a wavelength of ~4 mm and beyond. We also remark that the expression from Mishima et al. (1983) would give a penetration depth of 56 m at 2.2 cm, which is an order of magnitude larger than indicated by the laboratory measurements of Paillou et al. (2008). In addition, small concentrations of impurities can dramatically reduce the microwave transparency of water ice (e.g., Chyba et al. 1998 and references therein). Therefore, the above calculations likely indicate upper limits to the actual penetration depth of radiation in a H2O ice layer, from which we conclude that the seasonal layer is not reached at the Herschel wavelengths.
Citation: Mätzler (1998)
Citation function: Uses; Uses