adsabs/AstroCLIMB huggingface dataset:
Paper: The Importance of Dust Distribution in Ionizing-photon Escape: NIRCam and MIRI Imaging of a Lyman Continuum-emitting Galaxy at z ∼ 3.8
Authors: Zhiyuan Ji, Stacey Alberts, Yongda Zhu, Eros Vanzella, Mauro Giavalisco, Kevin Hainline, William M. Baker, Andrew J. Bunker, Jakob M. Helton, Jianwei Lyu, Pierluigi Rinaldi, Brant Robertson, Charlotte Simmonds, Sandro Tacchella, Christina C. Williams, Christopher N. A. Willmer, Joris Witstok
Figure caption: Left: MIRI/F1500W imaging of Ion1. The white “+” marks the stellar centroid determined using LW NIRCam imaging. The light-green arrows point to the two local flux maxima referred to in the text (Section 4). Right: The top panel shows the comparison between the best-fit PSF model from GALFIT (black dashed line) and the observed, azimuthally averaged surface brightness profile (red). Similarly, in the bottom panel, we compare the best-fit PSF model with the surface brightness variation along the direction of the vector illustrated in the inset plot. In both comparisons, we also include the alternative PSF model from M. Libralato et al. (2024), shown as a gray dotted line, which largely overlaps with the black dashed line, as it is very similar to the default PSF model we produced using our own F1500W mosaic (Section 4). To estimate the observational uncertainty, we use the error flux extension of the MIRI data to perform Monte Carlo resampling of the imaging pixel values, repeating the surface brightness measurements 104 times. The 16th–84th percentile range is adopted as the 1σ uncertainty. Significantly differing from an unresolved PSF, Ion1’s observed hot dust (F1500W) emission shows a complex spatial distribution near the center, i.e., within ≲0.2 of the stellar centroid.
Paper: The Importance of Dust Distribution in Ionizing-photon Escape: NIRCam and MIRI Imaging of a Lyman Continuum-emitting Galaxy at z ∼ 3.8
Authors: Zhiyuan Ji, Stacey Alberts, Yongda Zhu, Eros Vanzella, Mauro Giavalisco, Kevin Hainline, William M. Baker, Andrew J. Bunker, Jakob M. Helton, Jianwei Lyu, Pierluigi Rinaldi, Brant Robertson, Charlotte Simmonds, Sandro Tacchella, Christina C. Williams, Christopher N. A. Willmer, Joris Witstok
Figure caption: Left: fiducial SED fitting of Ion1 at zspec = 3.794. The orange line represents the best-fit model, which is decomposed into the stellar and nebular components (black line) and the dust emission component (red line). The bottom subpanel shows the relative difference between the data and the best-fit model, calculated as (Data − Model)/Data. The three filters covering the LyC emission—VLT/U band, HST/F410M, and F435W (the left-most three data points in the plot)—are excluded from the SED fitting. Hot dust emission is required to reproduce the observed F1500W flux of Ion1. Right: reconstructed SFH of Ion1. In addition to the SFH from our fiducial SED fitting, we also show results from two other assumed SFHs: a nonparametric continuity SFH with different lookback time bins (black dashed line), and a parametric delayed-tau (t · e−t/τ) SFH (blue dashed line). The green square indicates the SFR estimated using the flux excess of NIRCam/F356W relative to F335M due to Hα emission (Section 4.2).
Paper: The Importance of Dust Distribution in Ionizing-photon Escape: NIRCam and MIRI Imaging of a Lyman Continuum-emitting Galaxy at z ∼ 3.8
Authors: Zhiyuan Ji, Stacey Alberts, Yongda Zhu, Eros Vanzella, Mauro Giavalisco, Kevin Hainline, William M. Baker, Andrew J. Bunker, Jakob M. Helton, Jianwei Lyu, Pierluigi Rinaldi, Brant Robertson, Charlotte Simmonds, Sandro Tacchella, Christina C. Williams, Christopher N. A. Willmer, Joris Witstok
Figure caption: NIRCam 2″ × 2″ cutouts of Ion1. The rest-frame wavelength range probed by each filter is labeled in the top-left corner. In the bottom-left corner, the angular resolution of each filter is illustrated with a filled pink circle, whose diameter is set to the FWHM of the PSF. The dashed blue contour and diamond show the 0.5σ isophote and the peak (S/N ∼ 4.2) of Ion1’s LyC emission (from HST WFC3/UVIS imaging obtained by Z. Ji et al. 2020, see text). In these cutouts, we use a logarithmic color scale, with the minimum (black) and maximum values being the 1σ and 200σ local surface brightness limits. The 1σ limits are 25.8, 26.2, 26.3, 26.4, 26.5, 27.3, 27.0, 27.4, 26.8, 27.1 magAB/arcsec2 from F070W through F444W.
Paper: The Importance of Dust Distribution in Ionizing-photon Escape: NIRCam and MIRI Imaging of a Lyman Continuum-emitting Galaxy at z ∼ 3.8
Authors: Zhiyuan Ji, Stacey Alberts, Yongda Zhu, Eros Vanzella, Mauro Giavalisco, Kevin Hainline, William M. Baker, Andrew J. Bunker, Jakob M. Helton, Jianwei Lyu, Pierluigi Rinaldi, Brant Robertson, Charlotte Simmonds, Sandro Tacchella, Christina C. Williams, Christopher N. A. Willmer, Joris Witstok
Figure caption: Pixel-by-pixel SED fitting of Ion1. From left to right, we show the maps of AV, ﹩{\dot{n}}_{{\rm{ion}},0}﹩ , and ξion,0, respectively. The strong FUV-to-optical color gradient of Ion1 is primarily driven by significant spatial variation in dust attenuation. In particular, the northeastern regions of Ion1 exhibit much lower dust attenuation than the rest of the galaxy. The LyC contours, identical to those shown in the top row of Figure 4, are overlaid in dark pink. The black “+” marks the center of stellar light.
Paper: The Importance of Dust Distribution in Ionizing-photon Escape: NIRCam and MIRI Imaging of a Lyman Continuum-emitting Galaxy at z ∼ 3.8
Authors: Zhiyuan Ji, Stacey Alberts, Yongda Zhu, Eros Vanzella, Mauro Giavalisco, Kevin Hainline, William M. Baker, Andrew J. Bunker, Jakob M. Helton, Jianwei Lyu, Pierluigi Rinaldi, Brant Robertson, Charlotte Simmonds, Sandro Tacchella, Christina C. Williams, Christopher N. A. Willmer, Joris Witstok
Figure caption: Deep NIRCam imaging of the regions adjacent to Ion1. Two bright foreground galaxies at z < 3.794, previously detected by HST, are marked in orange with their redshifts and CANDELS IDs labeled (Y. Guo et al. 2013). White arrows indicate two galaxies newly detected by JADES/NIRCam observations, whose photometric redshifts are not consistent with Ion1. Pink arrows highlight the other two newly detected galaxies, whose photometric redshift solutions are consistent with Ion1’s spectroscopic redshift. The middle panel presents the best-fit EAZY models for these two galaxies, while the inset shows the probability distribution of the photometric redshift, ﹩P(z)\sim {e}^{-{\chi }^{2}(z)/2}﹩, with the black dashed line marking z = 3.794. The right panel shows the NIRCam wide filter images of these two galaxies.
Paper: The Importance of Dust Distribution in Ionizing-photon Escape: NIRCam and MIRI Imaging of a Lyman Continuum-emitting Galaxy at z ∼ 3.8
Authors: Zhiyuan Ji, Stacey Alberts, Yongda Zhu, Eros Vanzella, Mauro Giavalisco, Kevin Hainline, William M. Baker, Andrew J. Bunker, Jakob M. Helton, Jianwei Lyu, Pierluigi Rinaldi, Brant Robertson, Charlotte Simmonds, Sandro Tacchella, Christina C. Williams, Christopher N. A. Willmer, Joris Witstok
Figure caption: Comparison of model Lyα profiles with different NHI values and the observed Lyα profile of Ion1 (black line), extracted from a seeing-limited, R ∼ 600 VIMOS spectrum. Given the limited S/N of the VIMOS spectrum, we do not perform detailed model fitting. Instead, our goal is to qualitatively compare the data with various models to obtain a rough estimate of NHI (Section 5.2). Models with NHI ∈ [1020.5, 1021] cm−2 reproduce the observed profile reasonably well.
Paper: The Importance of Dust Distribution in Ionizing-photon Escape: NIRCam and MIRI Imaging of a Lyman Continuum-emitting Galaxy at z ∼ 3.8
Authors: Zhiyuan Ji, Stacey Alberts, Yongda Zhu, Eros Vanzella, Mauro Giavalisco, Kevin Hainline, William M. Baker, Andrew J. Bunker, Jakob M. Helton, Jianwei Lyu, Pierluigi Rinaldi, Brant Robertson, Charlotte Simmonds, Sandro Tacchella, Christina C. Williams, Christopher N. A. Willmer, Joris Witstok
Figure caption: Comparison between the NIRCam/F070W isophotes (λrest ∼  1500 Å, cyan contours) and the NIRCam/F444W (λrest ∼  9000 Å) image of Ion1. The contours correspond to 3, 9, 27, and 81σ levels. The rest-frame UV emission of Ion1 is observed preferentially from the northeast side.
Paper: The Importance of Dust Distribution in Ionizing-photon Escape: NIRCam and MIRI Imaging of a Lyman Continuum-emitting Galaxy at z ∼ 3.8
Authors: Zhiyuan Ji, Stacey Alberts, Yongda Zhu, Eros Vanzella, Mauro Giavalisco, Kevin Hainline, William M. Baker, Andrew J. Bunker, Jakob M. Helton, Jianwei Lyu, Pierluigi Rinaldi, Brant Robertson, Charlotte Simmonds, Sandro Tacchella, Christina C. Williams, Christopher N. A. Willmer, Joris Witstok
Figure caption: Illustration of LyC escape in Ion1. A detailed description is provided in Section 5. This illustration was partially created with the assistance of ChatGPT-4o (OpenAI 2024).
Paper: First Robust Detection of Linear Polarization from Metric Solar Emissions: Challenging Established Paradigms
Authors: Soham Dey, Devojyoti Kansabanik, Divya Oberoi, Surajit Mondal
Figure caption: The left and right panels show the posterior distributions of L and fL, respectively, of the western noise storm source from uGMRT observation at 218 MHz. The red vertical dashed line represents the mean, while the green and blue dashed–dotted lines represent the 16th and 84th percentiles, respectively. The uncertainty estimated throughout the Letter is taken as half the difference between the 84th and 16th percentiles, which is 0.005 for fL for this specific instance.
Paper: Impact of Two-population α-particle Distributions on Plasma Stability
Authors: Mihailo M. Martinović, Kristopher G. Klein, Rossana De Marco, Daniel Verscharen, Roberto Bruno, Raffaella D'Amicis
Figure caption: Direct comparison of the frequency and ∣σ∣ ≥ 0.6 of measured coherent magnetic field fluctuations in the spacecraft frame with the inferred MUM for each interval. LH polarized modes are shown with filled dots and RH with open circle symbols. The color coding of the strongest emitting component for each MUM is the same as in Figure 2. For each emitting component, we show 2 minute median values instead of full cadence for clarity.
Paper: Impact of Two-population α-particle Distributions on Plasma Stability
Authors: Mihailo M. Martinović, Kristopher G. Klein, Rossana De Marco, Daniel Verscharen, Roberto Bruno, Raffaella D'Amicis
Figure caption: Comparison of the power emitted by a single α component (four-component analysis, column 1) and α core and beams (five-component analysis, column 2), depending on (a1, a2) α beam drift, (b1, b2) α beam temperature anisotropy, (c1, c2) MUM propagation angle, (d1, d2) polarization, and (e1, e2) emitting component. Brown lines mark equal emitting powers. For panels (a1, a2) and (b1, b2), we mark the median values for 12 logarithmically spaced bins with black lines and small dots with labels on the right side. Areas marked with roman numerals are discussed in the text.
Paper: Impact of Two-population α-particle Distributions on Plasma Stability
Authors: Mihailo M. Martinović, Kristopher G. Klein, Rossana De Marco, Daniel Verscharen, Roberto Bruno, Raffaella D'Amicis
Figure caption: Same as Figure 3, with magnification on specific intervals with full cadence data where RH (top) and LH (bottom) modes are predicted by both models. The middle panel shows the period where the correctly estimated α core temperature anisotropy is necessary for the more accurate description of the observed waves.
Paper: Impact of Two-population α-particle Distributions on Plasma Stability
Authors: Mihailo M. Martinović, Kristopher G. Klein, Rossana De Marco, Daniel Verscharen, Roberto Bruno, Raffaella D'Amicis
Figure caption: Emitted power over one wave period for each of the VDF components: (a) proton core; (b) proton beam; (c) α-particle core; and (d) α-particle beam. Intervals in which the given component drives the MUM are marked by open circles, while others are shown with filled dots. For easier distinction, all circles are 75% transparent.
Paper: Impact of Two-population α-particle Distributions on Plasma Stability
Authors: Mihailo M. Martinović, Kristopher G. Klein, Rossana De Marco, Daniel Verscharen, Roberto Bruno, Raffaella D'Amicis
Figure caption: The confusion matrix (CM) of inferred MUMs for four- and five-component models for 14,044 intervals found to be unstable by both models. For each cell, the percentages compared to the total data set population are given in parentheses, while square brackets provide fractions of the nondiagonal part of the CM where different emitting populations are inferred.
Paper: Acceleration of Solar Eruptions via Enhanced Torus Instability Driven by Small-scale Flux Emergence
Authors: Satoshi Inoue, Takahiro Miyoshi, Keiji Hayashi, Huu Minh Triet Nguyen, Ju Jing, Wenda Cao, Haimin Wang
Figure caption: (a) Bz distribution of AR 12371 at 16:36 UT on 2015 June 22, 1 hr before the M6.5 flare observed in the eastern sunspots. Red and blue indicate positive and negative polarities, respectively. The simulation domain corresponds to this field of view. The inset shows a zoomed-in Bz map of the eastern sunspots, which is enclosed by a white square, at 17:35 UT on 2015 June 22, observed with the near-infrared imaging spectropolarimeter at BBSO. The yellow line marks the polarity inversion line (PIL), and the green circle highlights the small-scale emerging flux. (b) Bz distribution on the eastern sunspot at 16:36 UT, along with the temporal evolution of the small-scale emerging flux, marked by a white arrow. White and black indicate positive and negative polarities, respectively; the yellow line traces the PIL. (c) Magnetic field lines, which are traced from the small-scale emerging flux. Purple and light-blue lines originate from the positive and negative polarities of the small-scale emerging flux, respectively.
Paper: Acceleration of Solar Eruptions via Enhanced Torus Instability Driven by Small-scale Flux Emergence
Authors: Satoshi Inoue, Takahiro Miyoshi, Keiji Hayashi, Huu Minh Triet Nguyen, Ju Jing, Wenda Cao, Haimin Wang
Figure caption: (a) 3D magnetic field structure at t = 9.37 in the preeruption phase. The MFR is colored by Vz; the orange line indicates a field line just after tether-cutting reconnection. Black lines show surrounding field lines and postflare loops (projected on the x–z plane), while blue lines are magnetic field lines traced from the small-scale emerging flux. An enlarged view is shown in Figure 1. (b) Schematic of reconnection between the small-scale emerging flux and preexisting coronal loops. White/black regions denote positive/negative polarity; red and blue arrows indicate the emerging and coronal fields, respectively. (c) 3D field lines in sky blue for Runs R (t = 11.25) and 1 (t = 9.37), showing MFR formation via tether-cutting reconnection. Vertical cross sections show Vz; the black arrow marks reconnection sites with bidirectional flows for Run 1. (d) ∣J∣/∣B∣ distributions for Run R (t = 27.19) and Run 1 (t = 19.68) on vertical slices through the emerging flux region. The black arrow indicates the enhanced region of magnetic reconnection for Run 1. (e) The temporal evolution of the difference in the magnetic flux of the MFR (ΨM) for each run relative to Run R. The red, sky-blue, and purple lines indicate the differences in ΨM between Run 1 and Run R, Run 2 and Run R, and Run 3 and Run R, respectively. (f) The temporal evolution of the difference in the height of the MFR between Run 1 and Run R in black, and between Run R1 and R in red.
Paper: Acceleration of Solar Eruptions via Enhanced Torus Instability Driven by Small-scale Flux Emergence
Authors: Satoshi Inoue, Takahiro Miyoshi, Keiji Hayashi, Huu Minh Triet Nguyen, Ju Jing, Wenda Cao, Haimin Wang
Figure caption: (a) MFR velocity profile as a function of height for each run, based on Lagrangian tracking of a plasma element initially located at (x, y, z) = (0.36172, 0.49482, 0.054) at t = 0 on the thick black line (see Figure 3(c)). The red, light-blue, purple, and black lines represent Runs 1–3 and R, respectively. (b) Three-dimensional magnetic field structure at t = 11.25, using the same color coding as in Figure 2 (excluding the magnitude of the maximum and minimum values) when the tracking point passes through at h ≈ 1.1. The purple surface represents the isosurface where the decay index equals 1.5. (c) Temporal evolution of magnetic flux (ΨM) of the MFR associated with the highly negative twisted field lines satisfying ﹩| {T{}_{w}}_{n}| \geqslant 1﹩ with color coding identical to panel (a). (d) Toroidal current (IM) perpendicular to the MFR cross section, plotted as a function of height based on the same Lagrangian plasma element. The vertical green line marks the location where the MFR becomes unstable to the torus instability, as discussed in panel (a).
Paper: Acceleration of Solar Eruptions via Enhanced Torus Instability Driven by Small-scale Flux Emergence
Authors: Satoshi Inoue, Takahiro Miyoshi, Keiji Hayashi, Huu Minh Triet Nguyen, Ju Jing, Wenda Cao, Haimin Wang
Figure caption: (a)–(b) 3D magnetic field structures of the NLFFF and the updated magnetic field from the data-driven MHD simulation. Yellow lines show sheared field lines, and black lines represent overlying field lines. (c) Histograms of magnetic flux Φ as a function of negative twist magnitude Twn for the NLFFF and the updated field. (d) Temporal evolution of the 3D magnetic field in the preeruption phase for the case without small-scale emerging flux (Run R). Field line colors indicate vertical velocity Vz. The inset shows a green isosurface of strong current density (∣J∣ = 20), concentrated along the polarity inversion line of the eastern sunspots.
Paper: Hundreds of TESS Exoplanets Might Be Larger than We Thought
Authors: Te Han, Paul Robertson, Timothy D. Brandt, Shubham Kanodia, Caleb Cañas, Avi Shporer, George Ricker, Corey Beard
Figure caption: Planet M–R and mass–density distributions of literature and TGLC-fitted values. (a) M–R distribution of small TESS planets. (b) Mass–density distribution of small TESS planets. Both panels include the high-precision planet sample with TESS-free literature values (gray diamond) and TESS-dependent TGLC-fitted values (black empty circle). The error bars represent 1σ Gaussian standard deviations. For each TESS-dependent TGLC-fitted value, a line connects it to the corresponding literature value, where the color of the line shows whether it increased (green) or decreased (orange) from the literature value. We also include theoretical models of planet compositions for the Earth-like (red), water worlds (blue), and rocky planets with atmospheres (brown). The last model accounts for the boil-off initial conditions (solid brown) and a range of agnostic initial conditions (region between dashed brown). Earth and Neptune are included for reference.
Paper: Hundreds of TESS Exoplanets Might Be Larger than We Thought
Authors: Te Han, Paul Robertson, Timothy D. Brandt, Shubham Kanodia, Caleb Cañas, Avi Shporer, George Ricker, Corey Beard
Figure caption: Probabilistic radius–density relations for small TESS planets. (a) Probabilistic radius–density relations fitted to TESS-free and TESS-dependent literature values. (b) Probabilistic radius–density relations fitted to TESS-free and TESS-dependent TGLC-fitted values. The figure includes the high-precision planet sample with TESS-free literature values (gray), TESS-dependent literature values (orange), and TESS-dependent TGLC-fitted values (black). The error bars represent 1σ Gaussian standard deviations. Probability density maps (light gray) are shown together with the most probable models. From small to large radii, the line components correspond to three planet compositions: rocky planets (red), water worlds (blue), and sub-Neptunes (brown). Dashed lines indicate regions where planetary populations overlap in radius space. TGLC-fitted radii for TESS planets yield a broader and more populated water world regime, suggesting a modestly stronger statistical preference for their existence compared to the model using literature values.
Paper: Hundreds of TESS Exoplanets Might Be Larger than We Thought
Authors: Te Han, Paul Robertson, Timothy D. Brandt, Shubham Kanodia, Caleb Cañas, Avi Shporer, George Ricker, Corey Beard
Figure caption: TESS-free, TESS-dependent, and Kepler literature planet-to-star radius ratios compared to fitted TGLC-fitted values. (a) The inverse-variance weighted distribution of the fractional difference in radius ratios (fp) between TGLC and literature values for TESS-free (gray) and TESS-dependent (orange) planets. (b) The same distribution for Kepler planets (blue). The vertical dashed line and shaded region represent the medians of each distribution and the 1σ uncertainties of the medians estimated via bootstrap resampling. The black vertical dotted line is at fp = 0 for reference. The TGLC-fitted radius ratios statistically agree with literature values for the less diluted TESS-free and Kepler planets but disagree for TESS-dependent planets, implying a systematic underestimation of their radii in the literature.
Paper: Microwave Imaging Spectroscopy Diagnosis of the Slow-rise Precursor of a Major Solar Eruption
Authors: Yuankun Kou, Xin Cheng, Sijie Yu, Yingjie Luo, Bin Chen, Mingde Ding
Figure caption: Microwave sources covering AIA 131 Å images. The contours of the microwave emissions are at the levels of 50% of the maximum brightness temperature at each SPW and at each time. The restoring beam sizes are labeled in the lower left corner of each panel. White boxes represent precursor loops (A-1), hot channel leg (B-1), and flare loops (A-2 and A-3), respectively. The footpoints of the hot channel and precursor loops are annotated with the same symbols as in Figure 2(b-2). For better presenting microwave emissions from the precursor and flare structures, the contribution from the background active region, taken between 17:22 and 17:23 UT, is subtracted when reconstructing images. The average time for obtaining all microwave images is taken as 4 s.
Paper: Microwave Imaging Spectroscopy Diagnosis of the Slow-rise Precursor of a Major Solar Eruption
Authors: Yuankun Kou, Xin Cheng, Sijie Yu, Yingjie Luo, Bin Chen, Mingde Ding
Figure caption: Spatially resolved Tb spectra with the least-squares fitting results. The black data points and errors are from the observations, and the red lines are the best fittings with the least chi-square residuals. The main fitting parameters are indicated at each panel. (a) Results for the precursor loops (Box A-1). (b) Results for the hot channel leg (Box B-1). (c) and (d) For the post-flare loops at the beginning (Box A-2) and peak time (Box A-3) of the main phase. The brightness temperature of each spectrum is obtained by averaging the nine brightest pixels in each box to increase the signal-to-noise ratio. The errors are defined as the rms brightness temperature of a quiet region far from the flare region, multiplied with manually set frequency-dependent factors. The factors are set for reducing the effect from the different beam sizes at different frequencies.
Paper: Microwave Imaging Spectroscopy Diagnosis of the Slow-rise Precursor of a Major Solar Eruption
Authors: Yuankun Kou, Xin Cheng, Sijie Yu, Yingjie Luo, Bin Chen, Mingde Ding
Figure caption: Posterior probability distributions (PPDs) of the MCMC analysis for the microwave spectrum of the background active region that is derived through averaging the data between 17:22 and 17:23 UT. The red lines represent the fitting results by the nonlinear least chi-square method, while the blue lines are results from the MCMC simulation. The errors are the 1σ confidence intervals of the PPDs. The gray curves in the upper right panels are spectra and residuals associated with results from MCMC samplings shown in the corner plot.