adsabs/AstroCLIMB huggingface dataset:
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: starkiller applied to a data cube where a satellite strikes Blazar WISEA J014132.24-542751.0 (J0141-5427) on 2022 July 23. In a worst-case scenario satellite strike (left), the unknown satellite crosses directly over the central science target. With the satkiller extension to starkiller we are able to effectively model (middle) and remove the satellite signal in all wavelengths (right), such that the residuals are on the same scale as the detector imperfections. With starkiller we have potentially salvaged a 2960 s exposure from a satellite strike. The orange circle is a field star identified by the Gaia DR3 catalog.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Best-fitting E(B − V) values for the Gaia DR3 stars in NGC 6563. Left: histogram of E(B − V) occurrence rates. Right: spatial distribution superimposed on the IFU median image. The bimodal distribution may indicate a population of low-extinction foreground stars, and a population of high-extinction stars which are largely colocated with the nebula. While the validity of extinctions that starkiller applies to models is yet to be tested, it provides a way to independently and rapidly calculate extinction values for stars in a cluster.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: starkiller applied to a MUSE data cube of Didymos, observed on 2022 October 25, following the DART impact of 2022 November 27 (C. Opitom et al. 2023). Faint stellar sources crossing the tail are well modeled and subtracted. Brighter sources have poor subtractions in the wings of the PSF; this limitation is discussed in Section 4.4.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Comparison of source-subtracted MUSE data cubes for NGC 6563 processed by starkiller (left) and PempelMUSE (right). The two pipelines take different approaches: starkiller uses spectral models scaled by external flux catalogs, and PempelMUSE directly subtracts sources through PSF fitting. In this example, PempelMUSE appears to systematically oversubtract sources, particularly those that overlap with the nebula.
Paper: starkiller: Subtracting Stars and Other Sources from IFU Spectroscopic Data Through Forward Modeling
Authors: Ryan Ridden-Harper, Michele T. Bannister, Sophie E. Deam, Thomas Nordlander
Figure caption: Recreation of Figure 5 for sidereally tracked point sources extracted from the sky observation ADP.2023-09-27T15_07_36.629. As with the trailed sources, the data PSF outperforms both the Moffat and Gaussian PSF profiles.
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: This figure illustrates the process of estimating offsets, with data points color-coded according to the channels. Top left: raw data for GJ 908. Top right: GJ 908 data corrected by the median for individual runs. Bottom left: computed GLS periodograms for the median-corrected data for GJ 908. A significant signal is detected at a period of ∼26 days that likely corresponds to stellar rotation. Bottom right: offsets estimated by subtracting the best-fit GP model from the raw data in the top-left panel.
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: The upper plot illustrates the offsets estimated using the ensemble of stars for the red channel, while the lower plot shows the offsets for the blue channel. The circles represent individual offsets and are color-coded by targets. The open squares indicate the median offset for all targets in a run.
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: Percentage change in flux from the ThAr lamp between 2022 August and 2023 October. The change in flux is calculated with respect to the ThAr flux values on 2022 August 1 and plotted for the central order in the red channel (order 81) and blue channel (order 107) for ease of viewing.
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: Mean drift of the etalon from 2021 August to 2023 October as seen in the red channel (top) and the blue channel (bottom).
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: The top panel shows the phase-folded plot for HD 3651 b. A joint fit was performed between HIRES, NEID, EXPRES, and MAROON-X data. The second and third panels show the residuals for the MAROON-X red and blue channels. The fourth and fifth panels show the residuals for the EXPRES and NEID data.
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: The differential RV time-series data for all the stars used in this study. The top panel displays data from the red channel, while the bottom panel shows data from the blue channel.
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: Temporal variation in the etalon drift calculated for each order plotted as a function of wavelength.
Paper: Calibrating the Instrumental Drift in MAROON-X Using an Ensemble Analysis
Authors: Ritvik Basant, Tanya Das, Jacob L. Bean, Rafael Luque, Andreas Seifahrt, Madison Brady, Nina Brown, Julian Stürmer, David Kasper, Guđmundur Stefánsson
Figure caption: The top panel shows the ensemble offsets plotted as a function of ThAr offsets for the red channel, while the bottom panel shows it for the blue channel.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: The 3.6 μm (left) and 4.5 μm (right) residual dark frames calculated from the 1990 UA observations.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: IRAC 4.5 μm image patches from individual sky-subtracted cBCD frames displayed by NEOphot. The black labels above each frame show the frame number and relative time in seconds from the first frame in this series. The green label underneath show the relative offset in pixels of the source centroid relative to the expected NEO position. The images outlined in red are the frames that were rejected due to artifacts. An example of an artifact is visible in frame 335, where the NEO is passing near a residual from a bright star subtraction.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: Mosaic of the 4.5 μm sky background from the example 1990 UA observations. The stars appear slightly trailed because Spitzer is tracking on the NEO during these observations. The green circles indicate the average position of the NEO during various individual IRAC frames, with the NEO moving from right to left starting with frame 277 (see Figure 3). The missing positions in the sequence are frames that were rejected due to bright stars, cosmic rays, or the NEO landing on bad pixels on the array. The image is approximately 15﹩\mathop{.}\limits^{{\rm{^{\prime} }}}﹩5 wide, and centered near an R.A., decl. of 291﹩\mathop{.}\limits^{\unicode{x000B0}}﹩223, 10﹩\mathop{.}\limits^{\unicode{x000B0}}﹩649 (J2000), with the orientation shown in the image.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: A plot produced by NEOphot of the accepted photometry for this part of the 1990 UA data set, as final confirmation of the results. The plot shows the lightcurve (blue circles with error bars), rejected photometry (orange Xs), the mosaic photometry (red square with error bars), and the median of the lightcurve photometry (green diamond with error bars set to the standard deviation of the blue points). In general, the mosaic and mean of the BCD photometry should be within 1σ of each other, and both should be consistent with the individual BCD photometry points.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: Plot showing the R.A. and decl. offsets in arcsec relative to the expected position of the NEO for both the 3.6 and 4.5 μm images, which were taken in alternating on-source and sky frames. The decl. offset is relatively stable in both channels, whereas the R.A. offset in both channels changes by about 0﹩\mathop{.}\limits^{\unicode{x02033}}﹩4 during the observation, with a minimum near the halfway point. This behavior may be due to the change of apparent motion of the NEO from Spitzer’s viewpoint, where the R.A. non-sidereal rate changed by ∼0﹩\mathop{.}\limits^{\unicode{x02033}}﹩4 minute−1 during the observation, whereas the decl. rate was relatively unchanged.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: A plot from the NEOphot notebook that shows the 3.6 μm (left) and 4.5 μm (right) mosaics constructed from the frames shown in Figure 3, excluding the rejected frames. The axes are labeled in units of mosaic pixels (0﹩\mathop{.}\limits^{\unicode{x02033}}﹩6 pixel−1). The NEOs in this study were not spatially resolved, so these images effectively show the shape of the IRAC PSF.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: The periodogram produced by the L-S algorithm for the NEO 2009 DR3. The observations used the 100 s frame time, and with dithering, one frame was obtained every ∼110 s (or 0.031 hr), with some frames not used due to bad pixels or issues with subtracting the background field. The highest peak in the periodogram is at 0.28857 hr, and doubling this value gives a rotational period of 0.577 ± 0.003 hr (see its lightcurve in Figure 18). No evidence of significant power is seen at the data sampling period.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: Interactive plots from the NEOphot program of the x and y offsets of the NEO relative to the nominal position (left) and the NEO photometry (right) for a portion of the 1990 UA data set. The time is relative to the first frame in the data set being examined. The results for two frames have been rejected from the analysis, as marked by red Xs. The same rejected points are indicated in both graphs, showing that the frames were outliers in terms of the flux measured and their positions in the frame.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: The Spitzer lightcurve for 2012 BF86, forced to the period of 0.0491 hr as obtained by A. Thirouin et al. (2018).
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: The phase plot for the NEO 2005 GL9 when using only the first 5 hr of data. The rotational period determined was 5.288 ± 0.094 hr, compared to 5.149 ± 0.026 hr determined when using the full 9 hr data set.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: NEO periods as a function of derived diameter. Black points are data from the Lightcurve Database (B. D. Warner et al. 2009). Red points are Spitzer-determined periods and diameters from this work, and blue points are upper limits to the periods derived from Spitzer lightcurves that did not cover more than one period. The 1σ diameter uncertainties are shown for the Spitzer observations, and the upper limits are shown with a downward-pointing arrow for those Spitzer points where less than one period was observed. For the objects with Spitzer-determined periods, the statistical uncertainties are smaller than the plotted points.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: Lightcurves (left column) and phased lightcurves (right column) for sources with one or more periods sampled and periods determined. The periods are plotted with different colors in the plots on the right.(The data used to create this figure are available in the online article.)(The data used to create this figure are available.)
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: Phased plots at various alternate periods for 2015 XC. The top and middle plots show the Spitzer data phased according to periods found by P. Pravec as given by B. D. Warner (2016). The lower plot shows the phased plot using a period of 0.13831 hr, which was the second-highest peak in the power spectrum of the Spitzer lightcurve.
Paper: Infrared Fluxes and Lightcurves of Near-Earth Objects: The Full Spitzer Sample
Authors: Joseph L. Hora, Alicia J. Allen, David E. Trilling, Howard A. Smith, Andrew McNeill
Figure caption: Lightcurves (left column) and phased lightcurves (right column) for sources with one or more periods sampled and periods determined. The periods are plotted with different colors in the plots on the right.
Paper: Occurrence Rates of Accreting Companions from a New Method for Computing Emission-line Survey Sensitivity: Application to the Hα Giant Accreting Protoplanet Survey
Authors: Cailin Plunkett, Katherine B. Follette, Gabriel-Dominique Marleau, Eric L. Nielsen
Figure caption: Workflow for estimating direct-imaging survey completeness to accreting companions. First, select models for ﹩\dot{M}-M﹩ and LHα − Lacc, corresponding to assumptions about formation and accretion. Estimate the completeness for each survey star with the following Monte Carlo procedure. At each set of physical parameters (a, M), simulate 104 accreting companions. (A) Sample mass accretion rates ﹩\dot{M}﹩ using an assumed model for the ﹩\dot{M}-M﹩ scaling. We take the empirical fit of S. K. Betti et al. (2023) as a more “stellar” scenario (purple) and the result of D. Stamatellos & G. J. Herczeg (2015) as a more “planetary” model (green; for both, see Section 2.2). The colored bands are the 1σ and 2σ uncertainties. We convert each ﹩M\dot{M}﹩ to Lacc (Section 2.3). (B) Compute the observable LHα based on a model for the accretion scaling. This is either (see Section 2.4) an empirical, stellar magnetospheric scaling (purple; J. M. Alcalá et al. 2017) or a theoretical planetary relation (green; Y. Aoyama et al. 2021). (C) Obtain the projected separation distribution by sampling the companion orbital parameters (Section 2.5); the histogram is an example for an object at a = 100 au with eccentricities following E. L. Nielsen et al. (2019). (D) Next, compare the simulated companions to the star’s contrast curve(s) to estimate the detectable fraction. The panel shows two examples of 100 brown dwarfs with (a, M) = (100 au,  40 MJ) around TW Hya; the left image shows companions simulated using both “stellar” models, while the right image uses both “planetary” models. The light circles are recovered synthetic companions, while the dark squares are undetected. (E) Repeat across a grid in (a. M) for each combination of models, to obtain the entire completeness map. Take the average across the survey stars. Repeat for each combination of astrophysical models of interest.
Paper: Occurrence Rates of Accreting Companions from a New Method for Computing Emission-line Survey Sensitivity: Application to the Hα Giant Accreting Protoplanet Survey
Authors: Cailin Plunkett, Katherine B. Follette, Gabriel-Dominique Marleau, Eric L. Nielsen
Figure caption: Completeness to accreting companions for the 14 stars surveyed by GAPlanetS as a function of semimajor axis (astronomical units) and mass (MJ) for the four combinations of models. The color scale shows the depth of the search or the number of stars to which the survey is complete. The rows dictate the ﹩\dot{M}-M﹩ relations, with the top being the stellar (B23) model and the bottom being the planetary (SH15) model. The columns define the LHα−Lacc scaling, with the left being the stellar (A17) and right being the planetary (A21) scalings. The contours show the completeness to 2.5, 5, 7.5, and 10 (out of 14) stars in the sample.
Paper: Occurrence Rates of Accreting Companions from a New Method for Computing Emission-line Survey Sensitivity: Application to the Hα Giant Accreting Protoplanet Survey
Authors: Cailin Plunkett, Katherine B. Follette, Gabriel-Dominique Marleau, Eric L. Nielsen
Figure caption: Posteriors on the accreting object occurrence rate around stars hosting transitional disks, fp, for different subsets of the GAPlanetS detections. In all, we compare the stellar (purple) and planetary (green) accretion scaling relations. The legends give the median and 16th and 84th percentiles, also marked by filled circles. Left: posteriors on fp using the three confident detections. Center: posteriors on the rate of accreting companions inside disk gaps, excluding HD 100453 B, which lies outside the gap. Right: posteriors on the accreting protoplanet rate, excluding the low-mass stars HD 100453 B and HD 142527 B.
Paper: Occurrence Rates of Accreting Companions from a New Method for Computing Emission-line Survey Sensitivity: Application to the Hα Giant Accreting Protoplanet Survey
Authors: Cailin Plunkett, Katherine B. Follette, Gabriel-Dominique Marleau, Eric L. Nielsen
Figure caption: Left: posteriors on the occurrence rate of close (<200 mas, pink) vs. wide (≥200 mas, blue) companions, assuming the stellar accretion scaling. As in Figure 5, the legend provides the median and 16th and 84th percentiles, also marked by filled circles on the posteriors. Here, we consider the three confirmed companions, one of which is “close” (HD 142527 B) and two of which are “wide” (PDS 70 c and HD 100453 B). Right: posterior on the difference in planet occurrence rate at close vs. wide separations, fp,close − fp,wide; positive values (shaded in pink) indicate close companions are more common.
Paper: Occurrence Rates of Accreting Companions from a New Method for Computing Emission-line Survey Sensitivity: Application to the Hα Giant Accreting Protoplanet Survey
Authors: Cailin Plunkett, Katherine B. Follette, Gabriel-Dominique Marleau, Eric L. Nielsen
Figure caption: Top: GAPlanetS completeness to companions assuming circular orbits, P(e) = δ0,e, using the planetary ﹩\dot{M}-M﹩ and stellar LHα−Lacc scalings. The color scale and contours are as in Figure 2. Bottom: difference in survey sensitivity when assuming orbital eccentricities following P(e) ∝ 2.1−2.2e (lower left panel of Figure 2) vs. assuming circular orbits, P(e) = δ0,e. The color bar shows the difference in the number of stars to which the survey is complete (out of 14); positive values indicate eccentric companions are easier to detect.
Paper: Occurrence Rates of Accreting Companions from a New Method for Computing Emission-line Survey Sensitivity: Application to the Hα Giant Accreting Protoplanet Survey
Authors: Cailin Plunkett, Katherine B. Follette, Gabriel-Dominique Marleau, Eric L. Nielsen
Figure caption: Survey-averaged completeness to accreting companions as a function of projected separation (mas) and ﹩M\dot{M}﹩ (﹩{M}_{{\rm{J}}}^{2}\,{\mathrm{yr}}^{-1}﹩ ). The five GAPlanetS detections are overplotted as white stars. From upper left to lower right, these are CS Cha c, LkCa 15 b, HD 142527 B, PDS 70 c, and HD 100453 B.
Paper: Occurrence Rates of Accreting Companions from a New Method for Computing Emission-line Survey Sensitivity: Application to the Hα Giant Accreting Protoplanet Survey
Authors: Cailin Plunkett, Katherine B. Follette, Gabriel-Dominique Marleau, Eric L. Nielsen
Figure caption: Comparison of posteriors on the companion rate under different prior assumptions: log-uniform (pink), Jeffreys (gold), and uniform (blue). These use the companion inside the gap and assume the stellar accretion scaling relation. The filled circles mark the median and 16th and 84th percentiles.
Paper: Deconvolving X-Ray Galaxy Cluster Spectra Using a Recurrent Inference Machine
Authors: Carter Lee Rhea, Julie Hlavacek-Larrondo, Alexandre Adam, Ralph Kraft, Ákos Bogdán, Laurence Perreault-Levasseur, Marine Prunier
Figure caption: The RIM applied to synthetic X-ray spectra. In this figure, we show the results of the RIM deconvolution process on a randomly selected spectrum from the test set. We compare the ground truth in the upper-left panel vs. the RIM solution. In the upper-right panel, we compare the convolved observed spectrum with the RIM reconstruction created by passing the RIM solution through the forward model. The bottom-left panel shows the error between the ground truth and the RIM solution in units of σ. In the bottom-right panel, we show the error between the convolved observed spectrum and the RIM reconstruction in units of σ. These panels highlight the efficacy of the method in retrieving the unconvolved spectrum; importantly, the convolved observations and the RIM reconstruction are within the 1σ error.