adsabs/WIESP2022-NER huggingface dataset:
Paper: 2017MNRAS.471.2517W (fulltext)
x min in our research. Figure 1. Cumulative distributions of fluence, peak counts, rise time and duration for 4U 1728-34. The best-fitting results are shown by the red lines. The best-fitting parameters are given in each panel. Based on the criteria proposed by Aschwanden ( 2011 , 2014 ), which are the statistical independence of events, non-linear growth phase, random rise times and power-law distribution of these observed parameters, type I X-ray bursts can be explained by a SOC process. The SOC theory predicts that subsystems self-organize, owing to some driving force, to a critical state, at which a slight perturbation can cause a chain reaction of any size within the system (Bak, Tang Wiesenfeld 1987 ). The SOC theory also predicts a power-law distribution for the waiting times (Aschwanden 2011 ; Marković Gros 2014 ). The WTD has been widely discussed in astrophysics (Wheatland, Sturrock McTiernan 1998 ; Aschwanden McTiernan 2010 ; Wang Dai 2013 ; Li et al. 2014 ; Wang et al. 2015 ; Guidorzi et al. 2015 ; Wang Yu 2017 ). In the SOC theory, the WTD is usually described as a (non-)stationary Poisson process. The probability function is expressed by (Wheatland et al. 1998 ) where Δ t is the waiting time, T is the period and λ( t ) is the burst occurrence rate. Below, we model the occurrence rate λ. We propose that the burst rate can be modelled by λ( t ) ∝ t −γ . The reason is given below. Type I X-ray bursts are induced by a thin-shell instability. In LMXBs, the accreted H/He fuel accumulates on the stellar surface and forms a shell. The typical time for nuclear energy release is τ N ∝ Δ M / L N , where Δ M is the mass of the shell and L N is the nuclear energy generation rate (Hōshi 1968 ; Joss 1977 ). In the quiescent stage, L N remains almost unchanged. The energy will be diffused in a typical time τ d ∝ Δ M 2 , which also depends on the stellar temperature and the opacity of the shell (Hōshi 1968 ; Ayasli Joss 1982 ). The condition for triggering a burst is τ N /τ d = Δ M crit /Δ M ≤ 1, where the critical shell mass Δ M crit is obtained by τ N = τ d (Hōshi 1968 ; Ayasli Joss 1982 ). Alternative descriptions of this critical condition are also used (Fujimoto et al. 1981 , 1987 ; Narayan Heyl 2003 ). We assume that Δ M = Δ M crit happens at a typical time t 0 . When the shell grows thick enough at a time T , any perturbation affects the stellar hydrostatic structure significantly and leads to stable nuclear burning (Schwarzschild Harm 1965 ). Therefore, a burst can be triggered only in a time range t 0 ≤ t T . Since these time-scales are mainly determined by the shell mass, it is plausible to assume that the occurrence rate also mainly depends on the shell mass. Because the accreted mass is proportional to time, we can adopt for the burst rate The occurrence rate is taken as λ = 0 when t t 0 . We put all the time-dependent effects into the power-law index γ, which contains the dependence on shell mass and the possible time evolution of
Paper: 2016ApJ...821L...8S (fulltext)
(above 500 km) and 4 K at 200 km. Each observation was modeled independently and results for all five emission lines were combined using the technique provided in Nixon et al. ( 2008a ) Section 4 . A systematic error in the CO line intensity of 2% (Rothman et al. 2013 ) was also added to the measurement error. The best-fitting abundance for CO was found to be 49.6 1.8 ppm, which is consistent with and more accurate than previous measurements. Retrieved vertical temperature profiles from CO models were then used as fixed temperature profiles for modeling of the less abundant CO isotopologues ( 13 CO, C 18 O, and C 17 O.) For each isotopologue transition, the retrieved temperature profile which was closest in time to that observation was used as the fixed temperature profile with errors from that temperature retrieval propagated into the isotopologue retrieval. For a priori abundances, we assumed terrestrial isotopic ratios of 89.3 for 12 C/ 13 C, 498.8 for 16 O/ 18 O, and 2680.6 for 16 O/ 17 O (Lodders 2003 ). Best-fitting models of CO isotopologues were found using the same modeling procedures as CO (aside from the fixed temperature profile) and are presented in Figure 2 . The combined best-fitting 12 C/ 13 C ratio of 89.9 3.4 is consistent with similar studies of other molecules (Courtin et al. 2011 ; Mandt et al. 2012 ; Nixon et al. 2012 ), suggesting no significant carbon fractionation occurred during CO formation. Best-fitting ratios of 16 O/ 18 O and 16 O/ 17 O are 486 22 and 2917 359, respectively. Although the C 18 O (2–1) peak appears slightly under-fitted, the spectral residuals (model minus observation) for this transition indicate an optimal fit given the noise. The mixing ratios for C 18 O, derived independently from the J = 3–2 and J = 2–1 transitions, are consistent within the observational errors. Figure 2. Top: spatially integrated spectra of 13 CO with best-fitting models overlaid. Bottom: spatially integrated spectra of C 18 O and C 17 O (3–2) with best-fitting models overlaid. C 18 O (2–1) and C 17 O (3–2) are each combinations of two observations taken close in time to each other, while C 18 O (3–2) is a combination of three observations. Observations were combined in CASA before deconvolution. Additional systematic errors that have not been quantified in the final error estimate could exist. Sources of systematic errors include our assumption that Titan has the same temperature profile at all locations in our disc-averaged calculation, as well as our assumption that the Voigt profile is correct. Additional errors could exist in the line-broadening coefficients and temperature-dependence exponent used in the line database (Rothman et al. 2013 ), which could alter the line strength and shape. An accurate estimation of these systematic errors is difficult and beyond the scope of this paper, but these possible sources are mentioned for completeness. Our results constitute the most accurate determinations of atmospheric
Paper: 2017ApJS..230...24B (fulltext)
stars increases rapidly toward fainter magnitudes. The relative fractions are a combinations of the intrinsic distribution of different types of sources, whereby the density of Galactic stars increases toward the disk of the Milky Way, while the distribution of extragalactic sources does not depend on the Milky Way structure, but all sources are affected by the Milky Way dust, which is mostly confined to a thin disk. The reddening therefore depends on the line of sight toward the sources going through more or less of the dust disk. This effect was dramatically illustrated by Figure 2 (bottom) of Bianchi et al. ( 2011a ): the “V-shape” region devoided of UV-source counts in their figure is essentially a direct image of the dust disk. It is also visible, though less evident, in Figure 6 . Figure 6. Top: number of sources per square degree detected in NUV (left) and in FUV (right), as a whole (circles) or by magnitude ranges (dots). Values are shown for every 5° latitude strip. Bottom: fraction of FUV detections over NUV detections (left), and fraction of sources with FUV–NUV 0.5 (middle), and 0.0 (right) among the FUV detections (no error cuts, but sources in the footprint of extended objects have been excluded from the counts). While the faint sources (largely extragalactic) dominate the total samples, the FUV-detected sources are mostly bright stars. We recall that, for average Galactic dust, the UV extinction is similar in FUV and NUV, and much higher in both bands than at optical wavelengths (Table 1 and Bianchi 2011 ). In Figure 6 we plot the density of NUV and of FUV sources in GUVcat_AIS (top plot) as a whole and divided by NUV magnitude ranges; the plots show that the sources fainter than NUV_mag = 21mag dominate the sample, despite AIS being the shallowest survey, and especially in the NUV, where extragalactic objects are more prominent. The bottom panels show the fraction of FUV detections over NUV detections, again as a function of Galactic latitude, and among these, the hot and very hot sources (FUV_mag-NUV_mag ≤ 0.5 and ≤0.0 respectively). Such UV color cuts correspond to different stellar for different types of stars (Bianchi 2009 ), but roughly hotter than ∼15,000 K. Some QSOs may intrude on these FUV–NUV color cuts, as shown by Bianchi et al. ( 2009 ): these affect the faint sources most. The different behavior of relative source densities in Figure 6 reflects the fact that brighter samples (and hotter samples) are dominated by Galactic stars, which are more numerous in the Milky Way disk (see, e.g., Bianchi et al. ( 2011a )). 8.2. Summary of Suggestions and Caveats for Using the Catalog To conclude, we distill here, in terms of practical advice for users, the relevant information on the catalogs presented in this paper. 1. GUVcat_AIS contains unique measurements of all sources from AIS observations with both FUV and NUV detectors exposed. Duplicate measurements are removed in the main catalog, however, a version called
Paper: 2016ApJ...831..174M (fulltext)
dicarboxylic acid (Hollauer et al. 2001 ). The aforementioned study assigned the ν (C=O) + δ (COH) combination band to 1630 cm −1 . Assignment of the remaining newly emerging bands was accomplished using a study on the literature infrared spectra of the three benzene dicarboxylic acids (Arenas Marcos 1980 ). However, it is to be noted that two broad peaks, at 1776 cm −1 and 1793 cm −1 , in the spectrum at 8 K did not correspond to a single carrier. Rather, the bands were assigned to a combination of carbonyl stretches from the various carboxylic acid species in the ice. 3.1.2. Quantitative Analysis From the peak assignments in Section 3.1.1 , the column density changes throughout the irradiation can be determined for the two reactants, benzene and carbon dioxide, along with the irradiation-induced products. For carbon dioxide, the temporal development of the ν 1 + ν 3 and 2 ν 2 + ν 3 of CO 2 and the ν 3 of 13 CO 2 was monitored to quantify the carbon dioxide molecules destroyed. Exploiting the integrated absorption coefficients of the three previously mentioned bands, 1.4 × 10 −18 cm molecule −1 for the ν 1 + ν 3 of CO 2 , 4.5 × 10 −19 cm molecule −1 for the 2 ν 2 + ν 3 of CO 2 , and 7.8 × 10 −17 cm molecule −1 for the ν 3 of 13 CO 2 , we found that (1.9 ± 0.9) × 10 16 molecule cm −2 of carbon dioxide was destroyed over the course of the hour-long irradiation. Corresponding to the diminishing carbon dioxide column density were new bands assigned to carbon dioxide and carbon trioxide. The development of the two new carbon oxides was monitored using the fundamental band of carbon monoxide, assigned to 2141 cm −1 , and the ν 1 of carbon trioxide, assigned to 2044 cm −1 . Using a previously published work on the irradiation of carbon dioxide ices (Bennett et al. 2004 ), we found that the integrated absorption coefficients of the two previously mentioned carbon monoxide and carbon trioxide bands to be 1.1 × 10 −17 cm molecule −1 and 3.1 × 10 −17 cm molecule −1 , respectively. Utilizing this information, we determined that following irradiation with energetic electrons, the total increase in column density of carbon monoxide was (1.1 ± 0.1) × 10 16 molecule cm −2 , while the total increase of carbon trioxide was (7.9 ± 0.3) × 10 14 molecule cm −2 . The total column density of newly formed low-mass carbon species was therefore (1.2 ± 0.1) × 10 16 molecule cm −2 , i.e., 64 ± 3% of the total carbon dioxide destroyed was converted to carbon monoxide and trioxide. The difference between this value and the total quantity of carbon dioxide destroyed was therefore the amount reacted to form benzene carboxylic acids, i.e., (6.8 ± 1.0) × 10 15 molecule cm −2 . The destruction of benzene was monitored by the development of its ν 11 band at 690 cm −1 , with an integrated absorption coefficient of 1.5 × 10 −18 cm molecule −1 (Zhou et al. 2010 ). Comparing the initial column density of benzene with the column density following irradiation, we found that (4.4 ±
Paper: 2018MNRAS.480.1864G (fulltext)
at 3 s resolution. Magnetic field data is provided by the MFI instrument (Lepping et al. 1995 ) and density and velocity data by the 3DP instrument (Lin et al. 1995 ) measured during a stationary slow stream. The start time of the interval is 12:00 2000 April 4 and stop time is 16:00 of 2000 April 6. During this interval the solar wind speed remained about 300 km s −1 . As it is seen from Fig. 1 , λ 0.03 except for very small τ. We suggest that this enhancement at the small scales is probably due to measurement uncertainties (which are known strongly affecting plasma parameters at high frequencies Kasper et al. 2006 ; Gogoberidze et al. 2012 ) rather than indicating a real enhancement of compressible perturbations. To support this suggestion, we present another important characteristic of compressible/non-Alfvénic perturbations (Tu Marsch 1995 ; Bruno Carbone 2013 ) by dashed line in Fig. 1 . As can be seen λ m is approximately constant and does not increase with decreasing time-scale. Figure 1. The ratio of dimensionless rms amplitudes (solid line) and (dashed line, see the text for details) as a function of time-scale for a stationary stream of the slow solar wind. The above consideration suggests that the thermal-speed spectra reported by Safrankova et al. ( 2016 ) are in fact the pseudo-thermal spectra dominated by the magnetic fluctuations rather than the temperature fluctuations. This conclusion is supported by the fact that the level of spectra reported by Safrankova et al. ( 2016 ) cannot be caused lonely by the temperature fluctuations. Indeed, the spectrum of the (pseudo-)thermal speed in their fig. 1(b) is only about three times lower than the spectrum of the bulk speed driven by Alfvén waves (their fig. 1a), whereas the authentic temperature fluctuations should be at least one order less energetic (Goldsein Siscoe 1972 ; Tu et al. 1991 ; Tu Marsch 1995 ). To be more specific, let us utilize the straightforward expression relating the bulk velocity fluctuations δ V Bn measured by Safrankova et al. ( 2016 ) and magnetic fluctuations due to Alfvén waves. By means of ( 34 ), we can eliminate from ( 31 ) thus arriving to the following estimation for the velocity spectra ratio: With reasonable values T 0∥ / T 0⊥ ∼ 0.5 or T 0∥ / T 0⊥ ∼ 1.8 and , ( 35 ) easily explains the modest ratio ≳ 1/3 between 〈|δ V Tn | 2 〉 B and deduced from figs 1(a) and (b) by Safrankova et al. ( 2016 ). With autentic temperature perturbations this ratio would be at least one order less (Goldsein Siscoe 1972 ; Tu et al. 1991 ; Tu Marsch 1995 ). 4 DISCUSSION AND CONCLUSIONS We have shown that the nature of 'temperature fluctuations' derived from the currents of Faraday cup(s) is strongly affected by the temperature anisotropy. If the temperature anisotropy is close to zero, then the derived 'temperature fluctuations' are dominated by the perturbations of real temperature (thermal speed). However, when the temperature anisotropy is finite, as is typical
Paper: 2018MNRAS.474.3043V (fulltext)
parameter in N -body simulations. Numerous studies have argued that minimizing the scatter in certain statistical descriptions of the matter field (i.e. power spectrum or two-point correlation function) among an ensemble of N -body realizations requires a softening length ε that is at least as large as the mean inter-particle separation l = L box / N 1/3 (e.g. Melott et al. 1997 ; Splinter et al. 1998 ; Romeo et al. 2008 ; Joyce, Marcos Baertschiger 2009 ). Here, L box is the (periodic) box size of the cosmological simulation and N is the total number of particles used. Most cosmological simulations, though, are run with much smaller softening lengths, typically of the order of ε/ l ∼ 0.01–0.02. For example, the Millennium simulation (Springel et al. 2005 ) has ε/ l ∼ 0.022, while the MDPL and SMDPL simulations of Klypin et al. ( 2016 ) adopt ε/ l ∼ 0.019 and ε/ l ∼ 0.014, respectively. Whether such simulations produce reliable results on scales below the (comoving) mean inter-particle separation is still a matter of fierce, ongoing debate (see e.g. Knebe et al. 2000 ; Melott 2007 ; Joyce et al. 2009 ; Power et al. 2016 ; Benhaiem, Joyce Sylos Labini 2017 , and references therein). Several studies have focused on the optimal softening length for simulating individual objects (i.e. individual DM haloes or galaxies). For example, Dehnen ( 2001 ), extending studies by Merritt ( 1996 ) and Athanassoula et al. ( 2000 ), suggests that one should aim to minimize force errors. This can be achieved by optimizing the softening length such that it simultaneously minimizes the force bias (which increases with increasing ε) and the force noise (which decreases with increasing ε). Based on such considerations, Dehnen ( 2001 ) advocates that a collisionless system with a Hernquist ( 1990 ) density profile (which has the same r −1 -cusp as a NFW profile) should be simulated with a Plummer softening , where r 0 is the scale radius of the Hernquist (or NFW) profile and N 5 = N /10 5 with N the number of particles used to model the system in question. Power et al. ( 2003 ) use a different criterion to optimize the softening length: by minimizing the impact of two-body effects on the (central) density profiles of virialized DM haloes in cosmological simulations, they advocate a much larger softening length of , where c is the NFW halo concentration parameter. Note that both of these criteria have the optimal softening length depend on the size of the system as well as the number of particles that is used to represent the system. If we adopt a concentration–mass relation of the form c ∝ M −0.1 (e.g. Dutton Macciò 2014 ) and use that the virial radii of DM haloes scale according to r vir ∝ M 1/3 ∝ N 1/3 , we find that the optimal softening length depends on halo mass according to ε opt ∝ M α , with α = +0.2 and −0.17 for the criteria of Dehnen and Power et al., respectively. This scaling is sufficiently weak so that the softening is close to optimal for haloes
Paper: 2016MNRAS.461.4419B (fulltext)
of the inner binary progressively suppresses the effect. This is because a in decreases, bringing down the ratio in equation ( 38 ). The exact point at which K-L becomes effective also depends on the mass ratio of the intruder with respect to the inner binary, and on the eccentricities of the inner versus the outer binary. Note that as e in increases, the ratio decreases. Therefore, the K-L mechanism might eventually self-regulate itself: as it grows the inner binary more eccentric, it also makes relativistic precession more effective. The condition might therefore not be satisfied any longer, thus suppressing the K-L effect and eventually altering the overall dynamics of the system. Although our investigation is similar in spirit to that of Hoffman Loeb ( 2007 ), the above discussion highlights the importance of the differences in the two implementations. In particular, Hoffman Loeb ( 2007 ) did not include 1PN and 2PN relativistic precession in their equations. This might significantly alter the overall statistical properties of merging binaries (e.g. eccentricities, coalescence time-scales) because, as we just discussed, the conditions for triggering K-L resonances, and thus the general dynamics of the system, are different. Moreover, our treatment of the hardening in the stellar background is more accurate, since it also reproduces the eccentricity evolution in the hardening phase. This is important because (i), it affects the triggering point of K-L cycles (equation 38 ), and (ii), it has a strong impact on the stability of the hierarchical triplet and on the probability of close encounters leading to chaotic behaviour. 5.2 Astrophysical implications The main aim of this paper is to present and validate the code, and a thorough analysis of the dynamics of MBH triplets is deferred to forthcoming papers of the series we planned. Still, the few cases examined here already provide some interesting astrophysical insights that we briefly outline in the following. In all our simulations, two of the MBHs (not necessarily those originally forming the inner binary) coalesce in less than 1Gyr from the start of the dynamical friction phase of the intruder. Therefore, triple interactions might provide a viable channel to merge MBH binaries in massive, low-density galaxies, where hardening against the stellar and gaseous background might act on a time-scale of several Gyr (Khan et al. 2011 ; Sesana Khan 2015 ; Vasiliev et al. 2015 ). At least a fraction of massive elliptical galaxies, which host the most massive binaries targeted by PTAs, might realistically undergo multiple mergers at z ≲1 (see Gerosa Sesana 2015 , and references therein). If the typical coalescence time-scale of the formed MBHBs is several Gyr, then the occurrence of a second merger will bring in an intruder, typically leading to coalescence on a much shorter time-scale. Triple interactions might therefore be an important channel for merging very massive, gas-poor low-redshift
Paper: 2017MNRAS.469L..83W (fulltext)
the LG (e.g. see updates to McConnachie 2012 ). While environmental effects (e.g. efficient destruction of satellites, dwarfdwarf mergers, stellar stripping) could alleviate some tension, these mechanisms do not appear efficient enough to resolve the discrepancy (e.g. Kirby etal. 2013 ; Deason etal. 2014 ; Garrison-Kimmel etal. 2017 ). Furthermore, the overabundance of LG dwarfs is not limited to the faintest UFDs, as it is known to persist in the classical dwarf regime (Boylan-Kolchin etal. 2015 ), which is thought to be observationally complete (e.g. Koposov etal. 2008 ). Even more challenges arise if (i) the faint end of the UVLF approaches 2.4 (i.e. many more faint galaxies); and/or (ii) such low-mass galaxies have a low star formation duty cycle (e.g. 10percent; Wyithe etal. 2014 ). In the latter case, 90percent of the haloes would be in the off state at any given time, and thus have reduced UV luminosities. Effectively, this results in higher luminosity galaxies hosted in even lower mass haloes, assuming a canonical SHM. 3.2 Minimizing the flux contribution of ultra-faint dwarfs Up to this point, we have considered the consequences of extrapolating a Schechter UVLF into the regime of UFDs. However, several numerical simulations of galaxy formation predict a turnover in the UVLF, decreasing the predicted number of very faint galaxies in the early Universe (e.g. Jaacks etal. 2013 ; OShea etal. 2015 ; Gnedin 2016 ; Liu etal. 2016 ; Ocvirk etal. 2016 ; Yue etal. 2016 ; Finlator etal. 2017 ). Although details vary, the common threads among these simulations are that not all low-mass haloes necessarily host a galaxy and that baryonic effects internal to the galaxies (e.g. supernova feedback, radiation pressure) can significantly affect galaxy formation in low-mass haloes. Alternately, a turnover in the high- z UVLF is consistent with models that suppress or eliminate small-scale structure (e.g. warm dark matter; Schultz etal. 2014 ; Dayal etal. 2015 ). A broken luminosity function at high z is also necessary in order to avoid dramatically overproducing UFDs and even classical dwarfs in the LG (Boylan-Kolchin etal. 2014 , 2015 ). Fig. 4 illustrates the effects of two plausible UVLF turnovers. For simplicity, we focus only on the z 7 case and adopt analytic UVLFs that turn over from Jaacks etal. ( 2013 ) and Boylan-Kolchin etal. ( 2015 ). The UVLF from the latter study has 2 for M UV 13 and 1.2 for M UV 13 and is designed to reproduce z 0 LG dwarf galaxy counts. We have tuned the UVLF from Jaacks etal. ( 2013 ) to match that of Boylan-Kolchin etal. ( 2015 ). Figure 4. Top panel: a comparison between the UVLFs at z 7 with and without turnovers. The steep UVLF (black; 2) is from Finkelstein etal. ( 2015 ), while the other curves show models from Boylan-Kolchin etal. ( 2015 , orange) and Jaacks etal. ( 2013 , magenta). Bottom panel: the fraction of UV flux at z 7 for each of the UVLFs shown in the top panel, when integrated to M min 3.1. A break or