adsabs/FOCAL huggingface dataset:
As a first step, we need to specify the photoelectron sheath features. In this course, we first evaluate the steady state potential over the lunar surface (equation 4), and then after, we use this as a boundary condition to solve the Poisson equation (equation 2) and estimate the photoelectron sheath profile. In calculations, Lyman α (λ ∼ 121.57 nm, 10.29 eV, Λ ∼ 3 × 1011 cm–2 s–1) spike of solar photon radiation (Bauer 1973) is considered as the dominant source for the generation of photoelectrons from the lunar surface. The work function of the regolith material is taken from Grobman & Blank (1969), where it is suggested to vary in the range ϕr ∼ (4–6) V for the region across the subsolar point and limb. Moreover, Draine’s formulation is accounted to determine the lunar surface’s photoelectric efficiency (Draine 1978; Draine & Salpeter 1979) – its spectral dependence can be represented as ${\chi _{\nu r}} = {\chi _o}[1 - ({\phi _r}/{E_\nu })]$. For instance, for the Lyman α radiation χνr = 0.042 for optimum efficiency χo = 0.1 (Sickafoose et al. 2001) and ϕr = 6 V (Grobman & Blank 1969). Another significant parameter is the surface temperature which describes the electron population within the lattice available for the photoemission. Lunar Reconnaissance Orbiter based measurements (Williams et al. 2017) suggest that the surface temperature may vary from the equator (∼400 K) to the terminator (poles, ∼150 K). In order to take this account, we use the latitude (θ) dependent empirical relation ${T_\theta } = {T_0}[1 - (5/4\pi )\theta ]$; for instance, at θ = 70°, and To ≈ 205 K. These three parameters, viz., ϕr, To, χν, and Λ drive the photoemission current from the lunar regolith. The nominal solar wind plasma parameters are considered for calculating collection current over lunar regolith; the constituents are considered as40-41nes ≈ nis = 8.7 cm–3 and Tes ≈ Tis = 1.4 × 105 K (Mann et al. 2011; Kureshi et al. 2020). These solar radiation and wind plasma parameters might vary widely during active solar events and alter surface charging and sheath features. Popel et al. (2018) suggest the dust number density may also vary in a wide range depending on lunar altitude and particle size; for instance, nd ∼ 800 cm–3 for the particles of size 100 nm ≤ ao ≤ 200 nm and θ = 77°. Note that the secondary electron emission (Seitz 1940; Misra, Mishra & Sodha 2013) from the lunar regolith (and floating dust) is ignored, as it minimally contributes to the charging of sunlit surfaces (Mishra & Bhardwaj 2020). These parameters, along with equation (4), yield steady state potential over the sunlit locations. This estimate of the surface potential is used as a boundary condition (i.e. at l = 0, υ = υo) alongwith υ’ = υ = 0 as $l \to \infty $ to solve the Poisson equation (equation 2) numerically – using this framework, the sheath structure is derived in terms of electric potential (υ), electric field (Es), and photoelectron population density (npe).
Citation: Sickafoose et al. 2001
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Citation: Draine 1978
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1E 1841–045, located at the center of supernova remnant (SNR) Kes 73 (Vasisht & Gotthelf 1997), is another steady X-ray emitter. The source was monitored with NuSTAR between 2013 September 5 and 21, during which time six bursts were detected (An et al. 2015). In order to eliminate the contamination from the SNR, an annulus region with inner and outer radii of 60″ and 100″ around the source position was selected for background spectral extraction, as was also done in An et al. (2013). We searched for soft X-ray data from 2013 August 1 to October 30, and identified 11 Swift XRT observations, 10 executed in WT mode and 1 short observation in Photon Counting (PC) mode. Note that in WT mode, 10 rows are compressed into a single row, only the central 200 columns are read, and only 1D imaging is preserved. Consequently, it is impossible to resolve the SNR contribution and three SNR related emission lines (Mg, Si, and S) clearly appear in the stacked spectrum of 10 WT data. Since the source emission has been stable for more than 15 years (Dib & Kaspi 2014), we performed the joint fit with the longest, burst-free NuSTAR observations (ObsID = 30001025012) and XMM-Newton observations that were performed ∼11 years earlier. For the XMM-Newton observation, since the MOS1/MOS2 data were performed in the full frame mode and were seriously affected by pile up, we only use the pn data in the following spectral fitting. The joint spectra are fit by our model (STEMS3D+PL) and a 2% systematic error is added to the XMM-Newton data to account for calibration uncertainties. The fit results yielded that 1E 1841–045 has the lowest twist angle (Δϕ ∼ 0.83) and the highest electron velocities in the magnetosphere (β ∼ 0.28) among the four sources studied here. The resulting photon index of the PL component (Γ ∼ 1.23) is consistent with the value reported based on INTEGRAL data (Kuiper et al. 2006). However, due to the short exposure of the XMM-Newton data, in addition to the high interstellar absorption, the parameter values have large uncertainties (see Table 2 and Figure 2). Note that 1E 1841–045 is the only source whose non-thermal component (FP ∼ 5.1 × 10−11 erg s−1 cm−2) dominates the STEMS3D component (FS ∼ 3.6 × 10−11 erg s−1 cm−2) in the range of 1–79 keV.
Citation: Dib & Kaspi 2014
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Although the origin and evolution of linear-scale clustering is well described by the concordance model (Spergel et al. 2007), gravitational clustering of matter on smaller scales (galaxy clusters and groups) belongs to a non-linear regime of structure formation. This regime is more difficult to understand and to simulate because its evolution must include the role of baryons, which are driven by complex physics. Clusters of galaxies that are the most massive gravitationally bounded structures have been widely used over the past years to probe the cosmic evolution of the large-scale structures in the Universe (Voit 2005; Allen et al. 2011). In the standard model of structure formation driven by gravitation alone, clusters form a self-similar population that is only characterized by their mass and redshift. Including baryon physics introduces some distortions in the scaling relations between the mass and other physical quantities such as temperature, X-ray, or optical luminosity (Kaiser 1986; Giodini et al. 2013). Most recent research works have focused on the relationship between the dominant dark matter and the baryonic matter that forms gas and stars (Lin et al. 2003; Giodini et al. 2009). Both the mass-to-light (M/L) ratio of structures and the halo occupation number (HON, or the number of satellite galaxies per halo) correspond to observables that are easy to compare to predictions from numerical simulations (Cooray & Sheth 2002; Tinker et al. 2005). They are both representative of the way stellar formation occurred in the early stages of halo formation (Marinoni & Hudson 2002; Borgani & Kravtsov 2011). Recent progress on numerical simulations (Murante et al. 2007; Conroy et al. 2007; Aghanim et al. 2009) has also stressed the role of hierarchical building of structures in enriching the intra-cluster medium (ICM) with stars in a consistent way with the observed amount of ICM globular clusters and ICM light. This ICM light, although hardly detectable, can be considered as the extension of the diffuse envelope often seen in the central galaxy in rich clusters of galaxies. It is an important component, although not the only one, that explains the formation of the brightest cluster galaxies (BCG) in the centre of clusters of galaxies (Dubinski 1998; Presotto et al. 2014).
Citation: Giodini et al. 2013
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Regardless of their exact composition, particles suspended in these exoplanet environments likely undergo repeated particle–particle collisions in response to atmospheric circulation. Such dynamics have been inferred to drive efficient triboelectrification (e.g., Helling et al. 2013), resulting in electrified cloudy or hazy environments at elevation. As happens within Earth’s clouds, exoplanet clouds are likely gravitationally stratified, meaning that smaller, lighter grains become concentrated at the top of the clouds, while larger, heavier grains remain at lower elevation (see Figures 2 and 8 in Helling et al. 2008; also Helling & Fomins 2013; Helling et al. 2016). Because, as discussed above, the polarity of charge collected by particles from triboelectric processes depends on grain size, this stratification (smaller particles at elevation; larger particles on the bottom) has the ability to set up coherent electric fields. Such charge separation occurs in both thunderstorms and volcanic plumes and ultimately drives spark discharges–lightning–either through conventional breakdown of the gas or via runaway electron avalanche (Kikuchi & Endoh 1982; Gurevich et al. 1992; James et al. 1998; Dwyer 2005; Cimarelli et al. 2014; Dwyer & Uman 2014; Aizawa et al. 2016). On Earth, these discharges support a global electric circuit and have the ability to modulate chemical and physical reactions in the atmosphere (Price 1993; Rakov & Uman 2007; Siingh et al. 2007; Genareau et al. 2015; Wadsworth et al. 2017; Mueller et al. 2018). Indeed, lightning may have been involved in the production of prebiotic molecules in an early-Earth environment (Miller & Urey 1959; Navarro-González et al. 1998) and such lightning has been hypothesized to have been associated within dusty flows (namely, volcanic plumes) rather than hydrometeor clouds (Navarro-González et al. 1998; Segura & Navarro-González 2005; Johnson et al. 2008). If the mineral clouds inferred to exist on extrasolar worlds can be considered analogs to the dusty environments in our own solar systems, charging within these systems may also stimulate a wide array of electrostatic phenomena and help catalyze prebiotic chemistry (Hodosán et al. 2016).
Citation: Helling & Fomins 2013
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With the real-time pipeline, we also frequently detect eclipsing binaries, due to their significant changes in brightness. Often, when we trigger these sources, PV light curves reveal potentially eclipsing behaviour. In these cases, we can attempt to verify the nature of the variable source by creating Lomb-Scargle periodograms for the light curves38 and inspecting, by eye, the folded light curves that we create using the best periods found. We note that this is done independently of the rest of pipeline; it is not part of the automatic software. An example of an eclipsing binary we found using TUVOpipe is shown in Fig. 32. The strong variability (by over 1 optical magnitude) led us to create a long-term light curve; the PV light curves of all the used UVOT filters are shown in Fig. 33. The source is a known source that appears in many sky survey catalogues, including Gaia, where its G-band magnitude is listed as 14.1 and its inferred temperature is ~5000 K (see Andrae et al. 2018 for how the listed temperature we extract from the Gaia catalogue is inferred from the Gaia data). This G-band magnitude is brighter than the U-UV bands seen in the UVOT light curve, indicating (along with the temperature) that it is a relatively red source. The source is also present in the ATLAS catalogue of variable stars Heinze et al. (2018), where it is denoted as AT J098.1962+05.6837. The ATLAS catalogue gives a period of 1.985 days. However, no classification of the source was so far known, so the cause of the found periodicity is not clear. Our method gave a best period of 1.9899 days, so we used this period to fold the UVOT U-band light curve, which is shown in Fig. 34. The light curve clearly reveals an eclipse in which the source becomes dimmer by around 1.5 magnitudes, and the shape of the light curve confirms it as an eclipsing binary. There may also be additional very weak minima seen halfway between the deep eclipses (see around phase −0.5 and 0.5 in the plot shown). The fact that any potential secondary minima are very weak may suggest that this is an Algol-type system (these are known as EA binaries; see Carmo et al. 2020 for a review of these systems and example light curves; the inferred Gaia temperature is also consistent with this being an EA system).
Citation: Andrae et al. 2018
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With improved resolution, in this work we have resolved corrugated swept-up shells as well as small blobs of mixed material in the wind region that were not seen in Paper I. The swept-up shells are much smoother in the simulations including poloidal field, which is related to the stabilization of shear instability by the magnetic field. To check how an even higher resolution can affect the results, we have run simulations for case b2 at a resolution of 3200 × 990. In the upper panel of Figure 9 we present the density map at t = 1000 year for the run without ambient poloidal field. A close comparison to its ordinary resolution counterpart (see the upper left panel of Figure 5) shows that the details of the mixing structures are quite different in the two runs. More complex and fragmented mixing structures are generated in the higher resolution simulation, which indicates that the process producing these structures is not completely resolved at the current resolution (see, e.g., Frank et al. 1996). Despite the different fine structures, the overall outflow shape and the jet structure in the two simulations are in good agreement. In the lower panel of Figure 9 we present the same maps for the run with ambient poloidal field. The smoother and thicker shell seen here is almost identical to its ordinary resolution counterpart (see the lower left panel of Figure 5), and similar feather-like structures are also present near the wind boundary. There is also no sign of intense stochastic behavior like that seen in the upper panel of Figure 9. This suggests that the stabilization of the wind-ambient interface by the poloidal field is quite robust, and this conclusion holds well at least for the resolution we have used. Finally, it should be noted that the wind in the current simulations fans out in all radial directions even at the equator where an accreting inner envelope or disk is instead expected. Whether this setup could have anything to do with the growth of stochastic mixing structures near the inner toroid will need to be resolved in future simulations with more realistic setup of boundary conditions.
Citation: Frank et al. 1996
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Star-forming galaxies at redshifts z ∼ 1–3 probe the cosmic epoch when most of the stellar mass assembly in the universe took place (Madau & Dickinson 2014, and references therein). A better understanding of star formation (SF) during this epoch is therefore imperative to understand SF across cosmic time. Locally, less than 5% of the galaxy population has a star formation rate (SFR) that is significantly higher than the empirical main sequence for star-forming galaxies, i.e., the tight correlation (∼0.3 dex) between the SFR and stellar mass, M⋆ (Brinchmann et al. 2004; Elbaz et al. 2007, 2011; Noeske et al. 2007; Goto et al. 2011; Rodighiero et al. 2011; Sargent et al. 2012; Whitaker et al. 2012, 2014; Salmon et al. 2015). These often-called starburst galaxies, with an IR luminosity LIR ∼ (0.1–5) × 1012 L⊙ (e.g., Sanders & Mirabel 1996; Downes & Solomon 1998), become increasingly more common at high z. In fact, (sub)millimeter number counts reveal that galaxies with LIR > 1012–13 L⊙, at z > 0.5, are many hundreds of times more likely to exist than in the local universe (Blain et al. 2002; Chapman et al. 2005; Berta et al. 2011; Magnelli et al. 2011; Béthermin et al. 2012; Magnelli et al. 2013; Casey et al. 2013, 2014; Geach et al. 2013; Simpson et al. 2014; Strandet et al. 2016; Brisbin et al. 2017). Meanwhile, the cosmic molecular gas density also peaks at z ∼ 1–3 (Decarli et al. 2014, 2016a, 2016b, 2019; Walter et al. 2014; Lentati et al. 2015; Pavesi et al. 2018; Liu et al. 2019; Riechers et al. 2019). This suggests a strong link between molecular gas and SF. Rest-frame far-IR (FIR) measurements of spectral lines and thermal dust continuum emission have been used to investigate the cooling and heating processes of the interstellar medium (ISM) in star-forming galaxies; however, the physical conditions at high z are still, in general, poorly investigated (Popesso et al. 2012; Bothwell et al. 2013; Carilli & Walter 2013; Genzel et al. 2013; Yang et al. 2017; Tacconi et al. 2018, 2020; Aravena et al. 2020; Birkin et al. 2020; Boogaard et al. 2020; Lenkić et al. 2020).
Citation: Goto et al. 2011
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Citation: Sanders & Mirabel 1996
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We analyze the 10 BBH mergers reported by LIGO and Virgo in their O1 and O2 observing runs (Abbott et al. 2019a; LIGO Scientific Collaboration & Virgo Collaboration 2019). Before discussing results, it is useful to review expectations from the literature for the spin distributions resulting from different formation scenarios. Isolated binary evolution is predicted to yield black holes with spins preferentially aligned with their orbit. Although spin misalignments may be introduced by natal supernova kicks, episodes of mass transfer and tidal torques serve to realign component spins before the formation of the final black hole binary (Rodriguez et al. 2016; Zevin et al. 2017; Gerosa et al. 2018; Qin et al. 2018; Zaldarriaga et al. 2018; Bavera et al. 2020). The black holes’ spin magnitudes in this scenario are much more uncertain. Recent work indicates that angular momentum is efficiently transported away from stellar cores, leaving black holes with natal spins as low as a ∼ 10−2 (Qin et al. 2018; Fuller & Ma 2019). While tides on the progenitor of the second-born black hole can spin up the progenitor star (Zaldarriaga et al. 2018), this effect can be counteracted by mass loss in stellar winds, and more detailed simulations find only low or moderate spin increases due to tides (Qin et al. 2018; Bavera et al. 2020). Meanwhile, dynamically formed systems in dense stellar clusters have no a priori preferred axis, and so are likely to have random spin configurations (Rodriguez et al. 2016, 2018, 2019; Doctor et al. 2020). Once again, however, the expected spin magnitudes are largely unknown, subject to the same uncertainties mentioned above regarding natal black hole spins. One firm prediction of the dynamical scenario concerns the spins of second-generation binaries, whose components were themselves formed from previous mergers. Regardless of their component spins, black hole mergers generally yield remnants with a ∼ 0.7; thus the effective spin of two such second-generation binaries may be large (Fishbach et al. 2017; Gerosa & Berti 2017; Rodriguez et al. 2018, 2019; Doctor et al. 2020).
Citation: Zaldarriaga et al. 2018
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Citation: Zaldarriaga et al. 2018
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Various types of AGNs are known and one among them are the narrow-line Seyfert 1 (NLSy1) galaxies, which are classified based on the presence of narrow Hβ emission line with full width at half-maximum (FWHM) 2000 km s−1 and weak [O iii] emission line, with F([O iii])/F(Hβ) 3 (Osterbrock & Pogge 1985; Goodrich 1989). They are believed to be powered by low-mass black holes (${\sim } 10^7 \, \mathrm{M}_{\odot }$) having higher accretion rate and generally showing strong Fe ii emission compared to their broad line counterparts namely the broad-line Seyfert 1 (BLSy1) galaxies (Xu et al. 2012; Rakshit et al. 2017a). However, from spectro-polarimetric observations of a γ-ray emitting NLSy1 galaxy, PKS 2004 − 447 (Baldi et al. 2016) and accretion disc modelling of a sample of 23 radio-detected NLSy1 galaxies (Calderone et al. 2013) indicate that they have masses similar to the blazar class of AGNs. Other characteristics that make NLSy1 galaxies different from the BLSy1 galaxies are their rapid soft X-ray variability (Pounds, Done & Osborne 1995; Leighly 1999a), steep soft X-ray spectra (Boller, Brandt & Fink 1996; Wang, Brinkmann & Bergeron 1996; Leighly 1999b) and low amplitude optical variability (Grupe 2004; Rakshit & Stalin 2017). Also, the fraction of NLSy1 galaxies detected in radio is much lower (${\sim } 7{{\ \rm per\ cent}}$) compared to the fraction of radio detected BLSy1 galaxies (Komossa et al. 2006; Rakshit et al. 2017a). Among radio-loud NLSy1 galaxies, about a dozen (∼2 per cent) have been detected in γ-ray by the Fermi-Large Area Telescope (e.g. Abdo et al. 2009; D’Ammando et al. 2015; Paliya et al. 2018) suggesting the unambiguous presence of relativistic jets in them. Multiband broad-band SED modelling of these γ-ray detected NLSy1 galaxies indicate that these sources have many properties similar to the blazar class of AGNs (Paliya et al. 2013b) and specifically resembling the flat spectrum radio quasar (FSRQ) category (Paliya et al. 2018). In the radio, these γ-ray emitting NLSy1 galaxies have a compact core jet morphology, high brightness temperature, show superluminal motion and significant radio variability (Doi et al. 2006; Komossa et al. 2006). Detailed investigations of the population of NLSy1 galaxies need to be undertaken to understand more about their peculiar characteristics.
Citation: Calderone et al. 2013
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Being a benchmark system H + H2, H + HD, and their isotopic counterparts have received much attention over the last several decades (Marinero et al. 1984; Zhang & Miller 1989; D’Mello et al. 1991; Harich et al. 2002; Gao et al. 2015; Yuan et al. 2018a, b, 2020). Most early experimental and theoretical investigations were centered around benchmarking theory against experiments and providing improved descriptions of the H3 potential energy surfaces (PES; Boothroyd et al. 1996; Mielke, Garrett & Peterson 2002; Yuan et al. 2018a, b). Among the available PESs for the H3 system, the one by Boothroyd et al. (1996) referred to as the BKMP2 PES and by Mielke et al. (2002) referred to as the CCI PES, nearly equally well account for most experimental data for H + H2, H + HD, and D + HD collisions. These PESs have also been able to account for even subtle effects such as the GP (Kendrick et al. 2015; Hazra et al. 2016; Croft et al. 2017; Kendrick 2018, 2019). The GP effect, while not significant at temperatures relevant to astrophysics, is important below 1 K as illustrated in a series of calculations on H + HD (v, j) collisions for vibrational levels v = 4 − 9 (Kendrick et al. 2015; Hazra et al. 2016; Croft et al. 2017; Kendrick 2018, 2019). Though several prior studies of Flower and co-workers  (Flower 1999, 2000; Flower & Roueff 1999; Wrathmall et al. 2007) have reported rate coefficients for H + HD collisions, due to the approximations involved in the scattering calculations (e.g. neglect of hydrogen atom-exchange), the reliability of the available rate coefficients has been a source of debate (Desrousseaux et al. 2018). Recently, Desrousseaux et al. (2018) reported rate coefficients for pure rotational transitions for j ≤ 10 within the v = 0 vibrational level using accurate quantum calculations that include the exchange channel. In this paper, we report rate coefficients for state-to-state rovibrational transitions in HD induced by H atoms between and within the v = 0 and 1 vibrational levels and for temperatures ranging from T = 1–1000 K.
Citation: Kendrick 2018
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Citation: Kendrick 2018
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