adsabs/AstroCLIMB huggingface dataset:
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Four independently reduced JWST transmission spectra of K2-18 b. NIRISS SOSS and NIRSpec G395H data sets reduced using the FIREFLy pipeline (green error bars; Z. Rustamkulov et al. 2022, 2023; Liu & Wang et al. 2025, in preparation; Wang et al. 2025, in preparation) are compared with the same data reduced with the exoTEDRF pipeline (blue error bars; A. D. Feinstein et al. 2023; M. Radica et al. 2023; M. Radica 2024) and two NIRSpec G395H reductions using the Eureka! pipeline (error bars with gray (B)/white (A) central points; T. Bell et al. 2022). NIRISS data are shown at R ≈ 25, and NIRSpec data are shown at R ≈ 100. The four reductions demonstrate broad agreement.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: JWST NIRISS SOSS data and white light-curve fit for K2-18 b from the FIREFLy reduction. Left: first-order data. Right: second-order data. The photometric data points (points, top panels) are compared with the best-fit light curve (green lines), resulting in a 124 ppm residual scatter for order 1 and 414 ppm for order 2 (bottom panels). Integrations during a spot-crossing event are highlighted (brown points), which are trimmed in the white and spectroscopic light-curve fits.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: JWST NIRSpec G395H data and white light-curve fit for K2-18 b from the FIREFLy reduction. Left: NRS1 detector data. Right: NRS2 detector data. The photometric data points (points, top panels) are compared with the best-fit light curve (green lines), resulting in a 180 ppm residual scatter for NRS1 and 269 ppm for NRS2 (bottom panels).
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Self-consistent mini-Neptune models of K2-18 b’s atmosphere. Upper panel: 100× solar metallicity case. Lower panel: the same metallicity, but with 5000 × nitrogen depletion. The temperature (black lines) and composition profiles (colored lines) from VULCAN-HELIOS (solid lines) and Photochem-PICASO (dashed lines) with the 1σ CH4 range (orange bar) and 95% upper limits for other molecules (arrows).
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Extrapolated best-fit models compared to additional JWST transmission spectra of K2-18 b. Top: best-fitting POSEIDON model to the low-resolution FIREFLy near-infrared data (NIRISS SOSS, R ≈ 25; NIRSpec G395H, R ≈ 100) extrapolated into the mid-infrared for comparison with the MIRI LRS data from N. Madhusudhan et al. (2025) (R ≈ 40). Bottom: reproduction of the median model spectra from N. Madhusudhan et al. (2023; near-infrared only) and N. Madhusudhan et al. (2025; mid-infrared only) with POSEIDON, each extrapolated over the wavelength range of the other data sets. All models are shown binned to R = 100 for clarity, and a 100 ppm offset is applied to the MIRI LRS data, and the models corresponding to N. Madhusudhan et al. (2025), to account for differences in the baseline transit depth. The model from this study, exhibiting no absorption features from DMS or DMDS, provides an adequate fit to the MIRI data. However, the median atmospheric properties from N. Madhusudhan et al. (2025) predict DMDS absorption features with amplitudes inconsistent with the near-infrared data. Near-IR (NIR); mid-IR (MIR).
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Atmospheric composition over time for a hycean scenario for K2-18 b. Upper panel: the steady-state composition profiles computed by VULCAN in our hycean scenario. Lower panel: the composition evolution at 0.1 bar. The red arrow corresponds to the 2σ upper limit of CO2 from our retrievals, while the dashed line indicates the CO2 abundance required to produce a potentially detectable (∼100 ppm) transmission feature at 4.2 μm.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Reproduction of the results from N. Madhusudhan et al. (2023) using their full-resolution NIRISS + NIRSpec data. Retrieval results are overplotted for three retrieval models: (i) with no offset between NIRISS and NIRSpec (blue), (ii) an offset between NIRISS and NIRSpec (orange), and (iii) two offsets, one between NIRISS and NIRSpec G395H NRS1 and one between NIRISS and NIRSpec G395H NRS2 (violet). The statistically favored retrieval model has a single offset. Our POSEIDON retrieval framework produces consistent results with N. Madhusudhan et al. (2023) when using the same priors and data. Any differences in detections for our other retrievals are therefore due to differences in data reduction rather than differences inherent to our retrieval approach.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Potential interior compositions for K2-18 b given our retrieval analysis. The green shaded region on the ternary diagram shows an MCMC posterior of compositions consistent with K2-18 b’s mass, radius, host star flux, atmosphere metallicity (∼30% CH4), and system age. We group methane with water as volatile species for analysis in terms of ice-to-rock ratios, but is physically located in the H/He layer in our model. The three cases discussed in Section 5.2 are circled and labeled. The inset shows the posterior histogram of the log(H/He) mass fraction, with the amount permitting a liquid water ocean (shaded region) containing only 0.58% of our posterior. Above that, the water layer is a supercritical-fluid.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Grid of histograms showing the posteriors for CH4, CO2, and DMS for each of our retrievals. The arrangement and color map are the same as in Figure 5, with the color of the histogram representing the detection significance. While the CH4 posteriors exhibit little variance across reduction choices, there are major differences for CO2 and DMS that are indicative of a nondetection.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Influence of stellar contamination on K2-18 b retrievals. Top: two POSEIDON retrieval models for the low-resolution FIREFLy data variant, one including a planetary atmosphere and stellar contamination (orange) and an alternative atmosphere-only model (purple). Bottom: corresponding posterior distributions for the CH4, CO2, and DMS abundances. The inferred atmospheric composition is insensitive to whether or not stellar contamination is included.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: The equilibrium abundances of H2O and CH4 as a function of C/O ratio. The shaded regions represent the range across pressures from 100–1 bar and temperatures from 800–1000 K, which cover the expected quench levels. The dashed line is the 2σ upper limit of H2O from our retrieval analysis, and the open circle with an error bar represents our retrieved 1σ CH4 abundance.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Self-consistent mini-Neptune models for K2-18 b with an oxygen-depleted atmosphere. The atmospheric conditions and models are the same as the lower panel in Figure 9, but with C/O = 3.25.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Significance of the discrepancy in transit depths between the FIREFLy reduction and the three other independent reductions. On the left three panels, we plot the significance between NIRISS reduction at R ≈ 25 (top), R ≈ 100 (middle), and at the 2 pixel level (bottom). On the right three panels, we plot the significance between NIRSpec reductions at R ≈ 100 (top), R ≈ 200 (middle), and R ≈ 300 (bottom). Using the same color scheme as Figure 2, we plot as blue squares the exoTEDRF reduction and as gray triangles the Eureka! reductions, distinguishing between the two with unfilled downward-pointing (A) and filled upward-pointing (B) triangles. We plot as a black solid line on the right three panels the average deviation between the three, and as gray horizontal lines the 1σ (densely dashed) and 2σ (sparsely dashed) cutoffs. Our reductions are consistent with one another, although the rate of >2σ outliers increases with higher resolution.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: Corner plots corresponding to Figure 15, showing correlations between key atmospheric parameters. Parameters with only an upper or lower limit are marked by a vertical line and arrow at the 95% credible interval. We include 1σ credible regions for CO2 and DMS, even though they are not robustly detected, for comparison with N. Madhusudhan et al. (2023).
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: FIREFLy Spectroscopic light-curve residuals for NRS1.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: FIREFLy Spectroscopic light-curve residuals for NRS2.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: FIREFLy Spectroscopic light-curve fits for NRS2.
Paper: A Comprehensive Reanalysis of K2-18 b’s JWST NIRISS+NIRSpec Transmission Spectrum
Authors: Stephen P. Schmidt, Ryan J. MacDonald, Shang-Min Tsai, Michael Radica, Le-Chris Wang, Eva-Maria Ahrer, Taylor J. Bell, Chloe Fisher, Daniel P. Thorngren, Nicholas Wogan, Erin M. May, Piero Ferrari, Katherine A. Bennett, Zafar Rustamkulov, Mercedes López-Morales, David K. Sing
Figure caption: FIREFLy Spectroscopic light-curve fits for NRS1.
Paper: LAMOST Medium-resolution Spectroscopic Survey of the Rosette Nebula
Authors: Li-Yue Zhang, Chao-Jian Wu, Xuan Fang, Wei Zhang, Juan-Juan Ren, Jian-Jun Chen, Hong Wu
Figure caption: LAMOST medium-resolution spectra of the Rosette Nebula extracted from three different fiber positions, showing the highest data quality with signal-to-noise ratio (S/N)([S II]) > 60 (top panel, representing the majority of the fiber spectra reported in this work), medium data quality with S/N([S II]) ≃ 40 (middle panel), and relatively low data quality with S/N([S II]) ≃ 10. The spectra are all normalized such that the integrated flux F(Hα) = 300 (given that the theoretical intensity ratio H I Hα/Hβ = 2.85, P. J. Storey & D. G. Hummer 1995, combined with Galactic extinction). The vertical ranges of the three panels are set to accommodate the intensity of Hα.
Paper: LAMOST Medium-resolution Spectroscopic Survey of the Rosette Nebula
Authors: Li-Yue Zhang, Chao-Jian Wu, Xuan Fang, Wei Zhang, Juan-Juan Ren, Jian-Jun Chen, Hong Wu
Figure caption: The histograms (panel (a)) and two-dimensional spatial distributions of the RVs (in km s−1) measured with Hα (panel (c)), [N II] (panel (d)) and [S II] (panel (e)). Panel (b) shows the Gaussian-profile fits of the three histograms in panel (a). Panel (f) shows the error of RVs (in km s−1) measured in three regions shown in panel (c). Notably, the value of error in the northeast region is larger than in other parts of the nebula.
Paper: LAMOST Medium-resolution Spectroscopic Survey of the Rosette Nebula
Authors: Li-Yue Zhang, Chao-Jian Wu, Xuan Fang, Wei Zhang, Juan-Juan Ren, Jian-Jun Chen, Hong Wu
Figure caption: The histograms (panel (a)) and two-dimensional spatial distributions of the relative intensities of Hα (panel (b)), [N II] (panel c), and [S II] (panel d). In panel (a), the number peaks of the distributions of the three emission lines are marked by vertical dashed lines, with the same color-coding as the histograms. Note that the color scales for panels b, c, and d are the same.
Paper: LAMOST Medium-resolution Spectroscopic Survey of the Rosette Nebula
Authors: Li-Yue Zhang, Chao-Jian Wu, Xuan Fang, Wei Zhang, Juan-Juan Ren, Jian-Jun Chen, Hong Wu
Figure caption: The histograms (panel (a)) and the two-dimensional spatial distributions of the FWHMs of Hα (panel (b)), [N II] (panel (c)) and [S II] (panel (d)). The color scales for panels (b), (c), and (d) are the same.
Paper: LAMOST Medium-resolution Spectroscopic Survey of the Rosette Nebula
Authors: Li-Yue Zhang, Chao-Jian Wu, Xuan Fang, Wei Zhang, Juan-Juan Ren, Jian-Jun Chen, Hong Wu
Figure caption: The histogram (panel (a)) and the spatial distribution (panel (b)) of the S/N ratio of Hα as measured from the fiber spectra of the Rosette Nebula. Within the optical boundary of the nebula, the S/Ns are mostly >100.
Paper: LAMOST Medium-resolution Spectroscopic Survey of the Rosette Nebula
Authors: Li-Yue Zhang, Chao-Jian Wu, Xuan Fang, Wei Zhang, Juan-Juan Ren, Jian-Jun Chen, Hong Wu
Figure caption: The gas temperatures (top panels) and turbulent velocities (bottom panels) of the Rosette Nebula. Panel (a) and (b) show the histogram and the two-dimensional spatial distribution of gas temperature (in K). Panel (c) and (d) show the histogram and the spatial distribution of turbulent velocity.
Paper: LAMOST Medium-resolution Spectroscopic Survey of the Rosette Nebula
Authors: Li-Yue Zhang, Chao-Jian Wu, Xuan Fang, Wei Zhang, Juan-Juan Ren, Jian-Jun Chen, Hong Wu
Figure caption: The histogram (panel (a)) and two-dimensional spatial distribution (panel (b)) of the kinematic distance (in unit of kpc) measured with the Hα emission line.
Paper: LAMOST Medium-resolution Spectroscopic Survey of the Rosette Nebula
Authors: Li-Yue Zhang, Chao-Jian Wu, Xuan Fang, Wei Zhang, Juan-Juan Ren, Jian-Jun Chen, Hong Wu
Figure caption: The histogram (panel (a)) and the spatial distribution (panel (b)) of 12+﹩\mathrm{log}[{\rm{O}}\,{\rm{III}}]/{\rm{H}}\beta ﹩, which is used as a proxy of chemical abundance.
Paper: The Importance of Standardizing Spectra in the Era of Large Spectroscopic Surveys: A Case Study of M Dwarfs in SDSS-V
Authors: Ilija Medan, Zachary Way, Bárbara Rojas-Ayala, Guy S. Stringfellow, Conor Sayres, Keivan G. Stassun, Andrew R. Casey, Sébastien Lépine, Emma Galligan, Diogo Souto, Andrew K. Saydjari
Figure caption: The sum of the χ2 values ﹩({\sum }_{i}{\chi }_{i}^{2})﹩ between all the BOSS-like spectra and BT-NextGen models for each grid point in Teff and [Fe/H] when the spectra are standardized with our alpha hulling method (left panel). For this sum, we only consider the lower 90th percentile of χ2 values within a grid point. The other three panels show the difference between this sum for the other standardization methods and our method. The color map is set such that red regions are where the standardization performs better with our method, and blue is when it performs better for the other method. Our method generally performs better for large regions of parameter space. Both GISIC and the constant standardization performs better for the lowest-temperature, metal-poor stars, and the polynomial standardization is slightly preferred for high-temperature stars and some lower-temperature, metal-rich stars.
Paper: The Importance of Standardizing Spectra in the Era of Large Spectroscopic Surveys: A Case Study of M Dwarfs in SDSS-V
Authors: Ilija Medan, Zachary Way, Bárbara Rojas-Ayala, Guy S. Stringfellow, Conor Sayres, Keivan G. Stassun, Andrew R. Casey, Sébastien Lépine, Emma Galligan, Diogo Souto, Andrew K. Saydjari
Figure caption: H-R diagram of BOSS spectra from SDSS-V, where each grid point shows the maximum distance (in number of grid points) where ﹩{\chi }_{\nu }^{2}\lt {\rm{\min }}({\chi }_{\nu }^{2})+1﹩. Here, for each grid point ﹩{\chi }_{\nu }^{2}﹩ is calculated between all standardized spectra in that grid point and then for each median, standardized spectrum in all other grid points. This allows for the visualization of the 1σ level variance in regions across the H-R diagram. For bins where the distance between the H-R diagram bin for the spectra and the bin of the ﹩{\rm{\min }}({\chi }_{\nu }^{2})﹩ is greater than the maximum distance where ﹩{\chi }_{\nu }^{2}\lt {\rm{\min }}({\chi }_{\nu }^{2})+1﹩, the bin is grayed out as the solution is not statistically significant. The different panels in the above show this variance level for the different standardization methods. The far-right column of plots then shows the difference in the variance level between the other methods and our method. For these plots, the color bar indicates that the variance is smaller with our method when red. In all the above plots, only BOSS spectra within 100 pc, with an SNR > 5 and determined to be true single stars by Z. Way et al. (2025, in preparation) were included in the above. Additionally, only grid points with >5 spectra are shown. All spectra were reduced using v6_2_0 of the BOSS pipeline and include data up until MJD = 60715.
Paper: The Importance of Standardizing Spectra in the Era of Large Spectroscopic Surveys: A Case Study of M Dwarfs in SDSS-V
Authors: Ilija Medan, Zachary Way, Bárbara Rojas-Ayala, Guy S. Stringfellow, Conor Sayres, Keivan G. Stassun, Andrew R. Casey, Sébastien Lépine, Emma Galligan, Diogo Souto, Andrew K. Saydjari
Figure caption: The mean (top row) and standard deviation (bottom row) from a fit of a truncated normal distribution to the difference between the true and best-fit parameters from our grid search when BOSS-like spectra and BT-NextGen models are standardized using the various methods. This demonstrates the level of bias (top row) and scatter (bottom row) for each method, where we find that our alpha hulling method generally outperforms or produces similar results as the alternative methods.
Paper: The Importance of Standardizing Spectra in the Era of Large Spectroscopic Surveys: A Case Study of M Dwarfs in SDSS-V
Authors: Ilija Medan, Zachary Way, Bárbara Rojas-Ayala, Guy S. Stringfellow, Conor Sayres, Keivan G. Stassun, Andrew R. Casey, Sébastien Lépine, Emma Galligan, Diogo Souto, Andrew K. Saydjari
Figure caption: Results of the grid search for the hyperparameters α (inverse of the size of the alpha hull), radius (size of the kernel used for smoothing in local polynomial regression), and aspect ratio (spectrum is normalized with the aspect ratio of the flux to wavelength). The grid search was first run over the full bounds of the parameters (Table 1) in a course selection of 2500 randomly selected points. With these hyperparameters, we then standardized all BT-NextGen models and BOSS-like spectra, and calculated the χ2 and L1 norm for each spectrum normalized with those parameters. After this, we selected the course grid points that were either in the minimum 5% of ﹩{\sum }_{i}{\chi }_{i}^{2}﹩ or ∑iL1,i values, and resampled between all of these adjacent grid points for another 2500 parameters, and evaluated the χ2 and L1 for each BOSS-like spectrum at these points. The corner plots show the resulting ﹩{\sum }_{i}{\chi }_{i}^{2}/{N}_{\mathrm{spectra}}﹩ (left) and ∑iL1,i (right) evaluations, where it should be noted the color bar cuts off at 40% of the values. The red cross shows the global minimum in each case.