adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016ApJ...833..217B (fulltext)
and electron and ion heating, respectively. In the left-hand panels each individual histogram (denoted by line style and color) corresponds to a different type of heating function. This means, for example, that the solid blue histogram includes emission measure ratios for all values of t N , but for only those cases where heating events are evenly spaced (i.e., β = 0) and chosen from a power-law distribution of α = −1.5. The right panels show these same emission measure ratios, but now categorized by t N . For example, the solid red histogram includes emission measure ratios for every type of heating function (i.e., uniform, all α and all β ), but for only those runs where t N = 3000 s. Note that we choose to only show results for five values of t N for aesthetic purposes. Figure 8. Histograms of emission measure ratios EM( T hot )/EM( T cool ), where T hot = 10 6.942 K and T cool = 10 6.187 K, for all heating function types and heating frequencies for the single-fluid case. In both panels each histogram is normalized such that for each distribution P ( x ), and the bin widths are calculated using the Bayesian blocks method of Scargle et al. ( 2013 ). Left: emission measure ratios separated by heating function type for all heating frequencies, 250 ≤ t N ≤ 5000 s. Because there are too few (20) EM ratio measurements for the uniform case to construct a meaningful histogram, we denote the median of the uniform results with a vertical line, shown here in purple. Right: emission measure ratios separated by waiting time, t N . For aesthetic purposes, only five values of t N are shown, t N = 1000, 2000, 3000, 4000, 5000 s. Figure 9. Same as Figure 8 , but for the case where only the electrons are heated. Figure 10. Same as Figure 8 , but for the case where only the ions are heated. Considering first the left-hand panels, in the single-fluid model (Figure 8 ) the ratio is largely insensitive to α and is peaked sharply at ∼1–1.25 although the distribution peaks at slightly higher values for the β = 1 case (∼1.5). Note that the uniform heating results (whose median is denoted by the vertical purple line near ∼0.6) show emission measure ratios significantly less than those in the power-law cases, consistent with the reduced hot emission shown in Figure 3 . For electron heating (Figure 9 ) the ratio is again insensitive to α , but is narrower and falls off more quickly toward higher emission measure ratios. The β = 0 cases (for all α ) peak just above 0.5, with the β = 1 cases all peaking at slightly higher values just at or below 1. For ion heating (Figure 10 ), the β = 0 distributions peak at lower values compared to those with β = 1. Again the results are relatively insensitive to α . However, compared to the electron heating case, all of the distributions are much wider and peak at higher values, ∼1.75 for β = 0 and ∼2–2.5 for β = 1. Furthermore, in the β = 1 case, the α = −2.5 distribution peaks at lower values compared α = −1.5, −2.0. Turning to
Paper: 2019ApJ...874L..15R (fulltext)
3 (d), and can be compared with the MHD results in panel (a). There are several similarities between the two solutions, although also some important distinctions. First, both solutions produce two equatorial coronal holes at roughly the same Carrington longitudes. Additionally, both solutions map to the same positive-polarity equatorial coronal hole for roughly the same intervals, spanning the first encounter. However, the size and shape of the equatorial holes are substantially different, with the PFSS solution producing much smaller areas, in spite of the fact that we set the source surface radius to 2.0 R S , which is typically lower than is usually used, and chosen to open coronal holes as much as possible. Moreover, prior to first encounter, the PFSS solution mapped to the negative-polarity southern polar coronal hole, and, thus, this transition would not be associated with a current sheet crossing. By flying PSP ’s trajectory through the heliospheric solution, we are able to recover the predicted plasma and magnetic field variables in situ. These are summarized in Figure 4 . The panels show, from top to bottom, radial speed, radial component of the magnetic field ( B r ), scaled B r , plasma number density ( N p ), scaled N p , and the heliocentric position of the spacecraft, as summarized by distance ( R ) and Carrington longitude. Focusing first on panels (a), (b), and (d), we note the following points. First, the speed remained approximately constant during the interval from first encounter to second encounter (∼525 km s −1 ). Second, the magnetic field switched from positive polarity to negative polarity (day of year: 302), and remained so for approximately three weeks. It also increased to a maximum negative value of −80 nT. Third, plasma density rose to almost 80 cm −3 ; however, the peak in density lagged the magnetic field peak by approximately one day. Figure 4. Time series of predicted (a) radial velocity ( v r ), (b) radial magnetic field ( B r ), (c) scaled B r , (d) plasma number density ( N p ), (e) scaled N p , and (f) location of spacecraft in terms of heliocentric distance (aqua) and Carrington longitude (magenta). In (c) and (e), the radial magnetic field and number density have been scaled by r 2 to account for the radial fall-off expected from flow into a spherical geometry. These variations, however, are misleading, in the sense that both the density and radial magnetic field fluctuations lie on top of the geometric expansion of the solar wind, which naturally produces a 1/ r 2 fall off with heliocentric distance, or, because the spacecraft is moving toward perihelion, an increase of r 2 . To address this, in panels (c) and (e) of Figure 4 , we have removed the 1/ r 2 variation and scaled the measurements to 1 au values. Both the values and variations are markedly different (compare panels (b) and (c) and panels (d) and (e)). Now, B r remains virtually flat (∼8 nT) for the entire duration of the encounter. Number
Paper: 2019A&A...627A.122A (fulltext)
available for the recombination, resulting in the observed slight isotopic gradient with depth. Fig. 9 Left : D/H ratio measured in the labelled residue from a hot region (red), the bulk (green), and a cold region (blue). Black point indicates the D/H estimated from the IR ice mixture spectra prior to irradiation. Right : D/H histogram with dots corresponding to the hot (red), bulk (green), and cold (blue) D/H values. As a result, the total residue appears as a mixture between a poly-HCN component formed in the N 2 -CH 4 layers with some D due to migration and another layer formed within or at the vicinity of the D-rich ice layer. The use of a CD 4 layer was chosen to maximize the range of D/H variation in the residue. Formation of precursors at the direct vicinity of this layer induces the very high D/H ratios observed in this laboratory simulation, which are much larger than the values observed in UCAMMs or interplanetary organic matter in general. Strikingly, the spatial scale of the isotopic anomalies found in the residue is comparable to that observed in UCAMMs or IDPs ( Duprat et al. 2010 ; Messenger 2002 ). This suggests that the micro-scale isotopic heterogeneities observed in these organics may result from irradiation/condensation of thin ices layers with isotopic heterogeneities. In addition, these experiments show that energetic particle irradiation of D-rich ices preserves the bulk isotopic composition of initial ices and produces a residue which is an excellent candidate precursor compatible with the organic matter observed in UCAMMs. 5.1.2 Timescale The interaction of high energy ions from the GCR with the surface of objects orbiting at far heliocentric distances (in the Kuiper Belt or in the Oort cloud region) have been studied for more than a decade (e.g. Cooper et al. 1998 , 2003 ). These swift ions penetrate icy surfaces and deposit energy along their tracks. Ultraviolet photons may also contribute to the deposited energy, but they affect a much lower ice volume, as their penetration depth does not exceed a few to hundreds of nanometers. The dose deposited by cosmic rays at large heliocentric distances can be modelled using a functional form for the ions differential flux ( Shen et al. 2004 ). Including the respective Galactic abundance of elements and integrated over a wide energy range, Shen et al. (2004) give a mean deposited energy of about 6 × 10 −15 eV molecule −1 s −1 in ices, corresponding to an ionization rate of about 3 × 10 −17 s −1 . We irradiated our samples up to a total dose of 19 eV molecule −1 (≈4.0 × 10 23 eV cm −3 ), corresponding to about 100 million years of exposition to the GCR. This time is small compared to the solar system age and thus fully compatible with the astrophysical timescale of irradiation of small bodies after their formation. The irradiation period is therefore not time-constrained. It contrasts with the scenarios restricted to a hypothetical high irradiation episode occurring during
Paper: 2016ApJ...823...73L (fulltext)
those in A2, but there are too few points in A3. Statistically, the difference in the slope between A2 and A3 is not significant, although, neither is that between A1 and A3. 5. DISCUSSION The galactic conformity is very marginal in the central area of the Virgo Cluster (A1), which seems to be similar to the result in WHL J085910.0+294957 from Lee et al. ( 2014 ). Since the analysis in Lee et al. ( 2014 ) was limited to the central area within 500 kpc radius, the two clusters (Virgo and WHL J085910.0+294957) commonly show only weak signals of small-scale conformity in their central areas (∼2 σ significance). On the other hand, the signal of small-scale conformity in A2 appears to be more obvious, showing significance close to 3 σ . In the case of the outermost area A3, as mentioned in the previous section, the signal is very weak due to the insufficient size of the sample. It is noted that the correlation coefficient in A3 is as large as 0.44, which is similar to the value in A2, while that in A1 is only 0.27. This is not a decisive evidence of small-scale conformity in A3, but it shows a possibility that a clearer signal of conformity may be detected if a larger sample is available. In this paper, however, because the uncertainty for the result in A3 is too large, we will focus on the results in A1 and A2. These results show that small-scale conformity is weak or somewhat ambiguous in the inner region (roughly within the virial radius), while it seems to be more obvious in the outer region of the Virgo Cluster. Note that, in Section 3.1 , the average standard deviation of color indices in faint companions around a given bright galaxy is 0.116. This value is only approximately one fourth of the distribution over the entire sample, which ranges from 0.25 to 0.70. This small value of the average standard deviation of color indices implies that the faint companion galaxies in a possible group tend to have similar properties rather than have randomly mixed properties, which is consistent with the expected small-scale conformity. Lee et al. ( 2014 ) suggested three scenarios regarding the origin of the small-scale galactic conformity in a cluster. The first is the “tidal dwarfs” scenario, in which the massive galaxies are partially torn out by tidal interactions with many other galaxies (harassment) or the cluster potential itself, forming many low-mass galaxies that may be the faint companions we observe. The properties of these low-mass galaxies must be similar to their host massive galaxy because they have been a single galaxy. If this scenario is correct, the conformity may be detected better in the inner region than in the outer region of a cluster, because the tidal force by a cluster is stronger in the inner region and more numerous massive galaxies exist in the inner region of a typical cluster, which may cause stronger harassment. However, this does not agree with our results that show an exactly opposite trend. Furthermore, the
Paper: 2018ApJ...856..166H (fulltext)
from this indicator (Kewley Ellison 2008 ). At the time that Tüllmann et al. derived their metallicities, the tools for assessing which branch to adopt for this double-valued indicator were less robust. Extraplanar H ii regions in the two massive spirals NGC 3628 and NGC 4522 show modest or no abundance offsets relative to their disks. Our results for these galaxies are consistent with the conclusions reached by Stein et al. ( 2017 ). In particular, the nebula at z ≈ 1.4 from the midplane of NGC 4522 is projected onto extraplanar H i identified as matter being stripped from the disk via the ram pressure interaction with the intracluster medium of the Virgo cluster in the maps of Kenney et al. ( 2004 ). Stein et al. ( 2017 ) noted that the extraplanar H ii regions in NGC 3628 are projected onto an H i filament seen in the maps of Wilding et al. ( 1993 ) that has been identified as a tidal feature due to the interaction of this galaxy with its neighbor NGC 3627. Thus, the extraplanar H ii regions may plausibly arise in gas stripped from both of the galaxies, and they represent fundamentally different phenomena than the extraplanar H ii regions in NGC 55 and NGC 4013. The spiral galaxy NGC 4522 resides in the Virgo cluster; direct imaging shows spectacular evidence for ram-pressure-stripping of gas from the disk (Abramson Kenney 2014 ). The extraplanar H ii region measured in this galaxy is associated with this material that seems to clearly have an origin in the disk of that galaxy (Stein et al. 2017 ). We derive a joint abundance offset between the two disk H ii regions observed and the single extraplanar H ii region of = −0.03 ± 0.07 (68% confidence), consistent with no offset. This is as expected for material recently stripped from the disk. In the case of NGC 3628 (part of the Leo Triplet of galaxies), two extraplanar H ii regions are seen at z ≈ 3 kpc in close proximity to one another. Stein et al. note that these H ii regions are likely associated with a filament of H i at similar velocities that likely represents tidal material due to an interaction of NGC 3628 with its neighbor NGC 3627 (Wilding et al. 1993 ). There are hints that the filament may have arisen in the outer parts of NGC 3628 (Stein et al. 2017 ), but they seem inconclusive. Compared with the single disk H ii region measured in that galaxy, we find offsets of = −0.17 ± 0.10 and −0.05 ± 0.11 (68% confidence). If one assumes a single abundance offset is appropriate, the joint distribution implies = −0.12 ± 0.07. There is a hint that the abundances of these H ii regions may have a slightly lower abundance than the disk, but the hint is not robust at the 95% level. While the extraplanar regions tracing stripped material have abundances consistent with the disks of those galaxies, the extraplanar nebulae in the dwarf galaxy NGC 55 have higher abundances than the disk. The extraplanar H ii regions in NGC 55 seem to be connected with supershells produced by vigorous star
Paper: 2016MNRAS.457.2331W (acknowledgments)
This work is funded by IBM, ASTRON, the Dutch Ministry of Economic Affairs and the Province of Drenthe. It is also part of the SKA-TSM project and supported by the Northern Netherlands Provinces Alliance (SNN), Koers Noord and the Province of Drenthe, and the European Community FP7 programme MIDPREP, Grant Agreement PIRSES-GA-2013-612599. This work is based upon research supported by the South African Research Chairs Initiative of the Department of Science and Technology and National Research Foundation. The authors would like to thank Jonathan Kenyon, Julien N. Girard and Gianni Bernardi for their valuable suggestions. The authors would also like to thank the anonymous reviewer for his constructive feedback.
Paper: 2017ApJ...850...45R (fulltext)
anti-correlation between the expansion factor and the wind speed, which is in agreement with observations (see Wang Sheeley 1990 ; Wang 2016 ). At the source surface, the global anti-correlation is shown with a brownish line, and no correlation can be extracted for the point near minimum alone. Figure 9. Correlation between the wind speed and the expansion factor at three different heights in the corona: at the optimal source surface radius (on the left panel), at the sonic point (middle panel) and at (where the wind speed is computed for all panels). The colors indicate the parameter , so that orange colors indicate a very weak dipolar component (near maximum) and black colors indicate a strong dipolar component (near minimum). We see that the correlation changes with the cycle phase. The positive correlation between and the wind speed is the strongest at large heights, due to expansion beyond the sonic point. Nevertheless, higher in the corona, we can obtain two different regressions, for simulations whose parameter is over or below 50% of the maximum value () for the period considered. For near minimum cases, we get a positive correlation (shown by a black line) between the wind speed and the expansion factor starting at the sonic point. This correlation gets better as we go up in height at . Hence, for a simple, near-dipolar configuration of the solar magnetic field, where most of the open field lines come from the large polar coronal holes, the expansion around and beyond the sonic point operates a significant reorganization. Of course, beyond the source surface, the total area is conserved and both super and under radial expansion must compensate. As such, super (under) radial expansion increases (decreases) the wind speed, and the correlation between the terminal speed and the total expansion factor is reversed (see also Pinto Rouillard 2017 ). The additional acceleration provided only by the super radial expansion is maximum on field lines that cross local maxima of . This process must influence the acceleration of the fast solar wind, which is thought to occur at large distances from the Sun, where Alfvén waves dissipate. The correlation (shown by the orange line) stays globally negative for points near maximum of activity everywhere in the corona. In Figure 10 , we show the mass flux as a function of the expansion factor at the source surface ) at different heights in the corona. As shown by the blue dots, a large expansion below the source surface (associated with slow streams) increases the mass flux at the coronal base, through the velocity that is left free in the boundary. The mass flux at the surface spans over an order of magnitude, and the mass loading diminishes the energy per particle and the terminal speed. This explains the good correlation between the wind speed and the expansion factor at the source surface. However, near the source surface, the mass flux/expansion correlation is reversed with faster wind (low )
Paper: 2018ApJ...867...27N (acknowledgments)
We wish to acknowledge the anonymous referee whose questions and comments improved the content and quality of the manuscript. This research was supported by National Science Foundation (NSF) grants AST-1109243 and AST-1615848 to M.L.N. J.H.W. acknowledges support from NSF grant AST-1333360 and Hubble Theory grants HST-AR-13895 and HST-AR-14326. The simulations were performed using the ENZO code on the Comet system at the San Diego Supercomputer Center, University of California, San Diego, with support from XRAC allocation MCA-TG98020N to M.L.N. This research has made use of NASA’s Astrophysics Data System Bibliographic Services. The majority of the analysis and plots were done with yt (Turk et al. 2011 ). ENZO and yt are developed by a large number of independent researchers from numerous institutions around the world. Their commitment to open science has helped make this work possible.
Paper: 2017ApJ...835...95B (fulltext)
high SFRs of the present sample result in some of the X-ray luminosities being even greater than the erg s −1 value often used to identify sources as clear AGNs (e.g., Hornschemeier et al. 2001 ; Barger et al. 2002 ; Bauer et al. 2004 ; Szokoly et al. 2004 ) based on maximal local star-forming galaxy X-ray luminosities. Laird et al. ( 2010 ) similarly concluded that very high SFRs were responsible for the high X-ray luminosities of most of the sources in their submillimeter-selected sample in the same field. The AGN-classified sources in Figure 4 (b) show a much wider spread in , ranging from near quasar X-ray luminosities to nearly X-ray undetected sources. However, there are a number of sources with luminosities close to those of the star-forming galaxies, and there is clearly not a one-to-one correlation between our classifications and X-ray luminosity. 4. THE FIR-RADIO CORRELATION Radio power is often used along with the FIR-radio correlation as a measure of the SFR (e.g., Cram et al. 1998 ; Hopkins et al. 2003 ; Netzer et al. 2007 ; Mineo et al. 2014 ; Mushotzky et al. 2014 ). However, this could be risky when no other information is available on whether a source is AGN dominated or star-formation dominated. After all, it is well known that some local radio-quiet AGNs lie on the FIR-radio correlation (e.g., Condon 1992 ; Morić et al. 2010 ; Wong et al. 2016 ), even if it is not understood why. In Figure 5 , we plot (a) luminosity and (b) luminosity versus radio power for the radio sources with spectroscopic or photometric redshifts and erg s −1 Hz −1 . We use colors to denote the sources classified as star-forming galaxies (green circles), composites (blue circles), and AGNs (red circles). In (a), we also mark the sources that Chi et al. ( 2013 ) found to be AGNs using VLBI observations with surrounding black circles. All of these sources lie below the FIR-radio correlation. The star-forming galaxies in (a) have a mean , where we have computed the error with the jackknife resampling statistic; all lie within a multiplicative factor of three of the median value ( q = 2.35), which we denote by shading. Five AGNs and four composites also lie in the region. Figure 5. (a) luminosity and (b) luminosity vs. 20 cm power for the radio sources with spectroscopic or photometric redshifts and erg s −1 Hz −1 . Green circles denote star-forming galaxies, blue circles composites, and red circles AGNs. The central black line shows the median FIR-radio correlation of the star-forming galaxies, and the shading shows the region where we consider the sources to lie on the FIR-radio correlation (multiplicative factor of three of the central value). In (a), we mark the sources that Chi et al. ( 2013 ) found to be AGNs using VLBI observations with surrounding black circles. All of these sources lie below the FIR-radio correlation. In Figure 6 (a), we show the SEDs of 12 of the star-forming galaxies that lie on the FIR-radio correlation, as defined by the
Paper: 2015A&A...583A..23G (acknowledgments)
This research was supported by NASA under contracts JPL-1266313 at the University of Michigan, JPL-1345493 at the Southwest Research Institute, and JPL-1502225 at the University of Colorado. Rosetta is an ESA mission with contributions from its member states and NASA.