adsabs/AstroCLIMB huggingface dataset:
Paper: Identification of Outer Galaxy Cluster Members Using Gaia DR3 and Multidimensional Simulation
Authors: Vishwas Patel, Joseph L. Hora, Matthew L. N. Ashby, Sarita Vig
Figure caption: Sampling distances to simulate a cluster with a King profile. As an example, Cluster 257 is simulated here; tidal radius, rt ≈ 43 pc, concentration parameter, ξc = 0.579, and Φmem = 0.58, which corresponds to 452 cluster members out of 779 YSOs in the circular R.A.–decl. analysis region.
Paper: Identification of Outer Galaxy Cluster Members Using Gaia DR3 and Multidimensional Simulation
Authors: Vishwas Patel, Joseph L. Hora, Matthew L. N. Ashby, Sarita Vig
Figure caption: Proper motion vector plot of the Cluster 257 (W4/W5 complex), comparing observed and simulated cluster members. The color scale represents the number density of observed cluster members (depicted as squares) identified after applying the simulation-predicted Monte Carlo threshold (﹩{ \mathcal M }{{ \mathcal C }}_{{\rm{thr}}}﹩). Observed field YSOs are marked by cyan circles. The inset highlights the simulated cluster members for clarity. Gray error bars, displayed with reduced opacity, indicate proper motion uncertainties. This figure illustrates the comparison between the proper motions of simulated and observed cluster members in the W4/W5 region.
Paper: Identification of Outer Galaxy Cluster Members Using Gaia DR3 and Multidimensional Simulation
Authors: Vishwas Patel, Joseph L. Hora, Matthew L. N. Ashby, Sarita Vig
Figure caption: Distance sampling from the Inverse Weibull distribution for Monte Carlo simulation. The blue line represents the inverse Weibull distribution derived from the 16th, 50th, and 84th distance percentiles, indicated by the green, purple, and black dashed lines, respectively. These distance percentiles correspond to the source SRC15311. The faded red histogram illustrates 105 sampled distances, showing that they closely follow the parent distribution.
Paper: Improving Harmonic Analysis Using Multitapering: Precise Frequency Estimation of Stellar Oscillations Using the Harmonic F-test
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 沈佳士, David J. Thomson
Figure caption: Schematic diagram showing the detection of strictly periodic signals in Kepler-91 time series using the multitaper F-test. First, we show the mtNUFFT periodogram with NW = 4 and K = 7 (top left) and its corresponding F-statistic estimates (top middle). Then, we test the p-values of the F-test for significance (top right shows an example α = 0.05 level). Since we are testing multiple hypotheses, we perform selective inference by comparing the sorted p-values with the threshold curves of the Bonferroni and Benjamini–Hochberg (BHq) procedures (bottom right). The inset in the bottom-right panel zooms in to the smallest p-values and shows that BHq rejects more hypotheses than Bonferroni. Finally, we plot the detected periodic signals along with the F-statistic estimates and the mtNUFFT periodogram (bottom middle and left). It is interesting to note that three BHq-detected signals coincide with harmonic features that we expect to see due to the known transiting exoplanet Kepler-91b (N. M. Batalha et al. 2013).
Paper: Improving Harmonic Analysis Using Multitapering: Precise Frequency Estimation of Stellar Oscillations Using the Harmonic F-test
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 沈佳士, David J. Thomson
Figure caption: Schematic diagram demonstrating that the F-test frequency estimate ﹩{\hat{f}}_{p}﹩ corresponding to the Kepler-91b transit harmonic fp ≈ 2/6.25 is strictly periodic. The top panel shows how we divide the Kepler-91 time series into three chunks for studying the time evolution of ﹩{\hat{f}}_{p}﹩. The middle panel shows the three corresponding mtNUFFT periodograms (blue), and their respective periodic signal detections using the BHq procedure with α = 0.15 for the F-test (red dashed lines). The bottom panel zooms in to the ﹩{\hat{f}}_{p}﹩ estimates of the three chunks (red bars), with frequency on the y-axis and chunk length (T) in days on the x-axis. The estimates are compared with fp using the 2 standard deviation jackknife uncertainties (black error bars) and the Rayleigh resolution 1/T (pink) of the chunks. Both comparisons show that the estimates are consistent with fp and their uncertainties are a fraction of the Rayleigh resolution.
Paper: Improving Harmonic Analysis Using Multitapering: Precise Frequency Estimation of Stellar Oscillations Using the Harmonic F-test
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 沈佳士, David J. Thomson
Figure caption: Zoomed-in profiles of the F-test detections that show the rectangular multitaper shape (top and bottom panels) as opposed to the broader Lorentzian (e.g., l = 0, 2 p-modes in the middle panel). The bottom panel displays a section of the middle panel. mtNUFFT is plotted in blue (left axis is PSD), whereas the F-statistic is plotted in pink (right axis). Two of the F-test detections obtained using the BHq procedure (see Figure 3) coincide exactly with an exoplanet (Kepler-91b) harmonic and an l = 1 mixed mode. Also, the F-statistic corresponding to the mixed mode at 101.929 μHz has a fairly large value. The Kepler-91b period estimate and Kepler-91 mode estimates are from N. M. Batalha et al. (2013) and J. Lillo-Box et al. (2014), respectively.
Paper: Improving Harmonic Analysis Using Multitapering: Precise Frequency Estimation of Stellar Oscillations Using the Harmonic F-test
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 沈佳士, David J. Thomson
Figure caption: Comparison between sinusoidal, strictly periodic (top panel) and transient oscillations (bottom panel). The left and right panels show time and Fourier domains, respectively. In Fourier space, the strictly periodic or harmonic oscillation (e.g., coherent mode) is seen as a peak at the frequency of the oscillation, and the transient damped harmonic oscillations (e.g., p-modes) have Lorentzian frequency peaks with widths representing damping rates.
Paper: Improving Harmonic Analysis Using Multitapering: Precise Frequency Estimation of Stellar Oscillations Using the Harmonic F-test
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 沈佳士, David J. Thomson
Figure caption: The effect of windowing a sinusoidal signal. The left panels show that using a finite-length time series is equivalent to multiplying an infinite-length time series with a rectangular window. The right panels show that in the Fourier domain, windowing results in a sinc function instead of a delta function at the frequency of the signal. Essentially, multiplication in the time domain is convolution in the Fourier domain, and so the delta function is convolved with the window transform (sinc function).
Paper: The Initial Mass Function of Stars and Brown Dwarfs in the Upper Sco Association 
Authors: K. L. Luhman
Figure caption: Mass vs. spectral type for young stars with measurements of dynamical masses (Section 5.4). I have included a fit to these data (Table 4) and the relations predicted by evolutionary models for masses of 0.01–1.4 M⊙ at ages of 7, 10, and 14 Myr (I. Baraffe et al. 2015).
Paper: The Initial Mass Function of Stars and Brown Dwarfs in the Upper Sco Association 
Authors: K. L. Luhman
Figure caption: IMFs for Upper Sco, Taurus, IC 348, Chamaeleon I, and the solar neighborhood. The normalization for the latter is arbitrary. The completeness limits for the first four IMFs are near 0.01 M⊙.
Paper: The Initial Mass Function of Stars and Brown Dwarfs in the Upper Sco Association 
Authors: K. L. Luhman
Figure caption: Near-IR color–magnitude diagram for members of Upper Sco that have spectral classifications and that are located within the triangular field from K. L. Luhman & T. L. Esplin (2020), which encompasses the central concentration in the association (red and blue points; see Table 3). I also include the sources in that field that are not rejected by available membership constraints (crosses). Most of the latter sources have few bands of photometry available and are likely to be background stars and galaxies.
Paper: The Initial Mass Function of Stars and Brown Dwarfs in the Upper Sco Association 
Authors: K. L. Luhman
Figure caption: W1−W2 vs. spectral type for late-type members of Upper Sco. At <L0, the sequence of photospheric colors is well defined, and the indicated threshold is used for identifying redder sources that have color excesses (Table 5). At later types, the photospheric sequence is not well defined, and only one member shows a significant excess.
Paper: The Initial Mass Function of Stars and Brown Dwarfs in the Upper Sco Association 
Authors: K. L. Luhman
Figure caption: Proper motion offsets vs. parallactic distance based on Gaia DR3 for members of Upper Sco and Ophiuchus from K. L. Luhman (2022a, top) and candidate members from N. Miret-Roig et al. (2022a) that are rejected by the criteria in K. L. Luhman (2022a, bottom).
Paper: The MaNGA Dwarf Galaxy Sample (MaNDala): Stellar Profiles and Gradients Characterization
Authors: M. Cano-Díaz, A. Rodríguez-Puebla, A. C. Robleto-Orús, V. Ávila-Reese, H. M. Hernández-Toledo, J. A. Vázquez-Mata, O. Valenzuela, J. J. González, H. J. Ibarra-Medel, J. C. Clemente-González, L. Pavón-Alvarez
Figure caption: Two profiles for the galaxy manga-7815-6101 are shown to compare the two collapsed methods for the profiles, as well as their gradients derivation. The black circles in all panels represent the individual data from each pixel in their respective maps. The top-left panel shows the case of the median collapsed profile, in both of its plots; the green squares represent the collapsed profile, with its associated error bars, which correspond to 2σ, while the light-blue lines show the linear fits performed to these collapsed profiles in the two chosen radial ranges (0–1 Re and 0.75–1.5 Re). In the next panel to its right, we show the same as in the previous panels but for the collapsed integrated method. In the first bottom-left panel, we show the result of the nonlinear spline interpolation by the green solid line, while the resulting linear fits are shown with the light-blue lines. Similarly, in the next panel, we show with green line the posterior probability distribution of the nonlinear GPR fit; the green shadow corresponds to its 95% confidence interval, while the light-blue lines also show the linear fits in the inner and outer regions. The red solid lines in all of these panels represent the generalized fit performed over the previously introduced collapsed and nonlinear profiles. In the right panels (both top and bottom), we show comparisons of the inner and outer gradients for this galaxy (located at the medium point of their measured radial range), color and shape coded by the method used to obtain them: using solid lines, we show the results for (i) the differences between two points gradients, which were performed using the exponential fit over the collapsed or nonlinear profiles (dark blue and magenta), (ii) the differences between two point gradients obtained directly over the collapsed and nonlinear profiles (purple and light pink). Similarly, using dashed lines, we show the results for (iii) the gradients obtained performing the derivative of the exponential fits performed over the collapsed and nonlinear profiles (dark blue and magenta), and (iv) those obtained performing linear fits over the collapsed and nonlinear profiles (purple and light pink).
Paper: The MaNGA Dwarf Galaxy Sample (MaNDala): Stellar Profiles and Gradients Characterization
Authors: M. Cano-Díaz, A. Rodríguez-Puebla, A. C. Robleto-Orús, V. Ávila-Reese, H. M. Hernández-Toledo, J. A. Vázquez-Mata, O. Valenzuela, J. J. González, H. J. Ibarra-Medel, J. C. Clemente-González, L. Pavón-Alvarez
Figure caption: From left to right: the profiles of two properties, as examples, for the entire MaNDala working sample derived with the collapsed median, collapsed integrated, nonlinear spline and nonlinear GPR methods, are shown in gray lines. On top, with blue squares, the median profiles for each method are shown, made from bins of equal size of 0.2 Re, where the error bars represent 1σ of the distribution within each bin.
Paper: The MaNGA Dwarf Galaxy Sample (MaNDala): Stellar Profiles and Gradients Characterization
Authors: M. Cano-Díaz, A. Rodríguez-Puebla, A. C. Robleto-Orús, V. Ávila-Reese, H. M. Hernández-Toledo, J. A. Vázquez-Mata, O. Valenzuela, J. J. González, H. J. Ibarra-Medel, J. C. Clemente-González, L. Pavón-Alvarez
Figure caption: An illustration that shows the main points behind the four different methodologies to derive the radial profiles presented in Section 3. We use, as an example, the galaxy manga-7815-6101, for which we present its ZLW map. On the left, the strategies used to implement the collapsed methods are shown, while on the right, the same is visible but for the nonlinear methods.
Paper: AstroM3: A Self-supervised Multimodal Model for Astronomy
Authors: M. Rizhko, J. S. Bloom
Figure caption: Examples of in-class outliers flagged by the model due to distinctive features, despite correct labels. (a) EA-type star, V1174 Ori, an X-ray bright pre-main-sequence system (K. G. Stassun et al. 2022). (b) EB-type star with unusual out-of-eclipse modulations, possibly due to rotation. (c) Semidetached binary with emission lines. (d) Likely an EB misclassified as EA, with light curve patterns indicating rotation or pulsation.
Paper: AstroM3: A Self-supervised Multimodal Model for Astronomy
Authors: M. Rizhko, J. S. Bloom
Figure caption: Overview of the multimodal CLIP framework adapted for astronomy, incorporating three data modalities: photometric time-series, spectra, and metadata. Each modality is processed by a dedicated encoder to create embeddings, which are then mapped into a shared embedding space through projection heads. Pairwise similarity matrices align the embeddings across modalities, and a symmetric cross-entropy loss, computed over these matrices, optimizes the model. The total loss, derived from all pairwise losses, guides the model’s trimodal learning.
Paper: AstroM3: A Self-supervised Multimodal Model for Astronomy
Authors: M. Rizhko, J. S. Bloom
Figure caption: Examples of cross-modality contrast and similarity searches. The middle row represents the query object. We use its photometry and spectrum to find another object (top row) with the most similar photometry and the most dissimilar spectrum. For the bottom row, we use the query object’s photometry to find the closest matching spectrum in the dataset, illustrating how a single modality can retrieve a similar object in a different modality. Green arrows indicate high similarity, while red arrows indicate low similarity.
Paper: AstroM3: A Self-supervised Multimodal Model for Astronomy
Authors: M. Rizhko, J. S. Bloom
Figure caption: Examples of catalog misclassifications with photometry and spectrum for each object. Top to bottom: (1) likely EW misclassified as HADS; (2) V* AC CMi, a known semidetached binary misclassified as RR Lyrae; (3) possible SR or Mira variable with period alignment issues; (4) known Mira variable (V0439 Cas) misclassified as SR; (5) likely EW binary (N. Mowlavi et al. 2023) misclassified as RRC.
Paper: AstroM3: A Self-supervised Multimodal Model for Astronomy
Authors: M. Rizhko, J. S. Bloom
Figure caption: UMAP visualizations of multimodal embeddings: (a) training set and (b) test set, showing class separability and alignment between sets. Each source in the training and test set are colored by the class determined in (T. Jayasinghe et al. 2019) but these class labels are not used in the construction of the embeddings.
Paper: AstroM3: A Self-supervised Multimodal Model for Astronomy
Authors: M. Rizhko, J. S. Bloom
Figure caption: Projections of new, previously unused classes in the embedding space, aligning with related clusters and demonstrating the model’s ability to position unseen classes accurately.
Paper: AstroM3: A Self-supervised Multimodal Model for Astronomy
Authors: M. Rizhko, J. S. Bloom
Figure caption: Spectral examples of Mira variables, showing two distinct clusters corresponding to M-type and C-type Miras, “rediscovered” through unsupervised learning.
Paper: AstroM3: A Self-supervised Multimodal Model for Astronomy
Authors: M. Rizhko, J. S. Bloom
Figure caption: Color–magnitude diagram for ROT variables, with two clusters identified through unsupervised learning as giants and dwarfs.
Paper: AstroM3: A Self-supervised Multimodal Model for Astronomy
Authors: M. Rizhko, J. S. Bloom
Figure caption: The query spectrum (top) and its two closest matches (middle and bottom) based on spectral cosine similarity.
Paper: Interior and Climate Modeling of the Venus Zone Planet TOI-2285 b
Authors: Emma L. Miles, Colby Ostberg, Stephen R. Kane, Ondrea Clarkson, Cayman T. Unterborn, Tara Fetherolf, Michael J. Way, Sadie G. Welter
Figure caption: Plot of mass–radius relationship of TOI-2285 b with data points from Figure 2. Color represents the number of Earth's oceans present as steam within the atmosphere. Dashed lines outline the nominally rocky zone of C. T. Unterborn et al. (2023), which represents the range of densities for exoplanets without significant surface volatile levels consistent with the distribution of stellar abundances.
Paper: Interior and Climate Modeling of the Venus Zone Planet TOI-2285 b
Authors: Emma L. Miles, Colby Ostberg, Stephen R. Kane, Ondrea Clarkson, Cayman T. Unterborn, Tara Fetherolf, Michael J. Way, Sadie G. Welter
Figure caption: The ROCKE-3D GCM simulation outputs. Six climate scenarios were generated using Venus, aquaplanet, and Earth topographies with varying amounts of surface water. Here, we have plotted the surface temperature and the surface water fraction. The semiopaque white hatched regions in the bottom row indicate regions with at least partial ice coverage.
Paper: Interior and Climate Modeling of the Venus Zone Planet TOI-2285 b
Authors: Emma L. Miles, Colby Ostberg, Stephen R. Kane, Ondrea Clarkson, Cayman T. Unterborn, Tara Fetherolf, Michael J. Way, Sadie G. Welter
Figure caption: The GlobES modeled emission spectra of the six TOI-2285 b simulations, and a single spectrum of TOI-2285 b with no atmosphere and a Teq of 310 K (black line). The Venus Arid emission spectrum is the only one that has CO2 features around 10 μm. The emission spectra of all cases are easily distinguished from the no-atmosphere spectrum.
Paper: Interior and Climate Modeling of the Venus Zone Planet TOI-2285 b
Authors: Emma L. Miles, Colby Ostberg, Stephen R. Kane, Ondrea Clarkson, Cayman T. Unterborn, Tara Fetherolf, Michael J. Way, Sadie G. Welter
Figure caption: The GlobES modeled transmission spectra of each TOI-2285 b simulation using their final stable state atmospheres. For this model, TOI-2285 b is hypothetically observed by JWST NIRSpec PRISM. Each feature is labeled with its corresponding molecules.
Paper: Interior and Climate Modeling of the Venus Zone Planet TOI-2285 b
Authors: Emma L. Miles, Colby Ostberg, Stephen R. Kane, Ondrea Clarkson, Cayman T. Unterborn, Tara Fetherolf, Michael J. Way, Sadie G. Welter
Figure caption: Relationship between effective atmospheric temperature (assuming an ideal gas) and the number of oceans on the planet. The average number of oceans worth of steam in the atmosphere in the water-rich population was calculated to be 5260 Earth Oceans. In this plot, this equates to an atmospheric temperature of ∼3000 K. The average number of oceans worth of steam in the atmosphere in the extended water-poor population (<1000 Earth oceans) was calculated to be 241 Earth oceans (see Figure 2). In this plot, this equates to an atmospheric temperature of ∼1000 K.
Paper: Interior and Climate Modeling of the Venus Zone Planet TOI-2285 b
Authors: Emma L. Miles, Colby Ostberg, Stephen R. Kane, Ondrea Clarkson, Cayman T. Unterborn, Tara Fetherolf, Michael J. Way, Sadie G. Welter
Figure caption: Simulated JWST NIRSpec PRISM data using PandExo for the Earth 310 m TOI-2285 b scenario. The JWST data assumed 20 transit observations and was binned down to a resolving power of R = 12 for easier visibility.
Paper: Photometric Analysis of Asteroids in the Phocaea Region
Authors: Xiaoyun Xu, Xiaobing Wang, Karri Muinonen, Shenghong Gu, Antti Penttilä, Fukun Xu, Leilei Sun, Jing Huang, Pengfei Zhang, Ao Wang
Figure caption: Example light curves of four example asteroids, where K is the number of Gaia photometric data points.
Paper: Photometric Analysis of Asteroids in the Phocaea Region
Authors: Xiaoyun Xu, Xiaobing Wang, Karri Muinonen, Shenghong Gu, Antti Penttilä, Fukun Xu, Leilei Sun, Jing Huang, Pengfei Zhang, Ao Wang
Figure caption: The convex shapes of 44 asteroids in the Phocaea region.
Paper: Improving Harmonic Analysis Using Multitapering: Precise Frequency Estimation of Stellar Oscillations Using the Harmonic F-test
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 沈佳士, David J. Thomson
Figure caption: Detection of strictly periodic signals corresponding to two consecutive p-modes, νn=9, l=2 = 104.557 μHz and νn=10, l=0 = 105.792 μHz (Table 5 in J. Lillo-Box et al. 2014). The red bars indicate the ﹩{\hat{\nu }}_{n,l}﹩ detections across seven time chunks, with roughly continuous and even sampling. The x-axis shows the lengths of these chunks (T) in days. The y-axis represents the frequency, and helps compare the ﹩{\hat{\nu }}_{n,l}﹩ estimates (red bars) and their jackknife uncertainties (black error bars) with the mode frequencies νn,l and peak widths (J. Lillo-Box et al. 2014). The y-axis here is a broken axis, i.e., a portion of the axis is cut out to zoom in to the two mode frequencies. The Rayleigh resolution of each chunk is also shown in pink. We see that νn=9, l=2 is detected in chunks 1, 2, and 7, whereas νn=10, l=0 is detected in chunks 3, 4, 5, and 6. The frequency shifts and short-lived detections of modes is reminiscent of damped, short-lifetime p-modes.
Paper: The Initial Mass Function of Stars and Brown Dwarfs in the Upper Sco Association 
Authors: K. L. Luhman
Figure caption: Near-IR color–magnitude and color–color diagrams for adopted members of Upper Sco (Table 3; blue and red points) and the brown dwarf candidates observed spectroscopically in this work (circles). Six candidates lack J measurements, so they are absent from the diagram on the right. Two candidates were found to be nonmembers based on the spectroscopy. The planetary mass companion TWA 27B is included for a distance of 145 pc (cross, K. L. Luhman et al. 2023).
Paper: The Initial Mass Function of Stars and Brown Dwarfs in the Upper Sco Association 
Authors: K. L. Luhman
Figure caption: Near-IR spectra of brown dwarf candidates in Upper Sco. The Gemini data have been binned to the resolution of the SpeX data.
Paper: The Initial Mass Function of Stars and Brown Dwarfs in the Upper Sco Association 
Authors: K. L. Luhman
Figure caption: Near-IR spectra of brown dwarf candidates in Upper Sco. The Gemini data have been binned to the resolution of the SpeX data.(The data used to create this figure are available in the online article.)(The data used to create this figure are available.)
Paper: The MaNGA Dwarf Galaxy Sample (MaNDala): Stellar Profiles and Gradients Characterization
Authors: M. Cano-Díaz, A. Rodríguez-Puebla, A. C. Robleto-Orús, V. Ávila-Reese, H. M. Hernández-Toledo, J. A. Vázquez-Mata, O. Valenzuela, J. J. González, H. J. Ibarra-Medel, J. C. Clemente-González, L. Pavón-Alvarez
Figure caption: ∇G vs. M*. Here, we intend to compare the inner gradients of six galaxy properties G for the MaNDala sample, with the gradients available in the literature for samples of galaxies that are predominantly massive. Over the MaNDala sample, a magenta point shows the median values of Log(M*) and of the gradient property being plotted. The error bar corresponds to 1σ for each property. In the case of the Log(Σ*) panel, an equivalent point in cyan is shown for the outer gradients to make a better comparison with the outer gradients reported by E. Wang et al. (2019).