adsabs/FOCAL huggingface dataset:
Among the existing IACT systems, HESS has the largest FoV and hence provides the highest sensitivity for the diffuse γ-ray flux. Its electron spectrum analysis technique could be directly used to obtain a measurement of the diffuse Galactic γ-ray flux above energies of several TeV in the Galactic Ridge (|l|  30°, |b|  2°) region; see Figs. 3 and 4. A multi-year exposure of HESS could be sufficient for detection of the diffuse emission even from regions of higher Galactic latitude. This is illustrated in Fig. 5, where thick blue and red data points show mild high-energy excesses of the electron spectra derived by Kraus (2018), Kerszberg et al. (2017), Kerszberg (2017) over broken power-law models derived from the fits to lower energy data. Comparing these excesses with the level of the IceCube astrophysical neutrino flux and with the Fermi/LAT diffuse sky flux from the region |b| > 7° (corresponding to the data selection criterium of HESS analysis Kerszberg et al. 2017; Kerszberg 2017) we find that the overall excess flux levels are comparable to expected diffuse γ-ray flux from the sky region covered by the HESS analysis (the quoted systematic error on the electron flux is Δlog(EFE) ≃ 0.4). The overall excesses within 805 and 1186 h of HESS exposures (Kraus 2018; Kerszberg 2017) are at the levels of >4σ for the analysis of Kraus (2018) and 1.7σ for the analysis of Kerszberg (2017). A factor-of-ten longer exposure (which is potentially already available with HESS) could reveal a higher significance excess at the level of up to 5σ. Such an excess is predicted in a range of theoretical models including interactions of cosmic rays injected by a nearby source (Andersen et al. 2018; Neronov et al. 2018; Bouyahiaoui et al. 2019) or decays of dark matter particles (Berezinsky et al. 1997; Feldstein et al. 2013; Esmaili & Serpico 2013; Neronov et al. 2018) or a large-scale cosmic ray halo around the Galaxy (Taylor et al. 2014; Blasi & Amato 2019).
Citation: Kraus 2018
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Citation: Kraus (2018)
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Citation: Kerszberg et al. 2017
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Citation: Kraus (2018)
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In this Letter, we directly test the relationship between proton kinetic instabilities and plasma turbulence in the solar wind using a hybrid expanding box model that allows us to study self-consistently physical processes at ion scales. In the hybrid expanding box model, a constant solar wind radial velocity vsw is assumed. The radial distance R is then 





, where R0 is the initial position and 





 is the initial value of the characteristic expansion time 





 Transverse scales (with respect to the radial direction) of a small portion of plasma, comoving with the solar wind velocity, increase ∝ R. The expanding box uses these comoving coordinates, approximating the spherical coordinates by the Cartesian ones (Liewer et al. 2001; Hellinger & Trávníček 2005). The model uses the hybrid approximation where electrons are considered as a massless, charge-neutralizing fluid and ions are described by a particle-in-cell model (Matthews 1994). Here, we use the two-dimensional (2D) version of the code, fields and moments are defined on a 2D x–y grid 2048 × 2048, and periodic boundary conditions are assumed. The spatial resolution is Δx = Δy = 0.25dp0, where 





 is the initial proton inertial length (vA0: the initial Alfvén velocity, Ωp0: the initial proton gyrofrequency). There are 1024 macroparticles per cell for protons that are advanced with a time step 





, while the magnetic field is advanced with a smaller time step 





 The initial ambient magnetic field is directed along the radial z-direction, perpendicular to the simulation plane 





, and we impose a continuous expansion in the x- and y-directions. Due to the expansion, the ambient density and the magnitude of the ambient magnetic field decrease as 





 (the proton inertial length dp increases ∝ R; the ratio between the transverse sizes and dp remains constant; the proton gyrofrequency Ωp decreases as ∝R−2). A small resistivity η is used to avoid accumulation of cascading energy at grid scales; initially, we set 





 (μ0 being the magnetic permittivity of vacuum) and η is assumed to be 





 The simulation is initialized with an isotropic 2D spectrum of modes with random phases, linear Alfvén polarization (





), and vanishing correlation between magnetic and velocity fluctuation. These modes are in the range 0.02 ≤ kdp ≤ 0.2 and have a flat one-dimensional (1D) power spectrum with rms fluctuations = 0.24 B0. For noninteracting zero-frequency Alfvén waves, the linear approximation predicts 





 (Dong et al. 2014). Protons initially have the parallel proton beta 





 and the parallel temperature anisotropy 





 as typical proton parameters in the solar wind in the vicinity of 1 AU (Hellinger et al. 2006; Marsch et al. 2006). Electrons are assumed to be isotropic and isothermal with βe = 0.5 at t = 0.
Citation: Hellinger & Trávníček 2005
Citation function: Uses
In order to understand the accretion process and the structure of emitting regions/locations in AGNs, studies of broad-band spectral energy distributions and their temporal variations are necessary. The X-ray emission is produced in the innermost region or above the accretion disc by hot electrons, i.e. corona (Ramos Almeida & Ricci 2017), where ultraviolet (UV) photons are Compton upscattered (Haardt & Maraschi 1993), which results in a power-law continuum above 2 keV. The modified blackbody emission associated with the Keplerian portion of the accretion disc peaks around optical/UV (Sanders et al. 1989; Elvis et al. 1994). Some of the emitted UV radiation is reprocessed in a structure often known as ‘dusty torus’, located around tens of pc scale environment of AGNs, and is re-emitted in infrared/mid-infrared (MIR) (Suganuma et al. 2006; Kishimoto et al. 2007; Burtscher et al. 2013; Ramos Almeida & Ricci 2017; Leftley et al. 2018). Recent studies based on infrared observations with Very Large Telescope Interferometer suggest that the distribution of dust in the torus need not to be confined in a classical thick toroidal structure but possibly originates from two components, i.e. an equatorial thin disc and a hollow dusty cone towards the polar region (see Hönig & Kishimoto 2017; Stalevski et al. 2017, 2019). The hollow dusty cone is probably due to the puffed-up disc caused by the infrared radiation pressure, which releases the inflowing gas from the gravitational potential of the black hole (Hönig 2019). This structure is considered to be an extended polar feature probably from a dusty wind located at the edge of the NLR (López-Gonzaga et al. 2014; López-Gonzaga et al. 2016; Honig & Kishimoto 2017; Stalevski et al. 2017; Leftley et al. 2018). The MIR radiation is also considered to be emitted from this non-classical torus structure (Asmus et al. 2016) and the spectrum is often modelled by a warm component with a blackbody temperature around 300 K (e.g. Edelson & Malkan 1986). The orientation of the dusty molecular obscuring torus plays a key role in the characterization of the distinct classes of AGNs in the unification scheme (for more detail see, Antonucci 1993; Urry & Padovani 1995; Netzer 2015).
Citation: Kishimoto et al. 2007
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In addition to being an important participant in the evolution of galaxies, dust absorption and scattering can significantly alter the appearance of its host galaxy. Dust can absorb a large fraction of the total UV and optical energy emitted in a galaxy and re-radiate it in the IR. The absorbed energy can be re-radiated through several physical processes, each with different observational signatures. Dust emission in the far-IR (FIR) comes from equilibrium heating of dust grains and can be approximately described with a featureless modified blackbody function. However, rich spectral features that are commonly attributed to polycyclic aromatic hydrocarbons (PAHs) seen in the mid-IR emission (Leger & Puget 1984) arise predominantly in a nonequilibrium, single photon, process. Both the broad, featureless FIR and the spectral features of the mid-IR correlate with other galaxy properties, providing insight into the underlying physical processes operating within the galaxy. In local starburst galaxies Engelbracht et al. (2008) found that the equivalent width of the 8 μm aromatic emission complex negatively correlates with the radiation field hardness and positively correlates with metallicity. Gordon et al. (2008) further found that the former correlation is stronger than the latter in M101 H ii regions, suggesting that the variation in the strength of aromatic emissions is due to dust processing, rather than differences in dust formation. The ratio of the total infrared flux (TIR) to the far-UV (FUV) flux correlates with UV spectral slope, β (while the correlation holds for a general definition of TIR, FUV, and β, see e.g., Meurer et al. 1995; Kong et al. 2004 for specific definitions), both across galaxies and within galaxies (Meurer et al. 1995; Calzetti et al. 2005). While the relation is tight for starburst galaxies (Meurer et al. 1999), significant scatter exists for normal star-forming galaxies (Bell 2002). Kong et al. (2004) found that higher β values at a given IR to UV ratio in more quiescent star formation galaxies can be explained in terms of the balance between present and past averaged star formation rate (SFR). Given that β is commonly measured from the Galaxy Evolution Explorer (GALEX) FUV and near-UV (NUV) bands and that the NUV band captures the 2175 Å extinction feature, variation in the 2175 Å feature strength can have a profound impact on β, but separating such variations from the intrinsic behavior of β is challenging with empirical methods.
Citation: Leger & Puget 1984
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As the most luminous persistent sources in the Universe, quasars are bright enough to be detected up to redshifts z > 7 (Mortlock et al. 2011; Banados et al. 2018; Wang et al. 2018; Yang et al. 2020). According to the currently accepted model, quasars are extremely luminous active galactic nuclei (AGNs), where the observed intense energy release are related to the accretion of a gaseous disk onto a supermassive black hole (SMBH). Quasars have a wide spectral energy distribution, which normally contains a significant emission component in the optical-UV band LUV, the so-called big blue bump, with a softening at higher energies (Sanders et al. 1989; Elvis et al. 1994; Trammell et al. 2007; Shang et al. 2011). It has long been discussed that there is a nonlinear relationship between LUV and the quasar’s X-ray luminosity LX, parametrized as log(LX) = γlog(LUV)+β (Vignali et al. 2003; Strateva et al. 2005; Steffen et al. 2006; Just et al. 2007; Green et al. 2009; Young et al. 2010; Jin et al. 2012). From the theoretical point of view, this relation could be intrinsic since the UV emission is usually thought to originate from the optically thick disk surrounding the SMBH and the X-ray photons are thought to be generated through the inverse-Compton scattering of these disk UV photons by a plasma of hot relativistic electrons (the so-called corona) around the accretion disk. Such a relation is found to be independent of redshift (Lusso & Risaliti 2016), so that it could be used as a distance indicator to estimate cosmological parameters. The initial dispersion of the LUV − LX relation is relatively large (δ ∼ 0.35−0.4, Just et al. 2007; Young et al. 2010), but after a detailed study, Lusso & Risaliti (2016) suggest that most of the observed dispersion is not intrinsic, but it is rather due to observational effects. By gradually refining the selection technique and flux measurements, Risaliti & Lusso (2019) collected a complete sample of quasars, whose dispersion of the LUV − LX relation is smaller than 0.15 dex. The sample of main quasars is composed of 1598 data points in the range from 0.036  z  5.1. With this sample, they constructed a Hubble diagram of quasars in redshift range of 0.5  z  5.5, which is in excellent agreement with the analogous Hubble diagram for SNIa in the redshift range of 0.5  z  1.4. Moreover, this Hubble diagram of quasars has been studied in cosmological applications (Zheng et al. 2020, 2021). Considering that objects at the same redshift should have the same luminosity distance in any cosmology, here we first fit the model-independent cosmography formula that reflects the Hubble relation between the luminosity distance and redshif using the quasar sample, and then we obtained the distance moduli (also the luminosity distance) for GRBs at a given redshift with the best fit results.
Citation: Just et al. 2007
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Supernova explosions must be another promising source of gravitational waves. The gravitational waves from a core-collapse supernova have been mainly discussed with the numerical simulations of gravitational collapse of massive star, the bounce of central core, and subsequent accreting matter to the central compact object, i.e. protoneutron star (PNS), produced via supernova (e.g. Murphy, Ott & Burrows 2009; Cerdá-Durán et al. 2013; Müller, Janka & Marek 2013; Ott et al. 2013; Yakunin et al. 2015; Kuroda, Kotake & Takiwaki 2016; Andresen et al. 2017; O’Connor & Couch 2018). For instance, the three-dimensional (3D) numerical simulations for the core-collapse supernova tell us the existence of gravitational wave signals related to the oscillations of PNS (or core region) (Kuroda et al. 2016; Andresen et al. 2019; Radice et al. 2019; Mezzacappa et al. 2020), where the frequency increases with time from a few hertz up to kilohertz after corebounce. This signal is originally considered to be the evidence of the Brunt–Väisälä frequency at the PNS surface, i.e. the so-called surface gravity (g) mode (Cerdá-Durán et al. 2013; Müller et al. 2013), but it may be natural to consider that the signals come from the global oscillations of the PNSs because the Brunt–Väisälä frequency is a local value and depends strongly on the definition of PNS radius. In fact, the gravitational wave signals appearing in the numerical simulations can be identified with the global oscillations, such as fundamental (f-mode) oscillations of PNS (Morozova et al. 2018; Sotani et al. 2019a; Sotani & Takiwaki 2020b, c) or the g-mode-like oscillations in the region inside the shock radius (Torres-Forné et al. 2018, 2019a,b). In addition to the ramp up signals, the 3D simulations tell us the existence of another gravitational wave signal with ∼100 Hz, which seems to be associated with the standing accretion-shock instability (Kuroda et al. 2016; Andresen et al. 2017, 2019; O’Connor & Couch 2018; Radice et al. 2019; Mezzacappa et al. 2020).
Citation: O’Connor & Couch 2018; O’Connor & Couch 2018
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The fate of the early PWN depends on various parameters such as the spin-down power and baryon loading. If the spin-down power is high enough, some two-dimensional simulations suggest that the equatorial wind can be redirected by the anisotropic pressure, and hoop stresses lead to bipolar outflows10

10
In this case, the (collimated) wind radius is 





.
 that could explain GRBs (Bucciantini et al. 2007, 2008; Komissarov & Barkov 2007). If not, we expect a quasi-spherical expanding flow embedded in the expanding stellar material (see Figure 1). Assuming a SN explosion with 





 erg, the SN ejecta expands with its velocity 





 and radius 





. The early PWN radius Rw also increases non-relativistically, which is given by (e.g., Metzger et al. 2014)
7





for 





, otherwise 





 is used. Note that we have used the ejecta density
8





where δ ∼ 0–1 is a typical value used in the literature (Kasen & Bildsten 2010; Metzger et al. 2014). The mixture of material allows us to approximate the inner density profile to be reasonably smooth and flat (Chevalier 1977; Chevalier & Fransson 1992). For demonstration, we adopt 





 throughout this work (Kasen & Bildsten 2010; Metzger et al. 2014), and that the radiation pressure is given by 





. Here 





 is the PWN volume and 





 is the PWN expansion velocity that can be different from 





 In general, Rw is smaller than 





, and both of 





 and Rw are numerically determined in this work. Roughly speaking, 





 becomes a good approximation for small values of P such that 





 (implying 





). The ejecta velocity 





 and radius 





 can be determined by
9







10





The internal energy trapped in the SN ejecta, 





, is given by
11





where 





 is the dynamical time. Since X-ray and gamma-ray emission is expected in month-to-year timescales, we only consider energy injection due to 





. In the early phase, as in normal SNe, heating by shocks and unstable isotopes such as 





Ni can be relevant. In the later phase, one may assume that late interactions with circumstellar material are negligible, and injections via the β decay of 





Ni are irrelevant after their lifetime 





. Visible photons leave the SN ejecta in the escape time
12





where the Thomson optical depth in the ejecta is given by 





, which is estimated to be
13





where 





, 





 is the mean molecular weight per electron, and mu is the atomic mass unit. See also Equation (45) below. Two of the key parameters, 





 and 





, can be estimated from the SN peak emission and determination of the ejecta velocity 





 via detailed spectroscopy. Note that the bound–free or bound–bound cross section is much higher at 





 keV energies, and thermal photons are still generated at later times.
Citation: Chevalier 1977
Citation function: Uses
The electronic computations were performed using the molpro (Molpro 2015, http://www.molpro.net) package. In a preliminary work, we used the complete active space self-consistent field (Knowles & Werner 1985; Werner & Knowles 1985) to examine the electronic wavefunction of the HNCO–He complex. These computations showed that this wavefunction is dominantly described by a unique electron configuration (with a weight ≥0.93) over the grid used for the generation of this PES. This justifies hence the use of monoconfigurational ab initio methods. Accordingly, we applied the recently established methodology by Hochlaf and co-workers for mapping multidimensional PESs of weakly bound molecular systems with high accuracy and relatively low computational cost (Lique, Klos & Hochlaf 2010; Halvick et al. 2011; Ajili et al. 2013; Mathivon, Linguerri & Hochlaf 2013; Kalugina et al. 2014; Mogren Al Mogren et al. 2014). Briefly, these electronic computations were carried out using the explicitly correlated coupled cluster method with single, double and perturbative treatment of triple excitations (CCSD(T)-F12) (Adler, Knizia & Werner 2007; Knizia, Adler & Werner 2009) in connection with the augmented correlation-consistent aug-cc-pVTZ basis set of Dunning and co-workers (Dunning 1989; Kendall, Dunning & Harrison 1992). In addition, molpro default choices for the density fitting and resolution of identity basis sets have been applied (Yousaf & Peterson 2008). Benchmarks by Hochlaf and co-workers (Lique et al. 2010; Halvick et al. 2011; Ajili et al. 2013; Mathivon et al. 2013; Kalugina et al. 2014; Mogren Al Mogren et al. 2014) showed that results obtained from this highly correlated approach are close to those deduced using standard coupled cluster techniques extrapolated to the complete basis set (CBS) limit, whereas a strong reduction in CPU time and disc occupancy are observed. For illustration, we performed CCSD(T)/aug-cc-pVXZ calculations (X = D, T, Q, 5) on the HNCO—He cluster. Then the energies were extrapolated to the CBS limit. The comparison between CCSD(T)-F12/aug-cc-pVTZ and CBS calculations is given in Table 1. It shows that the CCSD(T)-F12/aug-cc-pVTZ results are off by 4 per cent (at the maximum) with those deduced from CBS extrapolation. We compare also our results with those done using the CCSD(T)/aug-cc-pV5Z approach. We can clearly see that the CCSD(T)-F12/aug-cc-pVTZ approach offers a good agreement with the CCSD(T)/aug-cc-pV5Z calculations with a very reduced computational cost.
Citation: Kalugina et al. 2014
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Citation: Knizia, Adler & Werner 2009
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NLFFF models have been widely adopted to study magnetic field structures in the solar atmosphere, for instance, magnetic flux ropes (Canou et al. 2009; Su et al. 2009; Canou & Amari 2010; Cheng et al. 2010; Guo et al. 2010a, 2010b; Jing et al. 2010), magnetic null points (Zhang et al. 2012; Sun et al. 2013, 2014), and quasi-separatrix layers (Savcheva et al. 2012, 2015; Guo et al. 2013; Zhao et al. 2014; Yang et al. 2015). Most of them are modeled in Cartesian coordinates, although some models are reconstructed in spherical geometry (Su et al. 2009; Tadesse et al. 2011; Guo et al. 2012) or with tetrahedral meshes (Amari et al. 2014b). In particular, Amari et al. (2014a) has developed another code to fulfill the need for reconstructions on the scale of local active regions within a global extrapolation, using an iterative Grad–Rubin scheme adapted to spherical coordinates. Such a state-of-the-art code resolves an active region in a global model with 





 grid points. This contrasts to most earlier modeling efforts, which were limited either to a small field of view (for Cartesian coordinates) or to lower spatial resolution (for spherical coordinates) due to limited computational resources. The data volume and the computation time increase for NLFFF modeling with a large field of view and high spatial resolution simultaneously, which implies a big data problem. On the other hand, we have to use data with high spatial resolution to resolve the small-scale features of the magnetic field, such as small flux tubes and electric current channels. They are crucial for reconstructing the non-potential magnetic field. We also have to consider a field of view as large as possible to include remote magnetic field connections (DeRosa et al. 2009). Since only the bottom boundary is available at present for realistic NLFFF modeling, the magnetic field concentration should be isolated to mitigate any effects of lateral boundary conditions (Wiegelmann et al. 2006). An isolated magnetic field region has magnetic field lines originating from the bottom boundary and connecting back to the bottom. A large field of view is required to fulfill this requirement of having an isolated magnetic domain. When the field of view is large, the curvature of the Sun cannot be neglected and spherical coordinates are recommended (e.g., Guo et al. 2012; Yeates 2014).
Citation: Guo et al. 2012; Guo et al. 2012
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