adsabs/AstroCLIMB huggingface dataset:
Paper: The NANOGrav 15 yr Data Set: Search for Transverse Polarization Modes in the Gravitational-wave Background
Authors: Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald, Zaven Arzoumanian, Jeremy Baier, Paul T. Baker, Bence Bécsy, Laura Blecha, Adam Brazier, Paul R. Brook, Sarah Burke-Spolaor, Rand Burnette, Robin Case, J. Andrew Casey-Clyde, Maria Charisi, Shami Chatterjee, Tyler Cohen, James M. Cordes, Neil J. Cornish, Fronefield Crawford, H. Thankful Cromartie, Kathryn Crowter, Megan E. DeCesar, Dallas DeGan, Paul B. Demorest, Timothy Dolch, Brendan Drachler, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Nate Garver-Daniels, Peter A. Gentile, Joseph Glaser, Deborah C. Good, Kayhan Gültekin, Jeffrey S. Hazboun, Ross J. Jennings, Aaron D. Johnson, Megan L. Jones, Andrew R. Kaiser, David L. Kaplan, Luke Zoltan Kelley, Matthew Kerr, Joey S. Key, Nima Laal, Michael T. Lam, William G. Lamb, T. Joseph W. Lazio, Natalia Lewandowska, Tingting Liu, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Chung-Pei Ma, Dustin R. Madison, Alexander McEwen, James W. McKee, Maura A. McLaughlin, Natasha McMann, Bradley W. Meyers, Chiara M. F. Mingarelli, Andrea Mitridate, Priyamvada Natarajan, Cherry Ng, David J. Nice, Stella Koch Ocker, Ken D. Olum, Timothy T. Pennucci, Benetge B. P. Perera, Nihan S. Pol, Henri A. Radovan, Scott M. Ransom, Paul S. Ray, Joseph D. Romano, Alexander Saffer, Shashwat C. Sardesai, Ann Schmiedekamp, Carl Schmiedekamp, Kai Schmitz, Brent J. Shapiro-Albert, Xavier Siemens, Joseph Simon, Magdalena S. Siwek, Ingrid H. Stairs, Daniel R. Stinebring, Kevin Stovall, Jerry P. Sun, Abhimanyu Susobhanan, Joseph K. Swiggum, Jacob A. Taylor, Stephen R. Taylor, Jacob E. Turner, Caner Unal, Michele Vallisneri, Sarah J. Vigeland, Haley M. Wahl, Caitlin A. Witt, Olivia Young
Figure caption: Distributions of the recovered amplitudes from single-component noise-marginalized optimal statistic (SCOS; left) and multicomponent noise-marginalized optimal statistic (MCOS; right) for HD (blue) and ST (orange) correlations. Additionally, CURN (gray) is plotted for comparison to determine the consistency with the common red noise process.
Paper: The NANOGrav 15 yr Data Set: Search for Transverse Polarization Modes in the Gravitational-wave Background
Authors: Gabriella Agazie, Akash Anumarlapudi, Anne M. Archibald, Zaven Arzoumanian, Jeremy Baier, Paul T. Baker, Bence Bécsy, Laura Blecha, Adam Brazier, Paul R. Brook, Sarah Burke-Spolaor, Rand Burnette, Robin Case, J. Andrew Casey-Clyde, Maria Charisi, Shami Chatterjee, Tyler Cohen, James M. Cordes, Neil J. Cornish, Fronefield Crawford, H. Thankful Cromartie, Kathryn Crowter, Megan E. DeCesar, Dallas DeGan, Paul B. Demorest, Timothy Dolch, Brendan Drachler, Elizabeth C. Ferrara, William Fiore, Emmanuel Fonseca, Gabriel E. Freedman, Nate Garver-Daniels, Peter A. Gentile, Joseph Glaser, Deborah C. Good, Kayhan Gültekin, Jeffrey S. Hazboun, Ross J. Jennings, Aaron D. Johnson, Megan L. Jones, Andrew R. Kaiser, David L. Kaplan, Luke Zoltan Kelley, Matthew Kerr, Joey S. Key, Nima Laal, Michael T. Lam, William G. Lamb, T. Joseph W. Lazio, Natalia Lewandowska, Tingting Liu, Duncan R. Lorimer, Jing Luo, Ryan S. Lynch, Chung-Pei Ma, Dustin R. Madison, Alexander McEwen, James W. McKee, Maura A. McLaughlin, Natasha McMann, Bradley W. Meyers, Chiara M. F. Mingarelli, Andrea Mitridate, Priyamvada Natarajan, Cherry Ng, David J. Nice, Stella Koch Ocker, Ken D. Olum, Timothy T. Pennucci, Benetge B. P. Perera, Nihan S. Pol, Henri A. Radovan, Scott M. Ransom, Paul S. Ray, Joseph D. Romano, Alexander Saffer, Shashwat C. Sardesai, Ann Schmiedekamp, Carl Schmiedekamp, Kai Schmitz, Brent J. Shapiro-Albert, Xavier Siemens, Joseph Simon, Magdalena S. Siwek, Ingrid H. Stairs, Daniel R. Stinebring, Kevin Stovall, Jerry P. Sun, Abhimanyu Susobhanan, Joseph K. Swiggum, Jacob A. Taylor, Stephen R. Taylor, Jacob E. Turner, Caner Unal, Michele Vallisneri, Sarah J. Vigeland, Haley M. Wahl, Caitlin A. Witt, Olivia Young
Figure caption: Distributions of the S/N for HD (blue) and ST (orange) correlations from the multicomponent- (MCOS) and single-component (SCOS) noise-marginalized optimal statistic techniques. The dashed lines correspond to the median values and the first and third quartiles. The median S/N values for HD are greater than ST but are within their interquartile range.
Paper: Small-scale Anisotropies of Cosmic Rays from Turbulent Flow
Authors: Yiran Zhang, Siming Liu
Figure caption: Left: fits to the CR angular power spectrum at 10 TeV, with the observational data from Abeysekara et al. (2019). The red solid and blue long-dashed curves represent scenarios described by Equations (6), (10), and (11). The cyan dotted–dashed curve marks the Ahlers (2014; A14) model. The green short-dashed curve refers to modeling by Ahlers & Mertsch (2015; AM15). The black solid line shows the noise level dominated by HAWC, with the dark and light gray bands indicating the 68% and 95% confidence levels, respectively. Though the noise level for IceCube alone is not displayed in Abeysekara et al. (2019), from the sky coverage and number of events one can estimate it to be around 10−11 (Ahlers & Mertsch 2017). Right: turbulence spectra used in the calculation. Note that here we set ﹩{j}_{L}\left({k}_{L}\lambda \right)=\max {j}_{L}﹩ for labeling k  L .
Paper: Small-scale Anisotropies of Cosmic Rays from Turbulent Flow
Authors: Yiran Zhang, Siming Liu
Figure caption: Energy dependence of some C  ℓ  (continued from Figures 2 and 3), where the Fermi data, which appear to be mainly fluctuations around 0 when ℓ > 2, are from Ajello et al. (2019; noise-subtracted).
Paper: Small-scale Anisotropies of Cosmic Rays from Turbulent Flow
Authors: Yiran Zhang, Siming Liu
Figure caption: Multienergy C  ℓ  corresponding to fitting results in Figure 1, with the observational data from Abeysekara et al. (2018; including systematic errors). The colored bands show the noises at a 90% confidence level.
Paper: Small-scale Anisotropies of Cosmic Rays from Turbulent Flow
Authors: Yiran Zhang, Siming Liu
Figure caption: Multienergy C  ℓ  (continued from Figure 2).
Paper: Alpha-to-proton Temperature Ratio Distributions Using Parker Solar Probe Measurements
Authors: Mário B. Amaro, Andris Vaivads
Figure caption: Encounter 5 featuring a crossing of the heliospheric current sheet (HCS). (a) The ratio between radial component and magnitude of the magnetic field; (b) the total magnitude of the magnetic field; (c) differential energy flux pitch angle distribution of electrons in the energy channel 391.4 eV; (d) proton temperature; (e) alpha particle temperature; (f) plasma β; (g) M  A : Alfvén Mach number; (h) alpha-to-proton temperature ratio; (i) proton velocity (black) and alpha velocity (green); (j) Alfvén velocity (green) and proton–alpha velocity difference (black).
Paper: Alpha-to-proton Temperature Ratio Distributions Using Parker Solar Probe Measurements
Authors: Mário B. Amaro, Andris Vaivads
Figure caption: Distribution of excess alpha-to-proton temperature ratio as a function of Coulomb number.
Paper: Alpha-to-proton Temperature Ratio Distributions Using Parker Solar Probe Measurements
Authors: Mário B. Amaro, Andris Vaivads
Figure caption: Distribution of excess alpha-to-proton temperature ratio as a function of NM  A  and N β.
Paper: Alpha-to-proton Temperature Ratio Distributions Using Parker Solar Probe Measurements
Authors: Mário B. Amaro, Andris Vaivads
Figure caption: Distribution of excess alpha-to-proton temperature ratio as a function of Alfvén Mach number and plasma beta.
Paper: Remarkably Compact Quiescent Candidates at 3 < z < 5 in JWST-CEERS
Authors: Lillian Wright, Katherine E. Whitaker, John R. Weaver, Sam E. Cutler, Bingjie Wang, 冰洁 王, Adam Carnall, Katherine A. Suess, Rachel Bezanson, Erica Nelson, Tim B. Miller, Kei Ito, Francesco Valentino
Figure caption: The key takeaway of this Letter is that the measured sizes of 8 out of 10 (80%) candidates in our sample are ∼40% smaller than the mass-dependent extrapolation of the rest-optical effective radii of quiescent galaxies out to z = 5. (Left) We show that the measured sizes of 7 out of 10 (70%) candidates in our sample are smaller than both the size–mass relation at z = 2.75 defined in van der Wel et al. (2014) and the best-fit size–mass relation for the UVJ-selected JWST sample defined in Ito et al. (2023). The black and colored points represent F277W and F444W sizes, respectively. (Right) From the size–mass distribution of our sample, when extrapolating the size–redshift mass-dependent relative evolution from van der Wel et al. (2014) to z = 2.5 (dashed) to the size–redshift distribution of our sample, both color-coded by corresponding stellar mass, the offset remains pronounced. The gray solid and open points represent the F150W and F444W sizes of the quiescent sample from Suess et al. (2022), probing similar rest-frame wavelengths (F150W sizes are not significantly offset from earlier relations). (Middle) The difference between the measured size and predicted size in log space when removing the average size–mass relation demonstrates a clear offset toward smaller sizes at z > 3, not present at lower redshifts or in the λ rest = 5000 Å size of the UVJ-selected quiescent sample from Ito et al. (2023; square).
Paper: CECILIA: Direct O, N, S, and Ar Abundances in Q2343-D40, a Galaxy at z ∼ 3
Authors: Noah S. J. Rogers, Allison L. Strom, Gwen C. Rudie, Ryan F. Trainor, Menelaos Raptis, Caroline von Raesfeld
Figure caption:  T  e [S III]–T  e [O III] trends measured in z ∼ 0 extragalactic H II regions (gray diamonds; see Section 3) and dwarf galaxies (blue squares; see Section 3) and in D40 (green circle) at z ∼ 3. The Garnett (1992) photoionization model T  e [S III]–T  e [O III] relation is shown as the solid red line; the empirical scaling relation of Rogers et al. (2021) is provided as the solid blue line. The dotted line represents equal T  e [S III] and T  e [O III]. The T  e  measured in D40 agree with the T  e  trends of local ionized regions and the empirical T  e –T  e  scaling relation.
Paper: CECILIA: Direct O, N, S, and Ar Abundances in Q2343-D40, a Galaxy at z ∼ 3
Authors: Noah S. J. Rogers, Allison L. Strom, Gwen C. Rudie, Ryan F. Trainor, Menelaos Raptis, Caroline von Raesfeld
Figure caption: Abundance trends of D40 (green circle), local H II regions (gray diamonds), and low-metallicity dwarf galaxies (blue squares). Open blue squares represent dwarf galaxies without direct T  e [S III]. The ⊙ symbol denotes solar abundances from Asplund et al. (2021); the dashed orange line and shaded areas are the solar N/O, S/O, and Ar/O ratios. Top: log(N/O) vs. 12+log(O/H). Middle: log(S/O) vs. 12+log(O/H). Bottom: log(Ar/O) vs. 12+log(O/H). The first T  e -based S and Ar abundances at z ∼ 3 indicate subsolar S/O and Ar/O, suggesting that these three elements are sensitive to O/H or star formation history.
Paper: CECILIA: Direct O, N, S, and Ar Abundances in Q2343-D40, a Galaxy at z ∼ 3
Authors: Noah S. J. Rogers, Allison L. Strom, Gwen C. Rudie, Ryan F. Trainor, Menelaos Raptis, Caroline von Raesfeld
Figure caption: The redshift-corrected NIRSpec spectrum of D40. The top two panels provide the full spectral range of the G235M (left) and G395M (right) spectra, while panels in the bottom row highlight the faint emission lines detected in the G235M spectrum. In each panel, key spectral features are denoted with vertical dotted lines. The Gaussian+linear continuum fits to the emission lines are shown in orange. The auroral lines [O III] λ4364 and [S III] λ6314 are detected at high significance, producing the data required to measure, for the first time in a high-z galaxy, simultaneous T  e [O III] and T  e [S III] and the gas-phase abundances from N, O, S, and Ar.
Paper: The Effect of Fast Solar Wind on Ion Distribution Downstream of Earth’s Bow Shock
Authors: Florian Koller, Savvas Raptis, Manuela Temmer, Tomas Karlsson
Figure caption: Normalized histograms of the highest four integrated energy flux bins given by Equation (1) for each solar wind type. Panel (a) corresponds to F high,4, (b) to F high,3, (c) to F high,2, and (d) to F high,1. The distribution of plasma originating in ejecta is given in black, coronal hole in red, sector reversal in blue, and streamer belt in orange.
Paper: The Effect of Fast Solar Wind on Ion Distribution Downstream of Earth’s Bow Shock
Authors: Florian Koller, Savvas Raptis, Manuela Temmer, Tomas Karlsson
Figure caption: Normalized histograms of F high,3 in different IMF cone angle regimes for each type of solar wind. Panels (a), (b), and (c) show the distribution given in Figure 4(b) divided into high, medium, and low cone angle conditions. Panel (b) shows the high cone angle distribution corresponding to panel (a), intermediate cone angles in panel (d) correspond to panel (c), and low cone angles in panel (f) correspond to panel (e). The same color code of Figure 4 is used.
Paper: The Effect of Fast Solar Wind on Ion Distribution Downstream of Earth’s Bow Shock
Authors: Florian Koller, Savvas Raptis, Manuela Temmer, Tomas Karlsson
Figure caption: THEMIS A magnetosheath measurements during coronal hole origin plasma. The panels follow the same format as Figure 2.
Paper: The Effect of Fast Solar Wind on Ion Distribution Downstream of Earth’s Bow Shock
Authors: Florian Koller, Savvas Raptis, Manuela Temmer, Tomas Karlsson
Figure caption: THEMIS A magnetosheath measurements during streamer belts origin plasma. The panels show (a) ion energy spectrum, (b) integrated top four bins of energy spectrum, (c) associated IMF cone angle, (d) temperature anisotropy, (e) magnetic field components, (f) ion velocity components, and (g) ion density.
Paper: The Effect of Fast Solar Wind on Ion Distribution Downstream of Earth’s Bow Shock
Authors: Florian Koller, Savvas Raptis, Manuela Temmer, Tomas Karlsson
Figure caption: Example events of magnetosheath measurements by THEMIS A during sector reversal (left) and coronal hole (right) plasma. The panels follow the same structure as Figure 7.
Paper: The Effect of Fast Solar Wind on Ion Distribution Downstream of Earth’s Bow Shock
Authors: Florian Koller, Savvas Raptis, Manuela Temmer, Tomas Karlsson
Figure caption: Example events of magnetosheath measurements by THEMIS A during ejecta (left) and streamer belt (right) plasma. The panels show ion energy spectrum (a), (h); integrated top four bins of the energy spectrum (b), (i); associated OMNI IMF cone angle (c), (j); temperature anisotropy (d), (k); magnetic field components (e), (l); ion velocity components (f), (m); and ion density (g), (n).
Paper: The Effect of Fast Solar Wind on Ion Distribution Downstream of Earth’s Bow Shock
Authors: Florian Koller, Savvas Raptis, Manuela Temmer, Tomas Karlsson
Figure caption: Schematic of the dayside magnetosphere and magnetosheath of the Earth. The system is affected by different incoming solar wind types (left side).
Paper: Alpha-to-proton Temperature Ratio Distributions Using Parker Solar Probe Measurements
Authors: Mário B. Amaro, Andris Vaivads
Figure caption: Distribution of excess alpha-to-proton temperature ratio as a function of heliographic distance.
Paper: Remarkably Compact Quiescent Candidates at 3 < z < 5 in JWST-CEERS
Authors: Lillian Wright, Katherine E. Whitaker, John R. Weaver, Sam E. Cutler, Bingjie Wang, 冰洁 王, Adam Carnall, Katherine A. Suess, Rachel Bezanson, Erica Nelson, Tim B. Miller, Kei Ito, Francesco Valentino
Figure caption: Effective radii measured with GALFIT vs. imcascade from F277W (filled symbols) and F444W (open symbols) imaging. Errors are calculated by adding the software generated 1σ errors in quadrature with a second term that scales with S/N in F160W. In general, we find broad agreement between the two independent size measurement methods, which further supports our assertion that these quiescent candidates are extremely compact.
Paper: Remarkably Compact Quiescent Candidates at 3 < z < 5 in JWST-CEERS
Authors: Lillian Wright, Katherine E. Whitaker, John R. Weaver, Sam E. Cutler, Bingjie Wang, 冰洁 王, Adam Carnall, Katherine A. Suess, Rachel Bezanson, Erica Nelson, Tim B. Miller, Kei Ito, Francesco Valentino
Figure caption: The left and middle panels show the Prospector-β-produced median stellar mass and redshift estimates compared to the BAGPIPES-produced estimates reported by Carnall et al. (2023a). All error bars are 1σ and the dashed line shows a 1:1 ratio. The right panel shows the 1σ upper-bound sSFR estimates produced by Prospector-β and BAGPIPES with 1σ errors. The shaded region marks the SFR–M ⋆ relation for star-forming galaxies at z = 3.5–4 from Speagle (2020). The transparent point represents one candidate in the sample that exhibits signs of ongoing star formation, and thus may not be fully quenched.
Paper: Remarkably Compact Quiescent Candidates at 3 < z < 5 in JWST-CEERS
Authors: Lillian Wright, Katherine E. Whitaker, John R. Weaver, Sam E. Cutler, Bingjie Wang, 冰洁 王, Adam Carnall, Katherine A. Suess, Rachel Bezanson, Erica Nelson, Tim B. Miller, Kei Ito, Francesco Valentino
Figure caption: F444W vs. F277W imcascade-measured sizes for our sample. A total of 7 out of 10 (70%) candidates in the sample exhibit F444W sizes smaller than their F277W sizes, 2 candidates (20%) exhibit larger F444W sizes, and 1 candidate (a point source that we believe to be a possible AGN) does not change in size.
Paper: Rest-frame UV Colors for Faint Galaxies at z ∼ 9–16 with the JWST NGDEEP Survey
Authors: Alexa M. Morales, Steven L. Finkelstein, Gene C. K. Leung, Micaela B. Bagley, Nikko J. Cleri, Romeel Dave, Mark Dickinson, Henry C. Ferguson, Nimish P. Hathi, Ewan Jones, Anton M. Koekemoer, Casey Papovich, Pablo G. Pérez-González, Nor Pirzkal, Britton Smith, Stephen M. Wilkins, L. Y. Aaron Yung
Figure caption: Examples of BAGPIPES SED fits to the observed photometry (orange circles) for six cases: (a) the highest-redshift source in our sample at ﹩{z}_{\mathrm{SED}}={15.5}_{-0.3}^{+0.3}﹩, (b) one of the faintest sources in our sample at ﹩{M}_{\mathrm{UV}}=-{16.2}_{-0.2}^{+0.3}﹩, (c) one of the bluest sources in our sample with ﹩{\beta }_{\mathrm{SED},\mathrm{corr}}=-{2.7}_{-0.1}^{+0.1}﹩, (d) one of the “reddest” sources in our sample with ﹩{\beta }_{\mathrm{SED},\mathrm{corr}}=-{1.5}_{-0.2}^{+0.3}﹩, (e) a source where β PL is redder than β SED, and (f) a source where β PL is bluer than β SED. The black line is the SED model with the lowest χ 2 from BAGPIPES, the light-gray shaded region represents the full range of SEDs being fit, and the darker-gray shaded region shows the 1σ bounds of the posterior sample of SED models. The blue (orange) shaded regions and lines represent the best-fit line to the photometry, where the UV spectral slopes and errors are obtained from when fit via the SED (photometric power-law) method. It is clear, especially in the last two cases, that scatter in a single photometric band can affect β PL significantly more than β SED.
Paper: Rest-frame UV Colors for Faint Galaxies at z ∼ 9–16 with the JWST NGDEEP Survey
Authors: Alexa M. Morales, Steven L. Finkelstein, Gene C. K. Leung, Micaela B. Bagley, Nikko J. Cleri, Romeel Dave, Mark Dickinson, Henry C. Ferguson, Nimish P. Hathi, Ewan Jones, Anton M. Koekemoer, Casey Papovich, Pablo G. Pérez-González, Nor Pirzkal, Britton Smith, Stephen M. Wilkins, L. Y. Aaron Yung
Figure caption: UV β slope derived from photometric power-law fitting vs. from SED fitting color-coded by redshift. Original β values are shown as open circles, while the filled circles have their SED-fitting-based β corrected for measurement bias (discussed in Section 4.2). The blue dashed horizontal line is the bluest β SED can go with BAGPIPES, and the gray dashed line is the one-to-one line when equating β SED to β PL. This relation shows that photometric power-law fitting, on average, yields bluer UV slopes and larger errors than SED fitting.
Paper: Rest-frame UV Colors for Faint Galaxies at z ∼ 9–16 with the JWST NGDEEP Survey
Authors: Alexa M. Morales, Steven L. Finkelstein, Gene C. K. Leung, Micaela B. Bagley, Nikko J. Cleri, Romeel Dave, Mark Dickinson, Henry C. Ferguson, Nimish P. Hathi, Ewan Jones, Anton M. Koekemoer, Casey Papovich, Pablo G. Pérez-González, Nor Pirzkal, Britton Smith, Stephen M. Wilkins, L. Y. Aaron Yung
Figure caption: Main panel:  The implicit prior on the UV β slope from our SED fitting method. We show here that the prior on β is allowed to reach β values ∼−3.0 and to the blue “floor.” Inset: The normalized posterior for β SED for a source whose mock spectrum is set to β = −3.0 (blue line). We use the same priors and allow redshift to be free from z = 0 to 20. Here we set the S/N to ∼5 (solid curve) and ∼10 (dashed curve) and show that BAGPIPES is able to recover β values close to the “true” β value.
Paper: Rest-frame UV Colors for Faint Galaxies at z ∼ 9–16 with the JWST NGDEEP Survey
Authors: Alexa M. Morales, Steven L. Finkelstein, Gene C. K. Leung, Micaela B. Bagley, Nikko J. Cleri, Romeel Dave, Mark Dickinson, Henry C. Ferguson, Nimish P. Hathi, Ewan Jones, Anton M. Koekemoer, Casey Papovich, Pablo G. Pérez-González, Nor Pirzkal, Britton Smith, Stephen M. Wilkins, L. Y. Aaron Yung
Figure caption: The results of our source injection simulations. The first two panels show the input value of β vs. the recovered SED-fitted (left) and photometric power-law (middle) β. The SED method has a tighter scatter, though it exhibits a clear bias to redder measured values at true values of β ≲ −2. The photometric power-law method shows a significantly larger scatter, as well as a larger bias (in the blue direction) at all input values of β. This scatter can be seen both for the sample as a whole (pink data points) and for the running median (black data points), which describes the median and 1σ spread of the distribution. We quantify these biases in the right panel, showing the difference in β as a function of the rest-UV color for our simulated sources. These colors are chosen because they can be measured for real galaxies (where the intrinsic β is not known). We show that the SED fitting method results in a more accurate recovery of β than photometric power-law fitting. However, as there is still a significant bias, we use this measured Δβ value as a correction factor applied to β SED for the observed galaxies in our sample (see Figure 2). As the scatter and bias are both worse for β PL, and we use β SED for our analysis below, we do not apply these corrections to β PL.