adsabs/AstroCLIMB huggingface dataset:
Paper: Consequences of Non-Gaussian Instrumental Noise in Perturbed Nulling Interferometers
Authors: Felix A. Dannert, Philipp A. Huber, Thomas Birbacher, Romain Laugier, Markus J. Bonse, Emily O. Garvin, Adrian M. Glauser, Veronika Oehl, Sascha P. Quanz
Figure caption: Overview of the instrument model and statistical pipeline. The top row shows the analytical approach (green). The bottom row traces the parallel seminumerical approach (gray), which is used for validation and later statistical bootstrapping. Combined (orange), the two approaches result in a closed form solution for the test statistic Tα and a factor correcting the analytical test statistic ﹩{T}_{{ \mathcal N }}/{T}_{\alpha }﹩ for its non-Gaussian distribution.
Paper: Consequences of Non-Gaussian Instrumental Noise in Perturbed Nulling Interferometers
Authors: Felix A. Dannert, Philipp A. Huber, Thomas Birbacher, Romain Laugier, Markus J. Bonse, Emily O. Garvin, Adrian M. Glauser, Veronika Oehl, Sascha P. Quanz
Figure caption: Comparison between a sample of 108 template-matched systematic noise time series ﹩\check{F}={{\boldsymbol{n}}}_{{\rm{sys}}}\cdot {\boldsymbol{\eta }}﹩ and Gaussian/IMB distributions. Left: the log-histogram of the samples compared to the pdf’s of Gaussian and IMB noise. Right: QQ plots between the sample and the noise models for different dof ν. The choice of ν = 36 maximizes the coefficient of determination R2.
Paper: Consequences of Non-Gaussian Instrumental Noise in Perturbed Nulling Interferometers
Authors: Felix A. Dannert, Philipp A. Huber, Thomas Birbacher, Romain Laugier, Markus J. Bonse, Emily O. Garvin, Adrian M. Glauser, Veronika Oehl, Sascha P. Quanz
Figure caption: Sketch of the flat wave front approximation for calculating the electric field response of a collector at position xj via OPDj to an arbitrary but fixed origin (x, y, z).
Paper: Consequences of Non-Gaussian Instrumental Noise in Perturbed Nulling Interferometers
Authors: Felix A. Dannert, Philipp A. Huber, Thomas Birbacher, Romain Laugier, Markus J. Bonse, Emily O. Garvin, Adrian M. Glauser, Veronika Oehl, Sascha P. Quanz
Figure caption: Influence of the modulation frequency of the planet signal on the systematic noise contribution. The black lines trace the noise PSDs of first and second order. The colored bars show the square modulus of the Fourier components of the planet signal for two different array stretching ratios.
Paper: Consequences of Non-Gaussian Instrumental Noise in Perturbed Nulling Interferometers
Authors: Felix A. Dannert, Philipp A. Huber, Thomas Birbacher, Romain Laugier, Markus J. Bonse, Emily O. Garvin, Adrian M. Glauser, Veronika Oehl, Sascha P. Quanz
Figure caption: 1/f shape of the pink-noise PSD assumed for the phase and amplitude perturbations. On timescales longer than the harmonics of array rotation Nrot, the PSD is constant.
Paper: Gas-phase Molecules in Protoplanetary Nebulae with the 21 μm Emission Feature. II. Carbon Monosulfide
Authors: Jian-Jie Qiu, 建 杰 邱, Yong Zhang,  泳 张, Deng-Rong Lu,  登 荣 逯, Zheng-Xue Chang,  正 雪 常, Jiang-Shui Zhang,  江 水 张, Xiao-Hu Li,  小 虎 李, Xin-Di Tang,  新 弟 汤, Yisheng Qiu,  逸 盛 邱, Jun-ichi Nakashima,  岛 淳 一 中, Lan-Wei Jia,  兰 伟 贾
Figure caption: Fractional abundance of CS as a function of the dynamical age of the CSEs. The filled and open squares denote the 21 μm sources with and without CS detection, respectively. These data points have been artificially shifted slightly for the sake of clarity. The filled circles denote the PNe investigated by J. L. Edwards et al. (2014). The open circles linked by straight lines denote the AGB CSEs and PPNe investigated in the literature listed in Table 2. The solid and dashed curves represent the calculated results from Model 1 and Model 2 (see the text), respectively. The open triangles linked by dashed-dotted line are the calculated results of the clumpy model for PNe at the dynamical ages of 2550, 6300, and 10,050 yr (M. P. Redman et al. 2003). The vertical dashed lines mark the dynamical ages and source names of the comparison sample. The asterisk denotes the fractional abundance of CS in IRAS 22272+5435 calculated from the observations reported in Y. Zhang (2020), and this value is connected to our results by a straight line for visual comparison.
Paper: NIR Filter Transformations Across the HR Diagram: JWST, Roman, and Euclid
Authors: M. J. Durbin, R. L. Beaton, A. J. Monson, B. Swidler
Figure caption: Euclid/NISP YE, JE, and HE TRGB magnitudes as a function of YE − HE color for the A. Serenelli et al. (2017) and A. Pietrinferni et al. (2021) theoretical TRGB calibrations.
Paper: NIR Filter Transformations Across the HR Diagram: JWST, Roman, and Euclid
Authors: M. J. Durbin, R. L. Beaton, A. J. Monson, B. Swidler
Figure caption: Throughput curves for all filters considered in this work.
Paper: A Search for Subdwarf B Binaries Using Pulsation Timing from TESS
Authors: Tomomi Otani, A. S. Baran, Lindsay C. Spence, Ted von Hippel, E. Lynum- Lozano, Julia. M. Clark
Figure caption: Pulsation timing analysis of targets with no observed periodic variations. Only the first sector in which each target was observed with a 20 s cadence is shown. When more than one pulsation frequency is used for the analysis, the pulsation with the largest amplitude is shown on top.
Paper: A Search for Subdwarf B Binaries Using Pulsation Timing from TESS
Authors: Tomomi Otani, A. S. Baran, Lindsay C. Spence, Ted von Hippel, E. Lynum- Lozano, Julia. M. Clark
Figure caption: Upper companion mass limits for i = 90° for each target using all available TESS sectors in the analysis.
Paper: A Search for Subdwarf B Binaries Using Pulsation Timing from TESS
Authors: Tomomi Otani, A. S. Baran, Lindsay C. Spence, Ted von Hippel, E. Lynum- Lozano, Julia. M. Clark
Figure caption: Pulsation timing analysis of TIC 202354658 using f5 (the largest amplitude pulsation—shown in “•”) and f2 (the second largest amplitude pulsation—shown in “■”). (Row1) Pulsation timing analysis of all available sectors, Sectors 48–51, 58, 75–78, 82, and 85. (Row2–4: top) The pulsation timing analysis of each sector. The solid curve shows the best-fit sinusoid. (Row2–4: bottom) The pulsation amplitude variations of each sector.(The data used to create this figure are available in the online article.)(The data used to create this figure are available.)
Paper: A Search for Subdwarf B Binaries Using Pulsation Timing from TESS
Authors: Tomomi Otani, A. S. Baran, Lindsay C. Spence, Ted von Hippel, E. Lynum- Lozano, Julia. M. Clark
Figure caption: Pulsation timing analysis of TIC 69298924 using f3 (the largest amplitude pulsation). (Row1) Pulsation timing analysis of all available sectors, Sectors 44–46, and 71–72. (Row 2 and 3:  top) The pulsation timing analysis of Sectors 44–46 and Sectors 71–72. The solid curve shows the best-fit sinusoid. (Row 2 and 3:  Bottom) The pulsation amplitude variations of each sector.(The data used to create this figure are available in the online article.)(The data used to create this figure are available.)
Paper: A Search for Subdwarf B Binaries Using Pulsation Timing from TESS
Authors: Tomomi Otani, A. S. Baran, Lindsay C. Spence, Ted von Hippel, E. Lynum- Lozano, Julia. M. Clark
Figure caption: Color–color diagram for all available sdB binaries in the (S. Geier 2020) database. TIC 202354698 and TIC 69298924 are indicated by filled squares.
Paper: NIR Filter Transformations Across the HR Diagram: JWST, Roman, and Euclid
Authors: M. J. Durbin, R. L. Beaton, A. J. Monson, B. Swidler
Figure caption: As Figure 5 for converting ground filters to Roman.
Paper: NIR Filter Transformations Across the HR Diagram: JWST, Roman, and Euclid
Authors: M. J. Durbin, R. L. Beaton, A. J. Monson, B. Swidler
Figure caption: As Figure 5 for converting Euclid filters to Roman.
Paper: The Interpolation Constraint in the RV Analysis of M Dwarfs Using Empirical Templates
Authors: Dhvani Doshi, Nicolas B. Cowan, Étienne Artigau, René Doyon, André M. Silva, Khaled Al Moulla, Yashar Hezaveh
Figure caption: Top: the normalized interpolation error, represented by the term in square brackets in Equation (5), is plotted against the spectral quality factor and follows a second-order polynomial shown by the black line. Diamonds indicate various spectra, with the positions of example M4, M6, M8, and M9 stars highlighted. Bottom: this provides the RV uncertainty floor due to interpolation error for a given spectral type and sampling resolution. RMSE in RV estimates for where S/N is 1000 per 1 km s−1 domain across sampling resolutions and spectral types. Dashed lines show RV precision using the intrinsic spectrum. Template-based estimates are limited to ∼0.5 m s−1 for SPIRou. A fourth-order polynomial fit captures template-based interpolation error.
Paper: The Interpolation Constraint in the RV Analysis of M Dwarfs Using Empirical Templates
Authors: Dhvani Doshi, Nicolas B. Cowan, Étienne Artigau, René Doyon, André M. Silva, Khaled Al Moulla, Yashar Hezaveh
Figure caption: The root mean squared error of the estimated RVs for 100 evaluation observations for templates created with a varying number of observations, Ntemp, and with the intrinsic stellar spectrum. In the first panel, we plot the RMSE for a hypothetical instrument with 4 pixels per FWHM observing an M9 star. We see that the RMSE of the template follows Poisson statistics. In the second panel, we observe the same M9 star but at the sampling resolution of SPIRou. Here we see an RMSE plateau at high S/N due to interpolation error. In the last panel, we compare this to observations of an M5 star with SPIRou.
Paper: The Interpolation Constraint in the RV Analysis of M Dwarfs Using Empirical Templates
Authors: Dhvani Doshi, Nicolas B. Cowan, Étienne Artigau, René Doyon, André M. Silva, Khaled Al Moulla, Yashar Hezaveh
Figure caption: Retrieved planetary RV curves using either the intrinsic stellar spectrum or a template built from 50 observations, shown for three S/N regimes. There is also a BERV that contributes to the overall RV curve, however, only the planetary RV is plotted. Results are displayed for both SPIRou’s native sampling and an instrument with 4 pixels per FWHM. Semitransparent points show per-order RVs; opaque points show the order-combined RV. At SPIRou resolution, interpolation error from the template introduces random RV offsets, especially at high and moderate S/Ns, which are absent at finer sampling or when using the intrinsic spectrum.
Paper: The Interpolation Constraint in the RV Analysis of M Dwarfs Using Empirical Templates
Authors: Dhvani Doshi, Nicolas B. Cowan, Étienne Artigau, René Doyon, André M. Silva, Khaled Al Moulla, Yashar Hezaveh
Figure caption: The standard deviation of the Z-scores between the observation and the template is shown for different cases. A standard deviation greater than one indicates interpolation errors. Top: the significance of interpolation error depends on both sampling resolution and photon noise, with each line representing a different sampling resolution. Bottom: the standard deviation of the Z-scores for different M-dwarf types at SPIRou’s native resolution shows that interpolation errors increase for cooler M dwarfs with higher RV content.
Paper: Dynamical Analysis of the HD 169142 Planet-forming Disk: Twelve Years of High-contrast Polarimetry
Authors: Miles Lucas, Michael Bottom, Ruobing Dong, 董若冰, Myriam Benisty, Mario Flock, Maria Vincent, Jonathan Williams, Kyohoon Ahn, Thayne Currie, Vincent Deo, Olivier Guyon, Tomoyuki Kudo, Lucinda Lilley, Julien Lozi, Maxwell Millar-Blanchaer, Barnaby Norris, Sebastián Pérez, Boris Safonov, Peter Tuthill, Taichi Uyama, Sébastien Vievard, Manxuan Zhang
Figure caption: Mean phase correlograms for the inner and outer rings with 1σ-uncertainty contours based on the azimuthal profiles in Figure 11. The locations of the peaks of the correlograms correspond to the estimated angular velocities of the azimuthal brightness profiles. The peak locations, measured with bootstrap resampling of the correlogram, are marked with vertical red and gray lines. The uncertainty in the peak estimates from bootstrap resampling is shown with a bar at the bottom of the plot. The expected Keplerian motion, based on the rings’ separations, is marked with black vertical dashed lines. The motion measured via phase cross correlation is consistent with Keplerian motion.
Paper: Dynamical Analysis of the HD 169142 Planet-forming Disk: Twelve Years of High-contrast Polarimetry
Authors: Miles Lucas, Michael Bottom, Ruobing Dong, 董若冰, Myriam Benisty, Mario Flock, Maria Vincent, Jonathan Williams, Kyohoon Ahn, Thayne Currie, Vincent Deo, Olivier Guyon, Tomoyuki Kudo, Lucinda Lilley, Julien Lozi, Maxwell Millar-Blanchaer, Barnaby Norris, Sebastián Pérez, Boris Safonov, Peter Tuthill, Taichi Uyama, Sébastien Vievard, Manxuan Zhang
Figure caption: Azimuthal scattered light profiles (Qϕ × r2) for each data set, normalized to the percent deviation from the mean value. The profiles were calculated using 5° wide azimuthal bins, the same as the polar images (Figure 8). The shaded areas are the 1σ standard errors, using the Uϕ × r2 image as an error map. Left: the inner ring, from 15 to 35 au. Right: the outer ring, from 48 to 110 au.
Paper: Dynamical Analysis of the HD 169142 Planet-forming Disk: Twelve Years of High-contrast Polarimetry
Authors: Miles Lucas, Michael Bottom, Ruobing Dong, 董若冰, Myriam Benisty, Mario Flock, Maria Vincent, Jonathan Williams, Kyohoon Ahn, Thayne Currie, Vincent Deo, Olivier Guyon, Tomoyuki Kudo, Lucinda Lilley, Julien Lozi, Maxwell Millar-Blanchaer, Barnaby Norris, Sebastián Pérez, Boris Safonov, Peter Tuthill, Taichi Uyama, Sébastien Vievard, Manxuan Zhang
Figure caption: Phase corellograms for pairs of azimuthal profiles of the inner ring (15–35 au). The row and column labels signify the two epochs correlated in the subsequent correlogram. Plots with a (*) are excluded from the mean combination and analysis in Figure 12.
Paper: Dynamical Analysis of the HD 169142 Planet-forming Disk: Twelve Years of High-contrast Polarimetry
Authors: Miles Lucas, Michael Bottom, Ruobing Dong, 董若冰, Myriam Benisty, Mario Flock, Maria Vincent, Jonathan Williams, Kyohoon Ahn, Thayne Currie, Vincent Deo, Olivier Guyon, Tomoyuki Kudo, Lucinda Lilley, Julien Lozi, Maxwell Millar-Blanchaer, Barnaby Norris, Sebastián Pérez, Boris Safonov, Peter Tuthill, Taichi Uyama, Sébastien Vievard, Manxuan Zhang
Figure caption: The same as Figure 13, but for the outer ring from 45 to 90 au.
Paper: Dynamical Analysis of the HD 169142 Planet-forming Disk: Twelve Years of High-contrast Polarimetry
Authors: Miles Lucas, Michael Bottom, Ruobing Dong, 董若冰, Myriam Benisty, Mario Flock, Maria Vincent, Jonathan Williams, Kyohoon Ahn, Thayne Currie, Vincent Deo, Olivier Guyon, Tomoyuki Kudo, Lucinda Lilley, Julien Lozi, Maxwell Millar-Blanchaer, Barnaby Norris, Sebastián Pérez, Boris Safonov, Peter Tuthill, Taichi Uyama, Sébastien Vievard, Manxuan Zhang
Figure caption: Polar images of the 15 7 2018 ZIMPOL scattered light (Qϕ × r2) and 1.3 mm dust emission for the inner ring (15–35 au). The ZIMPOL data have been desheared to correct for Keplerian motion between the two observation dates. The H2O snow line transition region is marked with a horizontal dashed line in both panels (A. S. Booth et al. 2023).
Paper: Dynamical Analysis of the HD 169142 Planet-forming Disk: Twelve Years of High-contrast Polarimetry
Authors: Miles Lucas, Michael Bottom, Ruobing Dong, 董若冰, Myriam Benisty, Mario Flock, Maria Vincent, Jonathan Williams, Kyohoon Ahn, Thayne Currie, Vincent Deo, Olivier Guyon, Tomoyuki Kudo, Lucinda Lilley, Julien Lozi, Maxwell Millar-Blanchaer, Barnaby Norris, Sebastián Pérez, Boris Safonov, Peter Tuthill, Taichi Uyama, Sébastien Vievard, Manxuan Zhang
Figure caption: The same as Figure 15, but for the outer ring (48–115 au).
Paper: LEO-Vetter: Fully Automated Flux- and Pixel-level Vetting of TESS Planet Candidates to Support Occurrence Rates
Authors: Michelle Kunimoto, Steve Bryson, Drayson Jaffee, Jason F. Rowe, Tansu Daylan, Steven Giacalone, Jack J. Lissauer, Michael R. B. Matesic, Susan E. Mullally, Yoshi Nike Emilia Eschen
Figure caption: Results from testing LEO-Vetter on simulated planets and false alarms, as functions of SNR and either number of transits (left panels; note that the boundaries between bins are inclusive for the bin to the right, so, e.g., the leftmost boxes have either 3 or 4 candidate transit events) and orbital period (right panels). Because different stars observed by TESS are associated with unique numbers of sectors and severity of data gaps, vetting performance does not directly map between the number of transits and orbital period. Completeness grids report the percentage of injected planets successfully classified as PCs (top numbers) and the actual fraction of injected TCEs classified as PCs (bottom numbers). Effectiveness grids report the percentage of simulated false alarms successfully classified as FAs (top) and the actual fraction of scrambled TCEs classified as FAs (bottom). Reliability grids report the percentage of observed PCs that are expected to be planets (top) and the actual number of PCs identified among observed TCEs (bottom).
Paper: LEO-Vetter: Fully Automated Flux- and Pixel-level Vetting of TESS Planet Candidates to Support Occurrence Rates
Authors: Michelle Kunimoto, Steve Bryson, Drayson Jaffee, Jason F. Rowe, Tansu Daylan, Steven Giacalone, Jack J. Lissauer, Michael R. B. Matesic, Susan E. Mullally, Yoshi Nike Emilia Eschen
Figure caption: An example of difference image analysis of the known false positive TOI-164.01. Left: average out-of-transit pixel image showing the pixels near TOI-164.01 (the average in-transit image looks very similar). Stars are shown as white-bordered disks with size and color determined by their TIC magnitudes, and the target star TOI-164 is marked by the magenta “⋆.” Center: the difference pixel image, showing that the largest change from out-of-transit to in-transit is on the pixels containing the brightest background star. Visually, the starlike pattern in the difference image looks like it is due to that brightest background star. Right: the location of the PRF fit to the difference image is shown as the red “+,” demonstrating that the PRF fit indicates that the transit signal is on the brightest background star. The colors scales are different between the images, but the quantitative details are irrelevant.
Paper: LEO-Vetter: Fully Automated Flux- and Pixel-level Vetting of TESS Planet Candidates to Support Occurrence Rates
Authors: Michelle Kunimoto, Steve Bryson, Drayson Jaffee, Jason F. Rowe, Tansu Daylan, Steven Giacalone, Jack J. Lissauer, Michael R. B. Matesic, Susan E. Mullally, Yoshi Nike Emilia Eschen
Figure caption: Examples of nonplanetary TCEs to demonstrate the typical false alarms and false positives targeted by select tests in LEO-Vetter. We show TCEs caused by stellar variability that failed the SWEET test (Section 3.3, top left) and the asymmetry test (Section 3.5, top right), a scattered light event that failed the single event domination test (Section 3.11, bottom left), and an eclipsing binary that failed the significant secondary test (Section 4.3, bottom right).
Paper: LEO-Vetter: Fully Automated Flux- and Pixel-level Vetting of TESS Planet Candidates to Support Occurrence Rates
Authors: Michelle Kunimoto, Steve Bryson, Drayson Jaffee, Jason F. Rowe, Tansu Daylan, Steven Giacalone, Jack J. Lissauer, Michael R. B. Matesic, Susan E. Mullally, Yoshi Nike Emilia Eschen
Figure caption: Period histograms of TCEs from observed (unscrambled) light curves (blue) and scrambled light curves (orange), demonstrating that scrambling effectively simulates false-alarm TCEs. The dotted gray lines indicate 0.5, 1, and 2 times the TESS orbital period (13.7 days). These histograms also demonstrate that a large majority of TESS TCEs are false alarms. However, LEO-Vetter is capable of producing planet catalogs with very high false-alarm reliability (Section 6.1).
Paper: LEO-Vetter: Fully Automated Flux- and Pixel-level Vetting of TESS Planet Candidates to Support Occurrence Rates
Authors: Michelle Kunimoto, Steve Bryson, Drayson Jaffee, Jason F. Rowe, Tansu Daylan, Steven Giacalone, Jack J. Lissauer, Michael R. B. Matesic, Susan E. Mullally, Yoshi Nike Emilia Eschen
Figure caption: Period histograms from Figure 3, but after applying LEO-Vetter flux-level vetting to remove false alarms and false positives and using larger bin sizes due to the smaller number of TCEs. The systematic pileups visible in Figure 3 are significantly reduced.
Paper: Characterizing the Time Variability of 2M1207 A + b with JWST NIRSpec/PRISM
Authors: Arthur D. Adams, Yifan Zhou, Gabriel-Dominique Marleau, Daniel Apai, Beth A. Biller, Aarynn L. Carter, Johanna M. Vos, Niall Whiteford, Stephan Birkmann, Theodora Karalidi, Xianyu Tan, Jason Wang, Yuhiko Aoyama, Brendan P. Bowler, Mickaël Bonnefoy, Jun Hashimoto
Figure caption: (a) The spectral flux density of the 2M1207 A data. The thickness of the line represents the range of values across the time series. Specific wavelength ranges are highlighted with colors that span the vertical extent below the spectrum. Each corresponds to a feature in the variability discussed in the text: Hα in pink, 0.73–0.80 μm in gray, 3.19–3.44 μm in light green, 3.36–3.38 μm in dark green, and >4.35 μm in red. (b) The variability data are shown on a color map with dimensions of wavelength vs. time of observation (20 exposures across 12.56 hr). The color shows the variability displacement as defined in Equation (1)). (c) The values of the model comparison between a linear and constant model for the variability displacement at each wavelength (gray region), considered our baseline test for a trend in time; and for a sinusoidal model vs. linear at each wavelength (green region). The wavelength elements containing Hα emission show an extreme outlier on this plot, with relative evidences for both model comparisons exceeding ΔBIC ≳ 1000. Panels (d) and (e): pairs of light curves chosen based on similarities in their best-fit sinusoidal parameters. Panel (d) shows the Hα light curve plotted along with the light curve integrated across all wavelengths beyond 4.35 μm. Panel (e) shows light curves integrated across the ranges 0.73–0.80 μm and 3.36–3.38 μm. Each plot shows the best-fit model for each light curve; each model is the most preferred out of the choices in Section 3.1 using a selection threshold of ΔBIC  ≥ 6.
Paper: Characterizing the Time Variability of 2M1207 A + b with JWST NIRSpec/PRISM
Authors: Arthur D. Adams, Yifan Zhou, Gabriel-Dominique Marleau, Daniel Apai, Beth A. Biller, Aarynn L. Carter, Johanna M. Vos, Niall Whiteford, Stephan Birkmann, Theodora Karalidi, Xianyu Tan, Jason Wang, Yuhiko Aoyama, Brendan P. Bowler, Mickaël Bonnefoy, Jun Hashimoto
Figure caption: Spectral variability amplitudes for the time-series data and a series of forward models for 2M1207 b. The individual variability amplitudes are shown in black, representing only those wavelength elements whose time series return a statistically significant linear fit vs. a flat model. The orange curve and shaded region represent the maximum likelihood and 68% credible interval, respectively, of the variability amplitudes derived from varying the areal filling fraction of the two-component model presented in Z. Zhang et al. (2025, termed QEQ-1). The purple curve represents the equivalent values for our reproduction of the same forward model, but where the absolute value and variation in the filling fractions are fit to our data. The model is fit only to the two regions as identified from our empirical characterization (0.86–1.77 μm, in Figure 7(e), and 3.29–4.34 μm, in Figure 7(f)).