adsabs/AstroCLIMB huggingface dataset:
Paper: Extreme Rarefaction of Solar Wind: A Study on Origin and Characteristics Using Ulysses Observations
Authors: Rajkumar Hajra, Bruce T. Tsurutani, Quanming Lu, Lican Shan, Aimin Du, Rongsheng Wang, San Lu, Xinliang Gao
Figure caption: Solar wind variations on days 150–169 of year 1993. From top to bottom, the panels are (a) V sw (km s−1, black, scale on the left), V A (km s−1, blue, scale on the right) and V ms (km s−1, red, scale on the right); (b) N  p  (cm−3); (c) N  α  (cm−3, black, scale on the left) and N  α /N  p  (red, scale on the right); (d) P sw (nPa, black, scale on the left) and J  p  (10−22 kg cm−2 s−1, red, scale on the right); (e) T  p  (K, black, scale on the left) and β (red, scale on the right); (f) M A (black) and M ms (red); (g) IMF B 0 (nT, black), B  R  (nT, blue), B  T  (nT, green), and B  N  (nT, red); (h) r  h  (au, black, scale on the left) and heliographic latitude (degree, red, scale on the right). Blue and red curves in panel (b) indicate the radially average N  p  (〈N  p 〉) and 10% level of 〈N  p 〉, respectively. Vertical solid lines show interplanetary fast reverse (FR) shocks, and the vertical dashed line shows a fast forward (FF) shock. The blue horizontal bar at the top and cyan shading indicate a CIR, the green bar indicates an interplanetary sheath, and the red bar and magenta hatching indicate a magnetic cloud. An ELDSW event is marked by a horizontal bar in panel (b) and a gray shading.
Paper: Extreme Rarefaction of Solar Wind: A Study on Origin and Characteristics Using Ulysses Observations
Authors: Rajkumar Hajra, Bruce T. Tsurutani, Quanming Lu, Lican Shan, Aimin Du, Rongsheng Wang, San Lu, Xinliang Gao
Figure caption: Solar wind plasma observations by Ulysses. From top to bottom, the panels show (a) proton density N  p ; (b) heliocentric distance r  h ; (c) heliographic latitude; (d) yearly numbers of ELDSW events (gray histograms, scale on the left), and yearly mean F 10.7 solar radio flux (red curve, scale on the right). In panel (a), the blue line indicates 4.21r  h  −1.98, the model fit to N  p , and the red line indicates 10% of the model values. See text for details. The vertical hatched region in 2009 and 2010 indicates a poor plasma data interval. The latter was not included in the analysis.
Paper: Extreme Rarefaction of Solar Wind: A Study on Origin and Characteristics Using Ulysses Observations
Authors: Rajkumar Hajra, Bruce T. Tsurutani, Quanming Lu, Lican Shan, Aimin Du, Rongsheng Wang, San Lu, Xinliang Gao
Figure caption: Variations of IMF on days 158–165 of year 1993. From top to bottom, panels are variations of (a) N  p ; (b) IMF B 0 (black), B  R  (blue), B  T  (green), and B  N  (red); normalized variances of (c) B  R , (d) B  T  and (e) B  N . In panels (c)–(e), black, red, and green colors correspond to the normalized variances for 45 minutes, 15 minutes, and 5 minutes, respectively. The markings of interplanetary structures are repeated from Figure 4.
Paper: Extreme Rarefaction of Solar Wind: A Study on Origin and Characteristics Using Ulysses Observations
Authors: Rajkumar Hajra, Bruce T. Tsurutani, Quanming Lu, Lican Shan, Aimin Du, Rongsheng Wang, San Lu, Xinliang Gao
Figure caption: Solar wind variations on days 80–97 of year 1991. Panels are in the same format as in Figure 4. The vertical dashed line indicates an FF shock. An interplanetary sheath following the shock is marked by a horizontal green bar at the top. Three MC intervals are marked by horizontal red bars at the top and magenta hatchings. The ELDSW events are marked by gray shadings and horizontal black bars in panel (b).
Paper: Extreme Rarefaction of Solar Wind: A Study on Origin and Characteristics Using Ulysses Observations
Authors: Rajkumar Hajra, Bruce T. Tsurutani, Quanming Lu, Lican Shan, Aimin Du, Rongsheng Wang, San Lu, Xinliang Gao
Figure caption: Solar wind variations on days 123–146 of year 1998. The format is the same as in Figure 4. Vertical dashed lines indicate FF shocks. A CIR following the shock is marked by a blue bar at the top and a cyan shading. The gray shading following the CIR is an HSS interval. A black bar in panel (b) shows an ELDSW event that is coincident with the HSS interval.
Paper: Extreme Rarefaction of Solar Wind: A Study on Origin and Characteristics Using Ulysses Observations
Authors: Rajkumar Hajra, Bruce T. Tsurutani, Quanming Lu, Lican Shan, Aimin Du, Rongsheng Wang, San Lu, Xinliang Gao
Figure caption: Radial variations of (a) N  p , (b) P sw, and (c) J  p . Black diamonds and red dots correspond to all solar wind (SW) data and the ELDSW events, respectively. Red curves in each panel indicate power-law variations of the average parameters for all solar wind data.
Paper: Extreme Rarefaction of Solar Wind: A Study on Origin and Characteristics Using Ulysses Observations
Authors: Rajkumar Hajra, Bruce T. Tsurutani, Quanming Lu, Lican Shan, Aimin Du, Rongsheng Wang, San Lu, Xinliang Gao
Figure caption: Radial and heliographic latitude dependences of the ELDSW events. (a) Radial distribution of ELDSWs. (b) ELDSW event number as a function of r  h  (horizontal scale) and heliographic latitude (left-hand vertical scale). The ELDSW number corresponding to each color is given by the color bar on the left. (c) Latitudinal distribution of ELDSWs.
Paper: Extreme Rarefaction of Solar Wind: A Study on Origin and Characteristics Using Ulysses Observations
Authors: Rajkumar Hajra, Bruce T. Tsurutani, Quanming Lu, Lican Shan, Aimin Du, Rongsheng Wang, San Lu, Xinliang Gao
Figure caption: Solar wind variations on days 115–129 of year 1998. Panels are in the same format as in Figure 4. The vertical dashed lines indicate FF shocks. Gray shading and a horizontal black bar in panel (b) indicate an ELDSW event.
Paper: Jet-powered Turbulence in Common Envelope Evolution
Authors: Shlomi Hillel, Ron Schreier, Noam Soker
Figure caption: Upper panels: velocity arrows on top of the curl of the velocity map ﹩{(\overrightarrow{{\rm{\nabla }}}\times \overrightarrow{v})}_{z}﹩ in the z = 6 × 1012 cm = 86 R ⊙ plane (left) and of ﹩{(\overrightarrow{{\rm{\nabla }}}\times \overrightarrow{v})}_{y}﹩ in the plane y = 1.8 × 1013 cm = 259 R ⊙ (right), at t = 3.2 yr  (the units of the color bar are s−1). Lower panels: velocity arrows on top of the velocity magnitudes according to the color bar (units of cm s−1) and in the same planes and the same times as in the upper panels. The maximum velocity in the plane on the left is 40 km s−1 and in the plane on the right it is 105 km s−1. The high-velocity flow on both sides of the equatorial plane in the right panels are due to the two jets launched by the NS, which at this time is at (x, y, z)NS  =  (151 R ⊙, 259 R ⊙, 0).
Paper: Jet-powered Turbulence in Common Envelope Evolution
Authors: Shlomi Hillel, Ron Schreier, Noam Soker
Figure caption: The angular momentum that the jets deposit into the envelope as function of time (dotted-blue line, scale on the left) and the specific angular momentum in the envelope (solid-red line, scale on the right) as a function of time.
Paper: On the Blackbody Spectrum of Kilonovae
Authors: Albert Sneppen
Figure caption: Best-fit Δχ 2(α, β) and luminosity distance given the varying rates of cooling and velocities using the Nelder–Mead method of χ 2 minimization. For each combination of parameters α and β = v  bb /c we determine the best-fit blackbody temperature, distance, and χ 2. The dashed lines in the left panel show the significance level in standard deviations of which parts of the parameter landscape are disfavored by when compared to the best-fit model. The significance level is computed from the p-value of the χ 2 distribution with the relevant number of degrees of freedom when assuming ﹩{\chi }_{\mathrm{reduced}}^{2}=1﹩ for the best-fit model. The blue hatched region in the right panel indicates all parts of the parameter landscape yielding distances within 2σ of the reported distance in Sneppen et al. (2023a), D  L  = 44.5 ± 0.8 Mpc. Naturally, if the normalization was kept fixed across the parameter landscape the variation in χ 2 would be even more significant. There are small-scale wiggles in the Δχ 2(α, β) and D  L  landscape, because of the numerical uncertainties in finding the best-fit global minimum (and not a nearby local minimum), while there are larger monotonic trends due to the spectral corrections from f(β, λ) toward low/high cooling rates and/or higher velocities.
Paper: On the Blackbody Spectrum of Kilonovae
Authors: Albert Sneppen
Figure caption: X-shooter spectra of AT2017gfo at 1.43 days postmerger displaying the UV (purple), VIS (blue), and NIR arms (red) separately. For each arm of the spectrograph, the best-fit temperature is fit independently assuming the same blackbody normalization (i.e., the same angular size). These best fits are drawn as solid lines across the spectral arm where they are fit, and shown as dashed lines over the wavelengths, where the fit is being extrapolated. The temperature constraints fitted from each arm are consistent at the percent level and the fits are in near agreement with the observed spectrum even at the extrapolated wavelengths. The blackbody normalization assumed for all epochs follows from the Planck cosmological distance D  L  = 44.2 ± 2.3 Mpc to NGC 4993 (Planck Collaboration et al. 2020), and assuming the emitting area predicted from the 1 μm P Cygni (Watson et al. 2019). We also fit the proposed 1.5 and 2 μm emission lines (Gillanders et al. 2023) when constraining the NIR arm, but ultimately these features are not prominent enough to bias the best-fit temperature significantly.
Paper: On the Blackbody Spectrum of Kilonovae
Authors: Albert Sneppen
Figure caption: The inferred temperature at the front of the expanding photosphere given varying cooling rates, α, and velocities, β = v  bb /c. Larger velocities result in a larger Doppler corrections to the observed temperature, which naturally imply that the ejected material was cooler in the emitted reference frame. Larger cooling rates imply the more distant portions of the photosphere are relatively hotter, so a smaller temperature at the front is required to fit the data. Constraints on v  bb  (blue; Sneppen et al. 2023a), α (orange and red; Drout et al. 2017) are elaborated in Section 3.
Paper: Constraints on Strong Phase Transitions in Neutron Stars
Authors: T. Gorda, K. Hebeler, A. Kurkela, A. Schwenk, A. Vuorinen
Figure caption: Regions of allowed pressures p and central energy densities ϵ (top panel) and the corresponding M–R region (bottom panel) along stable NS sequences for all EOSs within our ensemble after imposing the two astrophysical constraints M TOV > 2M ⊙ and ﹩{\tilde{{\rm{\Lambda }}}}_{\mathrm{GW}170817}\lt 720﹩. In the top panel, the cyan region corresponds to our matching p–ϵ region at n = 10n 0, while in the bottom panel, the black outline displays the allowed region of EOSs from Annala et al. (2022), which does not include explicit PTs.
Paper: Secondary Proton Beam Instability in a Turbulent Solar Wind at 50 R ⊙ 
Authors: S. A. Markovskii, Bernard J. Vasquez
Figure caption: Relative speed of the secondary beam V  d b /V A as a function of y and z averaged over the x coordinate at ﹩t=160{{\rm{\Omega }}}_{p}^{-1}.﹩
Paper: Secondary Proton Beam Instability in a Turbulent Solar Wind at 50 R ⊙ 
Authors: S. A. Markovskii, Bernard J. Vasquez
Figure caption: Reduced magnetic power spectrum P along the artificial spacecraft path at (a) A = 0.14 (black line) and (b) A = 0 (green line). The Kolmogorov −5/3 spectral slope is shown for reference by the red dashed line. The spectra are averaged over the time interval 460 ≤ Ω p  t ≤ 600 in the saturation phase of the instability.
Paper: Secondary Proton Beam Instability in a Turbulent Solar Wind at 50 R ⊙ 
Authors: S. A. Markovskii, Bernard J. Vasquez
Figure caption: Time dependence of the total intensity I of the magnetic fluctuations, normalized to ﹩{B}_{0}^{2},﹩ associated with (a) the nearly parallel instability without turbulence (black line), (b) the nearly parallel instability coexisting with the turbulence (red line), (c) the moderately oblique instability without turbulence (blue line), and (d) the moderately oblique instability coexisting with the turbulence (green line). The intensity of the moderately oblique instability is multiplied by a factor of 5 in the figure to enhance visibility.
Paper: Constraints on Strong Phase Transitions in Neutron Stars
Authors: T. Gorda, K. Hebeler, A. Kurkela, A. Schwenk, A. Vuorinen
Figure caption: The same M–R region as in the bottom panel of Figure 1 but this time keeping only EOSs with transition densities n PT < 2.0n 0 (top panel) or n PT ≥ 2.0n 0 (bottom panel). Note the different scales in the color bars.
Paper: Secondary Proton Beam Instability in a Turbulent Solar Wind at 50 R ⊙ 
Authors: S. A. Markovskii, Bernard J. Vasquez
Figure caption: Time dependence of the maximum intensity I max of the magnetic fluctuations, normalized to ﹩{B}_{0}^{2},﹩ associated with (a) the nearly parallel instability without turbulence (black line), (b) the nearly parallel instability coexisting with the turbulence (red line), (c) the moderately oblique instability without turbulence (blue line), and (d) the moderately oblique instability coexisting with the turbulence (green line).
Paper: Secondary Proton Beam Instability in a Turbulent Solar Wind at 50 R ⊙ 
Authors: S. A. Markovskii, Bernard J. Vasquez
Figure caption: Reduced magnetic power spectrum P along the artificial spacecraft path at A = 0.14 and a sampling angle of (a) 32° (black line), (b) 50° (red line), and (c) 90° (green line). The spectra are averaged over the time interval 460 ≤ Ω p  t ≤ 600 in the saturation phase of the instability.
Paper: Secondary Proton Beam Instability in a Turbulent Solar Wind at 50 R ⊙ 
Authors: S. A. Markovskii, Bernard J. Vasquez
Figure caption: Distribution functions f of the protons (in arbitrary units) in the regions marked in Figure 8. The top (black) and bottom (red) curve correspond to the top and bottom regions, respectively. The distributions are summed over v  y  and v  z .
Paper: Pulsar Timing Array Detections of Supermassive Binary Black Holes: Implications from the Detected Common Process Signal and Beyond
Authors: Yunfeng Chen, Qingjuan Yu, Youjun Lu
Figure caption: Distributions of individual BBHs in the strain–frequency diagram (left panel) and in the celestial sphere (right panel), obtained from realizations of the local BBH population based on the local sample of MBHs (≲500 Mpc). To obtain those individual BBHs, 10,000 realizations of the local BBH population have been conducted, based on the procedures outlined in Section 2.2.1, resulting in 347 loud sources in 344 skies being identified. In the figure, each filled circle located at either its GW emission frequency (left panel) or its celestial coordinates (right panel) corresponds to a BBH system with GW strain amplitude (see Equation (5)) being above the 95% upper limit skymap taken from Mingarelli et al. (2017), where the color and size of the circle indicate the GW strain amplitude and the BBH chirp mass, respectively. The BBH population model adopted here produces a stochastic GWB with amplitude the same as the fiducial value of the common process signal (Arzoumanian et al. 2020), i.e., the delay-﹩{{ \mathcal A }}_{1}﹩ model in Table 3. In the left panel, the sky-averaged 95% upper limit on the strain amplitude of individual BBHs based on the current PTAs, i.e., NANOGrav 11 yr timing data (Aggarwal et al. 2019), EPTA DR1 timing data (Babak et al. 2016), and PPTA DR1 timing data (Zhu et al. 2014), is also shown as references by the dotted, solid, and dashed curves, respectively. In the right panel, the six best MSPs among the EPTA pulsars are shown by the purple star symbols (Babak et al. 2016). See Section 4.2.2 for details.
Paper: Pulsar Timing Array Detections of Supermassive Binary Black Holes: Implications from the Detected Common Process Signal and Beyond
Authors: Yunfeng Chen, Qingjuan Yu, Youjun Lu
Figure caption: Expected S/Ns of the stochastic GWB detection (green; left y-axis) and expected numbers of detectable BBHs (red; right y-axis) by different PTAs as a function of PTA observation time T. In each panel, the “*” symbol appended to each PTA name indicates that the assumed parameters are the same as those listed in Table 2, except that the PTA observation time T is set as a free parameter. To quantify the uncertainties of the expected quantities, we have considered three sets of models, i.e., delay-﹩{{ \mathcal A }}_{1}﹩, delay-﹩{{ \mathcal A }}_{max}^{{\rm{e}}}﹩, and delay-﹩{{ \mathcal A }}_{\mathrm{med}}^{{\rm{e}}}﹩ (see Table 5), respectively, corresponding to the upper boundary, thick curve in the middle, and the lower boundary of each shaded region. Top panels show the results for the two conservative PTA configurations, and the lower panels for the two optimistic PTA configurations. In each panel, the green filled circles mark the observation times when the S/N of the stochastic GWB detection equals the values of 3, 5, and 8, and the red filled diamonds mark the observation time when the expected number of detectable BBHs equals the values of 1 and 3 (with a threshold S/N ρ th = 3). See Section 4.2.2 for details.
Paper: Pulsar Timing Array Detections of Supermassive Binary Black Holes: Implications from the Detected Common Process Signal and Beyond
Authors: Yunfeng Chen, Qingjuan Yu, Youjun Lu
Figure caption: Constraints on the parameters of the MBH–host galaxy scaling relation (see Equation (4)) from the GWB, with (left panel) and without (right panel) considering the time delays between BBH coalescences and their host galaxy mergers in the BBH population model, respectively, where the scaling relationship between M BH and M bulge is assumed to be redshift-independent, i.e., ﹩\tilde{\omega }=0﹩, ﹩\tilde{\beta }=0﹩. The GWB is assumed to have an amplitude the same as the common process signal discovered in the NANOGrav 12.5 yr data set (Arzoumanian et al. 2020). The top panel in each column shows the one-dimensional probability distribution of the parameters, and the values listed above each top panel give the median values and 16%–84% quantiles of the corresponding parameter as evaluated from the posterior distributions (also shown as the blue solid and dashed vertical lines in the panels). The other panels show the two-dimension distribution of the parameters. For comparison, the corresponding parameters of the M BH–M bulge relations taken from McConnell & Ma (2013; orange), Kormendy & Ho (2013; green) are also shown in the one- and two-dimensional distributions. See Section 4.1 for details.
Paper: Pulsar Timing Array Detections of Supermassive Binary Black Holes: Implications from the Detected Common Process Signal and Beyond
Authors: Yunfeng Chen, Qingjuan Yu, Youjun Lu
Figure caption: Detection probabilities of individual BBHs for different sets of models and for different PTAs capabilities. We consider the current PTA detection capability by adopting the 95% upper limit skymap taken from Mingarelli et al. (2017), and future PTA capabilities with sensitivity a factor of 1/2, 1/4, 1/8, or 1/16 of the current one. The results for models adopting the constrained scaling relations with and without redshift evolution are shown in the left and middle panels, respectively; while the right panel shows the results obtained from those models adopting the empirical scaling relations. The dashed and solid curves correspond to detections of the local and global BBH populations, respectively. The data points and their error bars are adapted from Table 4.
Paper: Pulsar Timing Array Detections of Supermassive Binary Black Holes: Implications from the Detected Common Process Signal and Beyond
Authors: Yunfeng Chen, Qingjuan Yu, Youjun Lu
Figure caption: The expected sensitivity curves for individual BBH detection by some (future) PTAs (in Table 2). The blue (orange) dashed and solid curves show the expected sensitive curves (with a threshold S/N ρ th = 1) for the conservative-CPTA and optimistic-CPTA (conservative-SKAPTA and optimistic-SKAPTA), respectively. The other curves are the reference curves. The gray dotted, solid, and dashed curves show the sky-averaged 95% upper limits on the strain amplitude of individual BBHs based on the current PTA observations, i.e., based on NANOGrav 11 yr timing data (Aggarwal et al. 2019), EPTA DR1 timing data (Babak et al. 2016), and PPTA DR1 timing data (Zhu et al. 2014), respectively. The black dots also show the sky-averaged 95% upper limits based on EPTA DR1 timing data (Desvignes et al. 2016) given by Mingarelli et al. (2017). The green curve shows the simulated sky-averaged 95% upper limits for the current NANOGrav program followed by 10 yr of ngVLA observations (NANOGrav Collaboration 2018). See Section 3.3 for details.
Paper: High-resolution Chemical Abundances of the Nyx Stream
Authors: Shuyu Wang, 书玉 汪, Lina Necib, Alexander P. Ji, Xiaowei Ou, Mariangela Lisanti, Mithi A. C. de los Reyes, Allison L. Strom, Mimi Truong
Figure caption: Absolute chemical abundances ([X/Fe] vs. [Fe/H]. The y-axis is [X/Fe], except in the panel where another ratio is indicated) of the observed Nyx stars, color-coded by effective temperature, T eff. The effective temperatures range from 4200 to 6000  K. For comparison, 3 Sgr dwarf galaxy stars from McWilliam et al. (2013) are shown by green triangles. The 12 Sgr dwarf galaxy giants from Sbordone et al. (2007) are indicated by red plusses. The dashed line at [X/Fe]  =  0.0 is shown in each panel as a reference. The dashed red line at [Ba/Eu]  = −0.8 indicates the pure r-process ratio (Sneden et al. 2008). In general, the chemical abundances of the metal-rich Nyx component are distinct from those of the Sgr stars.
Paper: Pulsar Timing Array Detections of Supermassive Binary Black Holes: Implications from the Detected Common Process Signal and Beyond
Authors: Yunfeng Chen, Qingjuan Yu, Youjun Lu
Figure caption: Legends are the same as that for Figure 4, except that the global BBH population are plotted here. Among the 10,000 realizations of the BBH global populations, 587 loud individual BBHs in 563 skies are identified with strain amplitudes above the EPTA sensitivity skymap (Mingarelli et al. 2017), as represented by each filled circle in both panels. See Section 4.2.2 for more details.
Paper: Pulsar Timing Array Detections of Supermassive Binary Black Holes: Implications from the Detected Common Process Signal and Beyond
Authors: Yunfeng Chen, Qingjuan Yu, Youjun Lu
Figure caption: Legends are the same as that for Figure 2, except that the MBH–host galaxy scaling relation (Equation (4)) is set to be redshift-dependent with ﹩\tilde{\gamma }=8.69﹩, and ﹩\tilde{\beta }=0﹩, the same as that given in Kormendy & Ho (2013). See Section 4.1 for details.
Paper: Jet-powered Turbulence in Common Envelope Evolution
Authors: Shlomi Hillel, Ron Schreier, Noam Soker
Figure caption: Maps in the z = 0 plane of the tracers of two shells (see text) at regular resolution (left column) and at high resolution (right column) for the no-jets simulations. The times from top to bottom are t = 0, t = 1.5 yr, and t = 3.2 yr. The value of the tracer is denoted according to the upper color bar from 0 (deep blue) to 1 in the upper two panels in the right column, and to 0.5 in the left column and in the lower right panel (deep red). The initial value of the tracer is 1, but in the regular-resolution grid the cells do not fully resolve the initial shell. The circles with a radius of R RSG = 881 R ⊙ are the surface of the RSG star at t = 0.