adsabs/FOCAL huggingface dataset:
For variable star classification, both convolutional neural networks (CNNs; LeCun, Bengio & Hinton 2015) and recurrent neural networks (RNNs; Hochreiter & Schmidhuber 1997; Cho et al. 2014) have been shown to be competitive to the traditional RF-based methods. Naul et al. (2018) used an RNN autoencoder network to learn low-dimensional representations of period-folded light curves in an unsupervised fashion. This representation was then, in a supervised context, used as feature inputs to an RF classifier. They showed that the learned features are at least as good as, and often better than, two sets of state-of-the-art hand-crafted features (Richards et al. 2011; Kim & Bailer-Jones 2016), in terms of downstream classification accuracy. Becker et al. (2020) used an RNN for which instead of period-folding, each input light curve is grouped with a moving time-sample window of size 50 and stride 25. Although period-folding improves performance (Naul et al. 2018), Becker et al. (2020)’s time-space RNN does not require the period to be calculated, and is thus less computationally expensive in terms of preprocessing. Again, they found similar performance to an RF classifier with the Nun et al. (2015) features over three data sets, although lower accuracy was seen for many sub-classes with the OGLE data set (Table 2; see Section 3.3 for data description). More recently, Jamal & Bloom (2020) systematically benchmarked the performance of different configurations of RNN and CNN network architectures on variable star classification. Aside from other work (e.g. Aguirre, Pichara & Becker 2018; Tsang & Schultz 2019) evaluating neural network (NN) performance retrospectively on previously labelled data sets, Dékány & Grebel (2020) used an RNN classifier to identify a new sample of fundamental-mode RR Lyrae (RRab) stars. Similarly, Dékány et al. (2019) found Classical and Type II Cepheids with a CNN classifier, also using the VISTA Variables in the Via Lactea (VVV) survey (Minniti et al. 2010) and using period-folded light curves.
Citation: Naul et al. (2018)
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We determine the spectroscopic parameters by using a relatively high S/N (∼ 65 per pixel) spectrum taken without the iodine cell at TCES-TLS. As a first step, we applied the empirical software SpecMatch-Emp code (Hirano et al. 2018) that compares well-characterized FGKM stars observed with Keck/HIRES to the data, in our case, the TCES-TLS spectra with R = 67 000. We obtain a stellar effective temperature, Teff = 5804 ± 110 K, a stellar radius, R*  = 2.078 ± 0.180R⊙, and the abundance of the key species iron relative to hydrogen, [Fe/H] = 0.29 ± 0.09 (dex) as mentioned in Table 4. To perform a more detailed model, we used the spectral analysis package SME (Spectroscopy Made Easy; Valenti & Piskunov 1996; Piskunov & Valenti 2017) version 5.22. This code is based on grids of recalculated stellar atmospheric models that calculates a synthetic spectrum. The best-fitted stellar parameters are derived through a χ2 −minimization iteration that compares the synthetic and observed spectra for a given set of parameters. The spectra was synthesised based on the atomic and molecular line data from VALD (Ryabchikova et al. 2015) and the Atlas12 (Kurucz 2013) atmosphere grids. We refer to Fridlund et al. (2017) and Persson et al. (2018) for a more detailed description of the modelling. Briefly, we chose to model spectral features sensitive to different photospheric parameters: Teff from the Hα line wings, and the surface gravity, log g*, from the Ca i λλ6102, 6122, and 6162 triplet, and the λ6439 line. The abundances of iron and calcium, and the projected stellar rotational velocity, v sin i were fitted from narrow, unblended lines between 6100 and 6500 Å. We derive the vsin i as 7.0 ± 0.5 km s−1. We fixed the micro- and macro-turbulent velocities, Vmic and Vmac, to 1 and 3 km s−1 (Bruntt et al. 2010; Doyle et al. 2014), respectively. The results from SME are in good agreement within the uncertainties with SpecMatch-Emp (Table 4). The SME derived stellar parameters are supplied as priors in the global modelling. The finally adopted stellar parameters obtained through global modelling of the RV and transit data are indicated in the last row of Table 4 in bold font. For more details on the global modelling, see Section 3.3.2. One thing to note here is that we find the TOI-1789 is a late F-type star with our spectral analysis. Nevertheless, SIMBAD reported it as ‘K0’ spectral type.
Citation: Valenti & Piskunov 1996
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The gravitational collapse of the G345.88-1.10 hub provides the means for rapid mass provision to the centre, along with non-steady accretion flows which might open the cavity on short timescales through an accretion burst. This can be the result of e.g. jet precession (Rosen & Krumholz 2020) and opening of the jet itself (Cesaroni et al. 2018). The modelling by Cesaroni et al. (2018) indicates that the jet opening angle can increase to values as high as 40–50°, but it should also be noted that this is model dependent. The simulations by Rosen & Krumholz (2020) indicate that a jet precession can be very rapid at the early stages of high-mass star formation with rapid angle changes that on average reach 40° kyr−1 with apparent peaks as high as 250° kyr−1. However, it should be noted that the opening of the cavities by an accretion burst also faces the issue that this is generally associated with a strong increase of the core brightness in the far-infrared (e.g. Stecklum et al. 2021; Hunter et al. 2021), which is not seen in G345.88-1.10. It could be that, after an accretion burst has occurred, there is a time delay between the dimming of the core and the dimming of the cavity. Such a time delay would be of the order of the jet’s crossing time of the cavity, i.e. ≲1000 yr. We could therefore be catching G345.88-1.10 right at that moment where the cavity is still bright but the core has dimmed. Although this would be a noteworthy coincidence, it can fit with the cooling timescale we estimate for the massive H1 fragment which should be lower than 20 yr and can be as low as a couple of days or months, see Appendix H. These timescales also seem to be in agreement with surveys of continuum variability, at least in low-mass star forming cores that typically find very rapid changes on the timescales of weeks to several years (e.g. Johnstone et al. 2013; Mairs et al. 2017; Lee et al. 2021). Because of these very short cooling timescales, it is even possible that multiple accretion bursts spread over few 10-100 yr are at the origin of the heated cavities. In Appendix H, we also estimated the cooling timescale in the cavities for which we find values between 1.7 × 103 and 2.7 × 104 yr which is significantly longer than for the core. Furthermore, the lower end of this estimated timescale is of the same order of magnitude as the crossing timescale for the jet in the cavities. This might explain why the full cavity is bright instead of only several subregions in the cavity.
Citation: Stecklum et al. 2021
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The evolution of colour or the spectral index, α, (F(ν) ∝ ν−α where ν is the radiation frequency and F(ν) is the flux density provides an insight into the particle distribution giving rise to the observed flux density and its variability. In particular, at the synchrotron frequencies, within the simplest scenario of single-zone emission models with homogeneous magnetic field distributions, clear patterns between the spectral index and the total intensity are predicted, i.e. a ‘spectral hysteresis’, depending on the relative lengths of the radiative cooling time-scale and the escape time-scale of the accelerated particles from the emission zone (e.g. Kirk, Rieger & Mastichiadis 1998). A significant fraction of long-term multiband flux monitoring studies have revealed bluer-when-brighter trends for BL Lac objects but frequently redder-when-brighter trends for FSRQs (Gu et al. 2006; Osterman Meyer et al. 2009; Hao et al. 2010; Rani et al. 2010; Ikejiri et al. 2011; Bonning et al. 2012; Sandrinelli, Covino & Treves 2014; Li et al. 2018; Meng et al. 2018; Gupta et al. 2019) while ‘achromatic’ flux variability (no colour evolution, Stalin et al. 2006; Bonning et al. 2012; Gaur et al. 2019), and erratic patterns (Wierzcholska et al. 2015) have also been reported. It has been argued that particles accelerated to higher energies are injected at the emission zone before being cooled radiatively in BL Lac sources leading to their overall SEDs being bluer-when-brighter; however, the ‘redder’ and more variable jet-component can overwhelm the ‘bluer’ contribution from the accretion disc, leading to redder-when-brighter trends for FSRQ type sources (Gu et al. 2006). Achromatic variability is often ascribed to changes in the Doppler boosting factor (δ) as each frequency notes the same special relativistic multiplication of flux (Gaur et al. 2012). However, erratic colour trends together with the opposite behaviours, i.e. redder-when-brighter changes for BL Lacs (Gu & Ai 2011) and bluer-when-brighter trends for FSRQs (Wu et al. 2011), indicate that more complex scenarios, presumably involving the dominance of the relative contributions of the Doppler boosted jet emission component and the accretion disc component, respectively, are particularly relevant for blazars with peak synchrotron frequencies in the range of 1013–15 Hz (low-frequency peaked blazars; Isler et al. 2017; Gopal-Krishna, Britzen & Wiita 2019).
Citation: Bonning et al. 2012
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The high-frequency break often found in interplanetary magnetic field power density spectra separates the fluid from the kinetic regime of fluctuations. This break is located around scales which are typical of protons kinetics like the proton inertial length λi = c/ωp and the proton Larmor radius λL = vth/Ωp, where ωp is the local plasma frequency while Ωp is the local gyro-frequency, with vth and c the thermal speed and the speed of light, respectively. Several authors tried to reproduce the location of the frequency break according to various models (Leamon et al. 1998; Perri, Carbone & Veltri 2010; Bourouaine et al. 2012) but Markovskii, Vasquez & Smith (2008) showed that none of the available model could predict a value for the frequency break in good agreement with the observations. Only recently, Bruno & Trenchi (2014), studying the radial behaviour of the frequency break location within the expanding high-speed wind, were able to conclude that the resonant condition for outward parallel propagating Alfv$\acute{\textrm{e}}$n/ion-cyclotron waves (ICWs) was the mechanism able to provide the best agreement with the observations. This result, although not expected on the basis of anisotropy predictions by any turbulent cascade (Chen et al. 2014), gave new relevance to the ion-cyclotron resonance mechanism in the frame of turbulence collisionless heating without cancelling the role of other possible mechanisms that might be at work as well. Leamon et al. (1999) proposed Landau damping of obliquely propagating kinetic Alfv$\acute{\textrm{e}}$n waves (KAWs) resulting in a frequency break corresponding to the scale of the Larmor radius λL; for Dmitruk, Matthaeus & Seenu (2004) 2D turbulence dissipation through turbulence reconnection process and generation of current sheets of the order of the ion inertial length λi enhances the role of this scale, which is the most relevant one also in the framework of incompressible Hall magnetohydrodynamics used by Galtier (2006) to explain the break.
Citation: Perri, Carbone & Veltri 2010
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Because of the high-energy extent of their emission, their large cosmological distances, and their fast variabilities, gamma-ray bursts (GRBs) have been deemed as the most promising sources for searching for LIV-induced vacuum dispersion (Amelino-Camelia et al. 1998; Jacob & Piran 2007; Amelino-Camelia & Smolin 2009; Amelino-Camelia 2013; Wei et al. 2016). To date, various limits on LIV have been obtained by studying the dispersion of light in observations of individual GRBs or a large sample of GRBs (Amelino-Camelia et al. 1998; Coleman & Glashow 1999; Schaefer 1999; Boggs et al. 2004; Pavlopoulos 2005; Kahniashvili et al. 2006; Jacob & Piran 2008; Abdo et al. 2009a, 2009b; Xiao & Ma 2009; Shao et al. 2010; Chang et al. 2012; Nemiroff et al. 2012; Kostelecký & Mewes 2013; Vasileiou et al. 2013; Zhang & Ma 2015; Xu & Ma 2016, see also Kostelecký & Russell 2011; Liberati 2013 and summary constraints for LIV therein). Although these limits on LIV have reached high precision, most were obtained by relying on the rough time lag of a single highest-energy photon. Performing a search for LIV using the true time lags of high-quality and high-energy light curves in different energy multi-photon bands is therefore crucial. Furthermore, the method of the arrival time difference used for testing LIV is tempered by our ignorance concerning the intrinsic time delay that depends on the unknown emission mechanism of GRBs. Most previous studies concentrated on the time delay induced by LIV, while neglecting the intrinsic time delay, which would impact the reliability of the resulting constraints on LIV. Most recently, however, Wei et al. (2017a, 2017b) provided some solutions to disentangle the intrinsic time delay problem. They first proposed that only GRB 160625B, which so far is the only burst with a well-defined transition from positive to negative spectral lags,3

3
The spectral lag is defined as the arrival time difference between high- and low-energy photons and is considered to be positive when high-energy photons precede low-energy photons.
 provides a good opportunity to distinguish the possible LIV effect from any source-intrinsic time delay in the emission of photons of different energy bands. By fitting the true multi-photon spectral lag data of GRB 160625B, they obtained both a reasonable formulation of the intrinsic energy-dependent time delay and robust limits on the QG energy scale and the Lorentz-violating coefficients of the Standard-Model Extension.
Citation: Kostelecký & Russell 2011
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The opacity at the radiative–convective boundary controls the atmosphere’s cooling rate, L∝1/κ, and as such is key to understanding the evolution of super-Earth atmospheres. As discussed in Section 2, we use a constant value of the atmosphere’s opacity, κ = 0.1 cm2g−1, throughout this work. This choice is based on the typical order of magnitude value expected for H/He-dominated atmospheres (e.g. Freedman et al. 2008). In reality, the atmospheric opacity depends on many factors which are likely to vary over the course of super-Earth atmospheric evolution. More complex opacity models can include a power law increase in opacity with density (e.g. Gupta & Schlichting 2019), and power law increases with temperature and atmospheric metallicity in addition to density (e.g. Lee & Chiang 2015). We found that implementing an opacity dependence on density did not have a major effect on our final atmospheric masses. The strongest effect, on the critical radiative convective boundary to which a planet cools during spontaneous mass-loss, is only logarithmic (equation 18). However, if the overall composition of the atmosphere changes significantly as the super-Earths lose atmospheric mass, an increase in opacity with metallicity over time could affect our results. To test whether we expect the hydrodynamic outflow to significantly fractionate the atmosphere, thereby increasing the metallicity of the remnant atmosphere, we compute the cross-over mass, $\mu _\mathrm{c} = \mu + k_\mathrm{B} T_\mathrm{eq} \dot{M}/(4 \pi b \mu G M_\mathrm{c})$, where b is the binary diffusion coefficient between the two species. This is the molecular weight above which a species cannot be liberated from the planet by the hydrodynamic wind, as the drag forces cannot overcome gravity (Hunten, Pepin & Walker 1987). Using b ∼ 5 × 1017T0.75 cm−1s−1, a value typical of the binary diffusion coefficients of common secondary species in hydrogen gas (Zahnle & Kasting 1986), we find – given our mass-loss rates – the smallest value for the cross-over mass for the planets considered in this paper is about μc ∼ 103 amu. This is much larger than any potential heavy species in these atmospheres. We therefore conclude that secondary species are efficiently carried away by the outflow and that the atmosphere does not become significantly enhanced in heavy elements due to the wind itself for the planets considered in this paper.
Citation: Gupta & Schlichting 2019
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HD 100546 is one of the closest very well studied Herbig Be stars (d = 110 ± 4 pc, Gaia Collaboration 2018). It shows clear evidence of a large flared disk, and based on images obtained with the Hubble Space Telescope (HST) and ground-based high-contrast images, an elliptical structure was detected that extends up to 350–380 au (Augereau et al. 2001). Furthermore, multiple-armed spiral patterns were identified as well (Grady et al. 2001; Ardila et al. 2007; Boccaletti et al. 2013; Avenhaus et al. 2014). The disk position angle measurements found in the literature range from ~ 130 to 160° (Grady et al. 2001; Pantin et al. 2000; Ardila et al. 2007; Panić et al. 2014; Augereau et al. 2001; Avenhaus et al. 2014), and the inclination of the disk is smaller than 50° (Avenhaus et al. 2014). An inner dust disk extending from ~0.2 to ~ 1−4 au was resolved using near-IR interferometry (Benisty et al. 2010; Tatulli et al. 2011; Mulders et al. 2013; Panić et al. 2014). The (pre-)transitional nature of HD 100546 was initially proposed by Bouwman et al. (2003) based on a spectral energy distribution (SED) analysis. The presence of a gap extending up to 10–15 au has been confirmed by mid-IR interferometry (Liu et al. 2003; Panić et al. 2014), spectroscopy in the UV and near-IR (Grady et al. 2005; Brittain et al. 2009; van der Plas et al. 2009), and high-resolution polarimetric imaging in the optical and near-IR (Avenhaus et al. 2014; Quanz et al. 2015; Garufi et al. 2016; Follette et al. 2017). Recent ALMA observations reveal an asymmetric ring between ~ 20−40 au with largely optically thin dust emission (Pineda et al. 2019). A central compact emission is also detected, which arises from the inner central disk, which given its mass and the accretion rate onto the star, must be replenished with material from the outer disk (Pineda et al. 2019). Miley et al. (2019) presented the first detection of C18 O in this disk, which spatially coincides with the spiral arms, and derived a lower-limit on the total gas mass (around 1% of the stellar mass) and a gas-to-dust mass ratio in the disk of ~ 20 assuming interstellar medium (ISM) abundances of C18O relative to H2. HD 100546 is also one of the few cases where protoplanet candidates have been suggested (e.g. Quanz et al. 2015; Currie et al. 2015), although this is still being debated (e.g. Follette et al. 2017; Rameau et al. 2017; Pérez et al. 2020). Recently, Pérez et al. (2020) detected a compact 1.3 mm continuum dust emission source that lies in the middle of the HD 100546 cavity (0.051′′ from the central star). This is compatible with circumplanetary disk emission.
Citation: Mulders et al. 2013
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In summary, our constraints on the elliptical galaxy structure in the context of previous observations and simulations are consistent with the following formation and evolution scenario for massive elliptical galaxies. The first stage of the formation of elliptical galaxies is through dissipational processes at z ≳ 2, when most of their present day stars are formed. The dissipation leads to contraction in the dark matter halo and the resultant total density profile observed in cosmological numerical simulations is steeper than the isothermal case (e.g. Gnedin et al. 2004; Naab et al. 2007; Duffy et al. 2010). After z ≈ 2, the growth of the elliptical galaxies is dominated by gas-poor dissipation-less mergers, explaining their growth in size without the addition of younger stellar populations (e.g. Newman et al. 2012; Nipoti et al. 2012). This growth mechanisms is consistent with the Reff–fdm correlation observed in our sample. Multiple dissipation-less mergers decrease the total density profile of the galaxies to bring it close to isothermal, and increase the half-mass radius and the central dark matter fraction with decreasing redshift (Tortora et al. 2014). Furthermore, AGN feedback expands back the contracted dark matter haloes (Martizzi, Teyssier & Moore 2013; Peirani et al. 2019), which is supported by the slope of our observed $\gamma ^{\rm LD}_{[0.4,\ 4]R_{\rm eff}}$–$f_{\rm dm}^{\rm 3D}$ distribution. Dynamical heating from accretion may also play a role in expanding the dark matter haloes in addition to the AGN feedback, however we do not find any indication either in favour or against the presence of dynamical heating in our sample. Gas-rich dissipational mergers can also happen at some point of the galaxies’ growth history. However, the small intrinsic scatter in the halo response parameter (σν ≲ 0.1) around the mean μν ∼ 0 in our sample, and the ages of the stellar populations (Thomas et al. 2005), indicate that such gas-rich mergers are relatively rare, even though their contribution cannot be ruled out or confirmed conclusively given the present precision of numerical simulations and observations (see, e.g. Sonnenfeld et al. 2014; Remus et al. 2017; Xu et al. 2017, for discussion).
Citation: Duffy et al. 2010
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A relation between the photon index and the Eddington ratio has been reported by several authors over the past two decades (e.g. Brandt, Mathur & Elvis 1997; Shemmer et al. 2006, 2008; Risaliti, Young & Elvis 2009; Brightman et al. 2013, 2016; Fanali et al. 2013; Kawamuro et al. 2016), which have shown that, for increasing λEdd, the X-ray continuum tend to be steeper. Most of these works have found that the correlation
(7)
\begin{equation*}
\Gamma =\psi \log \lambda _{\rm Edd}+ \omega
\end{equation*}
has a slope ψ ∼ 0.3 (e.g. Shemmer et al. 2008; Brightman et al. 2013), while a steeper slope (ψ ≃ 0.6) was reported by Risaliti et al. (2009), who studied SDSS quasars with archival XMM–Newton observations. More recently, Trakhtenbrot et al. (2017), using BASS, found instead a significantly weaker and flatter (ψ ≃ 0.15) correlation when using Γ obtained by considering complex spectral models (see Ricci et al. 2017a for details). Interestingly, when using Γ obtained by fitting the spectra of unobscured AGNs with a simple power law model in the 2–10 keV range, Trakhtenbrot et al. (2017) found a slope similar (ϕ = 0.30 ± 0.09) to that reported by previous studies. The existence of a relation between Γ and λEdd has been confirmed by repeated observations of individual sources, which have shown that the photon index increases with the flux (e.g. Perola et al. 1986; Matsuoka et al. 1990; Lamer et al. 2003; Sobolewska & Papadakis 2009). Interestingly, Sobolewska & Papadakis (2009) found that ψ differs from object to object, varying from ≃ 0.10 to ≃ 0.30, and that the slope for the average spectral slope versus the average Eddington ratio is ψ = 0.08 ± 0.02. This slope is consistent with that found for BASS by Trakhtenbrot et al. (2017), and with the value reported by Ricci et al. (2013; ψ = 0.12 ± 0.04) for a sample of 36 nearby AGNs, considering the average Γ and λEdd. The difference between the slopes found by the works reported above is likely related to the approach used for the spectral fitting (i.e. a simple power-law model or more complex models), to the energy band, and to the sample used.
Citation: Ricci et al. 2017a
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