adsabs/WIESP2022-NER huggingface dataset:
Paper: 2016ApJ...818..106R (fulltext)
from stellar activity). The likelihood function is given by where i indexes the observations acquired with the I th instrument, is the nominal uncertainty of each RV measurement, and s I are the zero-point and extra noise parameters (also called jitter) of each instrument, and the Doppler signal from a companion on the star is encoded in the model , which is a function of time t and the Keplerian parameters . The Keplerian parameters of the p th companion in the system are: the orbital period P p (in days), the semi-amplitude K p (in m s −1 ), the mean anomaly at the reference epoch t 0 (in degrees), the eccentricity e p , and the argument of periastron . The second and third terms in Equation ( 3 ) account for the possible presence of a long-period candidate whose orbit is only detected as a trend (acceleration, ) plus some curvature (jerk, ). These two terms are especially important for the analysis that follows. When performing the Bayesian MCMC analysis, one needs to specify some prior distributions for these parameters. In this paper, we use uniform distributions for the angles and ω , as any value would be equally likely a priori. Given that the objects involved are rather massive and the signals are large, we also allow for a uniform eccentricity distribution between [0,0.95). For K p , , s I , , and , we assume unbound non-normalized uniform priors. While this can cause issues when normalizing the posterior, we are only using the MCMC analysis to sample the shape of the posterior, so precise values of the bounds and the normalization factors are unnecessary. Furthermore, because we will later try to constrain the signal with a period much longer than the span of the observations, the possible values of these three quantities will be correlated, so bound priors might eliminate many long period solutions that would otherwise be highly probable. For example, a large K in general requires a large γ unless the companion is precisely crossing the plane of the sky at t 0 (which is highly unlikely). Regarding the prior on the period, in this work we assume that the prior is uniform in (equivalent to uniform in frequency). This is motivated by the following. When analyzing time series, the local solutions to periodic signals are approximately equally spaced in frequency. For example, if one produces a Lomb–Scargle periodogram of a time series and plots period versus power, one will quickly appreciate that the peaks become much broader with increasing period (Scargle 1982 ). However, when making the same plot in frequency, the peaks appear uniformly distributed over the possible frequencies. As discussed in Tuomi and Anglada-Escudé ( 2013 ), in Bayesian statistics the choice of the parameter automatically imposes implicit priors on all other alternative parameterizations. In the case of the period, a uniform prior at very long periods can outweigh the information content on the likelihood, producing a biased result. While this issue
Paper: 2016A&A...586A..75S (fulltext)
and planets with little Ly absorption but strong emission can be used to distinguish between these two classes of thermospheres. Based on the predicted strong absorption signals, WASP-80 b and GJ 3470 b are the most promising targets among our sample in the search for yet undetected escaping atmospheres. Appendix A: Calculation of the Ly<inline-formula specific-use="simple-math"><italic>α</italic></inline-formula> absorption signals Here, we describe the method used to calculate the Ly absorption in the simulated atmospheres. Although we use the term Ly absorption, we note that the actual physical process is scattering of photons out of our line of sight. Absorption of Ly with collisional de-excitation only occurs deep in the simulated atmospheres (see Fig. 6 ). We do not account for any emission or line transfer in the computation of the absorption signals, or for scattering of photons into our line of sight. We further assume a homogeneous brightness of the stellar disk in Ly emission. Fig. A.1 Computation of the transmission signals and images. The absorption is calculated by shooting rays through the planetary atmosphere. Density, temperature, and tangential velocity in each cell are taken into account. To compute the absorption signals we shoot rays through the spherical atmospheres (see Fig. A.1 ). The wavelength dependent transmission in a single ray with index is given by the product of the absorption in each cell: Here, is the neutral hydrogen density in cell with the cell width . is the standard Ly absorption cross-section with a Voigt-profile, shifted by the local tangential velocity of the gas. The Doppler width is given by the sum of the local thermal and turbulent widths (see Eq. ( 5 )); the latter is given by the speed of sound. Deuterium absorption is included with a deuterium fraction of according to measurements from Jupiter ( Lellouch et al. 2001 ). Fig. A.2 Simulated Ly transmission for low-potential planets. For each system we show the absorption in the Ly line from below the Roche lobe (solid line) and from unbound hydrogen (dashed, blue). Black dashed lines indicate the optical transit depth. Calculated transmission images are depicted next to each spectrum. The mass-loss rate decreases from top to bottom . Fig. A.3 Simulated Ly transmission spectra and images for high-potential planets plus WASP-80 b (same as Fig. A.2 ). With the exception of WASP-12 b (see text) and WASP-80 b, these planets produce small absorption signals. WASP-80 b produces the strongest absorption signal of all planets. The total transmission is given by: Here, is the number of rays and is half of the vertical resolution. In this equation, the first term accounts for the fraction of radiation that bypasses the simulated atmospheres (transmission equals one). In most of the systems this term is zero, because the simulated atmospheres cover the full stellar disk. The sum adds the transmission of each ray weighted with the fractional area that a ring
Paper: 2018ApJ...853..136K (fulltext)
conditions requires equilibrium total pressure balance across each interface. This demands that the total (gas plus magnetic) pressure is constant:where μ is the permeability of free space. The sound speed in each region can be expressed as for . Here, γ is the adiabatic index, which is uniform across every domain, under the assumption that the plasma composition in the entire volume is the same. Another characteristic speed in the plasma, i.e., the Alfvén speed, is denoted by for . Equation ( 2 ), which describes the equilibrium pressure balance, yields the following relationship between the density ratios and characteristic speeds for any two regions:Disturbances within the slab, as well as in its magnetic environment, are governed by the ideal MHD equations: where , , p , and ρ are the velocity, magnetic field strength, pressure, and density, respectively. Equation ( 4 ) expresses mass conservation, Equations ( 5 ) and ( 6 ) are the momentum and induction equations, respectively, and Equation ( 7 ) is the energy equation for adiabatic processes. We linearize these equations about a static basic state and seek plane-wave solutions propagating in the direction of the formwhere k is the z component of the wavenumber vector defined as , and ω is the angular frequency. The linearized governing equations then reduce to a single ordinary differential equation for each region, which governs perturbations in that region, given bywhereare wavenumber coefficients andare the tube speeds for each domain for . The solutions to Equation ( 9 ) are a linear combination of the hyperbolic functions. Physically realistic solutions prescribe that the slab perturbations have no effect on plasma far away from the system; that is, the waves are evanescent outside the slab. This imposes the restriction on that as , , and so and . The general solution in this case takes the formHere, A , B , C, and D are arbitrary real constants. Physical solutions further require that two boundary conditions be fulfilled: the perturbations in velocity have to be continuous, and total pressure balance has to be upheld across the slab boundaries at . Applying these boundary conditions gives us four homogeneous algebraic equations in terms of the constants A , B , C , and D . Nontrivial solutions only exist when the determinant of the coefficients of this system of equations is zero. This gives us the dispersion relation aswhere By substituting for into Equation ( 13 ), we can express the dispersion relation in terms of wavenumbers, frequencies, and characteristic speeds as 2.1. Validation with Earlier Studies There are at least two earlier models that the current results should remain consistent with. If we set , thus , then the wavenumbers m 1 and m 2 revert back toFurthermore, the dispersion relation (Equation ( 16 )) loses the factors containing the external Alfvén speeds and simplifies towhich corroborates with the result for the magnetic slab embedded in a nonmagnetic asymmetric
Paper: 2020ApJ...899..105L (fulltext)
Swift Observatory short GRBs suggests that of those with an X-ray afterglow, >30% have evidence for additional energy input at later times, most commonly in the form of a long-lived plateau, persisting at bright levels for hundreds to thousands of seconds (with the majority at the shorter end), or in the form of X-ray flares. Such properties are also common in long GRBs and are widely ascribed to additional energy injection. The origin of the prompt emission in GRB 170817A is difficult to explain with an off-axis-viewed typical short GRB (Kasliwal et al. 2017 ; Lamb Kobayashi 2018 ); however, some component of the observed GRB could be due to emission from the midpoint of a structured jet (Ioka Nakamura 2019 ). The required core energy and Lorentz factor are at the upper limits for the short GRB population but consistent with those from afterglow modeling assuming a Gaussian-structured jet (e.g., Gill Granot 2018 ; Lamb et al. 2019a ; Troja et al. 2019b ). For the refreshed shock models shown here, the top-hat jet structure, the initial on-axis isotropic equivalent kinetic energy ∼10 51 erg, and the separation of ι / θ j ∼ 3 for both models suggest 10 10 If we assume a typical γ -ray efficiency η γ ∼ 0.15, where , and following the method in Ioka Nakamura ( 2019 ) and including the opacity for high-energy photons as in Lamb Kobayashi ( 2016 ), we find an isotropic equivalent γ -ray energy for an observer at ι = 0.28(0.31) rad of erg and ∼2.5 × 10 38 erg for Models 1 and 2 respectively, with spectral peaks at E p ∼ 0.55 (0.23) keV, and well below the erg and E p ∼ 185 ± 62 keV for GRB 170817A. that the prompt emission of GRB 170817A is better explained as the shock breakout from a cocoon of material that is inflated by the successful, ultrarelativistic jet (Bromberg et al. 2018 ; Duffell et al. 2018 ; Gottlieb et al. 2018b ; Pozanenko et al. 2018 ). Then, GRB 170817A is more a “burst of γ -rays” than a “classical” GRB (Kasliwal et al. 2017 ). An interesting result of the posterior distribution from Model 1 for the Lorentz factor of the initial outflow is the preference of the model for “lower” values, see Figure 5 . Given the energy of the initial outflow, erg, any dissipation within an outflow with Γ 0,1 ≲ 25 is likely to be into an optically thick medium, resulting in a failed GRB (Dermer et al. 2000 ; Huang et al. 2002 ). This implies that GRB 170817A may be associated with a population of failed GRBs that would result in on-axis orphan afterglows for all but the nearest events where the burst of gamma rays from the shock breakout may be detected. Such a population could dominate the neutron star merger population; however, at cosmological distances the electromagnetic counterparts, even for an on-axis observer, would be difficult to detect (Lamb Kobayashi 2016 ). However, if we restricted the prior range for the initial Lorentz factor to Γ 0,1 ≳ 25, then higher Lorentz factor solutions to the fit exist, with some at Γ ≳ 100 (see the top
Paper: 2016A&A...586A..77C (acknowledgments)
We thank Ralf-Dieter Scholz for constructive conversations during the preparation stage and the anonymous referee for indicating revisions that have improved our analysis and results. We also thank the Cambridge Astronomy Survey Unit (CASU) and the Wide Field Astronomy Unit (WFAU) in Edinburgh for providing calibrated data products under the support of the Science and Technology Facility Council (STFC) in the UK. M.R. acknowledges support from the German Academic Exchange Service. R.d.G. acknowledges research support from the National Natural Science Foundation of China (grant 11373010). This work was supported by STFC grant numbers ST/J001333/1, ST/M001008/1. This research has made use of the NASA/IPAC Extragalactic Database (NED) which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.
Paper: 2019MNRAS.490..962F (fulltext)
would either require a larger sample of observed dwarf galaxies with smaller error bars and systematic errors of (a difficult prospect) or obtaining spatially resolved rotation curves for 400 pc (within the half-light radii) in small dwarfs, where Fig. 9 shows that CDM/WDM and SIDM/SIWDM could be differentiated. While the differences between DM models in Fig. 10 are marginal, the diversity in the observed population does appear greater than what we find in the suite of simulated dwarfs. Two field dwarfs, Cetus and IC 1613, have derived V 1/2 values that are lower than the 68 confidence region of the analytic fit. While the low V 1/2 values would be more consistent with a lower halo mass, the large sizes of these dwarfs are not expected for a lower halo mass given our simulations’ M halo – r 1/2 relation. Read et al. ( 2016b ) have noted that the gas morphology of IC 1613 implies a state of disequilibrium, which may explain why it is not consistent with our expected relation. A systematic difference in V circ (e.g. from the observed V circ underestimating the true V circ ; Verbeke et al. 2017 ; Oman et al. 2019 ) would explain the difference. We note, however, that we are plotting observationally determined V circ values that are derived from the galaxy kinematics, not from the underlying gravitational potential, for the simulations as well. Moreover, there are other FIRE -2 CDM simulations that agree fairly well with the two points with low V 1/2 values. Chan et al. ( 2018 )’s sample of ultra-diffuse dwarfs () occupy the same space as Cetus and IC 1613, with r 1/2 ∼ 2 kpc and V 1/2 ∼ 20 km s −1 , and the suite of ultra-faint dwarfs in Wheeler et al. (2019 ) contains a number of dwarfs that are directly in line with the analytic fits for haloes with . The two ‘compact’ dwarfs with high V 1/2 values and small half-light radii, Tucana and NGC 6822, are also difficult to explain with the results of our suite. Both reside much further outside the confidence region than the dwarfs with low V 1/2 values. Though our suite of simulations is not part of a Local-Group-like environment, FIRE -2 ΛCDM simulations that simulate LG analogues have found similar difficulty matching high V 1/2 values for isolated dwarf galaxies: Garrison-Kimmel et al. ( 2018 ) found no counterparts in the ELVIS on FIRE suite to observed ‘compact’ dwarfs with high V 1/2 values and small r 1/2 values (e.g.Tucana, NGC 6822, and even satellites such as NGC 205, NGC 147, and IC 10). It has been argued that Tucana has had a previous passage through the MW or M31 disc (Teyssier, Johnston Kuhlen 2012 ), which could invalidate the assumptions of Wolf et al. ( 2010 ) used to derive its V 1/2 . Finally, it is worth noting that the role of ‘chaos’ – more precisely, sensitivity of high-level results to very small numerical changes – could be significant when studying the combined effects of dark matter physics and hydrodynamics. This issue has not been studied extensively, but recent work by
Paper: 2020MNRAS.491.4543S (fulltext)
all but one observation the exposure time was particularly low (i.e. 0.5–1 ks). We estimated the Bayesian 95 per cent upper limit (Kraft et al. ( 1991 ) to the source count rate from the observation with the longer exposure (4.2 ks, n. 4, obs ID 00087498001). It was equal to 0.0025 count s −1 . Using WebPIMMS, it converts into an observed (unabsorbed) 0.3–10 keV flux of ∼4 × 10 −13 erg cm −2 s −1 (∼7.6 × 10 −13 erg cm −2 s −1 ). We assumed the same spectral model as from the Swift / XRT observation n. 3. 3.4.3 Investigation at lower frequencies with archival data Halpern et al. ( 2007 ), using the precise Chandra localization of XTE J1829–098, individuated its probable infrared counterpart through images in the K and H bands as obtained with the MDM 2.4 m telescope on 2005 June 17. The measured magnitudes were H ∼ 13.9 and K ∼ 12.7, no measurement was obtained in the J band. Back in 2005, no additional infrared measurements were available from other infrared surveys, e.g. the UKIDSS survey started on 2005. Currently, we note that the infrared counterpart proposed by Halpern et al. ( 2007 ) has been also detected during the UKIDSS GPS data release 6 with magnitudes J = 16.147 ± 0.009, H = 14.064 ± 0.003, and K = 12.591 ± 0.002. If we use the reddening-free NIR diagnostic Q (Negueruela Schurch 2007 ) with the extinction law of Fitzpatrick ( 1999 ), we note that it has a Q value of –0.7 which is very typical of early-type OB stars. In particular, the negative value strongly indicates an infrared excess. Adopting the UKIDSS infrared magnitudes of such proposed counterpart, we can obtain a rough idea about its distance: if we assume a supergiant B0.5Ib star (with M V = −6.8 mag, V − K = −0.7 and V − J = −0.54), the source should be located at a distance d ∼ 18 kpc (with A V ∼ 21 mag). This implies a V magnitude fainter than V ∼ 30–31 mag. A main-sequence B0 star (assuming M V = −4 mag, V − K = −0.9 and V − J = −0.7), would imply a distance d ∼ 4.5 kpc (with A V ∼ 22 mag), while a giant B0 star (assuming M V = −5 mag, V − K = −0.8 and V − J = −0.7), would be located at about 8 kpc. 3.5 Search for periodicities We performed a timing analysis using the Lomb–Scargle method (Lomb 1976 ; Scargle 1982 ) of the long term INTEGRAL -IBIS and Swift -BAT light curves of the sources under study, in order to search for periodicities which could eventually be ascribed to their orbital periods. For all four sources, the long term IBIS/ISGRI ScW light curves (18–60 keV) cover the observational period from 2003 March to 2015 January. We applied standard optimum filtering in order to exclude poor quality data points which could eventually disrupt the periodic signal (see Goossens et al. 2013 and Sguera et al. 2007 for details). Periodicities were searched for in the range 1–100 d, but none were found. The public access Swift /BAT light curves (15–50 keV) on daily time-scale of all sources but IGR J12341–6143 were also searched for periodic signals in the range 2–250
Paper: 2020ApJ...896...94D (fulltext)
component to the width. Dynamical studies of galaxies typically use Newton’s gravity. However, it has been argued that once galactic masses are considered, relativistic effects arising from large masses (rather than large velocities) may become important (Deur 2009 , 2017 , 2019 ). Their physical origin is that in general relativity (GR), gravity fields self-interact. In this article, we explore whether these effects can explain the relation in MLS2016 without requiring dark matter or modifying gravitation as we currently know it. The article is organized as follows. We first outline the self-interaction effects in GR, then discuss in Section 3 the empirical tight dependence of observed acceleration on baryonic mass in disk (i.e., lenticular and spiral) galaxies. In Section 4 , we use GR’s equations to compute the correlation. These CPU-intensive calculations allow us to study only a few galaxies, modeled as bulgeless disks. To cover the full range of disk galaxy morphologies, including those with a significant bulge, in Section 5 we develop two dynamical models of disk galaxies in different but complementary ways: uniform sampling (Section 5.1 ) and random sampling (Section 5.2 ) of the galactic parameter space. In Section 6 we show the results from these models and compare them to observations. Finally, in Section 7 , we summarize our findings and their importance. 2. Self-interaction Effects in GR Field self-interaction makes GR nonlinear. The phenomenon is neglected when Newton’s law of gravity is used, as is typically done in dynamical studies of galaxies or galaxy clusters. However, such a phenomenon becomes significant once the masses involved are large enough. Furthermore, it is not suppressed by low velocity—unlike some of the more familiar relativistic effects—as revealed by, e.g., the inspection of the post-Newtonian equations (Einstein et al. 1938 ). In fact, the same phenomenon exists for the strong nuclear interaction and is especially prominent for slow-moving quark systems (heavy hadrons), in which case, it produces the well-known quark confining linear potential. The connection between self-interaction and nonlinearities is seen, e.g., by using the polynomial form of the Einstein–Hilbert Lagrangian (see, e.g., Salam 1974 ; Zee 2013 ),where g μν is the metric, R μν is the Ricci tensor, T μν is the energy-momentum tensor, M is the system mass, and G is the gravitational constant. In the natural units () used throughout this article, . The polynomial is obtained by expanding g μν around a constant metric η μν of choice, with the gravitational field. The brackets are shorthand for sums over Lorentz-invariant terms (Deur 2017 ). For example, the n = 0 term is explicitly given by the Fierz–Pauli Lagrangian (Fierz Pauli 1939 ):While Equation ( 1 ) is often used to study quantum gravity—with questions raised regarding its applicability in that context, see, e.g., Padmanabhan ( 2008 )—we stress that the calculations and results