adsabs/AstroCLIMB huggingface dataset:
Paper: Atmospheric Characterization of Hot Jupiter CoRoT-1 b Using the Wide Field Camera 3 on the Hubble Space Telescope
Authors: Kayli Glidic, Everett Schlawin, Lindsey Wiser, Yifan Zhou, Drake Deming, Michael Line
Figure caption: Secondary eclipse light curves of CoRoT-1 b, Visit 4. The residuals in any wavelength channel maximally varied by ∼989 ppm from the median model. Inspecting the residuals for Visit 4, the light curves appear to contain some correlated noise, particularly at the beginning of the first orbit. Referencing our Lomb–Scargle periodograms in Figure B1 of Appendix B, we conclude that the time correlation in the residuals is minor. Additionally, Table 4 notes the correlation coefficients between wavelengths. Other comments are the same as for Figure 2.
Paper: Atmospheric Characterization of Hot Jupiter CoRoT-1 b Using the Wide Field Camera 3 on the Hubble Space Telescope
Authors: Kayli Glidic, Everett Schlawin, Lindsey Wiser, Yifan Zhou, Drake Deming, Michael Line
Figure caption: Representative secondary eclipse model corner plot of the posterior distributions pulled from Visit 4, wavelength channel 2 (1.164–1.215 μm). The parameter names are defined as used in the Python script. Parameter fp is the planet-to-star flux ratio. Parameters a and b are the y-intercept and the slope of the linear regression we applied to the models respectively. The four RECTE charge trap parameters are: the initial number of occupied charge carrier traps for the fast and slow populations (trap_pop_s, trap_pop_f) and the number of extra trapped charge carriers added in the middle of two orbits (dtrap_s, dtrap_f) for each population respectively. In the 1D histograms, the middle dashed line represents the mean result while the two adjacent lines represent 1σ from the mean.
Paper: Atmospheric Characterization of Hot Jupiter CoRoT-1 b Using the Wide Field Camera 3 on the Hubble Space Telescope
Authors: Kayli Glidic, Everett Schlawin, Lindsey Wiser, Yifan Zhou, Drake Deming, Michael Line
Figure caption: Primary transit light curves of CoRoT-1 b, Visit 1. The residuals in any wavelength channel maximally varied by ∼1247 ppm from the median model. Additionally, Table 5 notes the correlation coefficients between wavelengths. Other comments are the same as for Figure 2.
Paper: Atmospheric Characterization of Hot Jupiter CoRoT-1 b Using the Wide Field Camera 3 on the Hubble Space Telescope
Authors: Kayli Glidic, Everett Schlawin, Lindsey Wiser, Yifan Zhou, Drake Deming, Michael Line
Figure caption: Comparison of CoRoT-1 b transmission spectrum with results from Ranjan et al. (2014).
Paper: Atmospheric Characterization of Hot Jupiter CoRoT-1 b Using the Wide Field Camera 3 on the Hubble Space Telescope
Authors: Kayli Glidic, Everett Schlawin, Lindsey Wiser, Yifan Zhou, Drake Deming, Michael Line
Figure caption: Lomb–Scargle residual periodograms for each wavelength channel in Visit 4. Additionally overlaid are the smoothed residual and independently and identically distributed (IID) white noise periodograms, done with the astropy 1D Gaussian filter kernel with a standard deviation of 50. The smoothed residual and IID white noise periodograms show a slight statistical deviation that, overall, supports very minor residual time-correlated noise in the light curves of Figure 4.
Paper: Atmospheric Characterization of Hot Jupiter CoRoT-1 b Using the Wide Field Camera 3 on the Hubble Space Telescope
Authors: Kayli Glidic, Everett Schlawin, Lindsey Wiser, Yifan Zhou, Drake Deming, Michael Line
Figure caption: Top: individual emission spectra for each visit. Each emission spectrum is consistent with each other to within 1.4σ. Bottom: the averaged emission spectrum for CoRoT-1 b.
Paper: Atmospheric Characterization of Hot Jupiter CoRoT-1 b Using the Wide Field Camera 3 on the Hubble Space Telescope
Authors: Kayli Glidic, Everett Schlawin, Lindsey Wiser, Yifan Zhou, Drake Deming, Michael Line
Figure caption: Posterior distributions from the grid retrieval. Models calculate log(C/O), [M/H], the heat redistribution parameter (f ), and the scaling factor (a), which scales the resulting emission spectrum to account for a hot spot dominating the spectrum (Taylor et al. 2020). Here, f is consistent with no heat redistribution.
Paper: Atmospheric Characterization of Hot Jupiter CoRoT-1 b Using the Wide Field Camera 3 on the Hubble Space Telescope
Authors: Kayli Glidic, Everett Schlawin, Lindsey Wiser, Yifan Zhou, Drake Deming, Michael Line
Figure caption: Sc-CHIMERA modeled pressure–temperature profiles covering the 1σ confidence range (Figure 8). Also plotted are contribution functions for the WFC3 wavelength range and each Spitzer point.
Paper: The Hubble PanCET Program: A Featureless Transmission Spectrum for WASP-29b and Evidence of Enhanced Atmospheric Metallicity on WASP-80b
Authors: Ian Wong, Yayaati Chachan, Heather A. Knutson, Gregory W. Henry, Danica Adams, Tiffany Kataria, Björn Benneke, Peter Gao, Drake Deming, Mercedes López-Morales, David K. Sing, Munazza K. Alam, Gilda E. Ballester, Joanna K. Barstow, Lars A. Buchhave, Leonardo A. dos Santos, Guangwei Fu, Antonio García Muñoz, Ryan J. MacDonald, Thomas Mikal-Evans, Jorge Sanz-Forcada, Hannah R. Wakeford
Figure caption: Same as Figure 4, but for WASP-80b. In the optical portion of the spectrum, there is strong evidence for a hazy atmosphere with a scattering slope consistent with Rayleigh scattering. The prominent absorption feature in the WFC3 bandpass and the relatively high Spitzer 4.5 μm transit depth are indicative of H2O and CO2 in the photosphere, respectively. We find that the atmosphere has a near-solar C/O ratio and a cloud deck extending up to the 1 mbar pressure level. The atmospheric scale height (green) from the best-fit PLATON model is 155 ppm.
Paper: The Hubble PanCET Program: A Featureless Transmission Spectrum for WASP-29b and Evidence of Enhanced Atmospheric Metallicity on WASP-80b
Authors: Ian Wong, Yayaati Chachan, Heather A. Knutson, Gregory W. Henry, Danica Adams, Tiffany Kataria, Björn Benneke, Peter Gao, Drake Deming, Mercedes López-Morales, David K. Sing, Munazza K. Alam, Gilda E. Ballester, Joanna K. Barstow, Lars A. Buchhave, Leonardo A. dos Santos, Guangwei Fu, Antonio García Muñoz, Ryan J. MacDonald, Thomas Mikal-Evans, Jorge Sanz-Forcada, Hannah R. Wakeford
Figure caption: Measured transmission spectrum of WASP-29b (black data points) alongside the result of our PLATON atmospheric retrieval. The red curve shows the best-fit atmospheric model, while the medium and light blue shaded regions indicate the 1σ and 2σ bounds for the atmospheric models, respectively. The mostly flat transmission spectrum is consistent with a cloudy atmosphere without fine-particle aerosols and a wide range of atmospheric metallicities. Our preferred model includes an additive offset for the STIS points relative to the WFC3 points, which has been included in the plotted visible-wavelength points. The low Spitzer 4.5 μm transit depth is inconsistent with physically reasonable atmospheric models, and both Spitzer points (gray points) were excluded from the retrieval analysis, along with the outlier point at ∼1.5 μm. The green bar denotes the atmospheric scale height corresponding to the best-fit model from our PLATON retrieval (52 ppm).
Paper: The Hubble PanCET Program: A Featureless Transmission Spectrum for WASP-29b and Evidence of Enhanced Atmospheric Metallicity on WASP-80b
Authors: Ian Wong, Yayaati Chachan, Heather A. Knutson, Gregory W. Henry, Danica Adams, Tiffany Kataria, Björn Benneke, Peter Gao, Drake Deming, Mercedes López-Morales, David K. Sing, Munazza K. Alam, Gilda E. Ballester, Joanna K. Barstow, Lars A. Buchhave, Leonardo A. dos Santos, Guangwei Fu, Antonio García Muñoz, Ryan J. MacDonald, Thomas Mikal-Evans, Jorge Sanz-Forcada, Hannah R. Wakeford
Figure caption: Top panel: raw broadband light curves of all six WASP-29b transits considered in this work. The Spitzer light curves are binned by the optimized time intervals utilized in our fitting analysis. Middle panel: the corresponding systematics-corrected light curves, with the best-fit transit light curves shown in blue. Bottom panel: residuals from the best-fit instrumental and transit models. The error bars in each light curve are set to the corresponding best-fit photometric noise parameter. The WFC3 G141 residuals are amplified by five times for clarity.
Paper: The Hubble PanCET Program: A Featureless Transmission Spectrum for WASP-29b and Evidence of Enhanced Atmospheric Metallicity on WASP-80b
Authors: Ian Wong, Yayaati Chachan, Heather A. Knutson, Gregory W. Henry, Danica Adams, Tiffany Kataria, Björn Benneke, Peter Gao, Drake Deming, Mercedes López-Morales, David K. Sing, Munazza K. Alam, Gilda E. Ballester, Joanna K. Barstow, Lars A. Buchhave, Leonardo A. dos Santos, Guangwei Fu, Antonio García Muñoz, Ryan J. MacDonald, Thomas Mikal-Evans, Jorge Sanz-Forcada, Hannah R. Wakeford
Figure caption: Same as Figure 2, but for WASP-80. The offsets in the WFC3 G141 raw light curve are due to the systematic flux differences between the forward and backward scans.
Paper: The Hubble PanCET Program: A Featureless Transmission Spectrum for WASP-29b and Evidence of Enhanced Atmospheric Metallicity on WASP-80b
Authors: Ian Wong, Yayaati Chachan, Heather A. Knutson, Gregory W. Henry, Danica Adams, Tiffany Kataria, Björn Benneke, Peter Gao, Drake Deming, Mercedes López-Morales, David K. Sing, Munazza K. Alam, Gilda E. Ballester, Joanna K. Barstow, Lars A. Buchhave, Leonardo A. dos Santos, Guangwei Fu, Antonio García Muñoz, Ryan J. MacDonald, Thomas Mikal-Evans, Jorge Sanz-Forcada, Hannah R. Wakeford
Figure caption: Differential photometry of WASP-80 from our long-term photometric monitoring campaign at the AIT. Data are shown for the six semesters during which significant periodicity was detected. Each panel displays the relative R-band magnitude, phase-folded on the best-fit variability period. The period and peak-to-peak amplitude are listed for each semester.
Paper: Dependence of Molecular Cloud Samples on Angular Resolution, Sensitivity, and Algorithms
Authors: Qing-Zeng Yan, Ji Yang, Yang Su, Yan Sun, Xin Zhou, Ye Xu, Hongchi Wang, Shaobo Zhang, Zhiwei Chen
Figure caption: Scaling relations of σ  v –R (left) and L CO–R (right). Results of the three CO surveys, MWISP (blue), OGS (green), and CfA-Chile (red), are color coded. For the convenience of comparison, the same axis ranges are used with Figure 20. The cutoff of data cubes is 2σ, and only distance errors are considered, including the 5% systematic error (Yan et al. 2021a).
Paper: Dependence of Molecular Cloud Samples on Angular Resolution, Sensitivity, and Algorithms
Authors: Qing-Zeng Yan, Ji Yang, Yang Su, Yan Sun, Xin Zhou, Ye Xu, Hongchi Wang, Shaobo Zhang, Zhiwei Chen
Figure caption: Scaling relations between the equivalent line width (σ  v ) and radius (R, left) and between the CO luminosity (L CO) and radius (right). Results of different algorithms, DBSCAN (blue), HDBSCAN (green), and SCIMES (red), are color coded. The cutoff of data cubes is 3σ, and only distance errors are considered, including the 5% systematic error (Yan et al. 2021a).
Paper: Dependence of Molecular Cloud Samples on Angular Resolution, Sensitivity, and Algorithms
Authors: Qing-Zeng Yan, Ji Yang, Yang Su, Yan Sun, Xin Zhou, Ye Xu, Hongchi Wang, Shaobo Zhang, Zhiwei Chen
Figure caption: Variation of molecular cloud properties with respect to algorithms and velocity resolution. From left to right, this demonstration shows the number, the total angular area, and the total flux of molecular clouds identified with three algorithms, DBSCAN (blue), HDBSCAN (green), and SCIMES (red).
Paper: Dependence of Molecular Cloud Samples on Angular Resolution, Sensitivity, and Algorithms
Authors: Qing-Zeng Yan, Ji Yang, Yang Su, Yan Sun, Xin Zhou, Ye Xu, Hongchi Wang, Shaobo Zhang, Zhiwei Chen
Figure caption: Distribution of molecular clouds along the Galactic longitude and the portion of clouds that are single along lines of sight. Overall, the portion is 8.8%, 34.7%, and 2.9% for the MWISP survey, OGS, and CfA-Chile survey, respectively.
Paper: Dependence of Molecular Cloud Samples on Angular Resolution, Sensitivity, and Algorithms
Authors: Qing-Zeng Yan, Ji Yang, Yang Su, Yan Sun, Xin Zhou, Ye Xu, Hongchi Wang, Shaobo Zhang, Zhiwei Chen
Figure caption: Variation of angular areas with respect to cutoffs. These three molecular clouds are unique along their lines of sight. The cutoff is used as a proxy for sensitivity, and high cutoffs mean low sensitivity.
Paper: Dependence of Molecular Cloud Samples on Angular Resolution, Sensitivity, and Algorithms
Authors: Qing-Zeng Yan, Ji Yang, Yang Su, Yan Sun, Xin Zhou, Ye Xu, Hongchi Wang, Shaobo Zhang, Zhiwei Chen
Figure caption: Variation of molecular cloud properties with respect to algorithms and beam sizes (angular resolution). From left to right, this demonstration shows the number, the total angular area, and the total flux of molecular clouds identified with three algorithms, DBSCAN (blue), HDBSCAN (green), and SCIMES (red).
Paper: Rotation of Low-mass Stars in Upper Centaurus–Lupus and Lower Centaurus–Crux with TESS
Authors: L. M. Rebull, J. R. Stauffer, L. A. Hillenbrand, A. M. Cody, Ethan Kruse, Brian P. Powell
Figure caption: Histograms of the brightness (in K s) of the targets in the various subsets of data. (Note that the y-axis range is the same in all panels.) Top panel: the sources analyzed here (solid line) in comparison to all the literature sources identified as likely members of UCL/LCC (dotted line) and the sources identified here as periodic (dashed line). The sources that are missing LCs are biased toward fainter sources. Second panel: the sources with eleanor LCs (solid line), CDIPS LCs (dotted line), and QLP LCs (dashed line). The QLP LCs are biased toward brighter sources, as expected; the CDIPS LCs can reach fainter magnitudes than the eleanor LCs. Third panel: the sources without LCs (solid line) and the sources without LCs that could theoretically exist, as the target was on silicon (“on Si”) during TESS’s first year of operations (dotted line). The targets that are missing LCs are strongly biased toward fainter stars. Fourth panel: the sources with LCs that have unambiguous periods (solid line) and the LCs where the periods are less confident (dotted line). The targets with less confident periods are on average fainter. Based on these histograms, we conclude most importantly that the selection effect imposed by our requirement that there be an LC does not unduly bias our results; we are missing some of the fainter targets, which is unsurprising.
Paper: Rotation of Low-mass Stars in Upper Centaurus–Lupus and Lower Centaurus–Crux with TESS
Authors: L. M. Rebull, J. R. Stauffer, L. A. Hillenbrand, A. M. Cody, Ethan Kruse, Brian P. Powell
Figure caption: The locations of the targets in Galactic coordinates. The black lines denote the classical boundaries between USco, UCL, and LCC according to de Zeeuw et al. (1999); see the text. Note that no points belonging to UCL are “hidden” under the USco box. The gold, silver, and bronze members (see Section 2.3) are indicated, along with the rejected (discarded) sources (red). The gaps in the spatial distribution are an artifact of the TESS observation strategy. The targets from USco with rotation periods (Paper V) are shown in light gray, in the upper left; gaps between the K2 chips are readily apparent. Note that these regions are in the Galactic plane and near the Galactic center, and, as a result, given the large pixel size in TESS, source confusion is a concern. Note also that the UCL/LCC member sample is overwhelmingly gold (∼80%).
Paper: Rotation of Low-mass Stars in Upper Centaurus–Lupus and Lower Centaurus–Crux with TESS
Authors: L. M. Rebull, J. R. Stauffer, L. A. Hillenbrand, A. M. Cody, Ethan Kruse, Brian P. Powell
Figure caption:  J − H vs. H − K  s  (observed) for upper left: gold members (see Section 2.3 for membership); upper right: silver members; lower left: bronze members; and lower right: rejected targets. These plots show that there is not much reddening on average toward these targets (Section 3.3), and, moreover, that the stars that are being dropped are not particularly or obviously different than the ones that are retained.
Paper: Line-by-line Velocity Measurements: an Outlier-resistant Method for Precision Velocimetry
Authors: Étienne Artigau, Charles Cadieux, Neil J. Cook, René Doyon, Thomas Vandal, Jean-François Donati, Claire Moutou, Xavier Delfosse, Pascal Fouqué, Eder Martioli, François Bouchy, Jasmine Parsons, Andres Carmona, Xavier Dumusque, Nicola Astudillo-Defru, Xavier Bonfils, Lucille Mignon
Figure caption: Sample line-by-line velocity spectrum for Barnard’s star showing the scatter of velocity measurements over a wide velocity range (±10 km s−1 of mean velocity; upper panel); lines with uncertainties smaller than 300 m s−1 are shown in dark blue to improve readability. Lines with uncertainties <300 m s−1 are mostly concentrated within the H band and a large part of the Y and J bands are dominated by lines with kilometers-per-second-level radial velocity (RV) uncertainties. Lower panels show the same plot zoomed-in on one of the domains with the highest density of high-accuracy lines (1500–1550 nm; compare with RV accuracy in Figure 4), a domain strongly affected by telluric absorption but with significant RV content (1800–1850 nm), and the CO band head (past 2290 nm). Parts of the domain, such as the redder half of the K band and most of the J band, have very few, if any, high-quality lines. These regions correspond to domains where lines are either shallow (K) or broader (e.g., J; see Artigau et al. 2018b) than they are in the H band. This is also seen in Figure 4. These domains contribute very little to the overall RV budget. The large number of high-quality lines past 2290 nm (lower-left inset) correspond to the CO band heads.
Paper: Line-by-line Velocity Measurements: an Outlier-resistant Method for Precision Velocimetry
Authors: Étienne Artigau, Charles Cadieux, Neil J. Cook, René Doyon, Thomas Vandal, Jean-François Donati, Claire Moutou, Xavier Delfosse, Pascal Fouqué, Eder Martioli, François Bouchy, Jasmine Parsons, Andres Carmona, Xavier Dumusque, Nicola Astudillo-Defru, Xavier Bonfils, Lucille Mignon
Figure caption: Sample region of the Barnard’s star template spectrum with the limits of line domains shown as dashed gray lines. Color-coding is arbitrary and highlights individual lines.
Paper: Line-by-line Velocity Measurements: an Outlier-resistant Method for Precision Velocimetry
Authors: Étienne Artigau, Charles Cadieux, Neil J. Cook, René Doyon, Thomas Vandal, Jean-François Donati, Claire Moutou, Xavier Delfosse, Pascal Fouqué, Eder Martioli, François Bouchy, Jasmine Parsons, Andres Carmona, Xavier Dumusque, Nicola Astudillo-Defru, Xavier Bonfils, Lucille Mignon
Figure caption: Radial velocity (RV) accuracy achieved for a Δλ/λ = 5% running window (blue line). As demonstrated in Artigau et al. (2018b), the H band contains the domain with the highest RV content for the near-infrared domain. Remarkably, a single bin centered at 1.75 μm would allow a 5 m s−1 RV accuracy, only a factor of ∼2 worse than the full domain of SPIRou (2.53 m s−1) for the observation considered. The full spectrum of Barnard’s star is shown as an orange overplot.
Paper: Line-by-line Velocity Measurements: an Outlier-resistant Method for Precision Velocimetry
Authors: Étienne Artigau, Charles Cadieux, Neil J. Cook, René Doyon, Thomas Vandal, Jean-François Donati, Claire Moutou, Xavier Delfosse, Pascal Fouqué, Eder Martioli, François Bouchy, Jasmine Parsons, Andres Carmona, Xavier Dumusque, Nicola Astudillo-Defru, Xavier Bonfils, Lucille Mignon
Figure caption: Radial velocity measurements of the HARPS post-fiber change on Proxima Centauri with the line-by-line (LBL) and HARPS-TERRA algorithms. The top panel shows both data sets with Proxima b’s and d’s Keplerian contribution (solution from Faria et al. 2022). The bottom panel shows the difference between LBL and HARPS-TERRA; within each sequence the agreement is excellent (rms difference of 0.7 and 1.2 m s−1 in 2016 and 2017, respectively), but a systematic difference between sequences at the ∼3 m s−1 level is seen. Uncertainties in the difference between LBL and HARPS-TERRA are derived from the per-sequence rms. One cannot simply add the errors from each method in quadrature as the noise sources in the two are highly correlated; the two used the same input data sets with the same noise, albeit with different weighting schemes.
Paper: Line-by-line Velocity Measurements: an Outlier-resistant Method for Precision Velocimetry
Authors: Étienne Artigau, Charles Cadieux, Neil J. Cook, René Doyon, Thomas Vandal, Jean-François Donati, Claire Moutou, Xavier Delfosse, Pascal Fouqué, Eder Martioli, François Bouchy, Jasmine Parsons, Andres Carmona, Xavier Dumusque, Nicola Astudillo-Defru, Xavier Bonfils, Lucille Mignon
Figure caption: Radial velocity residuals as a function of barycentric radial velocity after subtracting Proxima b and d signals using the Faria et al. (2022) orbital fit. The HARPS-TERRA values display a K BERV signal at the 1.8 m s−1 level while it is consistent with zero for the line-by-line and NAIRA analysis. The cross-correlation data show an intermediate K BERV.
Paper: Line-by-line Velocity Measurements: an Outlier-resistant Method for Precision Velocimetry
Authors: Étienne Artigau, Charles Cadieux, Neil J. Cook, René Doyon, Thomas Vandal, Jean-François Donati, Claire Moutou, Xavier Delfosse, Pascal Fouqué, Eder Martioli, François Bouchy, Jasmine Parsons, Andres Carmona, Xavier Dumusque, Nicola Astudillo-Defru, Xavier Bonfils, Lucille Mignon
Figure caption: Radial velocity (RV) time series of Barnard’s star with the line-by-line (LBL) method and the standard SPIRou cross-correlation function. No activity correction has been performed. The median LBL RV uncertainty is 2.57 m s−1, only slightly smaller than the point-to-point dispersion of 2.59 m s−1. The Ribas et al. (2018) circular orbital solution is shown. The data strongly favors the scenario in which the RV is constant compared to that with the candidate planet with the reported solution (see Section 5.1).
Paper: Line-by-line Velocity Measurements: an Outlier-resistant Method for Precision Velocimetry
Authors: Étienne Artigau, Charles Cadieux, Neil J. Cook, René Doyon, Thomas Vandal, Jean-François Donati, Claire Moutou, Xavier Delfosse, Pascal Fouqué, Eder Martioli, François Bouchy, Jasmine Parsons, Andres Carmona, Xavier Dumusque, Nicola Astudillo-Defru, Xavier Bonfils, Lucille Mignon
Figure caption: Same as Figure 7, but for the NAIRA time series. The measurements are in remarkable agreement, with a 0.7 m s−1 rms difference between values. The ∼3 m s−1 bulk offset between the 2016 and 2017 data sets, as seen in the line-by-line to HARPS-TERRA comparison, is not present. Overall, the scatter after subtraction of the Proxima b and d ephemerides is the same at the 1.9 m s−1 level for both time series.
Paper: Line-by-line Velocity Measurements: an Outlier-resistant Method for Precision Velocimetry
Authors: Étienne Artigau, Charles Cadieux, Neil J. Cook, René Doyon, Thomas Vandal, Jean-François Donati, Claire Moutou, Xavier Delfosse, Pascal Fouqué, Eder Martioli, François Bouchy, Jasmine Parsons, Andres Carmona, Xavier Dumusque, Nicola Astudillo-Defru, Xavier Bonfils, Lucille Mignon
Figure caption: Residual time series for Proxima Centauri with the line-by-line (LBL) and HARPS-TERRA data sets after subtracting the Proxima b and d Keplerian solutions of Faria et al. (2022). The HARPS-TERRA time series shows a decrease of 3.2 m s−1 between the two runs, consistent with the reflex motion due to Proxima c. The LBL time series, extending over larger set of observations in mid-2019, shows no such trend and is inconsistent with the Damasso et al. (2020) orbital solution for Proxima c.