adsabs/AstroCLIMB huggingface dataset:
Paper: EXPRES. IV. Two Additional Planets Orbiting ρ Coronae Borealis Reveal Uncommon System Architecture
Authors: John M. Brewer, Lily L. Zhao, Debra A. Fischer, Rachael M. Roettenbacher, Gregory W. Henry, Joe Llama, Andrew E. Szymkowiak, Samuel H. C. Cabot, Sam A. Weiss, Chris McCarthy
Figure caption: Systems with four or more planets with measured masses with at least one having an orbital period >100 days around G0-M2 stars, from the NASA Exoplanet archive. The systems are less uniform and more widely spaced than those of Figure 7, although there are still quite a few “peas-in-a-pod” style systems. The topmost system is this one, ρ CrB . It has small planets both interior to and exterior to a warm Jupiter; a rare trait shared only with GJ 876 and 55 Cnc. Like Figure 7, symbol areas are scaled to planet mass, and colors to equilibrium temperatures. Representative masses are shown in the key.
Paper: EXPRES. IV. Two Additional Planets Orbiting ρ Coronae Borealis Reveal Uncommon System Architecture
Authors: John M. Brewer, Lily L. Zhao, Debra A. Fischer, Rachael M. Roettenbacher, Gregory W. Henry, Joe Llama, Andrew E. Szymkowiak, Samuel H. C. Cabot, Sam A. Weiss, Chris McCarthy
Figure caption: Systems with four or more planets with measured masses on orbital periods less than 100 days around G0-M2 stars, from the NASA Exoplanet archive. The planets within these systems all show a striking uniformity in their mass, as has been noted previously (Millholland et al. 2017) for Kepler transiting multiplanet systems. All but three of these systems were initially detected via transits. Symbol areas are scaled to planet mass and representative masses are shown in the legend. Symbol colors are scaled to the equilibrium temperatures of the planets.
Paper: EXPRES. IV. Two Additional Planets Orbiting ρ Coronae Borealis Reveal Uncommon System Architecture
Authors: John M. Brewer, Lily L. Zhao, Debra A. Fischer, Rachael M. Roettenbacher, Gregory W. Henry, Joe Llama, Andrew E. Szymkowiak, Samuel H. C. Cabot, Sam A. Weiss, Chris McCarthy
Figure caption: Stellar flux at the orbit of planet d, ∼281 days, over the host’s main-sequence lifetime (blue line). Also shown are the optimistic (yellow) and conservative (green) habitable zones for a 1 M ⊕ planet over the same time period. The inner edge of the habitable zone, where a runaway greenhouse would begin, is closer to the host for a 5 M ⊕ planet (orange dashed line).
Paper: EXPRES. IV. Two Additional Planets Orbiting ρ Coronae Borealis Reveal Uncommon System Architecture
Authors: John M. Brewer, Lily L. Zhao, Debra A. Fischer, Rachael M. Roettenbacher, Gregory W. Henry, Joe Llama, Andrew E. Szymkowiak, Samuel H. C. Cabot, Sam A. Weiss, Chris McCarthy
Figure caption: Posterior distributions for the model parameters. The parameter distributions for planets b and c are relatively Gaussian in shape and have been excluded from the plot to increase clarity. The vertical dashed lines in the single parameter distributions mark the 16th, 50th, and 84th percentiles of the distribution. The solid red lines are the location of the maximum likelihood values for each parameter in both the 1D and 2D distributions.
Paper: EXPRES. IV. Two Additional Planets Orbiting ρ Coronae Borealis Reveal Uncommon System Architecture
Authors: John M. Brewer, Lily L. Zhao, Debra A. Fischer, Rachael M. Roettenbacher, Gregory W. Henry, Joe Llama, Andrew E. Szymkowiak, Samuel H. C. Cabot, Sam A. Weiss, Chris McCarthy
Figure caption: Differential photometry of ρ CrB from the ground-based APT spanning 21 observing seasons. Top: Δ(b + y)/2 data (dark gray) with the long-term trend overplotted (red). Bottom: The same light curve, with the long-term trend removed.
Paper: EXPRES. IV. Two Additional Planets Orbiting ρ Coronae Borealis Reveal Uncommon System Architecture
Authors: John M. Brewer, Lily L. Zhao, Debra A. Fischer, Rachael M. Roettenbacher, Gregory W. Henry, Joe Llama, Andrew E. Szymkowiak, Samuel H. C. Cabot, Sam A. Weiss, Chris McCarthy
Figure caption: TESS light curves from Sectors 24 (top), 25 (middle), and 51 (bottom). Four CBVs have been removed from each light curve.
Paper: EXPRES. IV. Two Additional Planets Orbiting ρ Coronae Borealis Reveal Uncommon System Architecture
Authors: John M. Brewer, Lily L. Zhao, Debra A. Fischer, Rachael M. Roettenbacher, Gregory W. Henry, Joe Llama, Andrew E. Szymkowiak, Samuel H. C. Cabot, Sam A. Weiss, Chris McCarthy
Figure caption: Posterior distributions for the derived masses and semimajor axes for planets b–e.
Paper: Overfitting Affects the Reliability of Radial Velocity Mass Estimates of the V1298 Tau Planets
Authors: Sarah Blunt, Adolfo Carvalho, Trevor J. David, Charles Beichman, Jon K. Zink, Eric Gaidos, Aida Behmard, Luke G. Bouma, Devin Cody, Fei Dai, Daniel Foreman-Mackey, Sam Grunblatt, Andrew W. Howard, Molly Kosiarek, Heather A. Knutson, Ryan A. Rubenzahl, Corey Beard, Ashley Chontos, Steven Giacalone, Teruyuki Hirano, Marshall C. Johnson, Jack Lubin, Joseph M. Akana Murphy, Erik A Petigura, Judah Van Zandt, Lauren Weiss
Figure caption:                    SM21 preferred model prediction and contemporaneous observed data. The HIRES data have been scaled and offset by linear parameters that minimize the residual spread with respect to the GP model, and the median 4pPQP2 CARMENES data RV zero-point value was been applied in order to compare both data sets more easily with the model expectations. Top: mean model prediction (gray solid line), together with contemporaneous HARPS-N (black), CARMENES (red), and HIRES (purple) RVs overplotted. Bottom: model residuals, together with 1 and 2σ GP uncertainty bands (shaded dark and light gray regions, respectively). Takeaway: the preferred SM21 model is overfitting the HARPS-N data, which can be seen in the increased spread about the residual = 0 line for both HIRES and CARMENES data during epochs with contemporaneous HARPS-N data.
Paper: Accurate and Efficient Photoeccentric Transit Modeling
Authors: Mason G. MacDougall, Gregory J. Gilbert, Erik A. Petigura
Figure caption: Comparison of e values measured from the T 14 + umb and T 14 + dyn modeling methods at the 15th, 50th, and 85th percentiles of their distributions, along with the residuals Δe  k  for each comparison (e.g., Δe 50 = e 50,dyn − e 50,umb ). One outlier residual lies beyond the bounds of our residual plots, as indicated by the arrow pointing toward the outlier at Δe 50 = 0.417. We show the Δe  k ={0.05, 0.1, 0.15} in gray, as well as the ideal 1-to-1 line shown in black. These comparisons generally lie close to the 1-to-1 line, implying that the results of the two models are approximately equivalent. However, we do observe 42 tests where the T 14 + umb and T 14 + dyn model results are discrepant by more than ∣Δe  k ∣ ≲ 0.05. In these instances, we find that the T 14 + dyn model tends to overestimate e relative to the T 14 + umb model, as seen in the residuals and discussed in Section B.1.
Paper: Accurate and Efficient Photoeccentric Transit Modeling
Authors: Mason G. MacDougall, Gregory J. Gilbert, Erik A. Petigura
Figure caption: Ratio of sampling efficiencies ﹩{\eta }_{{T}_{14}+\mathrm{umb}}/{\eta }_{e\omega \rho }﹩ as a function of the duration ratio T 14/T 14,ref and S/N. We bin the data across every 10th percentile of the duration ratio distribution, showing a single point per bin per S/N (bins are separated by vertical gray lines). Each point shows the 15th, 50th, and 85th percentiles of a given bin. The increased efficiency of the T 14 + umb method relative to the e–ω–ρ method depends on the S/N of the modeled light curve. At higher S/N the T 14 + umb method is significantly more efficient, but at moderate-to-low S/N the two methods have more similar efficiencies. At shorter transit durations, the T 14 + umb method is always more efficient, but this behavior changes around T 14/T 14,ref ≈0.8. The large spread in some uncertainties reflects the heterogeneity of our injected light-curve parameters.
Paper: Overfitting Affects the Reliability of Radial Velocity Mass Estimates of the V1298 Tau Planets
Authors: Sarah Blunt, Adolfo Carvalho, Trevor J. David, Charles Beichman, Jon K. Zink, Eric Gaidos, Aida Behmard, Luke G. Bouma, Devin Cody, Fei Dai, Daniel Foreman-Mackey, Sam Grunblatt, Andrew W. Howard, Molly Kosiarek, Heather A. Knutson, Ryan A. Rubenzahl, Corey Beard, Ashley Chontos, Steven Giacalone, Teruyuki Hirano, Marshall C. Johnson, Jack Lubin, Joseph M. Akana Murphy, Erik A Petigura, Judah Van Zandt, Lauren Weiss
Figure caption: Another visualization of Figure 2. Histograms of the RV residuals, given in units of standard deviation from the mean prediction. Takeaway: the broader and more uniform distributions of HIRES and CARMENES residuals relative to the HARPS residuals is another hallmark of overfitting.
Paper: Accurate and Efficient Photoeccentric Transit Modeling
Authors: Mason G. MacDougall, Gregory J. Gilbert, Erik A. Petigura
Figure caption: Qualitative diagram showing the relative accuracy of measuring e and b from transit photometry in four distinct quadrants of the e−b parameter space, at three different ω values. The four scenarios shown are (top left) low e and low b, (bottom left) low e and high b, (top right) high e and low b, and (bottom right) high e and high b. Across all areas of the e−b parameter space, the T 14 + umb (blue) and e–ω–ρ (orange) modeling methods perform equivalently.
Paper: Accurate and Efficient Photoeccentric Transit Modeling
Authors: Mason G. MacDougall, Gregory J. Gilbert, Erik A. Petigura
Figure caption: Ratio of sampling efficiencies ﹩{\eta }_{{T}_{14}+\mathrm{umb}}/{\eta }_{{T}_{14}+\mathrm{dyn}}﹩ as a function of the duration ratio T 14/T 14,ref and S/N. We bin the data across every 10th percentile of the duration ratio distribution, showing a single point per bin per S/N (bins are separated by vertical gray lines). Each point shows the 15th, 50th, and 85th percentiles of a given bin. The efficiency of the T 14 + umb method relative to the T 14 + dyn method depends partially on the S/N of the modeled light curve. At shorter transit durations, the T 14 + umb method is typically more efficient, but the opposite is true at longer transit durations. The large spread in some uncertainties reflects the heterogeneity of our injected light-curve parameters.
Paper: Overfitting Affects the Reliability of Radial Velocity Mass Estimates of the V1298 Tau Planets
Authors: Sarah Blunt, Adolfo Carvalho, Trevor J. David, Charles Beichman, Jon K. Zink, Eric Gaidos, Aida Behmard, Luke G. Bouma, Devin Cody, Fei Dai, Daniel Foreman-Mackey, Sam Grunblatt, Andrew W. Howard, Molly Kosiarek, Heather A. Knutson, Ryan A. Rubenzahl, Corey Beard, Ashley Chontos, Steven Giacalone, Teruyuki Hirano, Marshall C. Johnson, Jack Lubin, Joseph M. Akana Murphy, Erik A Petigura, Judah Van Zandt, Lauren Weiss
Figure caption: Same as Figure 2, except that the model prediction is computed by conditioning on a randomly selected 80% subset of the HARPS-N data, as described in the text; the residuals are computed for the 20% subset that was held out. Takeaway: the effect seen in Figure 2 cannot be explained by instrument- or wavelength-dependent systematics, because the same larger residuals are seen within the data taken by only HARPS-N.
Paper: Overfitting Affects the Reliability of Radial Velocity Mass Estimates of the V1298 Tau Planets
Authors: Sarah Blunt, Adolfo Carvalho, Trevor J. David, Charles Beichman, Jon K. Zink, Eric Gaidos, Aida Behmard, Luke G. Bouma, Devin Cody, Fei Dai, Daniel Foreman-Mackey, Sam Grunblatt, Andrew W. Howard, Molly Kosiarek, Heather A. Knutson, Ryan A. Rubenzahl, Corey Beard, Ashley Chontos, Steven Giacalone, Teruyuki Hirano, Marshall C. Johnson, Jack Lubin, Joseph M. Akana Murphy, Erik A Petigura, Judah Van Zandt, Lauren Weiss
Figure caption: A tour of the RVs scrutinized in this study. The CARMENES and HARPS-N RVs are published in SM21, and the HIRES RVs are new in this study. Takeaway: the RV variability of V1298 Tau is hundreds of meters per second, which is similar across all three instruments. The variability is significantly greater than the instrumental errors (which are included, but too small to see for the majority of points on this plot).
Paper: Performance of the Quasar Spectral Templates for the Dark Energy Spectroscopic Instrument
Authors: Allyson Brodzeller, Kyle Dawson, Stephen Bailey, Jiaxi Yu, A. J. Ross, A. Bault, S. Filbert, J. Aguilar, S. Ahlen, David M. Alexander, E. Armengaud, A. Berti, D. Brooks, E. Chaussidon, A. de la Macorra, P. Doel, K. Fanning, V. A. Fawcett, A. Font-Ribera, S. Gontcho A Gontcho, J. Guy, K. Honscheid, S. Juneau, R. Kehoe, T. Kisner, Anthony Kremin, Ting-Wen Lan, M. Landriau, Michael E. Levi, C. Magneville, Paul Martini, Aaron M. Meisner, R. Miquel, J. Moustakas, N. Palanque-Delabrouille, W. J. Percival, F. Prada, C. Ravoux, Graziano Rossi, C. Saulder, M. Siudek, Gregory Tarlé, B. A. Weaver, S. Youles, Zheng Zheng, Rongpu Zhou, Zhimin Zhou
Figure caption: A subset of spectra from the DESI Truth Table that are classified as QSO by Redrock with the new QSO templates, but not classified as QSO with the previous QSO templates (pre-QSO afterburners). The observed flux is shown in gray, the error on the flux is shown in orange, and the flux after applying a Gaussian smoothing filter is shown in black. The DESI target ID, redshift estimate from the new templates (best z), and basic information on the type of spectrum are annotated at the top of each subplot. Prominent emission lines are indicated in the observer frame with vertical lines and labeled.
Paper: Performance of the Quasar Spectral Templates for the Dark Energy Spectroscopic Instrument
Authors: Allyson Brodzeller, Kyle Dawson, Stephen Bailey, Jiaxi Yu, A. J. Ross, A. Bault, S. Filbert, J. Aguilar, S. Ahlen, David M. Alexander, E. Armengaud, A. Berti, D. Brooks, E. Chaussidon, A. de la Macorra, P. Doel, K. Fanning, V. A. Fawcett, A. Font-Ribera, S. Gontcho A Gontcho, J. Guy, K. Honscheid, S. Juneau, R. Kehoe, T. Kisner, Anthony Kremin, Ting-Wen Lan, M. Landriau, Michael E. Levi, C. Magneville, Paul Martini, Aaron M. Meisner, R. Miquel, J. Moustakas, N. Palanque-Delabrouille, W. J. Percival, F. Prada, C. Ravoux, Graziano Rossi, C. Saulder, M. Siudek, Gregory Tarlé, B. A. Weaver, S. Youles, Zheng Zheng, Rongpu Zhou, Zhimin Zhou
Figure caption: Redshift precision of QSO targets from the SV Repeat Exposures sample estimated by the scaled MAD of the dispersion of velocity offsets between redshift pairs. The error bars indicate the 95% confidence interval, and the shaded regions show the redshift precision measured over all redshifts. f 1000 and f 3000 are the catastrophic failure rate over the failure thresholds of 1000 km s−1 and 3000 km s−1, respectively.
Paper: Performance of the Quasar Spectral Templates for the Dark Energy Spectroscopic Instrument
Authors: Allyson Brodzeller, Kyle Dawson, Stephen Bailey, Jiaxi Yu, A. J. Ross, A. Bault, S. Filbert, J. Aguilar, S. Ahlen, David M. Alexander, E. Armengaud, A. Berti, D. Brooks, E. Chaussidon, A. de la Macorra, P. Doel, K. Fanning, V. A. Fawcett, A. Font-Ribera, S. Gontcho A Gontcho, J. Guy, K. Honscheid, S. Juneau, R. Kehoe, T. Kisner, Anthony Kremin, Ting-Wen Lan, M. Landriau, Michael E. Levi, C. Magneville, Paul Martini, Aaron M. Meisner, R. Miquel, J. Moustakas, N. Palanque-Delabrouille, W. J. Percival, F. Prada, C. Ravoux, Graziano Rossi, C. Saulder, M. Siudek, Gregory Tarlé, B. A. Weaver, S. Youles, Zheng Zheng, Rongpu Zhou, Zhimin Zhou
Figure caption: Top: median composites of spectra in the DESI Truth Table classified as QSO by Redrock (red) and of spectra classified as QSO by the QSO afterburners but missed by Redrock (blue). The spectra are normalized over 3800–3900 Å. Vertical lines indicate prominent QSO emission lines. Bottom: similar to above but with the previous QSO templates and an expanded sample of afterburner-identified QSOs (Figure 12 of Alexander et al. 2023).
Paper: Performance of the Quasar Spectral Templates for the Dark Energy Spectroscopic Instrument
Authors: Allyson Brodzeller, Kyle Dawson, Stephen Bailey, Jiaxi Yu, A. J. Ross, A. Bault, S. Filbert, J. Aguilar, S. Ahlen, David M. Alexander, E. Armengaud, A. Berti, D. Brooks, E. Chaussidon, A. de la Macorra, P. Doel, K. Fanning, V. A. Fawcett, A. Font-Ribera, S. Gontcho A Gontcho, J. Guy, K. Honscheid, S. Juneau, R. Kehoe, T. Kisner, Anthony Kremin, Ting-Wen Lan, M. Landriau, Michael E. Levi, C. Magneville, Paul Martini, Aaron M. Meisner, R. Miquel, J. Moustakas, N. Palanque-Delabrouille, W. J. Percival, F. Prada, C. Ravoux, Graziano Rossi, C. Saulder, M. Siudek, Gregory Tarlé, B. A. Weaver, S. Youles, Zheng Zheng, Rongpu Zhou, Zhimin Zhou
Figure caption: The Lyα–QSO cross-correlation measured with QSOs at 2.0 < z < 2.5 using the new QSO templates (black) and the previous QSO templates (red). The best-fit Δr ∣∣ for each measurement is indicated with a vertical line. z eff is the effective redshift of the correlation function.
Paper: Performance of the Quasar Spectral Templates for the Dark Energy Spectroscopic Instrument
Authors: Allyson Brodzeller, Kyle Dawson, Stephen Bailey, Jiaxi Yu, A. J. Ross, A. Bault, S. Filbert, J. Aguilar, S. Ahlen, David M. Alexander, E. Armengaud, A. Berti, D. Brooks, E. Chaussidon, A. de la Macorra, P. Doel, K. Fanning, V. A. Fawcett, A. Font-Ribera, S. Gontcho A Gontcho, J. Guy, K. Honscheid, S. Juneau, R. Kehoe, T. Kisner, Anthony Kremin, Ting-Wen Lan, M. Landriau, Michael E. Levi, C. Magneville, Paul Martini, Aaron M. Meisner, R. Miquel, J. Moustakas, N. Palanque-Delabrouille, W. J. Percival, F. Prada, C. Ravoux, Graziano Rossi, C. Saulder, M. Siudek, Gregory Tarlé, B. A. Weaver, S. Youles, Zheng Zheng, Rongpu Zhou, Zhimin Zhou
Figure caption: The contamination fraction (dashed) and incompleteness (solid) of the QSO Main sample, and of the QSO and galaxy samples from the DESI Truth Table with redshift from Redrock with the new QSO templates. The same metrics for the previous QSO templates are shown in red.
Paper: Autoencoding Galaxy Spectra. II. Redshift Invariance and Outlier Detection
Authors: Yan Liang, Peter Melchior, Sicong Lu, Andy Goulding, Charlotte Ward
Figure caption: A sample of the outliers identified by the normalizing flow, ranked from top to bottom by the assigned probabilities, includes an interacting galaxy system, a double-peaked emission galaxy, a star misclassified as a galaxy, a galaxy with extreme dust attenuation, and a chance alignment of a WD-MS binary and background galaxy. The first column shows the entire normalized spectrum (black) with uncertainties (gray shading) and its reconstruction (red). The second, third, and fourth columns zoom in to important emission/absorption lines. The corresponding images are shown in the last column. The legend on the top left corner includes the SDSS ID, redshift, reduced chi-square, and the negative log probability of each spectrum.
Paper: Autoencoding Galaxy Spectra. II. Redshift Invariance and Outlier Detection
Authors: Yan Liang, Peter Melchior, Sicong Lu, Andy Goulding, Charlotte Ward
Figure caption: Visual classification of 100 SDSS objects that are deemed most unlikely given their position in the SPENDER latent space.
Paper: Autoencoding Galaxy Spectra. II. Redshift Invariance and Outlier Detection
Authors: Yan Liang, Peter Melchior, Sicong Lu, Andy Goulding, Charlotte Ward
Figure caption: The latent space distribution of the validation data (black) and the distribution of the mock samples generated by the normalizing flow (blue) for each of the six latent variables.
Paper: The Great Dimming of the Hypergiant Star RW Cephei: CHARA Array Images and Spectral Analysis
Authors: Narsireddy Anugu, Fabien Baron, Douglas R. Gies, Cyprien Lanthermann, Gail H. Schaefer, Katherine A. Shepard, Theo ten Brummelaar, John D. Monnier, Stefan Kraus, Jean-Baptiste Le Bouquin, Claire L. Davies, Jacob Ennis, Tyler Gardner, Aaron Labdon, Rachael M. Roettenbacher, Benjamin R. Setterholm, Wolfgang Vollmann, Costantino Sigismondi
Figure caption: The V-band light curve (lower panel) and V − I  c  color index (upper panel) of RW Cep over the past seven years. The lower panel shows the V-band light curve from the AAVSO archive (plus signs; mainly from observations made by W. Vollman) and the KWS (diamond symbols). The KWS includes estimates of the Johnson-Cousins I  c -band magnitude, and the top panel shows the time evolution of the V − I  c  color index. The top axis gives the calendar date (BY) of the observation. The vertical dashed line indicates the date of the CHARA Array observation. For comparison purposes, the dotted line in the lower panel shows the Great Dimming of Betelgeuse from Taniguchi et al. (2022) for their 0.51 μm band photometry (seven point averages, offset by +1040 days in time and by +5.2 in magnitude).
Paper: Catalog of Integrated-light Star Cluster Light Curves in TESS
Authors: Tobin M. Wainer, Gail Zasowski, Joshua Pepper, Tom Wagg, Christina L. Hedges, Vijith Jacob Poovelil, Tara Fetherolf, James R. A. Davenport, P. Marios Christodoulou, Jack T. Dinsmore, Avi Patel, Kameron Goold, Benjamin J. Gibson
Figure caption: Shown is the LSP results for 50 trials of our generated synthetic cluster light curves for ages of 1 Gyr (blue), 5 Gyr (green), and 10 Gyr (red). Inserted are the isochrones for the three clusters that we then populated and matched stars from Fetherolf et al. (2022). The shaded region represents the 1σ uncertainty of the 50 trials.
Paper: Catalog of Integrated-light Star Cluster Light Curves in TESS
Authors: Tobin M. Wainer, Gail Zasowski, Joshua Pepper, Tom Wagg, Christina L. Hedges, Vijith Jacob Poovelil, Tara Fetherolf, James R. A. Davenport, P. Marios Christodoulou, Jack T. Dinsmore, Avi Patel, Kameron Goold, Benjamin J. Gibson
Figure caption: Identification of individual pixel power contributing to frequency ranges in the LSP for NGC 6304. In the left panel is a TESS flux map for NGC 6304 (centered at (α, δ) = (258.635, −29.462)), with the cluster radius of 0.°13 shown by the red circle. The orange plus signs mark the location of the three largest contours in the right panel. In the middle panel is the integrated light curve’s LSP. The dashed horizontal yellow line shows the FAP of 0.007, and the grayed-out region is the part of frequency space (>10-day periods) we are not sensitive to. Two frequency ranges are highlighted, with 0.183–0.199 day−1 highlighted in purple and 2.367–2.608 day−1 highlighted in green. The right panel shows the spatial distribution of power in these frequency ranges, in the corresponding colors. The red circle has the same angular size as in the left panel. The purple and green contours show pixel power from the corresponding frequency ranges in the middle panel. The feature in purple corresponds to a low-mass X-ray binary candidate (Guillot et al. 2009; Heinke et al. 2020), and the second feature corresponds to two RRL stars whose literature frequencies are close together but are well separated in the TESS image (Gaia Collaboration et al. 2021). See Section 5.1 for more details.
Paper: Catalog of Integrated-light Star Cluster Light Curves in TESS
Authors: Tobin M. Wainer, Gail Zasowski, Joshua Pepper, Tom Wagg, Christina L. Hedges, Vijith Jacob Poovelil, Tara Fetherolf, James R. A. Davenport, P. Marios Christodoulou, Jack T. Dinsmore, Avi Patel, Kameron Goold, Benjamin J. Gibson
Figure caption: Demonstration of the light-curve corrections (Section 3.1) for the cluster NGC 330. The left column shows light curves for pixels inside the cluster radius (the green circle in the right column). The right column shows normalized individual pixel light curves at the 1700th time step (the green vertical line in the left panels). Inset into the top middle panel is a flux map at this time step of the region, to show the brightness of the cluster compared to the surrounding field. The first row shows the raw data, while the second row shows the light curve after using PCA to correct for background/scattered light and applying the spline correction. The third row shows the final light curve, with correction from all three elements included.