adsabs/AstroCLIMB huggingface dataset:
Paper: Metallicities and Refined Stellar Parameters for 52 Cool Dwarfs with Transiting Planets and Planet Candidates
Authors: Rebecca Gore, Steven Giacalone, Courtney D. Dressing, Emma V. Turtelboom, Ashley Schroeder, Charles D. Fortenbach, Kevin K. Hardegree-Ullman, Jon K. Zink, Andrew W. Mayo, Joshua E. Schlieder, Jessie L. Christiansen
Figure caption: Comparison of planet radii derived in this paper and those previously reported for the confirmed planets in Table 3 (left) and the planet candidates in Table 4 (right).
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Cutout (﹩2\buildrel{\,\prime}\over{.} 3\times 2\buildrel{\,\prime}\over{.} 3﹩) of a region around an elliptical galaxy in A262 (smoothed ﹩g^{\prime} ﹩-band data) after SExtractor’s background subtraction with a background size of 128 px in the left panel and 45 px (corresponding to the optimal background size for UDG detection in A1656 scaled to the distance of A262) in the right panel.
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Masks 1, 4, 5, 6, and 7 (from left to right and top to bottom) and all masks together (bottom right) applied to a four-by-four binned cutout (﹩4\buildrel{\,\prime}\over{.} 9\times 4\buildrel{\,\prime}\over{.} 9﹩) of the ﹩g^{\prime} ﹩-band data of A262.
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Two-by-two binned cutout (50″ × 50″) around a UDG in A262. The top panel shows those without masks, the bottom-left panel shows those masked with the SExtractor segmentation map and with the central object demasked, and the bottom-right panel shows those using the masks from our masking routine combined with the SExtractor segmentation map. The masks are shown in blue.
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Illustration of the dither pattern. The four CCDs are represented by gray squares. The illustrated pointing corresponds to the first element of the dither pattern. The position of the center on the detectors is indicated by the number i for each dither element i. Figure adapted from Kluge et al. (2020).
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Two by two binned cutout (﹩12\buildrel{\,\prime}\over{.} 8\times 11\buildrel{\,\prime}\over{.} 7﹩) of the central region of the ﹩g^{\prime} ﹩-band A262 object stack both before the star and BCG+ICL subtraction (top) and after the subtraction (bottom).
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: 3σ depth on a 10″ × 10″ scale of our A1656 (left), A262 (middle), and reference field (right) data in the ﹩u^{\prime} ﹩ (top), ﹩g^{\prime} ﹩ (middle), and ﹩r^{\prime} ﹩-band (bottom).
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Number density of our A1656 (top left) and A262 (top right) dwarf cluster member candidates in the M tot−μ  e  parameter space. The middle panel shows the number density of the galaxies found in the reference field when analyzed for the respective cluster and scaled to match the size of the cluster images. The bottom panels show the number density in the M tot−μ  e  parameter space of the dwarf cluster member candidates after subtracting the number density from the reference field. The red line indicates the chosen cutoff in between the two sequences.
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption:                          ﹩g^{\prime} -r^{\prime} ﹩ color–magnitude diagram of A1656 (top-left panel), A262 (top right panel), and the reference field analyzed for the respective cluster (bottom). The best-fit red sequence is depicted as a solid red line, and the upper and lower red sequence selection limits are depicted as dashed red lines. For the reference field, the red sequence for the respective cluster is used. Those objects previously rejected in the bicolor selection are marked in black. Those galaxies classified as quiescent, as well as bright ellipticals and S0 are depicted as red points.
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Comparison between M tot, R  e , and μ  e  of dwarf cluster member candidates (light blue) from our A1656 (right) and A262 (right) sample, as well as galaxies from the reference field analyzed for the respective cluster (brown). The basis for this plot is Figure 37 in Kormendy et al. (2009) with updates in Figure 2 in Kormendy & Bender (2012), Figure 14 in Bender et al. (2015), and Figure 16 in Kluge et al. (2020) including BCGs (orange), ellipticals (green), classical bulges (green), and spheroidals (gray).
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption:                          ﹩u^{\prime} -g^{\prime} ﹩ vs. ﹩g^{\prime} -r^{\prime} ﹩ color–color diagrams for A1656 and A262, as well as for the reference field when alanyzed for the respective cluster. The black line indicates the selection cutoffs. All galaxies in the top-left corner are considered as quiescent.
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Selected outputs of the fitting routine for the galaxy 2MASX J01515160+3615027 in the ﹩g^{\prime} ﹩ band. The ellipticity, position angle, and central coordinates are fixed after the orange marked isophote. The background is determined at the red marked position. In the surface brightness profile plot, the green dots are the data points used for the fit, the green line corresponds to the best-fit double Sérsic profile, and the two gray lines correspond to the two individual Sérsic profiles.
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Comparison between our measured structural parameters and those obtained by van Dokkum et al. (2015; left) and Yagi et al. (2016; right).
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Overview of our A1656 (left) and A262 (right) UDG samples (yellow circles) and DF UDGs (red circles).
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Original cutout image, automatically masked cutout image, best-fit GALFIT model, and residuum for a UDG in A262 from left to right.
Paper: Ultradiffuse Galaxies—A Distinct Population? Dwarf Galaxies in the Coma Cluster and A262 from Deep u′–g′–r′ Wendelstein Imaging Data
Authors: Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender
Figure caption: Original cutout image, manually edited masks applied to the cutout image, best-fit single Sérsic plus PSF GALFIT model, and residuum.
Paper: An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Architecture of the CNN model used for image classification.
Paper: An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: The result of the colocalization map and Otsu's method. Panels (a) and (d) show the original LASCO C2 and C3 coronagraph image. Panels (b) and (e) show the colocalization map overlying the original images of LASCO C2 and LASCO C3. A warmer color in the colocalization map reflects a higher positive correlation and vice versa. Panels (c) and (f) show the binary tagged colocalization map after Otsu’s method of the LASCO C2 and C3 images. The yellow pixels indicate the CME region. The example C2 and C3 images are taken from the observation of the CME event on 2011 March 29.
Paper: An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Overall process of the track-match method. After obtaining the binary-labeled CME region image, we transform the image from Cartesian coordinates to polar coordinates for further tracking. This algorithm scans the frames one by one. Assume that the algorithm is working on frame i, two contours are detected from the frame and compared with all existing tracks. One of the detections is matched with Track-1, and then it is added to Track-1. Meanwhile, another detection is matched to Track-2, and it is added to Track-2 as well.
Paper: An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: An illustration of the parameter determination. The red part is the CME region and the black part toward the bottom of the image is the solar disk after polar transform. The AW is the difference of the start and end PA. The height of the CME is measured from the bottom of the image to the top of the CME region.
Paper: An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Detection results for the CME event on 2012 January 15.
Paper: An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: The CPA variation at different distances from the Sun during the propagation of the CME event on 2010 August 14. The value of the red stars in the figure is 268.°5, which might be the reason why it is denoted as the representative value by the affinity propagation method in Table 4.
Paper: An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Detection results for the CME event on 2012 February 14.
Paper: An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: The variation of the classification accuracy as a function of the number of epochs on the C2 and C3 test data sets, respectively.
Paper: An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Detection results for the CME event on 2011 March 8.
Paper: An Algorithm for the Determination of Coronal Mass Ejection Kinematic Parameters Based on Machine Learning
Authors: Rongpei Lin, 荣沛 林, Yi Yang, 易 杨, Fang Shen, 芳 沈, Gilbert Pi, Yucong Li, 雨淙 李
Figure caption: Detection results for the CME event on 2010 August 14.
Paper: Magnetic Activity of Millions of G-type Stars Based on the LAMOST DR10 Low-resolution Spectral and TESS Light-curve Surveys and the Future CSST Survey
Authors: Tianhao Su, Li-yun Zhang, Liu Long, Prabhakar Misra, Xianming L. Han, Gang Meng, ZiLu Yang, Qingfeng Pi
Figure caption: Left panel: the relationship between ﹩{R}_{{\rm{H}}\alpha }^{{\prime} }﹩ and rotation period. The red point is the median value of each bin. Right panel: the relationship between ﹩{R}_{{\rm{H}}\alpha }^{{\prime} }﹩ and Ro. The black dotted line represents the results of Newton et al. (2017), the blue dotted line represents the results of Douglas et al. (2014), and the red dotted line is the result of this work. The color bars in both panels represent the T eff scale.
Paper: Magnetic Activity of Millions of G-type Stars Based on the LAMOST DR10 Low-resolution Spectral and TESS Light-curve Surveys and the Future CSST Survey
Authors: Tianhao Su, Li-yun Zhang, Liu Long, Prabhakar Misra, Xianming L. Han, Gang Meng, ZiLu Yang, Qingfeng Pi
Figure caption: The left panel displays the relationship between R eff and T eff. The middle panel displays the relationship between ﹩{R}_{{\rm{H}}\alpha }^{{\prime} }﹩ and R eff. The right panel displays the relationship between period and R eff.
Paper: Magnetic Activity of Millions of G-type Stars Based on the LAMOST DR10 Low-resolution Spectral and TESS Light-curve Surveys and the Future CSST Survey
Authors: Tianhao Su, Li-yun Zhang, Liu Long, Prabhakar Misra, Xianming L. Han, Gang Meng, ZiLu Yang, Qingfeng Pi
Figure caption: The ﹩{\mathrm{EW}}_{{\rm{H}}\alpha }^{{\prime} }﹩ relationship between the LAMOST 1800 resolution spectra and the simulated CSST 250 resolution spectra. The color bar represents the number density, where the density increases as the color changes from blue to red.
Paper: Magnetic Activity of Millions of G-type Stars Based on the LAMOST DR10 Low-resolution Spectral and TESS Light-curve Surveys and the Future CSST Survey
Authors: Tianhao Su, Li-yun Zhang, Liu Long, Prabhakar Misra, Xianming L. Han, Gang Meng, ZiLu Yang, Qingfeng Pi
Figure caption: Examples of G-type stars with variability in both ﹩\mathrm{EW}^{\prime} ﹩                      Hα  and RV. The four groups of panels from left to right are normalized spectra, subtracted spectra, and ﹩\mathrm{EW}^{\prime} ﹩                      Hα  and RV curves, respectively. The names of the three corresponding stars from top to bottom are LAMOST J085615.70+165152.6, J061921.71+224432.3, and J085952.64+180053.3, respectively.
Paper: Magnetic Activity of Millions of G-type Stars Based on the LAMOST DR10 Low-resolution Spectral and TESS Light-curve Surveys and the Future CSST Survey
Authors: Tianhao Su, Li-yun Zhang, Liu Long, Prabhakar Misra, Xianming L. Han, Gang Meng, ZiLu Yang, Qingfeng Pi
Figure caption: The two-dimensional distribution of the fraction of active G-type star in the Galaxy. Different panels represent different G subtypes. The color bars in the figures represent the proportion of active stars.
Paper: Magnetic Activity of Millions of G-type Stars Based on the LAMOST DR10 Low-resolution Spectral and TESS Light-curve Surveys and the Future CSST Survey
Authors: Tianhao Su, Li-yun Zhang, Liu Long, Prabhakar Misra, Xianming L. Han, Gang Meng, ZiLu Yang, Qingfeng Pi
Figure caption: The left panel displays statistical plots of data with repeated exposure times, with the inset showing cumulative histograms. The middle panel displays the calculation of the ﹩{\mathrm{EW}}_{{\rm{H}}\alpha }^{{\prime} }﹩ of the sample. The right panel displays the distribution of δ                      ﹩\mathrm{EW}^{\prime} ﹩, and the inset shows the details in the larger ﹩\mathrm{EW}^{\prime} ﹩.
Paper: Magnetic Activity of Millions of G-type Stars Based on the LAMOST DR10 Low-resolution Spectral and TESS Light-curve Surveys and the Future CSST Survey
Authors: Tianhao Su, Li-yun Zhang, Liu Long, Prabhakar Misra, Xianming L. Han, Gang Meng, ZiLu Yang, Qingfeng Pi
Figure caption: The relationship between the ratio of active G-type stars and the distance above the Galactic disk. The error bars in these figures are 95% confidence intervals.
Paper: Magnetic Activity of Millions of G-type Stars Based on the LAMOST DR10 Low-resolution Spectral and TESS Light-curve Surveys and the Future CSST Survey
Authors: Tianhao Su, Li-yun Zhang, Liu Long, Prabhakar Misra, Xianming L. Han, Gang Meng, ZiLu Yang, Qingfeng Pi
Figure caption: The left panel shows the RV distribution for the entire LAMOST DR10 G-type star sample. The right panel shows the distribution of RV for the sample with multiple observations. The inset shows details of the data where RV is greater than 40.
Paper: Magnetic Activity of Millions of G-type Stars Based on the LAMOST DR10 Low-resolution Spectral and TESS Light-curve Surveys and the Future CSST Survey
Authors: Tianhao Su, Li-yun Zhang, Liu Long, Prabhakar Misra, Xianming L. Han, Gang Meng, ZiLu Yang, Qingfeng Pi
Figure caption: CV of RV and EW’Hα .
Paper: A Fast Second-order Solver for Stiff Multifluid Dust and Gas Hydrodynamics
Authors: Leonardo Krapp, Juan Garrido-Deutelmoser, Pablo Benítez-Llambay, Kaitlin M. Kratter
Figure caption: From left to right, we plot the evolution of the velocity for the gas and two dust species. The dashed line corresponds to the analytical solution, given by Equation (39). The circles indicate the numerical solutions obtained with different integrators. Green color shows the first-order method, orange and dark lines the second-order method with ﹩\gamma ={\gamma }^{+}=1+1/\sqrt{2}﹩ and ﹩\gamma ={\gamma }^{-}=1-1/\sqrt{2}﹩, respectively. The upper and lower panels show the results for tests 1 and 2, respectively. In the top and bottom panels, the time step is Δt 1 = 0.005, Δt 2 = 0.05, respectively (see Section 3.1). In the rightmost panel, we plot the error by Equation (40) as a function of the time step Δt, for the first-order method (green color) and the DIRK method with ﹩\gamma =1\pm 1/\sqrt{2}﹩. The vertical solid line corresponds to Δt = t s,max, where condition (18) is applied for the DIRK method.
Paper: A Fast Second-order Solver for Stiff Multifluid Dust and Gas Hydrodynamics
Authors: Leonardo Krapp, Juan Garrido-Deutelmoser, Pablo Benítez-Llambay, Kaitlin M. Kratter
Figure caption: Comparison of the (local) truncation error for different methods described in Section 2.1. The blue solid line corresponds to the first-order implicit method of Equation (12), whereas the red solid line shows the error for the second-order implicit method of Equation (13). The solutions obtained with the DIRK method are shown in blue and red dashed lines. The black solid line indicates the transition to a stiff regime, where γ is set to γ = 1/2 for the DIRK method. For Δt ≳ 0.002 (vertical dotted line) time-explicit methods will be unstable. The analytical solution, u  k (Δt), is obtained by solving the eigenvalue problem of the linear Equation (11).
Paper: A Fast Second-order Solver for Stiff Multifluid Dust and Gas Hydrodynamics
Authors: Leonardo Krapp, Juan Garrido-Deutelmoser, Pablo Benítez-Llambay, Kaitlin M. Kratter
Figure caption: Numerical (open circles) and analytical (solid lines) solution of the five-fluid test described in Section 3.3 in Benítez-Llambay et al. (2019). We plot the time evolution of the normalized density. The blue circles correspond to the gas, while the other color corresponds to the dust species. All solutions were obtained at x = 0. The normalized density is defined as ﹩\delta \hat{\rho }/(A{\rho }^{0})﹩, with A = 10−4. We include in the plot the L 1 error, composed of the sum of the errors of the density and velocity (not shown) components of the five fluids. Individual errors are calculated over the whole grid after t = 2.0.
Paper: A Fast Second-order Solver for Stiff Multifluid Dust and Gas Hydrodynamics
Authors: Leonardo Krapp, Juan Garrido-Deutelmoser, Pablo Benítez-Llambay, Kaitlin M. Kratter
Figure caption: Relative velocity between the gas and dust species for the damping test with a constant external force (see Section 3.2). The numerical solution is shown with orange and blue circles. The dashed line corresponds to the analytical solution.
Paper: Powerful Radio Sources in the Southern Sky. III. First Results of the Optical Spectroscopic Campaign
Authors: A. García-Pérez, H. A. Peña-Herazo, A. Jimenez-Gallardo, V. Chavushyan, F. Massaro, S. V. White, A. Capetti, B. Balmaverde, W. R. Forman, C. C. Cheung, J. P. Madrid, C. Mazzucchelli, N. P. H. Nesvadba, I. Andruchow, S. Cellone, R. Grossová, A. Paggi, E. Sani, V. Reynaldi, R. P. Kraft, C. Leto
Figure caption: Left panel: relation between 3.4 μm AllWISE magnitudes and the redshifts of 189 sources of the G4Jy-3CRE catalog. Right panel: same as left panel, but using K s magnitudes from 2MASS instead, for 128 sources.
Paper: Powerful Radio Sources in the Southern Sky. III. First Results of the Optical Spectroscopic Campaign
Authors: A. García-Pérez, H. A. Peña-Herazo, A. Jimenez-Gallardo, V. Chavushyan, F. Massaro, S. V. White, A. Capetti, B. Balmaverde, W. R. Forman, C. C. Cheung, J. P. Madrid, C. Mazzucchelli, N. P. H. Nesvadba, I. Andruchow, S. Cellone, R. Grossová, A. Paggi, E. Sani, V. Reynaldi, R. P. Kraft, C. Leto
Figure caption: Upper panel: comparison between redshifts obtained during our literature search from Paper I (gray) and including all the redshifts that we now have thanks to our campaign (red). Lower panel: we show the distribution of redshifts for sources of the G4Jy-3CRE catalog (red) in comparison with that of the 3CR catalog (blue).
Paper: A Comparative Analysis of the Solar Ultraviolet Spectral Irradiance Measured from Earth and Mars: Toward a General Empirical Model for the Study of Planetary Aeronomy
Authors: Zhen Xu, Jianqi Qin
Figure caption: (a) Time series of the integrated solar irradiance between 0 and 45 nm (i.e., Q EUV) observed by TIMED/SEE and MAVEN/EUVM during 2014–2016. Black: the SEE measurements from Earth. Blue: the EUVM measurements from Mars. Magenta: solar irradiance at Mars calculated by geometric extrapolation of the SEE measurements, denoted as SEEM. (b)–(c) Same as (a), but for solar irradiance between 45 and 100 nm and between 121 and 122 nm, respectively. (d) Blue: same as the blue line in (a). Red: linearly scaled SEEM using a single factor of 0.79 to fit the EUVM measurements (i.e., to fit the blue line), denoted as SEEMS. (e)–(f) Same as (d), but for solar irradiance between 45 and 100 nm and between 121 and 122 nm, respectively, and both using a scaling factor of 0.95.
Paper: A Comparative Analysis of the Solar Ultraviolet Spectral Irradiance Measured from Earth and Mars: Toward a General Empirical Model for the Study of Planetary Aeronomy
Authors: Zhen Xu, Jianqi Qin
Figure caption: (a) Fourier transform of the time series of the percentage differences between the modeled irradiance and the SEE measurements during 2002–2016. (b) The uncertainties in the modeled irradiance that are calculated using Equation (2). Model V1: the original version of the empirical model developed based on Equation (1). Model V2: the extended version of the empirical model developed based on Equations (1), (3), and (4).