adsabs/FOCAL huggingface dataset:
ΓCR can be expressed as the product of three factors – the total cosmic ray ionization rate per H nucleus ζH (including both primary and secondary ionizations), the average energy deposited into the medium per ionization ΔQ, and nH. Both ζH and ΔQ are rather uncertain and can vary considerably over different Galactic environments. Typical values of ζH in dense gas are ∼1–5 × 10−17 s−1 (Dalgarno 2006), but there is evidence from H3+ observations that ζH is considerably higher in the diffuse gas under consideration here (Dalgarno 2006; Indriolo & McCall 2012). Indriolo & McCall (2012) find a mean ζH of 1.8 × 10−16 s−1 in their sample of diffuse molecular sight lines, and values as large as ∼1 × 10−15 s−1 have been reported in the literature (Snow & McCall 2006; Shaw et al. 2008). In this paper, we adopt the value 1.8 × 10−16 s−1. For ΔQ, we use 10 eV, as estimated for diffuse molecular gas from table 6 of Glassgold, Galli & Padovani (2012), although it is important to note that this value can vary by several eV depending on the precise physical and chemical conditions in the cloud. Combining these factors, the cosmic ray heating rate is

(11)

\begin{eqnarray}
\Gamma _{\rm {CR}} &amp;=&amp; \zeta \Delta Q n_{\rm {H}} \nonumber \\
&amp;\approx&amp; 1.9 \times 10^{-25} \left( \frac{n_{\rm {H}}}{30 \hspace{3.0pt} \rm {cm}^{-3}} \right) \hspace{3.0pt} \rm {ergs} \hspace{3.0pt} \rm {cm}^{-3} \hspace{3.0pt} \rm {s}^{-1}.
\end{eqnarray}

For ΓPE, we adopt the expression:

(12)

\begin{equation}
\Gamma _{\rm {PE}} = 1.3 \times 10^{-24} \hspace{3.0pt} n_{\rm {H}} \epsilon G_0 \hspace{3.0pt} \rm {ergs} \hspace{3.0pt} \rm {cm}^{-3} \hspace{3.0pt} \rm {s}^{-1}
\end{equation}

from Wolfire et al. (2003), where G0 is the intensity of FUV light in units of the Habing (1968) field and ϵ is the heating efficiency factor given by equation 20 of Wolfire et al. (2003). For nH = 30 cm−3, T = 100 K, an electron fraction of 1.6 × 10−4, and a FUV field of G0 = 1.1 (Mathis, Mezger & Panagia 1983), ϵ evaluates to 1.8 × 10−2, yielding

(13)

\begin{equation}
\Gamma _{\rm {PE}} = 7.6 \times 10^{-25} \left( \frac{n_{\rm {H}}}{30 \hspace{3.0pt} \rm {cm}^{-3}} \right) \hspace{3.0pt} \rm {ergs} \hspace{3.0pt} \rm {cm}^{-3} \hspace{3.0pt} \rm {s}^{-1}.
\end{equation}
Citation: Shaw et al. 2008
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The trends between the LF slope α and the aforementioned parameters, with the addition of the morphological T type, are shown in Fig. 4 together with their Spearman correlation coefficient (ρ) and their p value, indicating the probability that the two sets of data are uncorrelated. We summarize the properties for which we look for a correlation in Table 4. We define a correlation to be negligible when |ρ|=[0 − 0.2], weak when |ρ|=[0.2 − 0.4], moderate when |ρ|=[0.4 − 0.6], strong when |ρ|=[0.6 − 0.8], and very strong when |ρ|=[0.8 − 1]; using the p value to evaluate the probability that, despite showing a correlation, two variables may be uncorrelated. It should be noted that only a handful of studies so far have looked at the correlation between α and global galaxy properties: Kennicutt et al. (1989), Elmegreen & Salzer (1999), Youngblood & Hunter (1999), van Zee (2000), and Thilker et al. (2002) investigated nebular LFs as in this paper, while Liu et al. (2013) identified H II regions via Paα, and Cook et al. (2016) studied the GALEX far-ultraviolet (FUV) LFs of H II regions. While the sample of Cook et al. (2016) includes a few hundred galaxies, the other studies are based on samples ranging from 10 to 35 galaxies, similar to our study. In this section and in Sect. 6.1, we compare our results to those studies that, as in our case, applied a uniform analysis methodology on galaxy samples. It should be noted that using different tracers means probing different source ages and, as reported by Oey & Clarke (1998), older H II regions tend to have steeper LF slopes, mainly due to the short main-sequence lifetimes of the more massive stars constituting the brighter H II regions. This is the reason why, for example, FUV observations, probing H II regions with ages less than 100 Myr, are expected to deliver a steeper LF compared to Hα observations, typically probing H II regions younger than 10 Myr, and our comparison remains qualitative.
Citation: Liu et al. (2013)
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A growing body of work suggests that planet formation is strongly dependent on the birth environment of the host star. Stars preferentially form in groups (Lada & Lada 2003), and in sufficiently dense environments the evolution of a PPD can be significantly influenced by neighbours (de Juan Ovelar et al. 2012). Close star–disc encounters are one such environmental influence on PPDs that can result in enhanced accretion and hasten disc depletion (Clarke & Pringle 1993; Ostriker 1994; Pfalzner et al. 2005; Olczak, Pfalzner & Spurzem 2006; Bate 2018; Winter et al. 2018a; Cuello et al. 2019). However, the stellar number densities required for tidal truncation are high, and in practice few observed regions satisfy this condition (Winter et al. 2018b, 2019a). The influence of tidal truncation is therefore limited to stellar multiples, either in bound systems (Dai et al. 2015; Kurtovic et al. 2018) or during the decay of higher order multiplicity (Winter, Booth & Clarke 2018c). Since stellar multiplicity does not appear to be strongly dependent on environment (see Duchêne & Kraus 2013, for a review), this suggests that encounters are not an environmental influence, but may set disc initial conditions during the early phases of cluster evolution (Bate 2018). Discs can also be externally depleted via thermal winds driven by far-ultraviolet (FUV) and extreme ultraviolet (EUV) photons from neighbouring massive stars (Johnstone, Fabian & Taylor 1998; Störzer & Hollenbach 1999; Adams et al. 2004; Facchini, Clarke & Bisbas 2016; Haworth et al. 2018; Haworth & Clarke 2019). This process of external photoevaporation dominates over dynamical encounters in observed environments, and can deplete PPDs rapidly for many stars that are born in massive and dense clustered environments (Scally & Clarke 2001; Winter et al. 2018b). Many stars in the solar neighbourhood are born in regions where UV fields are sufficient to significantly shorten disc lifetimes (Fatuzzo & Adams 2008; Winter et al. 2018b), and the fraction of stars born in such environments may be much greater outside of this region, dependent on galactic environment (Winter et al. 2019a). From an observational perspective, Guarcello et al. (2016) report disc survival fractions that decrease with increasing FUV flux in Cygnus OB2 (see also Winter, Clarke & Rosotti 2019b), and Ansdell et al. 2017 find a correlation between the dust mass in PPDs and separation from σ Ori. However, Richert et al. (2015) find no correlation of disc fraction with distance from OB stars. Reconciling these contradictory findings may require appealing to the inefficiency of external photoevaporation at small radii within the disc, dynamical and projection effects, or the stellar age gradient apparent in many star forming regions (Getman et al. 2018).
Citation: Winter, Booth & Clarke 2018c
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Citation: Winter et al. 2018b
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Citation: Kurtovic et al. 2018
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Citation: Winter et al. 2018b
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Since long cosmologists have felt motivated to look for alternative explanations for the DE beyond a rigid cosmological constant Λ. The scalar field paradigm was then profusely used also to make the cosmic vacuum dynamical: Λ = Λ(ϕ). In the old days, the main aim was to adjust the large value of Λ typically predicted in QFT to be zero. There were many early proposals (see e.g. Endo & Fukui 1977, 1982; Fujii 1982; Dolgov 1983; Abbott 1985; Zee 1985; Barr 1987; Ford 1987; Peccei, Solà & Wetterich 1987; Weiss 1987; Barr & Hochberg 1988). In spite of the hopes raised by these works at solving the ‘old CC Problem’, it was later shown in Weinberg (1989) through the so-called no-go theorem that most if not all the dynamical adjustment mechanisms existing in the literature to date were plagued by more or less obvious forms of subtly hidden fine tuning. For this reason, the subsequent use of scalar fields in cosmology was mostly focused on trying to explain another aspect of the CCP: the cosmic coincidence problem (viz. the fact that $\rho _\Lambda$ happens to be so close to the matter density ρm right now; see e.g. Peebles & Ratra 2003). The new wave of dynamical scalar fields in cosmology crystalized in the notions of quintessence, phantom fields and the like, which have had a tremendous influence in cosmology till our days (see e.g. Peebles & Ratra 1988; Ratra & Peebles 1988; Wetterich 1988; Wetterich 1995; Caldwell, Dave & Steinhardt 1998; Zlatev, Wang & Steinhardt 1999; Amendola 2000; Caldwell, Kamionkowski & Weinberg 2003), the reviews (Sahni & Starobinsky 2000; Padmanabhan 2003; Peebles & Ratra 2003; Copeland, Sami & Tsujikawa 2006), and the many references therein. At the same time a blooming crest of models based on ascribing a direct phenomenological time-dependence to the CC term, Λ = Λ(t), broke with impetus into the market. For an account of some of the old attempts, see Overduin & Cooperstock (1998, and references therein).
Citation: Barr & Hochberg 1988
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Horizon scale imaging promises to test basic predictions of GR and improves our understanding of the physics responsible for accretion and emission in a strong gravitational field. In particular, imaging a black hole shadow has been a long-standing goal of black hole astronomy. However, imaging the black hole shadow feature in Sgr A* has been inherently challenged by two known effects. First, the scattering by interstellar medium blurs the strong GR features near the black hole. In a recent work, it has been shown that this effect can be mitigated based on the fact that the scattering is well understood over the relative range of baseline lengths provided by the EHT (Fish et al. 2014). Second, while the predicted shadow feature is nearly independent of the spin or orientation of the black hole to within 10% (Bardeen 1973; Takahashi 2004), the emission region surrounding the black hole depends on the details of the underlying accretion process and is intrinsically time variable primarily due to the stochastic nature of magnetorotational-instability-driven turbulence and magnetic reconnection in the accretion flow. Magnetorotational instability (MRI, Balbus & Hawley 1991, 1998) is believed to be the leading mechanism driving turbulence in accretion disks and develops on orbital timescales. The timescale for the Keplerian motion at the innermost stable circular orbit around the black hole in Sgr A* ranges from 30 minutes for a non-rotating black hole to 4 minutes for prograde orbits around a maximally rotating black hole (Doeleman et al. 2009b). These timescales are much less than the typical duration of a Very Long Baseline Interferometry (VLBI) experiment, which violates one of the basic requirements for VLBI Earth-rotation aperture synthesis imaging. In contrast, the corresponding timescales in the nearby giant elliptical galaxy M87, which has the second largest apparent event horizon, are much larger (a minimal timescale of a few days).
Citation: Takahashi 2004
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The main goal of this paper was to further expand the recent transport theory of Zank etÂ al. (2014) and thus, by default, earlier attempts by Drake etÂ al. (2006, 2013) and Bian & Kontar (2013). In our approach, similar to Zank etÂ al. (2014), the focus was on inertial-scale flux ropes that were modeled as quasi-2D magnetic islands superposed transversely on a strong large-scale magnetic field imbedded in the large-scale plasma flow, as suggested by the 3D MHD turbulence simulations with a strong guide field of Dmitruk etÂ al. (2004). We adopt a different perspective in proceeding from the basic guiding center kinetic equation (e.g., Kulsrud 1983) instead of the transformed Vlasov equation (Skilling 1975) used by Zank etÂ al. (2014). This offers the advantage of explicitly identifying drift acceleration for various guiding center drift mechanisms and the betatron acceleration that energetic particles would be subject to in both the large-scale plasma flow and magnetic field, and in the inertial-scale plasma flow and magnetic fields of contracting and merging flux ropes. Our approach allows us to distinguish between particle drift and betatron energization when magnetic flux ropes behave in an incompressible fashion (later stage contraction or during merging) or when they are compressible (early stage contraction and during island collisions). The transformation of the guiding center kinetic equation for nearly gyrotropic particle distributions into a focused transport equation clarifies the role of drift and betatron acceleration in focused transport. In the process, a more general focused transport formalism of particle transport and momentum change in contracting and merging flux ropes was derived, whereas Zank etÂ al. (2014) followed a more targeted focused transport approach based on specific conservation laws (magnetic moment conservation, conservation of parallel action, and conservation of magnetic flux) that are thought to apply to the above-mentioned three acceleration mechanisms (see also Drake etÂ al. 2006, 2013).
Citation: Kulsrud 1983
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An EM counterpart is not strictly necessary to use compact binary mergers such as BBHs and BNSs as standard sirens. By matching the sky localization region of GW sources – which can be inferred from the GW measurements – with galaxy catalogues, one might in fact be able to extract complementary information on the redshift of the sources, without the need of spotting an EM counterpart. The idea was originally proposed by Schutz (1986) and it has subsequently been used and developed in different analyses (Holz & Hughes 2005; MacLeod & Hogan 2008; Petiteau, Babak & Sesana 2011; Del Pozzo 2012; Chen et al. 2018; Gray et al. 2020). It has already been tested with real data collected by the LIGO and Virgo detectors (Fishbach et al. 2019; Soares-Santos et al. 2019; Palmese et al. 2020; Abbott et al. 2020d; Finke et al. 2021), though the constraints obtained so far with this ‘statistical’ method are not competitive with the ones derived from GW170817 and its EM counterpart, mainly because of the poor spatial resolution of the current network of ground-based interferometers. Future observations, taken with an enlarged network of ground-based GW detectors, will allow for better cosmological measurements (Chen et al. 2018), mainly thanks to the improved sky localization accuracy. Other complementary methods, which analogously do not require the identification of an EM counterpart, might yield interesting results as well (Taylor & Gair 2012; Oguri 2016; Del Pozzo, Li & Messenger 2017; Mukherjee & Wandelt 2018; Farr et al. 2019; Mukherjee et al. 2020a; Mukherjee, Wandelt & Silk 2020b, c, d; Ezquiaga & Holz 2021). The era of precise cosmological measurements with GWs will however start only with next-generation interferometers, such as the Einstein Telescope (ET) (Punturo et al. 2010; Sathyaprakash, Schutz & Van Den Broeck 2010; Belgacem et al. 2019a; Maggiore et al. 2020) and the Cosmic Explorer (Abbott et al. 2017a; Reitze et al. 2019a, b) on the Earth, or TianQin (Mei et al. 2020), Taiji (Luo et al. 2020), and the Laser Interferometer Space Antenna (LISA) (Amaro-Seoane et al. 2017) in space. The latter instrument is the focus of the present investigation. In what follows, we will briefly introduce LISA and review previous studies of LISA’s capability to do cosmological analyses using standard sirens. More details on how to extract cosmology from GWs by statistically matching with galaxy catalogues will be given in Section 2.
Citation: Fishbach et al. 2019
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Driven by the influx of spatially resolved observations coming from integral field units (IFU), more recent investigations have focused on attempting to infer structural, dynamical, and/or chemical properties for localized regions of galaxies, by decomposing them into physically motivated components. In fact, this concept pre-dates the large-scale use of IFU with works dealing with, for instance, photometric disc/bulge decompositions of surface brightness profiles (e.g. see Kent 1985; Cinzano & van der Marel 1993; Scorza & Bender 1995; Moriondo, Giovanardi & Hunt 1998; Krajnović et al. 2013), including using multiple filters (Dimauro et al. 2018). Aside from surface brightness, radial profiles of other parameters have also been subject to analogous decompositions. For instance, the decomposition of gas (usually H i) circular velocity profiles into contributions from different galaxy sub-components is a well-established practise (as in van Albada et al. 1985; Carignan, Sancisi & van Albada 1988; Battaglia et al. 2006; Noordermeer et al. 2007; Swaters et al. 2012; Aniyan et al. 2016, 2018; Sofue 2017), whilst decompositions of mass profiles have attempted to infer the contributions from dark matter (DM) and baryons (stars and globular clusters, gas, et cetera; Annunziatella et al. 2017; Poci, Cappellari & McDermid 2017; Bellstedt et al. 2018). These concepts have been extended to two dimensions, including multiband photometric disc/bulge decompositions of images, rather than profiles (for instance, see Scorza et al. 1998; de Souza, Gadotti & dos Anjos 2004; Norris, Sharples & Kuntschner 2006; Simard et al. 2011; Méndez-Abreu et al. 2017; Dalla Bontà et al. 2018). Moreover, there have been recent efforts to conduct the decomposition directly on an observed spectrum (Johnston et al. 2012; Coccato et al. 2015; Tabor et al. 2017; Coccato et al. 2018), to similarly determine the contributions to various spectral features coming from ‘distinct’ galaxy sub-components. This type of component-based approach attempts to isolate the distinct contributions to observed galaxies from regions that may or may not have had different origins and/or formation paths; however, they have thus far dealt with the problem from only one perspective – dynamics or stellar populations.
Citation: Moriondo, Giovanardi & Hunt 1998
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The WSN/ISN series is based on the counts of both sunspot groups and individual sunspots, with the former being weighted with a factor of ten: (1)\begin{equation} R = k\cdot(10\cdot G + S), \end{equation}R=k·(10·G+S),where G and S are the numbers of sunspot groups and individual sunspots, respectively, and k is a correction factor, characterizing each observer. However, resolving individual spots may be imprecise with poor instrumentations, and a new series, based only on sunspot groups, was proposed, called the group sunspot number, GSN (Hoyt et al. 1994; Hoyt & Schatten 1998). The GSN is more robust than WSN regarding observational conditions (e.g., Usoskin 2017). There is still a potential problem related to the grouping of individual spots, which may have been considered by earlier observers in a different manner to that currently accepted (Clette et al. 2014). This uncertainty is related to both WSN/ISN and GSN but can be fixed by redefining groups in historical sunspot drawings (Arlt et al. 2013). The GSN series produced by Hoyt & Schatten (1998) also uses the linear scaling and daisy-chaining method to reduce different data to the same reference observer, for which the RGO was chosen. The GSN is constantly scaled up by a factor 12.08 to make it comparable with the WSN series. The main advantage of the GSN series is that Hoyt & Schatten (1998) had collected and published the original database of raw data, including all the records of individual observers. This makes it possible to revise the entire series if needed. Since some corrections and additions have been recently made to this dataset, a revised database of the sunspot group numbers, separate for each observer, is published (Vaquero et al. 2016, referred to as V16 hereafter). The GSN series was revised by Svalgaard & Schatten (2016) who performed a full re-calibration of the observers using a modified daisy-chaining method with a reduced number of links (the “backbone” method). The revised backbone GSN series suggests that the level of solar activity was relatively high in the 18th and 19th centuries, much higher than that implied by the original GSN series by Hoyt & Schatten (1998) and by WSN.
Citation: Hoyt et al. 1994
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We find that, even though the physical parameters such as kTe and Ïe are very well constrained by the data, it is still impossible to formally distinguish the geometry. The slab (disk-like) and the spherical geometries, as parameterized by the compTT and compPS models used here, both describe the MCGâ05-23-016 spectrum equally well. We note that a similar result was found in observations of the Seyfert 1.2 ICÂ 4329a and the narrow-line Seyfert 1 SWIFT J2127.4+5654 with NuSTAR (Brenneman etÂ al. 2014a, 2014b; Marinucci etÂ al. 2014). Both of these AGNs and MCGâ05-23-016 are radio-quiet, however, they differ in other properties. With a mass of the super-massive black hole of â¼5 Ã 107Â M (Wandel & Mushotzky 1986), the mean intrinsic 2â10âkeV luminosity of 1.66 Ã 1043 ergÂ sâ1 (see TableÂ 1) and a bolometric correction from Marconi etÂ al. (2004), MCGâ05-23-016 is accreting at approximately 5% of the Eddington rate. This is almost an order of magnitude less than the key other two AGNs. Interestingly, SWIFT J2127.4+5654 has the lowest black hole mass and the lowest cut-off, followed by MCGâ05-23-016 in the middle, and ICÂ 4329a with highest mass and cut-off energy. In a number of other AGNs, a stringent lower limit on the cut-off energy was placed using the NuSTAR data, indicating a generally higher coronal temperature and lower optical depths, e.g., Ecut > 190âkeV in 3C 382 (Ballantyne etÂ al. 2014) and in Ark 120 (Matt etÂ al. 2014), and Ecut > 210âkeV in NGCÂ 2110 (Marinucci etÂ al. 2015). Using long-term averaged data from INTEGRAL, Malizia etÂ al. (2014) constrained cut-off energies for 26 AGNs in the range between 50 and 200âkeV, some of which have been or will be observed with NuSTAR. With more high-quality measurements in the near future, covering a wide range of physical properties, it will be possible to directly probe the physics of the AGN corona. In order to distinguish the fine differences due to the coronal geometry, longer observations of sources with a weaker reflection continuum will be needed.
Citation: Brenneman etÂ al.; 2014b
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