adsabs/FOCAL huggingface dataset:
Similar to Chen et al. (2017), we also follow Li & Draine (2001a) to derive upper limits on the abundance of the graphene C24 in the Galactic cirrus and in the diffuse ISM towards l = 44°20′, b = −0°20′ based on comparison of the observed IR emission with the calculated emission spectrum of C24. For the Galactic cirrus, the average emission per H has been measured by COBE/DIRBE (Arendt et al. 1998), COBE/FIRAS (Finkbeiner, Davis & Schlegel 1999), and Planck (Planck Collaboration XVII 2014). The diffuse ISM towards l = 44°20′, b = −0°20′ has been observed by COBE/DIRBE (Hauser et al. 1998). The Mid-Infrared Spectrograph (MIRS) aboard the Infrared Telescope in Space (IRTS) has also obtained the 4.7–11.7$\, {\rm \mu m}$ spectrum for the diffuse ISM towards l = 44°20′, b = −0°20′ (Onaka et al. 1996). As shown in Fig. 5(a), even locking up 20 $\, {\rm ppm}$ of C/H – the upper limit of graphene derived from the interstellar extinction – all in the specific graphene species C24, the 6.6, 9.8, and 20 $\, {\rm \mu m}$ emission features of C24 would still be hidden by the PAH features at 6.2, 7.7, 8.6, and 11.3 $\, {\rm\, \mu m}$ and would remain undetected by Spitzer or by the Short Wavelength Spectrometer (SWS) aboard the Infrared Space Observatory (ISO). This is also true for the diffuse ISM towards l = 44°20′, b = −0°20′. As illustrated in Fig. 5(b), as much as $\sim \, 20\, {\rm ppm}$ of C/H could also be tied up in the C24 graphene while the characteristic 6.6, 9.8, and 20 $\, {\rm \mu m}$ emission features of C24 are still not strong enough to be detected by IRTS. Therefore, for both the Galactic cirrus and the line of sight towards l = 44°20′, b = −0°20′, a upper limit of C/H ≲ 20 $\, {\rm ppm}$ is imposed by the COBE/DIRBE photometric data and the IRTS spectrum. Nevertheless, the actual abundance of C24 could be much lower than 20 $\, {\rm ppm}$ since, if graphene is indeed present in the ISM, it could span a wide range of sizes and charging states.
Citation: Onaka et al. 1996
Citation function: Uses
Molecular hydrogen H2 is conventionally believed to make up 17% of the interstellar medium (ISM) by mass in the Galaxy (e.g., Draine 2011, Table 1.2, not including He), but, unlike atomic hydrogen H i (at 60% by mass), H2 is not generally detectable in the cold, diffuse conditions that predominate the volume of the ISM. In order to determine the mass and structure of interstellar H2, emission from other “trace” molecules must be observed instead. The primary tracer for H2 in current use is the J = (1−0) ground-state rotational transition of 12CO at a wavelength of 3 mm. While this tracer has become widely adopted over the years (see, e.g., Heyer et al. 1998; Dame et al. 2001) and has been often defended as a reliable large-scale tracer for molecules in the ISM, it also remains the primary such tracer in common use. There are several reasons to be concerned about this. First, the critical volume density of the 12CO (1–0) transition at low optical depths is 





 





; this means that gas at lower volume density will be less excited by collisions, thus emitting fewer photons, and may even effectively disappear from sensitivity-limited surveys. Second, in sufficient quantities to avoid the “excitation” problem, the 12CO signal is optically thick, so that direct calculation of column densities from line profile integrals is not possible. Instead, indirect methods of inferring the quantity of H2 must be used, such as the “X-factor” method (see, e.g., Bolatto et al. 2013, for a review). However, recent evidence from gamma rays and IR surveys has suggested that there are significant regions of the ISM apparently containing molecular gas that is not adequately traced by CO emission (see, e.g., Grenier et al. 2005). The “dark gas” appears not to be hidden optically thick H i (see Murray et al. 2018), and as such is most likely molecular. While several other molecular gas tracers have been studied (see, e.g., Jacob et al. 2019, on CH), these tracers may not be ideal for detecting low-density, diffuse portions of the large-scale ISM in emission owing to their high critical densities. A reliable alternative molecular tracer for diffuse gas is needed to confirm the identity of this “CO-dark” gas, as well as to provide information on its nature, kinematics, column density, and structure.
Citation: Dame et al. 2001
Citation function: Background; Compare/Contrast
Stellar rotation is known to be related to the activity level; e.g. faster rotators tend to have larger star-spot coverages (e.g. Paper I), and stronger chromospheric emissions (e.g. Stauffer et al. 1997; Douglas et al. 2014; Newton et al. 2017; Paper II) and X-ray emissions (e.g. Pizzolato et al. 2003; Mamajek & Hillenbrand 2008); thus, a correlation between rotation and variation level should also be expected. In fact, Fig. 7 shows that there exists a large scatter in variation amplitude even for stars in the same cluster. It is reasonable to connect the scatter to the stellar rotation rate diversity, considering the fact that there exist noticeable differences in rotation periods between stars of the same temperature in young open clusters (e.g. Stauffer et al. 2016). To understand further on this scenario, we provided variation amplitudes as a function of temperature in Fig. 8, wherein shown are stars with known rotation periods. For comparison purpose, we also displayed the corresponding rotation periods in the upper panels. The periods were collected from the literature (Pleiades: Hartman et al. 2010; Covey et al. 2016; Rebull et al. 2016a; Praesepe: Agüeros et al. 2011; Delorme et al. 2011; Kovács et al. 2014; Rebull et al. 2017; Hyades: Hartman et al. 2011; Armstrong et al. 2015; Douglas et al. 2016); for a few stars in Praesepe, such as EPIC 211852399 and EPIC 211875458, the periods were obtained by us based on K2 data (see Appendix A). The colour contrast in Fig. 8 denotes the Rossby number, Ro, the normalized rotation period by the convective turnover time (the convective turnover time was estimated by using the correlation reported by Wright et al. 2011; see Paper I/II for details). It is known that the open cluster members mainly locate in two rotation sequences in the rotation–colour diagram (Barnes 2003), i.e. I (interface) and C (convective) sequence, corresponding to slow and fast rotators, respectively, as shown in the top panels in Fig. 8. The figure shows a tendency that GK-type C sequence stars in Pleiades have larger variation amplitude of EWH α compared to I sequence stars of the same temperature. We found no evident difference between different rotators among M-type Pleiades stars, partially because most of them are very fast rotators that reside in activity saturation regime (when Ro ≲ 0.1; e.g. Paper II). For Praesepe/Hyades sample, almost all GK-type stars rotate slowly (e.g. Ro ∼ 0.5), located in the I sequence (those stars with blue colours); there is no clear trend among these stars. Among M-type stars, some stars are fast rotators in C sequence (red or green colours), while others are slow rotators (in I sequence), as shown in the upper right panel of Fig. 8. Thus, there is a tendency that faster rotators have larger variation amplitude of EWH α. Unlike EWH α, TiO2n shows no clear difference among all sample stars with different rotation periods, probably due to its small intrinsic variation amplitude, which could be dominated by observational noise.
Citation: Stauffer et al. 2016
Citation function: Uses
We used the position and distance of the MCs in the FQS catalogue to describe the structure of the Milky Way in this poorly known portion of the third quadrant. In Fig. 16 we show the distribution of the clouds projected onto the Milky Way plane. At any Galactic longitude the clouds are grouped in three well-separated structures that trace the position of the spiral arms. The dispersion of the positions in each structure is given not only by the width of the arms but also by the uncertainty of the distance determination. Indeed, kinematic distances are affected by significant uncertainties due not only to the assumed Galactic rotation model but also to the unknown possible peculiar motions of the clouds themselves. In Fig. 16 we compare the positions of the clouds derived from FQS data with the expected locations of the spiral arms, adopting a log-periodic spiral form of the Galaxy (Reid et al. 2014). The pitch angle and the distance at a reference position of the three arms are taken from Xu et al. (2013) for the Local arm, Choi et al. (2014) for the Perseus arm, and Hachisuka et al. (2015) for the Outer arm. These authors used the positions of water masers derived from parallax measurements as part of the Bar and Spiral Structure Legacy (BeSSeL) survey to fit the parameters of the spiral arms. We found good agreement between the position of the FQS clouds and the modelled position of the Local and the Perseus arms, while the modelled Outer arm lies further than the observed clouds. We note that while the parameters of the Local and Perseus arms are derived by fitting about 20 water masers located in both the second and third quadrants, covering also the Galactic longitude of the FQS survey, the parameters of the Outer arm are derived from only 5 water masers, 4 of which are located in the second quadrant. Therefore it is not surprising that they might not be fully appropriate to describe the location of the Outer arm in the longitude range of the FQS survey of 220°  l   240°. In fact, an alternative model of the Outer arm from Hou & Han (2014), also shown in Fig. 16, seems in better agreement with the FQS results.
Citation: Xu et al. (2013)
Citation function: Uses; Uses; Background; Similarities
Much of the progress in PPS has come from thorough Monte Carlo simulations that generate pulsars and test whether they fulfil the criteria for detection according to geometrical factors and sensitivity issues. It is then possible to develop and optimize a model for the underlying pulsar population, which informs us about the important intrinsic neutron star parameters and distribution, enabling predictions for future surveys. Usually, PPS studies follow two simple approaches. The first one is to take a ‘snapshot’ of the Galaxy as it appears today, where no assumptions are made regarding the prior evolution of the pulsar population. Instead, this population is generated assuming various distribution functions (typically spatial distribution, spin period P and, 



E
˙


$ \dot{E} $


- or Ṗ), which are optimized to match the observations. Inspired by earlier studies from Taylor & Manchester (1977) and Lyne et al. (1985), Lorimer et al. (2006) applied the snapshot approach to the canonical3 pulsar population to determine best-fitting probability density functions in Galactocentric radius (R), luminosity (L), height with respect to the Galactic plane (z), and the period P for the currently observed population of pulsars. Alternatively, one may consider ‘evolution’ strategies where the pulsars are evolved from birth up to the present era, starting from an initial spatial distribution, and an initial period and magnetic field distribution. A fine example of the latter genre is the comprehensive study of Faucher-Giguère & Kaspi (2006), which quite successfully reproduced the properties of the main part of the radio pulsar population using a model in which the luminosity has a power-law dependence on P and Ṗ. PPS studies can be also extended to the population of neutron stars observed in other bands, such as X-rays (see for instance Popov et al. 2010) and γ-rays. Indeed, with the broad increase in γ-ray pulsar numbers, a statistical treatment of the γ-ray population in combination with deep radio surveys of the Galactic plane is now feasible. Early works on radio-loud gamma-ray pulsar populations carried out before the Fermi era include Gonthier et al. (2002), (2004), (2007a,b). With the advent of Fermi/LAT, new studies emerged (see for instance Gonthier et al. 2018; Ravi et al. 2010; Takata et al. 2011; Watters & Romani 2011; Pierbattista et al. 2012), trying to constrain the geometry and the location of the gamma-ray emission sites. Watters & Romani (2011) showed that an initial spin period of P0 = 50 ms and a birth rate of one neutron star per 59 yr were required to reproduce the observed γ-ray population. They made the prediction that after ten years of operations, Fermi should detect ∼120 young γ-ray pulsars, of which about one half would be radio-quiet. Gonthier et al. (2004) included an exponentially decaying magnetic field with a 2.8 Myr timescale and displaying a satisfactory agreement with the P−Ṗ distribution at that time. Later, more accurate magnetic field decay models were elaborated, especially for magnetars, as presented in Viganò et al. (2013).
Citation: Lyne et al. (1985)
Citation function: Background; Background
The properties of the persistent radio source associated with FRB 121102 may be constrained independently of the Faraday-rotating medium. We assume equipartition between the relativistic gas and magnetic field as is common in synchrotron sources3 (Readhead 1994). The source becomes self-absorbed at $1.5$ GHz for radius $R_{\rm per} < 0.05$ pc; this is thus the lower bound on the source size. European Very Long Baseline Interferometry (VLBI) Network observations of the source at 5 GHz set an upper bound on the source radius of Rper ≲ 0.35 pc (Marcote et al. 2017). This is consistent with the ${\approx } 30\, {{\rm per\, cent}}$ amplitude modulations observed in the source at 3 GHz (Chatterjee et al. 2017) being caused by refractive interstellar scintillation in the Milky Way interstellar medium (ISM; Walker 1998). For any radius within the allowed range (0.05  Rper/pc  0.35), we can determine the equipartition magnetic field, Beq, and the column of relativistic electrons, Nrel, using the standard expressions for synchrotron emissivity and absorption coefficients (Rybicki & Lightman 1979, their equations 6.36 and 6.53). We assume a power-law energy distribution of radiating electrons with somewhat shallow index of b = −1.5 that can account for the relatively flat spectrum of the source (Chatterjee et al. 2017). The peak Lorentz factor of the distribution, γmax, is chosen to correspond to the observed spectral break frequency of $\nu _{\rm max}=10$ GHz. If the lower Lorentz factor cut-off corresponds to emission at $\nu _{\rm min}=1$ GHz,4 then the equipartition magnetic field and electron column thus determined for minimum and maximum source sizes are $B_{\rm eq}\approx 140$ mG, $\gamma _{ \rm min}\approx 50$, γmax ≈ 160, $N_{\rm rel} \approx 0.95\, {\rm pc}\, {\rm cm}^{-3}$ for $R_{\rm per}=0.05$ pc, and $B_{\rm eq}\approx 27$ mG, $\gamma _{ \rm min}\approx 120$, γmax ≈ 370, $N_{\rm rel} \approx 0.1\, {\rm pc}\, {\rm cm}^{-3}$ for $R_{\rm per}=0.35$ pc. The reader can scale the equipartition field to other source sizes using Beq(R) ∝ R−6/7. The total energy contained in the relativistic electrons and the magnetic field (‘equipartition energy’) is ∼1049.1 and ∼1050.2 erg, respectively. If the relativistic electrons were injected in a one-off event, the synchrotron cooling rates at γmax yield source ages of $14$ yr for R = 0.05 pc and 60 yr for $R=0.35$ pc. The corresponding expansion velocities are $0.011\, c$ and $0.02\, c$, respectively.
Citation: Chatterjee et al. 2017
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Citation: Chatterjee et al. 2017
Citation function: Uses
After the cosmological recombination, the universe went into the dark ages during which the density fluctuations in the matter distribution grew, and after reaching a threshold, the matter collapsed to make the first bound objects. The nature of dark matter sets the timeline and characteristics of these first bound objects, which were the hosts for the first sources of light, so it is essential to see the impact of different dark matter models on the observables from the Cosmic Dawn and EoR. Then, the natural question that arises is whether one can use the differences in these observables, estimated for different dark matter models, in order to constrain the nature of dark matter. The present observational probes that allow us to have a peak in this epoch are the absorption spectra of high-redshift quasars (Loeb & Barkana 2001; White et al. 2003; Boera et al. 2019) and the Thomson scattering optical depth of the cosmic microwave background (CMB) radiation photons (Kaplinghat et al. 2003; Komatsu et al. 2011). However, these indirect probes provide very limited and weak constraints on the CD-EoR. The H i 21-cm line, which arises due to the hyperfine splitting of the ground state of the neutral hydrogen, is a direct and most promising probe to study this period. Motivated by this, a large number of radio interferometers, including the GMRT (Paciga et al. 2013), LOFAR (Ghara et al. 2020; Mertens et al. 2020), MWA (Barry et al. 2019; Li et al. 2019), and PAPER (Kolopanis et al. 2019), are attempting a statistical detection of this signal using the power spectrum statistic. In parallel, there is a complementary approach to detect the sky-averaged global 21-cm signal from the CD-EoR using experiments, e.g. the EDGES (Bowman et al. 2018), DARE (Burns et al. 2017), and SARAS (Singh et al. 2018). The next-generation interferometers like the SKA (Koopmans et al. 2015; Mellema et al. 2015) are expected to see a giant leap in the sensitivity, which will enable them to make tomographic images of the H i distribution across cosmic time.
Citation: Loeb & Barkana 2001
Citation function: Background
What is the dominant mode of star formation for AGNs in general, and for quasars in particular? The main sequence gives a useful framework for discussing the evolutionary status of AGN host galaxies and their relation to the galaxy population at large. The existing literature in this field, however, is complicated enormously by the diverse strategies of AGN sample selection, the accuracy of the SFR and M* tracers, and the myriad choices of main-sequence prescription. While there is almost unanimous agreement that AGNs of low to moderate luminosity (Lbol ≲ 1045 erg s−1) at z ≈ 0–3 lie on or below the main sequence (e.g., Shao et al. 2010; Mullaney et al. 2012, 2015; Santini et al. 2012; Rosario et al. 2013a; Shimizu et al. 2015; Ellison et al. 2016; Leslie et al. 2016; Suh et al. 2017; Bernhard et al. 2019; Grimmett et al. 2020; Jackson et al. 2020), no consensus exists for AGNs with Lbol > 1045 erg s−1. The situation is particularly contentious at redshifts higher than ∼0.5, where luminous AGNs have been reported to be above (e.g., Rovilos et al. 2012; Florez et al. 2020; Kirkpatrick et al. 2020), on (e.g., Harrison et al. 2012; Xu et al. 2015; Stanley et al. 2017; Schulze et al. 2019), and below (e.g., Scholtz et al. 2018; Stemo et al. 2020) the main sequence. Fortunately, a better consensus of opinion can be found for luminous (Lbol ≳ 1045 erg s−1) AGNs at z ≲ 0.5. Most agree that low-redshift quasars are located largely on and above the main sequence (Husemann et al. 2014; Xu et al. 2015; Zhang et al. 2016; Stanley et al. 2017; Jarvis et al. 2020). Regardless of redshift, it appears that the magnitude of an AGN’s offset from the main sequence correlates positively with its luminosity (Bernhard et al. 2019; Grimmett et al. 2020). For their large sample of z ≈ 0.3 type 1 AGNs with uniform SFRs based on extinction-corrected [O II] λ3727 emission, Zhuang & Ho (2020) demonstrated that SFR systematically rises with increasing Lbol at fixed M*.
Citation: Leslie et al. 2016
Citation function: Similarities; Differences
One of the fundamental tasks of the Galactic studies is to estimate the structure parameters of the major structure components. Bahcall & Soneira (1980) fit the observations with two structure components, namely a disc and a halo. Gilmore & Reid (1983) introduce a third component, namely a thick disc, confirmed in the earliest Besancon Galaxy Model (Crézé & Robin 1983). Since then, various methods and observations have been adopted to estimate parameters of the thin and thick discs and of the halo of our Galaxy. As the quantity and quality of data available continue to improve over the years, the model parameters derived have become more precise, numerically. Ironically, those numerically more precise results do not converge (see table 1 of Chang, Ko & Peng 2011, table 2 of López-Corredoira & Molgó 2014 and sections 5 and 6 of Bland-Hawthorn & Gerhard 2016, for a review). The scatters in density law parameters, such as scale lengths, scale heights and local densities of these Galactic components, as reported in the literature, are rather large. At least parts of the discrepancies are caused by degeneracy of model parameters, which in turn can be traced back to the different data sets adopted in the analyses. Those differing data sets either probe different sky areas (Bilir et al. 2006a; Du et al. 2006; Cabrera-Lavers et al. 2007; Ak et al. 2007; Yaz & Karaali 2010; Yaz Gökçe et al. 2015), are of different completeness magnitudes and therefore refer to different limiting distances (Karaali et al. 2007), or consist of stars of different populations of different absolute magnitudes (Karaali, Bilir & Hamzaolu 2004; Bilir et al. 2006b; Jurić et al. 2008; Jia et al. 2014). It should be noted that the analysis of Bovy et al. (2012), using the SEGUE spectroscopic survey, has given a new insight on the thin and thick disc structural parameters. This analysis provides estimate of their scale height and scale height as a function of metallicity and alpha abundance ratio. However, it relies on incomplete data (since it is spectroscopic) with relatively low range of Galactocentric radius as for the thin disc is concerned.
Citation: López-Corredoira & Molgó 2014
Citation function: Motivation; Motivation; Motivation
A common feature of all previous models is that the relation between the central galaxy stellar mass and the halo mass reaches a maximum at halo masses ~1012 M⊙. According to Yang et al. (2012), below this threshold the mass accretion of the central galaxy is dominated by star formation. Thus, when the halo mass reaches ~1012 M⊙ a process takes place that quenches the star formation. Interestingly, this mass scale is very similar to the cold-mode to hot-mode transition scale (Birnboim & Dekel 2003; Kereš et al. 2005) in the theory of gas accretion, as derived in hydrodynamic simulations, whereas large halos primarily accrete hot gas and low mass halos cold gas. This would suggest that the quenching of central galaxies coincides with the formation of a hot gaseous halo, and thus with a lack of cold gas supply. What would be the fate of satellites? According to Simha et al. (2009), the subhalos also retain their identity for quite some time after accreting a larger halo, so satellites in subhalos less massive than ~1012 M⊙ do not immediately see the effect of the hot gas in the larger halo and accrete in cold mode. Thus, consistent with the results of Yang et al. (2012) and Béthermin et al. (2013), satellite galaxies continue to accrete gas and convert it to stars over a rather long period, which according to Simha et al. (2009) is about of 0.5−1 Gyr after the merger. The gas accretion declines steadily over this period. Since star formation follows mass accretion with a short delay, satellites should experience quenching in a similar amount of time. This scenario would be consistent with our observations. Indeed, at z ~ 1 when massive halos are just forming via merger, the SF activity in the accreted subhalos is still high. At later epochs, instead, the transition to the hot mode accretion of the satellites and the consequent progressive quenching of their SF activity would lead to the faster decline of their contribution to the CSFH with respect to lower mass halos, which evolve in a cold mode accretion phase maintaining a high SFR.
Citation: Simha et al. (2009)
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Citation: Simha et al. (2009)
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