adsabs/AstroCLIMB huggingface dataset:
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: Top: the phase map of the first year of TESS observations of TIC 364588501. Flares are indicated as dots, and the color indicates the amplitude of the quiescent luminosity model. Bottom: excerpt of cycles 57–69 (indicated in red on the above phase map), with the period of high flaring activity denoted between the two orange lines. The histogram on the side indicates the apparent phase dependence observed, using only the flares in the block. Uncertainties in the histogram correspond to the square root of the counts.
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: Composite WTD log-linear plots, showing the WTD for the whole star (blue) and for each of the identified blocks (other colors), and the associated model for each distribution (colored lines). For each panel, the vertical axis represents the cumulative number of events with a larger waiting time, shown with a log scaling. The distributions for the different stars have been given arbitrary vertical offsets so that they do not overlap. Left: TIC 382575967, a star which exhibited only a single change in flaring rate. Right: TIC 364588501, a star which exhibited four rate changes.
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: The phase map of TIC 382575967 during one of its identified rate blocks. Color indicates the amplitude of the quiescent luminosity model, and black dots indicate identified flares. The histogram on the right bins the flares according to their phase. Uncertainties in the histogram correspond to the square root of the counts.
Paper: Observed Rate Variations in Superflaring G-type Stars
Authors: James Crowley, Michael S. Wheatland, Kai Yang
Figure caption: The WTDs for all the rate-variable stars in our sample, shown in log-linear plots. The lines are the distributions corresponding to the Bayesian blocks models. The distributions for each star have been given arbitrary vertical offsets to avoid overlapping.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption:  L AGN,bol detection limits for different filters (colored solid lines) in the JADES (top panels) and MIRI-HUDF surveys (bottom panels). We show the predictions for unobscured AGNs (A  V  = 0) on the left, heavily obscured AGNs (A  V  = 10, corresponding to a ∼10 μm silicate absorption strength τ 10 ∼ 1.5) in the middle, and extremely obscured AGNs (A  V  = 20, corresponding to τ 10 ∼ 2.6) on the right. For all the bands, we assume that the AGN light contributes 20% of the total flux. In all the panels, we also plot the AGNs identified in this work with blue squares for low obscuration (A  V  = 0–1), green diamonds for moderate obscuration (A  V  = 1–10), and red circles for high obscuration (A  V  = 10–20). The SED-identified AGNs are denoted in darker colors, while the other AGNs are shown in lighter colors.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: The relation between the rest-frame 6 μm luminosity from AGNs and the intrinsic 2–10 keV luminosity for our radio-flux-limited AGN sample. We have shown the SED-identified AGNs in blue and red, corresponding to [otype_sed] and [mtype_sed], and other AGNs in gray. The open black circles indicate the locations of some AGNs with very low mid-IR emission relative to their X-ray luminosity after detailed visual SED inspections (four objects whose SEDs will be shown in Figure 19 are highlighted with their 3D-HST IDs). We have also plotted some empirical relations of these quantities for bright AGNs (ν L  ν (6 μm) ≳ 1042–1043 erg s−1) reported in the literature.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: Example SED fittings of X-ray-bright but IR-weak AGNs (these sources are identified in Figure 18). The meanings of the lines and the symbols are the same as in Figure 4. The logarithms of the absorption-corrected X-ray luminosities (erg s−1) between 2 and 10 keV are 42.50, 42.44, 43.36, and 43.36 for sources with ID 3D-HST 2383, 32478, 1924, and 38472, respectively.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: The distribution of the X-ray gas column density and SED-inferred 10 μm silicate strength of SED AGNs. After dropping seven AGNs with very high mid-IR extinction (S10 > − 2; open circles), the other objects (filled circles) show a weak trend. The red line is the correlation established in Shi et al. (2006). The green lines are the analytical relations described in this work.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: AGN number counts (top panels) and obscured fraction (bottom panels) as a function of luminosity (left) and redshift (right). We have limited the sample to 216 AGNs with ﹩\mathrm{log}({L}_{\mathrm{bol}}/{L}_{\odot })=[9.5,12.5]﹩ and z = [0.5, 3.5]. The SED obscuration is defined by the number of optical SED AGNs relative to the total sample, and the X-ray obscuration is defined by the number of objects with N  N  < 1022 cm−2 relative to the total sample. We define two groups of obscuration: direct—the sample is limited to objects with the relevant measurements; and inferred—the whole AGN sample is considered and objects without the relevant measurements are considered as obscured AGNs. For example, if an AGN identified in other ways is not detected at the expected X-ray luminosity, we attribute this to obscuration in the X-ray.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: Gas column density, N H, and X-ray intrinsic luminosity, L X,int, of all Chandra 7 Ms sources (gray circles) and VLA-detected AGNs (blue circles). The red horizontal line indicates ﹩\mathrm{log}({N}_{{\rm{H}}}/{\mathrm{cm}}^{2})=22﹩, above which the source is classified as an obscured AGN. The top panel shows the fraction of objects that are obscured as a function of L X,int (blue for VLA-detected AGNs, and green for all Chandra 7 Ms sources).
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: The apparent AGN luminosity function from this work and a comparison with the modeling work by Shen et al. (2020).
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: Venn diagram of AGNs in the VLA 6 GHz HPBW that are detected in X-ray 0.5–7.0 keV, mid-IR 24 μm, and radio 3 GHz.
Paper: AGN Selection and Demographics in GOODS-S/HUDF from X-Ray to Radio
Authors: Jianwei Lyu, 建伟 吕, Stacey Alberts, George H. Rieke, Wiphu Rujopakarn
Figure caption: Plots similar to Figure 12, but for AGNs detected in subsamples of radio-selected, X-ray-detected, or mid-IR parent sources.
Paper: The Impact of Beam Variations on Power Spectrum Estimation for 21 cm Cosmology. I. Simulations of Foreground Contamination for HERA
Authors: Honggeun Kim, Bang D. Nhan, Jacqueline N. Hewitt, Nicholas S. Kern, Joshua S. Dillon, Eloy de Lera Acedo, Scott B. C. Dynes, Nivedita Mahesh, Nicolas Fagnoni, David R. DeBoer
Figure caption: Averaged Fourier transformed antenna gain over all antennas for the axial (left), the lateral (middle), and the tilting (right) feed motions. The perturbed gains are normalized to the fiducial ones. The dashed and solid lines indicate the results after the redundant baseline and after the full calibration, including the absolute calibration, respectively. The different colored lines denote the different levels of perturbation in the feed motions. Even in the case where the feed is least perturbed, a broad wing ≳300 ns or 0.17 h Mpc−1 (the vertical line) is present. This is due to chromatic gain errors caused by the nonredundancy in the visibilities emerging from the redundant baseline calibration. The existence of this wing is critical, since it affects detection of cosmological signals at low k ∥, where high signal-to-noise ratios are expected. The chromatic gain errors above 2000 ns mainly come from the absolute calibration.
Paper: The Impact of Beam Variations on Power Spectrum Estimation for 21 cm Cosmology. I. Simulations of Foreground Contamination for HERA
Authors: Honggeun Kim, Bang D. Nhan, Jacqueline N. Hewitt, Nicholas S. Kern, Joshua S. Dillon, Eloy de Lera Acedo, Scott B. C. Dynes, Nivedita Mahesh, Nicolas Fagnoni, David R. DeBoer
Figure caption: The foreground power spectrum for the fiducial beam model with the combined sky model. The power spectrum is estimated with the calibrated visibility at LST = 2.25 hr for the 160–180 MHz band. The black dashed line indicates the geometric horizon limit. The strong emission at low k ∥ is due to the point sources located at the zenith, while the emission aligned with the horizon limit is due to the diffuse source near the horizon. The white and orange contours are where the foreground spillovers are the same as and 10% of the EoR power, respectively. The foreground spillover beyond the horizon limit is not due to calibration errors, but due to the intrinsic chromaticity of the beam in the far side lobes convolved with the diffuse power originating from the pitchfork effect. Without the fringe-rate filter, the cosmological information below k ∥ ∼ 0.5 h Mpc−1 is obscured by the foreground power, even with the perfect calibration.
Paper: The Impact of Beam Variations on Power Spectrum Estimation for 21 cm Cosmology. I. Simulations of Foreground Contamination for HERA
Authors: Honggeun Kim, Bang D. Nhan, Jacqueline N. Hewitt, Nicholas S. Kern, Joshua S. Dillon, Eloy de Lera Acedo, Scott B. C. Dynes, Nivedita Mahesh, Nicolas Fagnoni, David R. DeBoer
Figure caption: Foreground power spectra for the vertical (top row), horizontal (middle row), and tilting (bottom row) feed motions, with the combined sky model. From left, power spectra of σ feed = 1, 2, 3, and 4 cm for the translation motions and σ feed = 1°, 2°, and 3° for the tilting motion are presented. The solid white and orange contours indicate where the foreground is equal to and 10% of the EoR power, respectively. The dashed white contour representing the fiducial model is shown in all panels, for comparison. As expected, there is contamination when the feed positions are perturbed. We do not apply any mitigation techniques to reduce the chromatic gain errors, such as down-weighting the effect of long baselines in calibration or smoothing the gain solutions along the frequency axis, which will be discussed in the subsequent paper.
Paper: The Impact of Beam Variations on Power Spectrum Estimation for 21 cm Cosmology. I. Simulations of Foreground Contamination for HERA
Authors: Honggeun Kim, Bang D. Nhan, Jacqueline N. Hewitt, Nicholas S. Kern, Joshua S. Dillon, Eloy de Lera Acedo, Scott B. C. Dynes, Nivedita Mahesh, Nicolas Fagnoni, David R. DeBoer
Figure caption: The χ 2/dof of the redundant baseline calibration for simulated visibilities with perturbed primary beams. From left to right, the vertical, horizontal, and tilting feed motions are presented. The fiducial model yields χ 2/dof close to 1, as expected, which indicates a perfect calibration. When the feed is displaced from the fiducial position, χ 2/dof also deviates from 1. This effect is largest for the tilting motion, which is consistent with the σ red of the raw visibilities shown in Figure 7. The noisy features are due to the thermal noise, which is included only for the χ 2 statistics.
Paper: The Impact of Beam Variations on Power Spectrum Estimation for 21 cm Cosmology. I. Simulations of Foreground Contamination for HERA
Authors: Honggeun Kim, Bang D. Nhan, Jacqueline N. Hewitt, Nicholas S. Kern, Joshua S. Dillon, Eloy de Lera Acedo, Scott B. C. Dynes, Nivedita Mahesh, Nicolas Fagnoni, David R. DeBoer
Figure caption: The relative foreground power spectra, P pGSM/P pGLEAM, for the vertical (left), horizontal (middle), and tilting (right) feed motions. P pGSM is from the visibility that is simulated using the GSM with the perturbed beam and the GLEAM with the fiducial beam. P pGLEAM indicates the opposite case, when the GLEAM is with the perturbed beam and the GSM is with the fiducial beam. The black dashed line indicates the horizon limit. Based on the analyses with σ red in Figure 7, P pGLEAM is expected to have larger foreground leakage than P pGSM for the vertical motion, while P pGSM is responsible for leaking the foreground into the EoR window for the horizontal and tilting motions.
Paper: The Impact of Beam Variations on Power Spectrum Estimation for 21 cm Cosmology. I. Simulations of Foreground Contamination for HERA
Authors: Honggeun Kim, Bang D. Nhan, Jacqueline N. Hewitt, Nicholas S. Kern, Joshua S. Dillon, Eloy de Lera Acedo, Scott B. C. Dynes, Nivedita Mahesh, Nicolas Fagnoni, David R. DeBoer
Figure caption: The amplitude of the gain derived from Equation (8). The response is normalized to the peak of the full band and has an arbitrary linear unit. The shaded region indicates the frequency band of 160–180 MHz, which we use for visibility simulations. The inset panel shows the spectral features of the smoothed gain in the band.
Paper: The Impact of Beam Variations on Power Spectrum Estimation for 21 cm Cosmology. I. Simulations of Foreground Contamination for HERA
Authors: Honggeun Kim, Bang D. Nhan, Jacqueline N. Hewitt, Nicholas S. Kern, Joshua S. Dillon, Eloy de Lera Acedo, Scott B. C. Dynes, Nivedita Mahesh, Nicolas Fagnoni, David R. DeBoer
Figure caption: The slope of the x-direction phase gradient that is solved for by absolute calibration for vertical (left), horizontal (middle), and tilting (right) feed motions. ∂ ν Φx represents the derivative of the linear phase gradient in the x-direction with respect to frequency. We see that the slope is nearly constant for the fiducial model, while there is high-frequency structure for the perturbed model, which introduces additional chromatic gain errors.
Paper: The Impact of Beam Variations on Power Spectrum Estimation for 21 cm Cosmology. I. Simulations of Foreground Contamination for HERA
Authors: Honggeun Kim, Bang D. Nhan, Jacqueline N. Hewitt, Nicholas S. Kern, Joshua S. Dillon, Eloy de Lera Acedo, Scott B. C. Dynes, Nivedita Mahesh, Nicolas Fagnoni, David R. DeBoer
Figure caption: The rms of the fractional gain errors for the vertical (left), horizontal (middle), and tilting (right) feed motions. As expected, larger feed motion perturbations result in the larger rms of the fractional gain errors. Although these gain errors are largely kept to about 1%, when convolved with bright foregrounds this could easily swamp the intrinsic 21 cm signal, if the gain errors have sufficient structure.
Paper: The Impact of Beam Variations on Power Spectrum Estimation for 21 cm Cosmology. I. Simulations of Foreground Contamination for HERA
Authors: Honggeun Kim, Bang D. Nhan, Jacqueline N. Hewitt, Nicholas S. Kern, Joshua S. Dillon, Eloy de Lera Acedo, Scott B. C. Dynes, Nivedita Mahesh, Nicolas Fagnoni, David R. DeBoer
Figure caption: The EoR power spectrum estimated at z ∼ 7.4. The spectral structure in the cosmological signal allows the power spectrum to spread beyond the horizon limit (the black dashed line) defined in Equation (20), forming the isotropic power spectrum.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Results for KOI-268 (KIC 3425851; Group A with ΔLS = 0.014; panels (a) to (e)) and KIC 6116048 (Group B with ΔLS = 0.372; panels (a′) to (e′)). Panels a and a’ show the LS periodogram. The middle panels are the ACF (b,b′), smoothed ACF (c,c′), and the LS periodogram of the smoothed ACF (d,d′), where P 0 denotes the period associated to the first maximum and P max labels the period associated to the highest maximum. Panels (e) and (e′) show the WPS and GWPS from wavelet analysis (WA).
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Log surface gravity as a function of effective temperature for the 92 stars of our sample. Colors indicate the period measured with the LS method (〈P LS,q 〉). Triangles are for KOI stars and circles for stars without planets. Indicative evolution tracks are at solar metallicity (solid black lines) for masses between 0.8M ⊙ and 1.6 M ⊙.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Flow chart of our preprocessing of stellar light curves.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Classification of 70 targets on the ΔP astero/P astero—ΔLS plane. The solid lines indicate the thresholds, ΔLS = 0.2 and ΔP astero/P astero = 0.4, that we adopt in the classification. Green filled circles, blue open squares, magenta open triangles, and gray crosses correspond to stars in Groups Aa, Ba, Ab, and Bb, respectively.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: The detrended light curve of Kepler-1655 (KIC 4141376, KOI-280) for Q2 to Q14 quarters. We remove the three quarters, Q4, Q8, and Q12, in the subsequent photometric analysis, which exhibit anomalous variations illustrated in red.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: 〈P LS,q 〉 vs. P  astero  for 17 targets. There are 19 targets that do not agree within their uncertainties, but we do not plot Kepler-100 and Kepler-409 here because part of their quarters are removed during the light-curve processing. The green, blue, magenta, and gray symbols with error bars correspond to Groups Aa, Ba, Ab, and Bb, respectively.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Same as Figure 7 but for 16 non-KOI stars classified in Group Bb.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Stellar inclination ﹩\sin {i}_{* }﹩ against the effective temperature for KOI stars. The left panels plot the values of ﹩\sin {i}_{* }﹩ derived from asteroseismology (Kamiaka et al. 2018) and the photospectroscopic method adopting spectroscopic ﹩v\sin {i}_{* }﹩ values from the California-Kepler Survey (Petigura et al. 2017) and Huber et al. (2013). The green, blue, magenta, and gray symbols with error bars correspond to Groups Aa, Ba, Ab, and Bb, respectively. The right panels show the distribution functions of ﹩\sin {i}_{* };﹩ the black lines consider all stars, while the shaded regions correspond to stars in Groups Aa, Ba, and Ab excluding the least-reliable group, Group Bb.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Comparison among four different photometrically measured rotation periods: P ACF vs. 〈P LS,q 〉 (upper left), P WA vs. P ACF (upper right), P WA vs. 〈P LS,q 〉 (lower left), and P LS vs. 〈P LS,q 〉 (lower right). We use green, magenta, blue, and gray to represent stars in Groups Aa, Ab, Ba, and Bb, respectively.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Comparison of P astero against photometrically derived rotation periods: 〈P LS,q 〉 (upper left), P LS (upper right), P ACF (lower left), and P WA (lower right). The green, blue, magenta, and gray symbols with error bars correspond to Groups Aa, Ba, Ab, and Bb, respectively.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Stellar rotation periods against the effective temperature. From top to bottom, P astero, ΔP astero/P astero, 〈P LS,q 〉, and ΔLS are plotted as a function of the stellar effective temperature. The green, blue, magenta, and gray symbols correspond to Groups Aa, Ba, Ab, and Bb, respectively.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Part of quarters of light curves of KIC 3456181 and KIC 7106245. The shaded region marks the anomalous quarters where the flux variation suddenly increases.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Part of the light curves for KIC 6603624, and the shaded region corresponds to Q14. Two black arrows indicate the locations of the possible 30 day periodic signal.
Paper: Meta-analysis of Photometric and Asteroseismic Measurements of Stellar Rotation Periods: The Lomb–Scargle Periodogram, Autocorrelation Function, and Wavelet and Rotational Splitting Analysis for 92 Kepler Asteroseismic Targets
Authors: Yuting Lu, 鈺婷 卢, Othman Benomar, Shoya Kamiaka, 翔也 上赤, Yasushi Suto
Figure caption: Same as Figure 7 but for seven KOI stars in stellar binary/multiple systems.