adsabs/FOCAL huggingface dataset:
A realistic EoS that is able to reproduce the properties of compact astrophysical objects has to fulfill several requirements. The possibility of including many particle species, which is known as multicomponent character, is of crucial importance for modeling the NS interiors, which in even the simplest treatment include neutrons, protons, and electrons, while more advanced descriptions have to account for the presence of hyperons (Schaffner-Bielich et al. 2002). Therefore, the grand canonical ensemble is the natural choice for the formulation of such an EoS. Another element of the realistic phenomenological hadronic EoS corresponds to the short-range repulsive interaction of the hard core nature between particles  (Andronic et al. 2006; Bugaev et al. 2016). Analysis of the particle yields produced in relativistic A+A collisions within statistical (thermal) models, i.e., the Hadron Resonance Gas (HRG) model (Bugaev et al. 2016), shows the importance of the particle hard core repulsion. In this approach every particle species is defined as a rigid sphere with a fixed radius estimated from experimental data analysis. These radii do not exceed 0.5 fm  (Andronic et al. 2017; Sagun et al. 2017a). Note that the hard core of hadrons in phenomenological EoSs is important in order to suppress thermal excitations of the hadronic spectrum and provide deconfinement of the color degrees of freedom expected at high temperatures/densities  (Satz 2012). Another requirement to the phenomenological EoS is related to its causal behavior when the speed of sound cannot exceed the speed of light. At sufficiently high densities this condition is violated by the hard core repulsion. As was shown by Sagun et al. (2017a), introducing the induced surface tension (IST) of particles to the model with the hard core repulsion between an arbitrary number of hadron species makes the EoS significantly softer and extends its causality range up to 7.5 normal nuclear densities, where formation of the quark-gluon plasma is expected. The IST is the key element of this approach (Sagun et al. 2014), as it allows us to account for the hard core repulsion between constituents in the most accurate way, and to properly reproduce the virial expansion of the multicomponent EoS. Recently, the IST EoS was used to describe the experimental data of hadron multiplicities measured at AGS, SPS, RHIC, and LHC energies of nuclear collisions (Sagun et al. 2017b), as well as the nuclear matter properties (Sagun et al. 2014). In this work the focus is on the application of IST EoS to the study of NS properties.
Citation: Bugaev et al. 2016
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Citation: Bugaev et al. 2016
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HCOOH is the simplest carboxylic acid and has been observed toward high-mass and low-mass star-forming regions (e.g., Woods et al. 1983; Liu et al. 2001, 2002; Bisschop et al. 2007; Lefloch et al. 2017; Oya et al. 2017; Csengeri et al. 2019), protoplanetary disks (e.g., Favre et al. 2018), pre-stellar sources (e.g., Irvine et al. 1990; Vastel et al. 2014; Jiménez-Serra et al. 2016), and comets of the solar system (Biver et al. 2014). Although the production of HCOOH has also been investigated experimentally (Ioppolo et al. 2011) and theoretically (Tielens & Hagen 1982; Garrod & Herbst 2006; Aikawa et al. 2008; Garrod et al. 2008; Vasyunin et al. 2017), its formation process and chemical link to nitrogen-bearing species are puzzling. Indeed, the chemical network calculation tracing a pre-stellar/protostellar core by Aikawa et al. (2020) indicates that nitrogen-bearing COMs and HCOOH appear in the same region (i.e., a hot core) as oxygen-bearing COMs: no differentiation is found. It should be noted that the differentiation is not ascribed to the desorption temperature of these molecules formed on grain mantles. As described in Section 4.2, the temperature of the outer envelope traced by CH3OH is 150–165 K, which is higher than that of the inner envelope traced by HCOOH and NH2CHO, 75–112 K. Hence, ice mantles containing various COMs should have already been liberated from dust grains in the outer envelope. However, the results of PCA-3D suggest that HCOOH and the nitrogen-bearing species, NH2CHO, HNCO, and HC3N, do not appear in the gas phase outside the radius of ∼0.″06, even though these desorption temperatures are comparable to those of CH3OH (e.g., Oya et al. 2019). In other words, other factors rather than the desorption temperature should be responsible for these molecules to be observed in the gas phase. It may be the high-density condition, protostellar radiation, or both of them. The gas-phase production of nitrogen-bearing COMs and HCOOH should be considered seriously.
Citation: Ioppolo et al. 2011
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N-body simulations represent the most widely used and convenient method of exploring the highly non-linear regime of cosmic structure formation. Starting from a set of initial conditions, the numerical simulations follow the formation and evolution of structures from an early epoch down to present day. Motivated by the fact that DM represents most of the matter in the Universe and because of the relatively simple physics of collisionless DM particles, DM-only simulations represent the most widely used category of numerical simulations. When designing a cosmological N-body experiment, one is concerned by two major factors. Ideally, one would like to simulate a region of the universe that is as large as possible to get a representative census of the structures encompassed within it. On the other hand, one would also want very high mass resolution, to be able to resolve accurately even the smallest cosmologically relevant objects. Unfortunately, due to limited computational resources, these two requirements are in conflict, which implies that various compromises need to be made when designing a numerical simulation. So far, the biggest efforts were focused into two, somewhat complementary approaches. The first is represented by simulations like Millennium (ms; Springel et al. 2005), Millennium II (ms-II; Boylan-Kolchin et al. 2009), Millennium XXL (MXXL; Angulo et al. 2012), Bolshoi (Klypin et al. 2011), MultiDark (Prada et al. 2012), Horizon Run I-III (Kim et al. 2009, 2011), Horizon-4π (Prunet et al. 2008; Teyssier et al. 2009), MareNostrum Universe (Gottloeber et al. 2006), Jubilee project (Watson et al. 2014), Coyote Universe (Heitmann et al. 2010), DEUS simulation (Alimi et al. 2012; Rasera et al. 2014) or MICE suite (Fosalba et al. 2015). These follow structure formation in a large cosmological volume at the expense of having a medium or a low-mass resolution. Such simulations provide the formation histories for a very large number of medium- and high-mass DM haloes, but do not necessary resolve all the details relevant for galaxy formation. On the other side we have N-body simulations like the aquarius project (Springel et al. 2008), the Via Lactea (Diemand, Kuhlen & Madau 2007), the Phoenix project (Gao et al. 2012), CLUES (Gottloeber, Hoffman & Yepes 2010) and the ELVIS suite (Garrison-Kimmel et al. 2014b) that are characterized by a very high mass and force resolution but are limited to very small cosmic volumes. These give a very detailed picture of galaxy- and cluster-size haloes, but do so only for a very limited number of objects, which makes their results sensitive to small number statistics, and are unable to capture the full interconnection between small (DM haloes) and large (the cosmic web) cosmic scales.
Citation: Boylan-Kolchin et al. 2009
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Strong controversies are however still present regarding the way stars form in gravitationally unstable cores, in particular high-mass stars. Whether it happens on approximately a free-fall time, as suggested in the competitive accretion scenario by Bonnell et al. (2001), or rather slowly, implying at least several free-fall times, in the core accretion model by McKee & Tan (2003), which assumes that turbulence and/or magnetic fields provide a major stabilizing contribution. It is therefore of central importance to obtain independent constraints on the time-scale of star formation. A potentially powerful tool that was suggested in the literature is the measurement of deuteration fractions, which may be translated into time-scales via chemical models (Caselli et al. 2002; Fontani et al. 2011; Pagani et al. 2011a; Kong et al. 2015; Barnes et al. 2016; Lackington et al. 2016). In relation to filaments, a time-scale estimate has recently been achieved by Lackington et al. (2016) for the infrared dark cloud L332. They found deuteration ratios N2D+/N2H+ in the range 0.003–0.14. Based on the chemical models by Kong et al. (2015), the authors deduced time-scales for various cores within L332 of the order of several free-fall times to match the observed deuteration fractions, indicating rather old cores. The free-fall time of their best-fitting model was tff = 1.39 × 105 yr at a density of nH = 105 cm−3. However, the authors emphasize that a change in the CO depletion factor reduces the time-scale to only one free-fall time, which points towards (dynamically) young objects. In addition, Barnes et al. (2016) deduce a chemical age of about eight free-fall times (defined for spherical systems at a density of n = 104 cm−3, giving tff = 3.4 × 105 yr) for the dark cloud G035.39-00.33 to fit the observed average deuteration fraction of 0.04 ± 0.01, which they attribute to support of the filament by magnetic fields and turbulence. Furthermore, these authors find that deuteration is widespread over the filament rather than concentrated in individual cores, in agreement with recent findings by Pillai et al. (2012) who report widespread H2D+ emission in Cygnus X.
Citation: Caselli et al. 2002
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As described in Köhler et al. (2015)2, we assume that the dust properties change with increasing local density through accretion and coagulation. First, in the transition between the diffuse ISM and dense clouds, a second mantle can form on the surface of the CM grains that is due to the coagulation of the small aromatic-rich carbon grains on top of the bigger grains, which might be subsequently hydrogenated (a-C → a-C:H) and/or to the accretion of a-C:H material from the gas phase. Such carbonaceous mantles are efficiently processed by UV photons (Alata et al. 2014), but can stay H-rich as long as the radiation field is attenuated (Jones et al. 2014) or if the rehydrogenation process is efficient enough. This leads to grains with two mantles (core/mantle/mantle grains, CMM). Second, inside dense clouds, the CMM grains can coagulate into aggregates (AMM). On average, regarding the material abundance, one aggregate is composed of three CMM grains with amorphous silicate cores and one CMM grain with an amorphous carbon core. The formation of ice mantles on the surface of the aggregates (AMMI) can also occur in the densest regions, where the shielding from energetic photons is efficient enough to allow either gas molecules to form and to freeze out on the grains or surface chemistry to proceed effectively. The three types of evolved grains (CMM, AMM, and AMMI) contain 406 ppm of C in agreement with Parvathi et al. (2012), who found that 355 ± 64 ppm of C are enclosed within grains for lines of sights where NH ≳ 2 × 1021 H/cm2 (equivalently where E(B − V) ≳ 0.4 or AV ≳ 2). For each grain type, a size distribution consistent with grain growth is considered as explained in Köhler et al. (2015) and shown in Fig. 2. For the CMM grains, ~65% of the dust mass is in grains with \hbox{$40~{\rm nm} \leqslant a \leqslant 0.25$}40 nm ⩽ a⩽ 0.25μm, ~25% in grains with \hbox{$0.25 \leqslant a \leqslant 0.5$}0.25 ⩽ a⩽ 0.5μm, and ~10% in grains with \hbox{$0.5 \leqslant a \leqslant 0.7$}0.5 ⩽ a⩽ 0.7μm. For the AMM (AMMI) aggregates, ~50% of the dust mass is in grains with \hbox{$48~(91)~{\rm nm} \leqslant a \leqslant 0.25$}48 (91) nm ⩽ a⩽ 0.25μm, ~40% in grains with \hbox{$0.25 \leqslant a \leqslant 0.5$}0.25 ⩽ a⩽ 0.5μm, and ~10% in grains with \hbox{$0.5 \leqslant a \leqslant 0.7$}0.5 ⩽ a⩽ 0.7μm. The optical properties of all grains and a detailed description of the calculation method can also be found in Köhler et al. (2015), while a more specific description of the grain scattering properties and efficiencies are given in Paper I. A schematic view of the dust composition and stratification from the diffuse ISM to dense molecular clouds is shown in Fig. 1.
Citation: Jones et al. 2014
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Analyzing optical emission lines, emanating from within the northern lobe, Tylenda et al. (2019) found a reddening with EB − V ≈ 0.9 mag or AV ≈ 2.8 mag, which we assume is mainly circumstellar in origin. Hajduk et al. (2013) observed two stars shining through the southern lobe and found AV = 3.3 − 4.4 mag with unknown contribution from the interstellar component. We assume here that those observations quantify the amount of circumstellar dust that is the main actor in shielding molecules from the central source. We recalculated the lifetimes of molecules assuming AV = 3 mag, and with (1) standard dust properties (i.e. with composition and size distribution as of interstellar dust) or (2) with larger and less opaque grains, at the gas-to-dust mass ratio of 124 (see Heays et al. 2017, for more details on the assumed dust properties). We used shielding functions from Heays et al., which include effects in lines. Results are shown in Cols. (3) and (4) of Table 3. The presence of ISM grains makes it possible for the observed molecules to survive for a very long time, longer than 350 yr. The lifetimes in the presence of the large grains considered by Heays et al. are typically a few times shorter than the age of the remnant. It is uncertain what kind of grains populate the dusty remnant of CK Vul, but given its anomalous elemental and molecular compositions and eruptive history, dust may have a peculiar chemical composition and size distribution. In such a case, the total to selective extinction law would also be different and the assumed AV may not be adequate. Nevertheless, if the molecules formed 350 yr ago and are shielded by big grains, with the calculated lifetimes a considerable fraction of molecular species would survive, except perhaps for a few most fragile ones which indeed are almost absent in the lobes. We conclude that the lifetimes in Table 3 that were calculated with an attenuated ISRF are consistent with the molecule formation 350 yr ago or more recently.
Citation: Heays et al.
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Citation: Heays et al. 2017
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Citation: Heays et al.
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In Equations (24) and (25) the cumulative effect of all ions with Zi ≥ 2 is included in the term ζ(T, f), where a (rather weak) dependence on frequency f appears due to the Gaunt factor. The ζ(T, f) function depends both on the elemental abundances and on each element’s ionization state, which are different in equilibrium and nonequilibrium conditions. In this work, we will provide the ζ(T, f) function calculated under the assumption of ionization equilibrium using the CHIANTI spectral code (Dere et al. 1997, 2019), as detailed below. In this framework it is straightforward to users to replace the CHIANTI values for the equilibrium ion fractions by their own values calculated under nonequilibrium conditions, depending on the physical process they model. We carried out the calculations for the plasma element abundances typical of the solar corona (Feldman 1992), as well as for two abundance models obtained for the solar photosphere (Caffau et al. 2011; Scott et al. 2015). The main difference between these models is that in the solar corona all elements with low first ionization potential (FIP) are overabundant by a factor of about four over their photospheric abundances. However, this overabundance factor is somewhat uncertain—while it has been extensively used in the field, its value has been suggested to vary with time (Widing & Feldman 2001) and also within the same active region; also, the absolute correction of the abundances has been disputed, as some studies suggest that the FIP effect affects both low-FIP and high-FIP ions (Schmelz et al. 2012). Furthermore, solar abundances can be different from those of other stars, both in the photosphere and in the corona, even to the point that some stars exhibit an inverse FIP effect (Laming 2015). So, the software we implemented to carry out the calculations allows the user to interactively select an abundance data set that is best suited for the star or the solar region under consideration.
Citation: Dere et al. 1997
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The effectiveness of an IRX-β relation depends on its validity for different types of galaxies across cosmic time. While the original MHC99 IRX-β relation applies to majority of galaxies, large scatters around this relation have been observed. Theoretical studies have shown that the IRX-β scatter may depend on the type of dust, gas metallicity, star formation history (SFH), dust-star geometry, and stellar population age (Popping et al. 2017; Safarzadeh et al. 2017; Narayanan et al. 2018; Schulz et al. 2020). Observations have shown that the IRX-β relation varies with stellar mass (Bouwens et al. 2016, 2020; Reddy et al. 2018; Fudamoto et al. 2020), infrared (IR) luminosity (Buat et al. 2012; Casey et al. 2014), age (Siana et al. 2009; Reddy et al. 2010; Shivaei et al. 2015), redshift (Capak et al. 2015; Pannella et al. 2015), and intrinsic β0 (β for a dust-free system; Boquien et al. 2012; Reddy et al. 2018; Schulz et al. 2020). These variations are linked to the diversity of galaxies’ attenuation curves, seen in previous studies (e.g., Kriek & Conroy 2013; Scoville et al. 2015; Battisti et al. 2020). The attenuation curve variations stem from two main sources: (a) different geometrical distributions of dust with respect to stars (and different dust optical depths), and (b) different dust grain properties, which affect the shape of the underlying extinction curve irrespective of the dust-star geometry (see the review by Salim & Narayanan 2020). While scenario (a) is extensively studied by comparing the attenuation curves of galaxies with different dust optical depths (references above), scenario (b) is less explored. Dust compositions are related to gas-phase element depletions and abundances (Jenkins 2009). Following this relation, Shivaei et al. (2020, hereafter S20) studied scenario (b) by deriving the attenuation curve of z ∼ 2 galaxies in two different metallicity (





) bins, while the dust optical depth distributions were kept the same. They found a steep SMC-like curve for galaxies with 





, and a shallower Calzetti et al. (2000, hereafter C00)-like curve at 





.
Citation: Shivaei et al. 2015
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It is likely that some of these products are also formed in our experiments, but except for CO2, HNCO, and NCO−, they cannot be unequivocally identified with IR spectroscopy alone. Some of them have the same functional groups as urea and their IR spectra present absorptions in the same spectral regions, albeit with different band shapes and intensities. They could contribute somehow to the changes, both in shape and intensity, observed in the absorption bands during processing and thus introduce uncertainty, but by analogy with the literature results just mentioned (Renoult et al. 1969; Navarro-González et al. 1989; Duvernay et al. 2005; Poch et al. 2014) we expect that the prevalent dissociation channels will lead to small molecules that will not interfere much with the absorptions of urea. It is worth noting that urea fits in an isoelectronic sequence with carbonic acid and acetone: O = C(OH)2, O = C(NH2)2, and O = C(CH3)2. Under energetic processing, carbonic acid ice has been shown to decompose into H2O and CO2 (Peeters et al. 2010), and acetone ice into CH4 and H2C2O (ketene) among other products (Hudson 2018). In a similar way, urea, the middle term in the sequence, should decompose into NH3 and HNCO. Acid base reactions could transform HNCO and NH3 into OCN− and NH4+. As indicated repeatedly in the text, HNCO and OCN− were found in our measurements, but we did not find NH3 (expected peak at 1070 cm−1, A = 1.4 × 10−17 cm molecule−1). The presence of NH4+, which has been reported by Poch et al (2014) in the photolysis of crystalline urea, is not evident in our measurements, but cannot be completely excluded. The ν4 bending mode of ammonium (A = 4.1 × 10−17 cm molecule−1; van Broekuizen et al. 2004) appears at 1440–1480 cm−1, but its exact location and bandwidth are strongly dependent on the ice environment (see discussion in Maté et al. 2009; Gálvez et al. 2010). In our case, the corresponding ammonium band, which would be the most obvious counterion for OCN−, could be masked by the νCN band of urea. Compounds of very high molecular weight do not seem to form in appreciable amounts in our experiments, since all products evaporate without leaving any residue upon warming of the substrate to 300 K during a few minutes.
Citation: Navarro-González et al. 1989
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The IRIS spectra measure the flare in a “sit-and-stare” mode with a roll angle of 45∘. The spectral scale is ∼25.6 mÅ per pixel in the far-ultraviolet (FUV) wavelengths. The IRIS slit crosses the flaring loop and one ribbon (Fig. 1). Two red bars enclose the flaring loop region used to study the quasi-periodic oscillations in this work. IRIS spectrum was pre-processed with the SSW routines of “iris_orbitval_corr_l2.pro” (Tian et al. 2014; Cheng et al. 2015) and “iris_prep_despike.pro” (De Pontieu et al. 2014). To improve the signal-to-noise ratio, we apply a running average over five pixels to the IRIS spectra along the slit (Tian et al. 2012, 2016). We also manually perform the absolute wavelength calibration using a relatively strong neutral line, O I 1355.60 Å (see De Pontieu et al. 2014; Tian et al. 2015; Tian 2017). IRIS observations show that Fe XXI 1354.08 Å is a hot (∼11 MK) and broad emission line and is always blended with many narrow chromospheric lines at the flaring ribbons (Li et al. 2015b, 2016b; Tian et al. 2015; Young et al. 2015; Brosius et al. 2016; Polito et al. 2016). However, the Fe XXI 1354.08 Å line is much stronger than those blended emission lines at the flaring loops (Tian et al. 2016). Figure 2a gives the time evolution of the line profiles of Fe XXI 1354.08 Å, averaged over the slit positions between ∼18.3″ and 21.6″. Figure 2 panels b−f show the spectral line profiles at the time indicated by the yellow lines in panel a. We can see that only the cool line of C I 1354.29 Å is blended with the hot line of Fe XXI 1354.08 Å, but its contribution is negligible. Therefore, double Gaussian functions superimposed on a linear background are used to fit the IRIS spectra at “O  I” window (Tian et al. 2016). Next, we can extract the hot line of Fe XXI 1354.08 Å, as shown by the turquoise profile. The purple profile is the cool line of C I 1354.29 Å. Two orange peaks represent the cool lines of O I 1354.60 Å and C I 1354.84 Å (Tian 2017), which are far away from the flaring line of Fe XXI 1354.08 Å. Finally, the line properties of Fe XXI 1354.08 Å are extracted from the fitting results, that is, Doppler velocity, peak intensity, and line width (Li et al. 2016b; Tian et al. 2016; Tian & Chen 2018).
Citation: Tian 2017
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Citation: Tian 2017
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Citation: Li et al. 2015b
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