adsabs/WIESP2022-NER huggingface dataset:
Paper: 2020MNRAS.495.3929P (fulltext)
concept beyond one dimension (1D) or to unstructured/meshfree methods is less clear (e.g. Chiapolino, Saurel Nkonga 2017 ). A physical interpretation can be seen from our equation ( 6 ). For the drag term to provide a positive definite contribution to the entropy, and must have the same sign, such that d u /d t | drag is positive. Pairwise positivity is not strictly necessary so long as the sum over all neighbours is positive. We tried setting if the signs differ, but found this to be more dissipative than using slope limiters (see Fig. 3 ). We found the van Leer MC limiter to provide the best compromise between monotonicity and dissipation. 3 RESULTS We test our improved algorithm in 1D using the ndspmhd code (Price 2012 ) and in 3D using phantom (Price et al. 2018 ). We use explicit global time-stepping with a leapfrog integrator, the M 6 quintic kernel for the SPH terms with the double hump M 6 employed for the drag terms ( LP12a ). The results are not sensitive to the choice of kernel, provided a double hump kernel is used for the drag. The time-step was set to 0.9 times the minimum stopping time (we found that setting Δ t = t s exactly as in LP12a could result in instability with reconstruction). We use the van Leer MC limiter unless otherwise specified. 3.1 DUSTYWAVE Fig. 1 shows the results of the dustywave described in Laibe Price ( 2011 ), performed using 2 × n x particles with a fixed drag coefficient K = 1000, ρ g = ρ d = 1 and c s = 1 (giving t s = 5 × 10 −4 ) and a perturbation amplitude of 10 −6 . We use an adiabatic equation of state P = ( γ − 1) ρu with γ = 5/3 in the gas. In the absence of reconstruction, overdamping occurs when h ≳ c s t s , i.e. for n x ≲ 1024 (left-hand column), as found by LP12a . Adding reconstruction captures the true solution to within a few per cent for n x ≳ 64 (middle column), while the slope limiter does not visibly degrade it (right-hand column). Figure 1. Dust and gas velocities in the dustywave test after 10 wave periods, using K = 1000 with 2 × n x particles without reconstruction and with and without the slope limiter (see labels). Reconstruction avoids the need to resolve h ∼ t s c s (resolved at n x = 1024 particles). Exact solution shown in red. Fig. 2 shows the results in 3D using phantom . We follow the procedure used in Price et al. ( 2018 ), placing the particles using dense sphere packing and cropping the grid in the y and z directions at 12 particle spacings (for efficiency), giving 2 × 128 × 12 × 12 particles. The results in 3D are indistinguishable from those shown in Fig. 1 , showing our method also works in 3D. Figure 2. As in Fig. 1 , but in 3D with phantom using n x × 12 × 12 gas particles (solid) and n x × 12 × 12 dust particles (open) initially placed using dense sphere packing. Exact solution from Laibe Price ( 2011 ) shown in red. 3.1.1 Choice of slope limiter Fig. 3 shows the kinetic energy as a function of time in the 1D dustywave problem at a resolution of n x = 128. The
Paper: 2019A&A...623A..13T (acknowledgments)
Acknowledgements This article was supported by the realization of the Project ITMS No. 26220120029, based on the supporting operational Research and development program financed by the European Regional Development Fund. The work was also supported in part by the Slovak Grant Agency for Science, VEGA, grant No. 2/0037/18, and by the Slovak Research and Development Agency under contract No. APVV-16-0148.
Paper: 2019ApJ...885..138S (fulltext)
et al. 2018 ). A common assumption involves the population of states, which, in the absence of knowledge to the contrary is assumed, for want of other choices , to be Maxwellian with density and temperature as parameters. This type of inversion is used to produce impressions of the temperature in plasmas far removed from the observer. A rather general argument is presented here that this mode of inverting photon information has a systematic bias by presuming the Maxwellian eVDF of the LTE when inferring the population of states involved in the line’s formation. A suggested alternative is presented based on this paper’s Steady Electron Runaway Model (SERM). Modeling astrophysical plasmas often involves solving the fluid-scale magnetohydrodynamical (MHD) equations. Within the derivation of the MHD fluid equations from the kinetic equations and their closure are further hidden assumptions of LTE (Hazeltine Walbroeck 2004 ) that are generally unwarranted on the same large scales of the modeling. These hidden assumptions also preempt consideration of non-LTE types of physics from occurring in such models (Scudder 1992 ; Meyer-Vernet et al. 1995 ). Barring improvements that do not make these small Knudsen number LTE approximations, this compromised modeling continues (Scudder 2019a ). To move beyond these (hidden) reliances on LTE requires the formulation of an alternative that challenges the likelihood that the Maxwellian eVDF is the most likely one to occur in the regions under study. To be sure, considering this possibility faces considerable resistance best redressed by studying plasmas with in situ experimental access, such as the solar wind as presented here. There finite is clearly common, and this paper argues that this parameter (or its dimensionless parallel electric field cousin) is the central index of the importance of non-Maxwellian eVDF’s that is explored in this paper. The present calculation and its comparison with solar wind measurements furthers the description of transport in plasmas with finite Knudsen number, , quantitatively defined bywhere is the local magnetic field-aligned unit vector. A fully defined Knudsen number associated with χ depends on the mean free path for scattering, , and the magnetic field-aligned scale, L , of χ . The pressure profile usually has the steepest gradient, determining the shortest transport scale L ; it thus determines the relevant for the mean free path over scale that enters as a small perturbative parameter in Chapman–Enskog closures (Chapman 1916 ; Enskog 1917 ), which are also discussed in Chapman Cowling ( 1939 ), Rossi Olbert ( 1970 ), Fitzpatrick ( 2004 ), and Zank ( 2014 ). Spitzer and Braginskii use slightly different versions of these expansions (Spitzer Harm 1953 ; Braginskii 1965 ). Between 0.3 and 5 au the observed solar wind plasma electrons possess . At 1 au (Scudder 2019b ). In all speed states of the wind “ubiquitously nonthermal” eVDF have been observed over the last 50
Paper: 2017MNRAS.466.2547B (acknowledgments)
Acknowledgments M. Brouwer and M. Visser would like to thank Erik Verlinde for helpful clarifications and discussions regarding his EG theory. We also thank the anonymous referee for the useful comments that helped to improve this paper. The work of M. Visser was supported by the European Research Council (ERC) Advanced Grant 268088-EMERGRAV, and is part of the Delta Institute for Theoretical Physics (ITP) consortium, a program of the Netherlands Organisation for Scientific Research (NWO). M. Bilicki, H. Hoekstra and C. Sifon acknowledge support from the ERC under FP7 grant number 279396. K. Kuijken is supported by the Alexander von Humboldt Foundation. M. Bilicki acknowledges support from the NWO through grant number 614.001.103. H. Hildebrandt is supported by an Emmy Noether grant (No. Hi 1495/2-1) of the Deutsche Forschungsgemeinschaft. R. Nakajima acknowledges support from the German Federal Ministry for Economic Affairs and Energy (BMWi) provided via DLR under project no. 50QE1103. Dominik Klaes is supported by the Deutsche Forschungsgemeinschaft in the framework of the TR33 The Dark Universe. This research is based on data products from observations made with ESO Telescopes at the La Silla Paranal Observatory under programme IDs 177.A-3016, 177.A-3017 and 177.A-3018, and on data products produced by Target OmegaCEN, INAF-OACN, INAF-OAPD and the KiDS production team, on behalf of the KiDS consortium. OmegaCEN and the KiDS production team acknowledge support by NOVA and NWO-M grants. Members of INAF-OAPD and INAF-OACN also acknowledge the support from the Department of Physics and Astronomy of the University of Padova, and of the Department of Physics of Univ. Federico II (Naples). GAMA is a joint European-Australasian project based around a spectroscopic campaign using the Anglo-Australian Telescope. The GAMA input catalogue is based on data taken from the Sloan Digital Sky Survey and the UKIRT Infrared Deep Sky Survey. Complementary imaging of the GAMA regions is being obtained by a number of independent survey programs including GALEX MIS, VST KiDS, VISTA VIKING, WISE , Herschel -ATLAS, GMRT and ASKAP providing UV to radio coverage. GAMA is funded by the STFC (UK), the ARC (Australia), the AAO and the participating institutions. The GAMA website is www.gama-survey.org . This work has made use of python ( www.python.org ), including the packages numpy ( www.numpy.org ), scipy ( www.scipy.org ) and ipython (Prez Granger 2007 ). Plots have been produced with matplotlib (Hunter 2007 ). All authors contributed to the development and writing of this paper. The authorship list is given in three groups: the lead authors (M. Brouwer and M. Visser), followed by two alphabetical groups. The first alphabetical group includes those who are key contributors to both the scientific analysis and the data products. The second group covers those who have either made a significant contribution to the data products or to the scientific analysis.
Paper: 2018ApJ...867...84G (fulltext)
could be adjusted, but should not be orders of magnitude lower or the jet would not be observed in the EUV given the TRACE 195 Å response and reasonable temperatures. For the closed loop, the thermal density is taken to be cm −3 . Values larger than this would violate three observational constraints: (1) 195 Å emission would be stronger than observed for all reasonable coronal (including flaring) temperatures; (2) SXR emission would be stronger than is observed; and (3) the microwave spectrum would be dominated by a free–free component, which would not match the observed microwave spectral shape. The density could be smaller but would require adjustment of the loop geometry; therefore, there is a range of thermal densities that could fit the observed data. For the likely value of 1 × 10 10 cm −3 for the jet density, a temperature of 2.05 MK fits the measured TRACE 195 Å emission from the jet location. As the TRACE 195 Å temperature response function (Handy et al. 1999 ) decreases for all higher temperatures, a higher density would be required for any jet temperatures higher than this (and would violate the density constraint from microwave data mentioned earlier). For the closed loop, a density of cm −3 can produce the observed 195 Å brightness at the jet base, where this loop is located, for a temperature between 7.3 and 10.6 MK. Since the plasma temperature is not constrained within this range, we choose a temperature of 7.3 MK. For the nonthermal electrons in the jet, the microwave spectrum deviates from observations if the upper cutoff to the electron energy E max is below ∼300 keV; it is not well constrained from above. Further decrease of this parameter could be compensated by an increase of the source area, but this would be in conflict with the microwave source size. For the closed loop, the microwave spectrum deviates from observations if . In the model we use . 4. Discussion To recap the observations, we find high time variability in HXRs and microwaves, with HXR spectral hardening strongly correlated with fast bursts of intense flux. HXR images are dominated by the flaring (thermal) loops at low energies and (nonthermal) footpoints at high energies, but at intermediate energies (∼18–30 keV), some RHESSI emission is elongated along the jet, where OVSA data also reveal an elongated microwave source at the location of the jet. We interpret the fast HXR spikes as bursts of particle acceleration, and the duration of these peaks gives the timescale over which electrons are accelerated. The very short time lag between the burst intensity and its hardening (less than 200 ms in the case of G1 and no lag in the case of G2) implies that electrons are accelerated quickly to ∼100 keV. Combining the time lag from Figure 4 with the peak width from Figure 5 , we conclude that the event exhibits electron energy increases on an average timescale of 0.2 s, with acceleration episodes lasting, on average, 1 s. Once accelerated, the electrons that have
Paper: 2016MNRAS.461L..16M (fulltext)
has delayed or is preventing prodigious star formation in the Brick? Dynamical arguments, such as its highly turbulent nature (Kauffmann, Pillai Zhang 2013 ; Johnston et al. 2014 ; Rathborne et al. 2015 ) or its apparent location within a coherent ring-like stream of molecular clouds in orbit about Sgr A* (Molinari et al. 2011 ; Longmore et al. 2013 ; Kruijssen et al. 2015 ) have been cited as possible agents of star formation suppression. In order to set more stringent constraints on the level of star formation activity, it would seem worthwhile to examine other possible indicators, such as the presence of localized peaks in dust temperature that might signal the presence of protostars at early stages of evolution. With this in mind, we present here the results of a detailed study of the variation of dust temperature within the cloud. Studies of the temperature structure of the Brick show that the gas temperature is uniformly higher than the dust temperature and that those two components are heated by different mechanisms. The observed dust temperatures of T D ∼ 19–27 K (Longmore et al. 2012 ) are consistent with heating by the local interstellar radiation field (ISRF), assuming that the latter is ∼1000 times stronger than that in the solar vicinity (Clark et al. 2013 ). However, the gas (Güsten, Walmsley Pauls 1981 ; Mills Morris 2013 , T G ∼ 60–100 K) is most likely heated by a combination of cosmic rays (Clark et al. 2013 ) and turbulent compression (Ginsburg et al. 2016 ), with the former dominating at high densities. Our study of the dust temperature distribution makes use of the PPMAP procedure (Marsh, Whitworth Lomax 2015 ), whose purpose is to generate resolution-enhanced image cubes of differential column density as a function of dust temperature, T D , and sky position ( x , y ), given sets of observed images of dust continuum emission at multiple wavelengths. Differential column density, in this case, is defined as the column density of material (gas plus dust) per unit interval of dust temperature, and is expressed in units of hydrogen molecules per square centimetre per degree Kelvin. PPMAP is a Bayesian technique whose output is the expectation value of the differential column density in each cell of an image cube whose axes are ( x , y , T D ), given the input data. The a priori probability of cell occupancy is controlled by a ‘dilution’ parameter, η, such that the smaller the value of η, the more the algorithm tries to fit the data with as few source components as possible. The exact value of η is not critical, but the most appropriate value is one which results in a reduced chi-squared value of the order of unity, indicating that the data have been fit within the error bars using a minimum number of source components. The procedure also yields a corresponding image cube of uncertainty values. Errors are Poisson-like, and increase in regions of high total column density. A key underlying assumption is that the dust is
Paper: 2021ApJ...908L..42F (fulltext)
elemental-abundance ratios ([X/Fe]) were derived with the BACCHUS code. Table 1 Atmospheric Parameters and Elemental Abundances of Stars in VVV CL001 Note. The errors were determined in the same manner as described in Fernández-Trincado et al. ( 2020a ) by varying the atmospheric parameters one at a time by the typical, albeit conservative, values of Δ T eff = ±100 K, g = ±100 cgs, and Δ ξ t = ±0.05 km s −1 . Thus, the reported uncertainties are defined as . Figure 2 shows the good quality of the APOGEE-2 spectrum compared to the best-fit synthetic spectra for selected atomic and molecule lines of the two stars in VVV CL001, from which the chemical-abundance ratios were determined. For each spectrum we were able to identify reliable lines for six chemical species (N, O, Mg, Al, Si, and Fe). The same figure also reveals the scarcely detectable Fe i lines. The resulting elemental-abundance ratios are listed in Table 1 . Figure 2. Detection of atomic and molecular lines. Spectral synthesis is shown for the determination of the [N/Fe], [O/Fe], [Mg/Fe], [Al/Fe], [Si/Fe], and [Fe/H] abundances for two stars in the innermost regions of VVV CL001. Each panel shows the best-fit syntheses (red line) from BACCHUS compared to the observed spectra (black squares) of selected lines (black arrows). The resulting chemical abundances are also displayed in Figure 3 , and compared to four GCs at similar metallicity taken from the APOGEE-2 GC sample of Mészáros et al. ( 2020 ). We find that the two program stars exhibit an iron abundance ratio of −2.47 to −2.44, suggesting that VVV CL001 has a mean metallicity [Fe/H] = −2.45, with an uncertainty due to systematics of 0.24 dex, which makes this cluster possibly the most metal-poor GC identified so far within the Sun’s Galactocentric distance, and with an extreme metallicity close to the apparent “floor” in the empirical metallicity distribution function for GCs in the MW and Local Universe (e.g., Geisler et al. 1995 ; Simpson 2018 ; Kruijssen 2019 ; Larsen et al. 2020 ; Wan et al. 2020 ). Note that VVV CL001 has the lowest Fe abundance among this sample, which includes the lowest metallicity GCs observed by APOGEE. With our limited sample, we do not find evidence of an intrinsic Fe-abundance spread. Figure 3. Elemental abundance of stars in VVV CL001 (black symbols) and four comparison metal-poor GCs. Each violin representation show the univariate kernel density estimate of the abundance ratios of each cluster as determined from Mészáros et al. ( 2020 ). Each GC has been slightly offset horizontally to distinguish them. Regarding the α -elements (O, Mg, and Si), VVV CL001 displays a modest α -element enhancement, a clear signature of the fast enrichment provided by SNe II events, and compatible with other Galactic metal-poor GCs at similar metallicity (see Figure 3 ). Furthermore, no Mg–Al anticorrelation is evident in our small sample; the two VVV CL001 stars exhibit an aluminum deficit, which places them within
Paper: 2016MNRAS.458.2848J (acknowledgments)
We are grateful to Peter Behroozi, for updating the Bolshoi halo catalogue upon our request, to Hao-Yi Wu for sharing data from the Rhapsody simulation project, and to the anonymous referee for an insightful report that greatly helped to improve the presentation. We also thank the organizers of the programme ‘First Galaxies and Faint Dwarfs: Clues to the Small Scale Structure of Cold Dark Matter’ held at the Kavli Institute for Theoretical Physics (KITP) in Santa Barbara, for creating a stimulating, interactive environment that started the research presented in this paper, and the KITP staff for all their help and hospitality. This research was supported in part by the National Science Foundation under Grant No. PHY11-25915.
Paper: 2017ApJ...846...19R (acknowledgments)
The National Radio Astronomy Observatory is a facility of the National Science Foundation operated under cooperative agreement by Associated Universities, Inc. T.B. acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 714769.
Paper: 2021MNRAS.505.5183R (fulltext)
can be constrained to be From this equation, we can satisfy the observed mass scale () using reasonable θ and ε values. Although the individual parameters are still uncertain, the calculation shows that the gravitational contraction could release sufficient kinetic energy to account for the observed gas motion. Figure 4. A zoom-in of the PV plot along the three filaments. (a) The systemic velocity map showing the PV cuts. (b)–(d) The PV plot along the three directions. For each filament, the offset is measured from the MMS-7 centre. The solid line represents the v ( r ) function that closely goes through the spine of the PV emission region. The v ( r ) function is calculated from equation ( 5 ). The two dashed lines represent the v ( r ) curves with c 0 varying by a factor of 0.5 and 2, respectively. In (b) and (d), the red solid line denotes the central velocity variations along the PV sampling direction. 4.3 Velocity variations Despite the agreement in energy budget, the velocity distribution still has two features deviating from the modelled v ( r ) curves that should be further examined. First, the theoretical v ( r ) function will approach infinity towards the centre, while the observed velocity profiles are terminated at final velocities around the centre. For the NW filament (Fig. 4b ), the velocity profile reaches the maximum value in the area of r 4 arcsec around the centre. This area is comparable to the size of MMS-7 core ( r = 3.7 arcsec). As a reasonable explanation, this energy release of could be largely transferred to MMS-7, accelerating this core as an entire body to the final velocity. Second, although the three filaments have a similar velocity increase towards the centre, their final velocities are different. This could be attributed to IRAC-2405 and 2407. As shown in Fig. 4(d) , the north filament becomes weaker at IRAC-2407, but still connected to MMS-7, and the gas structure follows the v ( r ) curve well. This suggests that the gas motion is still towards the centre and would reach the same velocity with MMS-7. The south filament, according to its velocity gradient, could have a similar connection to MMS-7 except for a more significant interruption by IRAC-2406 (Core-2). The two YSOs could have dissipated the surrounding N 2 H + component but not significantly affected the global inward motion towards MMS-7. For the NW filament, its outer part ( r > 20 arcsec) could also be affected by the local dense cores. As seen in Fig. 4(b) , the emission region largely deviates from the v ( r ) curve in the spatial range between Core-3 and Core-4 with a value of Δ v ≃ 1.0 km s −1 , suggesting that the gas motion could be affected by these two cores. Although the filaments exhibit these systematic velocity variations, the N 2 H + (1 0 −0 1 ) line profile is usually single-peaked and has a relatively small linewidth of Δ v 0.65 km s −1 over the whole region. This suggests that the filaments should have no further internal