adsabs/FOCAL huggingface dataset:
The number of objects in a specific volume such as a sphere is called counts-in-cells (CIC) (Hubble 1936; Zwicky 1957; Balian & Schaeffer 1989). We know that in small scales, the distribution of CIC or equivalently one-point probability of the matter density field is not Gaussian and follows approximately a lognormal distribution (Coles & Jones 1991; Ueda & Yokoyama 1996). The nearly lognormal behaviour of the cosmic matter density field is a feature of evolving perturbations from the linear Gaussian inflationary initial conditions (Guth 1981; Linde 1982) to the late time non-linear and non-Gaussian distribution. Accordingly, it is informative to investigate the shape of the probability distribution of the matter density field and its evolution (Lam & Sheth 2008; Bernardeau, Pichon & Codis 2014; Uhlemann et al. 2016; Ivanov, Kaurov & Sibiryakov 2019; Mandal & Nadkarni-Ghosh 2020; Repp & Szapudi 2020b). It is worth mentioning that other interesting ideas such as an Edgeworth expansion, skewness, and kurtosis analysis are argued in this field of study (Colombi 1994; Gaztanaga, Fosalba & Elizalde 2000; Shin et al. 2017; Klypin et al. 2018; Einasto et al. 2021). On large scales, the CIC contains the same information as the two-point correlation function. But there is more information encoded in the lognormal shape of the CIC distribution on small scale. Accordingly, the cosmological dependence of the CIC statistics is interesting to be explored in mildly and strongly non-linear regimes from an observational and theoretical point of view. Uhlemann et al. (2020) showed that the measured CIC statistics are sensitive to the cosmological parameters and neutrino mass. Repp & Szapudi (2020a) used the CIC to break the degeneracy between σ8 and galaxy bias. Also, it is employed to study the primordial non-Gaussianity in LSS by measuring the fNL parameter (Friedrich et al. 2020). Recently, Jamieson & Loverde (2020) introduced an approach to use a position-dependent one-point distribution of matter density as a cosmological observable. Besides all this progress, there are some limitations. The results depend on the size and shape of the cell, where for large smoothing scales the distribution is Gaussian whereas, for small scales, the distribution is approximately lognormal. So for each cell size, one should calculate the CIC distribution, which is a computationally expensive procedure. Finally, we conclude that although the CIC is a computationally costly process, it is advantageous to explore different regimes and compare the linear and non-linear scales.
Citation: Uhlemann et al. 2016
Citation function: Motivation
When comparing the results obtained with our computational approach with the previously published decay rates, we find an overall good agreement. This is illustrated in Figs 2–5, where our calculations are compared with the experimental data reported by Salih et al. (1985), Crespo López-Urrutia et al. (1994), Mullman et al. (1998a,b) and those obtained theoretically by Raassen et al. (1998). More precisely, as shown in Fig. 2, we obtain a mean ratio of 1.036 ± 0.205 when comparing our transition probabilities with those of Salih et al. (1985), who combined lifetime values obtained by TR-LIF with branching fractions measured on spectra recorded with the 1-m Fourier-transform spectrometer at the Kitt Peak National Observatory, to deduce the decay rates for 41 transitions depopulating the 3d74p z5F, z5D and z5G levels. Fig. 3 shows a slightly larger scatter between our calculations and the transition probabilities published by Crespo López-Urrutia et al. (1994). Here the mean ratio gAThiswork/gACrespo is equal to 1.098 ± 0.493. However, it is worth noting that the gA-values obtained by the latter authors were deduced from the combination of branching ratio measurements with available experimental lifetimes for the 3d74p z5F, z5D, z5G levels (Pinnington, Lutz & Carriveau 1973; Pinnington et al. 1974; Salih et al. 1985) but also with estimated lifetimes for the z3G, z3F and z3D levels from the measurement of total intensity of all lines of each of these levels under the assumption of almost equal population. The branching fractions were found using intensity measurements with a special hollow electrode radio frequency discharge and using a phase method with a modified wall-stabilized arc in a spectrointerferometric arrangement. Mullman et al. (1998a) reported 28 oscillator strengths for ultraviolet Co ii lines deduced from laser-induced fluorescence lifetimes and branching fraction measurements using a high-resolution grating spectrometer and an optically thin hollow cathode discharge. As illustrated in Fig. 4 , our gf-values were found to agree in general within 20–30 per cent with the results obtained by Mullman et al. (1998a). More particularly, the mean ratio gfThiswork/gfMullman was found to be equal to 1.339 ± 0.552 when using all the common lines, and to 1.238 ± 0.411 when using the strongest transitions for which log gf > −1. Finally, Fig. 5 shows the comparison between our computed oscillator strengths and those published by Raassen et al. (1998) who used the theoretical method of orthogonal operators to determine the log gf-values for (3d8+3d74s)–3d74p transitions in Co ii. In this case, the two sets of data generally agree within about 20 per cent, this percentage difference being reduced to 12 per cent when considering the most intense transitions with log gf > −1. We also note that our oscillator strengths are on average larger than those obtained by Raassen et al. This could be due to the fact that these latter authors included explicitly a less extended set of interacting configurations in their model.
Citation: Pinnington et al. 1974
Citation function: Background; Background
As scattered light imaging is sensitive to the stellar irradiation, it allows one to search for misalignments between various disk regions. While studying the morphology of the innermost disk region is challenging due to its very small radial extent, often marginally resolvable by optical interferometry (Lazareff et al. 2017), scattered light imaging of the outer disk can indirectly reveal the presence of a misaligned inner disk. In this scenario, depending on the misalignment angle, the outer disk image will show narrow shadow lanes (e.g., Pinilla et al. 2015; Stolker et al. 2016; Benisty et al. 2017; Casassus et al. 2018), broad extended shadows (Benisty et al. 2018) or low-amplitude azimuthal variations (Debes et al. 2017; Poteet et al. 2018). In some cases, studies of the CO line kinematics support a misalignment between inner and outer disk regions (Loomis et al. 2017; Pérez et al. 2018). The exact origin of such a misalignment is still unclear. In the case of T Tauri stars, if the stellar magnetic field is inclined, it can warp the innermost edge of the disk, which would then rotate at the stellar period (AA Tau; Bouvier et al. 2007). Alternatively, inner and outer disk regions can have different orientations if the primordial envelope had a different angular momentum vector orientation at the time of the inner/outer disk formation (Bate 2018). Other scenarios involve the presence of a massive companion/planet that is inclined with respect to the disk. If the companion is massive enough, the disk can break into two separate inner and outer disk regions, that can then precess differently and result in a significant misalignment between each other (e.g., Nixon et al. 2012; Facchini et al. 2013; Nealon et al. 2018; Zhu 2019). A clear example of such a scenario is the disk around HD 142527, in which an M-star companion was detected (Biller et al. 2012), likely on an inclined and eccentric orbit (Lacour et al. 2016; Claudi et al. 2019). Dedicated hydrodynamical simulations successfully reproduce most of the observed features in this disk (eccentric cavity, spiral arms, misaligned inner disk and shadows; Price et al. 2018).
Citation: Stolker et al. 2016
Citation function: Background
Citation: Casassus et al. 2018
Citation function: Compare/Contrast
In the previous section, we discussed how SNe Ia with blueshifted Na i D have broader light curves but this may be driven by their preference for late-type host galaxies and their differing environments. One of the main aims of this study was to investigate, for the first time, if there is a connection between the presence of broad high-velocity Ca ii features in SNe Ia and the presence of narrow blueshifted Na i D features. As previously discussed, high-velocity Ca ii features are ubiquitous in SNe Ia and we confirm this here finding that the vast majority of the sample require a high-velocity Ca ii component. We also identify high-velocity Si ii features in 12 SNe Ia in our sample, although these features are not clearly ‘detached’ from the photospheric component. The reason that high-velocity features are interesting to investigate in connection with blueshifted Na i D features is that there are suggestions that the high-velocity Ca ii features may be at least partially due to ejecta–CSM interaction (e.g. Mazzali et al. 2005; Tanaka et al. 2006). Therefore, if a link between these quantities was identified, it would provide evidence that blueshifted Na i D features are due to CSM also rather than contamination. We remind the reader that the two probes do explore different distances from the SN, with Ca ii originating at significantly shorter distances than Na i D. However, when we examine the strength of the high-velocity Ca ii components (parametrized through the ${\rm Ca\, {\small{\rm II}}}~R_{\textrm {HVF}}$ of Childress et al. 2013a) compared to the blueshifted${\rm Na\, {\small{I}}}~\text{D}_{2}$ pEQW (15), we do not identify any clear trend between them. In particular, we also find that a number of SNe Ia with no Na i D absorption at all have very high ${\rm Ca\, {\small{\rm II}}}~R_{\textrm {HVF}}$ values, which is difficult to interpret in the context of a common CSM origin for both strong blueshifted Na i D features and strong high-velocity Ca ii components, as with this interpretation of their origin a strong signature would be expected in both probes rather than singularly. We also find no correlation between the pEQW of the high-velocity Ca ii features and the pEQW of the blueshifted Na i D features.
Citation: Mazzali et al. 2005
Citation function: Motivation; Motivation
We consider time-varying dynamical effects, breaking the assumption of a steady state, to be the most probable reason for this unexpected result. We do see how local phase-space substructures can bias our result for individual stellar samples, most clearly for those of area cell B8. However, explaining the steep gravitational potential close to the Galactic mid-plane, inferred for almost all stellar samples, requires a phase-space structure that spans the whole spatial volume that is studied in this work. Indeed, spatially large time-varying phase-space structures are present in the Galaxy, for example in the form of phase-space spirals and ridges (Gaia Collaboration 2018c; Antoja et al. 2018), and Galactic plane mirror asymmetries (Bennett & Bovy 2019, especially prominent for heights |z|≳400 pc). In order to produce a steep gravitational potential at low |z|, there could be a breathing mode in the stellar disk (Widrow et al. 2014; Monari et al. 2016) which is currently in its most compressed state. Such a configuration would not be detectable by comparing the mean vertical velocities above and below the mid-plane, because the breathing oscillation would be at a turning point between contraction and expansion. Mass estimates close to the mid-plane and under the steady state assumption would be biased towards more massive results, as the stellar disk would have a smaller scale height and larger vertical velocities. In order to explain our results, such a breathing mode would have to be large enough for the stellar number density in the mid-plane to oscillate with a relative amplitude of ∼5%. Monari et al. (2016 see for example Fig. 4) have shown that a local breathing mode could be created by a spiral arm that passes close enough to the Sun, inducing a net motion away from (towards) the Galactic mid-plane for stars on the outside (inside) of the spiral arm. Furthermore, such a close passage of a spiral arm is indicated by some dynamical models of the horizontal motions within the Galactic disk (for example Siebert et al. 2012). The dynamics of the Galactic disk are very complex and probably contains a combination of breathing and bending modes created by the last impact of the Sagittarius dwarf galaxy (for example Laporte et al. 2019); it is very plausible to think that the famous phase-space spirals in the z–w plane are a local manifestation of these larger scale perturbations. The phase-space spiral structure could have an effect on our analysis, especially for the stellar samples with higher Zlim.. On a larger scale, the bending and breathing modes of the Galaxy have been shown to affect dynamical mass measurements of the Galactic disk, especially at greater heights (Banik et al. 2017; Haines et al. 2019).
Citation: Widrow et al. 2014
Citation function: Uses; Uses
At the disc age t ≈ 1.5 Myr, the decay of 26Al has sufficiently advanced to not melt forming planetesimals and dust from the inner disc has enriched the outer disc (Ciesla 2011). At rh = 30 au, we get τ ≈ 0.1 Myr and t0 ≈ 0.5 Myr because ρ(1 au)/ρ(30 au) = 170 and 1800 in the MMSN and Nice models, respectively (Zsom et al. 2010). The number of fractals is still larger than that of pebbles of similar sizes:
(3)
\begin{equation}
N_{\rm F} / N_0 \gtrsim \exp [-(t - t_0)/\tau ] \gtrsim N_{\rm P} / N_0 \approx \phi _{\rm F} / \phi _{\rm P}
\end{equation}
with ϕF ≈ 10−5, the others being restructured into cm-sized pebbles (Weidling et al. 2009; Zsom et al. 2010). Any further pebble growth would require so longer times at so high relative speeds (Davidsson et al. 2016) to destroy or convert into pebbles all the remaining fractals. The input of dust from the inner disc triggers a streaming instability in the outer disc (Youdin & Goodman 2005; Johansen et al. 2007), lasting ≈0.1 Myr and concentrating pebbles and fractals sticking to pebbles into filaments where the comet nucleus collapses by gravity at speeds 1 m s−1 into a randomly packed (Onoda & Liniger 1990; Song, Wang & Makse 2008) aggregate of cm-sized pebbles, with the fractals stored in the voids among the pebbles (Fulle et al. 2016b). The voids fill (40 ± 5) per cent of the nucleus volume (Onoda & Liniger 1990; Song, Wang & Makse 2008). This scenario is confirmed by the pebbles observed in the pristine terrain at the final Philae landing site, which have a narrow differential size distribution (Fig. 2) peaked at diameters of $6^{+4}_{-2}$ mm (Poulet et al. 2016). For polydisperse spheres, the void volume occupies a lower percentage of the total, e.g. 32 per cent for a log-normal size distribution with a standard deviation of 0.3 (Baranau & Tallarek 2014). These facts allow us to model the 67P nucleus as composed of pebbles of the same size, with a void volume filling (37 ± 5) per cent of the total nucleus volume. A random packing of spheres does not result in the densest possible configuration, i.e. small pebbles will not always occupy available void spaces, because access to these voids is not necessarily available during the formation of the cometary nucleus.
Citation: Youdin & Goodman 2005
Citation function: Uses; Uses; Uses
Given their potentially profound impact on both the stellar and gas properties, galaxy mergers are often invoked to explain the presence of metals and low ionization species in the CGM at large impact parameters (e.g. Farina et al. 2013, 2014; Johnson, Chen & Mulchaey 2015b). Indeed, merger-induced tidal torques can give rise to observed stellar tidal features extending to many tens of kpc (e.g. Hernández-Toledo et al. 2006; Patton et al. 2011, 2013; Casteels et al. 2014). Although some gas asymmetries coexist with asymmetries in the stellar profiles of interacting galaxies, tidally induced asymmetries can persist even longer in H i gas (e.g. Lelli, Verheijen & Fraternali 2014a,b; Scott et al. 2014). Such tidal debris can potentially diffuse into the CGM contributing a significant gas and metal mass. In addition to morphological disturbances, galaxy mergers can trigger vigorous galactic outflows associated with feedback from the enhanced star formation (e.g. Martin 2005; Rupke, Veilleux & Sanders 2005a; Strickland & Heckman 2009; Hayward & Hopkins 2017) and AGN activity (e.g. Rupke, Veilleux & Sanders 2005b; Veilleux et al. 2013; Zschaechner et al. 2016; Woo, Son & Bae 2017) which can populate the CGM with metals while giving rise to multiphase absorbers (e.g. Borthakur et al. 2013; Bird et al. 2015; Heckman & Borthakur 2016; Bordoloi et al. 2017; Heckman et al. 2017). Besides, merger-induced shocks and feedback can increase the CGM's internal energy; numerical simulations of galaxy mergers show that CGM gas can be significantly heated (to X-ray emitting temperatures) through shocks and feedback processes (e.g. Cox et al. 2004, 2006b; Sinha & Holley-Bockelmann 2009). Furthermore, studies of galaxies in dense environments (higher merger probability) show different CGM properties when compared to a matched isolated galaxy sample: The CGM of galaxies in groups show distinct kinematics (Pointon et al. 2017) and ionic covering fractions (Johnson, Chen & Mulchaey 2015a; Burchett et al. 2016). Despite the possibly significant influence of galaxy mergers on the CGM, the details of the interplay between galaxy mergers and the CGM remain relatively unexplored and we are currently lacking clear and quantitative predictions of how the CGM will be affected during the merger process. Current observations of the impact of galaxy mergers on the CGM are limited to a few case studies (e.g. Keeney et al. 2011; Johnson et al. 2014). A systematic survey targeting the CGM of kinematic galaxy pairs (i.e. COS-Pairs: Bordoloi et al. in preparation) is needed to place observational constraints on the effect of mergers on the CGM.
Citation: Zschaechner et al. 2016
Citation function: Background
On the same SSA22 field, Nestor et al. (2011) and Nestor et al. (2013) show nine LBGs and 20 Lyman-α emitters (LAEs) with LyC detection out of a sample of 41 LBGs and 91 LAEs (all spectroscopically confirmed). They started from a different narrowband image centred at ~3640 Å, which is deeper than that used by Iwata et al. (2009), at ~3590 Å. A careful analysis of their LBG detections, however, shows that even in this case the LyC emission for many z ~ 3 sources is offset by 0.4–1.0 arcsec. The observed ratio between the 900 and 1500 Å rest-frame emission is difficult to reconcile with that expected by standard stellar populations (Vanzella et al. 2012a). The HST images in I814W filter available for a few of them show the presence of clearly separated galaxies, sometimes fainter at 1500 Å than in the ionizing continuum (i.e. their C16 object), with a resulting escape fraction well exceeding 1000% if estimated in the LyC position. For the majority of them, no HST imaging is available but even ground-based images often show the presence of slightly offset emission in LyC, w.r.t. the non-ionizing continuum. Similar conclusions can be reached for the Mostardi et al. (2013) sample where they adopt the same analysis as in Nestor et al. (2013). At z ~ 2.8, they found four LyC emitters out of 49 LBG galaxies and seven LyC emitters out of 91 LAEs. In this case the lack of high spatial resolution data from HST for the majority of the sample prevents any detailed analysis about possible contamination by interlopers/foregrounds. These conclusions have been strengthened by recent observations by Siana et al. (2015), who found no convincing detection in their deep HST imaging with WFC3-UVIS of five LyC emitters extracted from the sample of Nestor et al. (2011), or by Mostardi et al. (2015), who only found one robust LyC emitter after a reanalysis of a sample of 16 galaxies by Mostardi et al. (2013). More interestingly, the only robust candidate LyC emitter by Mostardi et al. (2015), the galaxy MD5b, has an observed ratio FUV/FLyC = 4.0 ± 2.0, equivalent to a relative escape fraction of 75%, when assuming complete transmission of the IGM. Instead, if a mean value of ⟨ exp(−τIGM) ⟩  = 0.4 at z ~ 3.1 is adopted, following Inoue et al. (2014), the relative escape fraction of MD5b turns out to be 188%. Imposing the constraint of a physical value for the relative escape fraction of \hbox{$f^{\rm rel}_{\rm esc}<100\%$}fescrel100%, the LoS of MD5b must be very transparent, exp(−τIGM) > 0.75, which corresponds to a probability 10-4, according to Inoue et al. (2014). This could be an indication that this galaxy is also a low-z contaminant, similar to the other cases studied by Mostardi et al. (2015).
Citation: Mostardi et al. (2013)
Citation function: Similarities
Citation: Mostardi et al. (2013)
Citation function: Similarities; Similarities
Figure 1 shows our synthetic color–magnitude diagrams (CMDs) for the two RCs at four different metallicity regimes, which are almost identical to those presented in Figure 1 of Paper I, but here (





) CMDs are added in the right panels. We recall that in our models, the fRC and bRC are produced by G1 and G2, respectively, where G1 follows the standard helium-enrichment parameter (i.e., 





), while G2 is substantially enhanced in helium abundance (Y = 0.406). Following Paper I, we have also adopted a 0.2 dex difference in metallicity between G2 and G1, and assumed 12 and 10 Gyrs for the ages of G1 and G2, respectively, with the same population ratio for the two RCs (Nataf et al. 2010; Paper I and references therein). It is evident from these models that in the metal-rich population like the bulge, highly helium-enhanced stars 





 are not placed on the very blue HB as in the metal-poor GCs, but are instead placed on the bRC. We refer the reader to Section 2 of Paper I for a detailed description of the RC features of our models at four different metallicity regimes in Figure 1. Here, we note from the (





) CMDs that the variation of the overall RC features on metallicity is similar to that in (





) CMDs. Panel (f) in (





) CMD can also naturally reproduce the observed double RC feature, i.e., ∼0.5 mag difference with almost negligible color difference between the two RCs, as is the case in panel (b) in (





) CMD. Hereafter, we refer to these models in panels (b) and (f) constructed at 





 as “





,” to distinguish them from the models with different input parameters presented below. The CMDs for these reference models, down to the MS luminosity level, are further presented in Figure 2. This figure confirms that, in the position and width of the lower red-giant-branch (RGB) and main-sequence turn-off (MSTO), our models are not inconsistent with the observed CMDs of bulge population by Clarkson et al. (2008, 2011) and Brown et al. (2010).
Citation: Nataf et al. 2010
Citation function: Uses