adsabs/AstroCLIMB huggingface dataset:
Paper: Different Planetary Eccentricity-period (PEP) Distributions of Small and Giant Planets
Authors: Dolev Bashi, Tsevi Mazeh, Simchon Faigler
Figure caption: Minimum-mass histogram (blue bins) of all planets with RV orbits, eccentric and circular alike. Dashed curves represent our best Gaussian mixture model of the small- and giant-planet samples. The mean and standard deviation of the small planets (in log M J) are −1.53 (=9.4M ⊕) and 0.40, and 0.00 (=1M J) and 0.43 for the giant planets. The red dotted line marks the intersecting point between the two Gaussians at M p = 0.165M J. Overlaid, using gray bins, is the distribution of the transiting planets in our sample.
Paper: Different Planetary Eccentricity-period (PEP) Distributions of Small and Giant Planets
Authors: Dolev Bashi, Tsevi Mazeh, Simchon Faigler
Figure caption: Color–magnitude-diagram (CMD) of all planet-hosting stars with eccentric orbits in our sample. Left: low-mass planets. Right: high-mass planets. Background grayscale sample is added for reference, using the GCNS. Red polygons in both panels mark our selected sample of planet-host stars with similar stellar characteristics. See text for further description.
Paper: Probe the Regolith Characteristics of Asteroids from 9 yr Infrared Observations of WISE/NEOWISE: A Case Study of The Main-belt Object (656) Beagle
Authors: Liang-Liang Yu, 亮亮 余
Figure caption: The lightcurve inversion shape model of (656) Beagle from the DAMIT database. ph represents rotational phase defined as ph = 1 − φ/(2π), in which φ is the local longitude of the observer in the body-fixed coordinate system.
Paper: Probe the Regolith Characteristics of Asteroids from 9 yr Infrared Observations of WISE/NEOWISE: A Case Study of The Main-belt Object (656) Beagle
Authors: Liang-Liang Yu, 亮亮 余
Figure caption: Left panel: seasonal variation of the diurnal-averaged surface temperature as a function of local latitude. Right panel: seasonal average temperature of each local latitude. The so-called local latitude is defined as the complementary angle of the angle between the local normal vector and the rotation axis.
Paper: Probe the Regolith Characteristics of Asteroids from 9 yr Infrared Observations of WISE/NEOWISE: A Case Study of The Main-belt Object (656) Beagle
Authors: Liang-Liang Yu, 亮亮 余
Figure caption: The contour of ﹩{\chi }_{{\rm{r}}}^{2}({\theta }_{\mathrm{RMS}},b)﹩, which is obtained by fitting the observations with two free parameters: the roughness rms slope θ RMS and the mean grain radius b. The blue region stands for the 1σ level constraint, and the red region represents the 3σ level constraint.
Paper: Probe the Regolith Characteristics of Asteroids from 9 yr Infrared Observations of WISE/NEOWISE: A Case Study of The Main-belt Object (656) Beagle
Authors: Liang-Liang Yu, 亮亮 余
Figure caption: The observation/model ratios as a function of wavelength (upper panel) and solar phase angle (under panel) for the case of best-fit parameters. Panel (A; left): best-fit model results are obtained by using constant input thermal emissivity ϵ ≈ 0.9; Panel (B; right): using wavelength-dependent thermal emissivity ϵ ≈ 0.72, 0.72, 0.72, and 0.95 for the W1, W2, W3, and W4 band, respectively.
Paper: Probe the Regolith Characteristics of Asteroids from 9 yr Infrared Observations of WISE/NEOWISE: A Case Study of The Main-belt Object (656) Beagle
Authors: Liang-Liang Yu, 亮亮 余
Figure caption: The fraction of sunlight reflection in the observed flux of Beagle for each band of WISE/NEOWISE.
Paper: Probe the Regolith Characteristics of Asteroids from 9 yr Infrared Observations of WISE/NEOWISE: A Case Study of The Main-belt Object (656) Beagle
Authors: Liang-Liang Yu, 亮亮 余
Figure caption:                       ﹩{p}_{{\rm{v}}}\sim {\chi }_{{\rm{r}}}^{2}﹩ profiles fit to the observations in consideration of the derived 1σ and 3σ ranges of roughness and mean grain radius.
Paper: Probe the Regolith Characteristics of Asteroids from 9 yr Infrared Observations of WISE/NEOWISE: A Case Study of The Main-belt Object (656) Beagle
Authors: Liang-Liang Yu, 亮亮 余
Figure caption: Ratios of observation/model as a function of rotation phase for each band.
Paper: Probe the Regolith Characteristics of Asteroids from 9 yr Infrared Observations of WISE/NEOWISE: A Case Study of The Main-belt Object (656) Beagle
Authors: Liang-Liang Yu, 亮亮 余
Figure caption: The regolith specific heat capacity c p, thermal conductivity κ, and thermal inertia Γ of Beagle in consideration of seasonal temperature variation and 3σ level range of mean grain radius b. ﹩{\rm{\Gamma }}=\sqrt{(1-\phi ){\rho }_{{\rm{g}}}{c}_{{\rm{p}}}\kappa }﹩, and porosity ϕ ∼ 0.5, regolith grain density ρ g = 3110 kg m−3.
Paper: Probe the Regolith Characteristics of Asteroids from 9 yr Infrared Observations of WISE/NEOWISE: A Case Study of The Main-belt Object (656) Beagle
Authors: Liang-Liang Yu, 亮亮 余
Figure caption: Best-fit results to the infrared lightcurves of WISE/NEOWISE for each observation epoch. Panels (A), (B), and (C): thermal lightcurves at band W4, W3, and W2, respectively. Panel (D): reflection lightcurves at band W1.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: Illustration of Gibbs oscillations due to the aliasing of high frequencies in the frequency domain allowed by the pixel size. Top: from left to right, a noise-free point source is perfectly centered on a pixel and is deconvolved with a PSF that has the same FWHM. Here, we use direct Fourier division to do the deconvolution, as there is no noise involved. The deconvolved point source is a delta function also perfectly centered on a pixel. All frequencies, even infinite, are well represented regardless of the pixel size, i.e., no artifacts appear. Middle: the exact same experiment, but now the signal is off-centered by 0.1 pixels with respect to the center of a pixel. High frequencies are not well represented and Gibbs oscillations do appear. Note also that (i) the mean flux level is now wrong; and (ii) the impact of the Gibbs oscillations depends on where a given star in the data falls with respect to the pixels, with the worst effect corresponding to stars appearing exactly between two pixels. Bottom: the same as in the middle row, but now the PSF used to deconvolve is narrower than the data, hence the deconvolved image does not contain infinitely high frequencies that are impossible to sample. The deconvolved point source has a finite resolution and does not present Gibbs oscillations.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: Upper panel: STARRED’s deconvolution runtime on an NVIDIA RTX 3060 GPU for the deconvolution of 32 × 32 input images (64 × 64 deconvolved images) as a function of the number of epochs. The full optimization runtime for 200 iterations of adabelief is shown in blue (in seconds), whereas the time needed for a single evaluation of the loss and its gradient is shown in orange (in milliseconds). Lower panel: STARRED deconvolution runtime for 10 epochs as a function of the output image size. These plots can be reproduced from this notebook ✎.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: PSF reconstruction of the TinyTim PSF from six simulated stars with STARRED, PSFR, and PHOTUTILS (top row). The PSF is reconstructed with a pixel size three times smaller than that of the original data. The bottom row shows the difference between the reconstructed PSFs and the ground truth. This figure can be reproduced from this notebook ✎.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: Multi-epoch deconvolution of a galaxy hosting an SN Ia. From top to bottom and from left to right, the different panels show a single-epoch image, the model produced by STARRED at the original resolution, the residuals for one epoch, the reconstructed narrow PSF  s , the deconvolved model, and the reference HST image of the host galaxy. In the lower right panel, we indicate the four different locations chosen for the SN Ia explosion. This example corresponds to the fourth location, i.e., 2″ from the center of the host galaxy. Note that the deconvolved model of the extended channel benefits from the SNR of the whole data set.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: Weight matrix  W  used in the regularization term of Equation (6). It is computed in a Monte Carlo procedure by generating 5000 random noise realizations, propagating it into the starlet space, and measuring the variance of each starlet scale. In the last panel, we show our reconstructed model of the JWST/Nircam PSF in the F200W band at a sampling of 0.″013 per pixel. The PSF has been reconstructed from four stars located near the Sparkler galaxy in the field of view of the galaxy cluster SMACS J0723.3-732. This figure can be reproduced from this notebook ✎.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: Astrometric precision (first panel), photometric precision (second panel), photometric accuracy (third panel), and PSF reconstruction fidelity (fourth panel) as a function of the SNR of the stars used to reconstruct the PSF. The dotted, dashed–dotted, and solid lines, respectively, indicate that the PSF is reconstructed at the same, at twice, or at three times the original pixel size. STARRED’s performance (in blue) is compared to that of other empirical PSF reconstruction codes, such as PSFR (in orange) and PHOTUTILS (in green). The PHOTUTILS algorithm failed to converge at an SNR below 100 and the reconstructed PSF models were not sufficiently accurate to extract meaningful PSF photometry, which is why these results are not included in this figure.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: SEDs of the compact objects labeled in Figure 9 in the observer frame. The point-source photometry is measured from the deconvolved images. The dotted lines correspond to the SEDs measured in Mowla et al. (2022) using aperture photometry. Note that point sources #13–#18 were not measured previously. Some of them have SEDs compatible with those of globular clusters, such as the ones in Mowla et al. (2022). In addition, the aperture photometry of point sources exhibiting the closest alignment with the underlying arc is clearly biased compared to STARRED.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: SN Ia light curve extracted with STARRED using the deconvolved model shown in Figure 5 and with DIA + aperture photometry. The bottom panel displays the residuals compared to the true light-curve input in the simulation. For the sake of clarity, the 30 observation epochs prior to the SN Ia explosion are not shown in this plot.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: Left panel: JWST/Nircam color composite (R: F200W; G: F150W; B: F090W) image of the “Sparkler,” a strongly lensed galaxy by the galaxy cluster SMACS J0723.3-7327 (R.A. = 7:23:21.8, decl. = −73:27:18.7). The pixel size is 0.″04 per pixel. Middle panel: STARRED deconvolved model. The pixel size is two times smaller than the original image, i.e., 0.″02 per pixel. Right panel: location and ID number of the “sparkles,” modeled as point sources.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: Multi-epoch deconvolution of a quadruply imaged quasar for different Einstein radii θ  E . From left to right, the panels show single-epoch simulated LSST images, the deconvolved models reconstructed from all 100 images, and the truth images at the same resolution as the deconvolved image and the PSF.
Paper: Image Deconvolution and Point-spread Function Reconstruction with STARRED: A Wavelet-based Two-channel Method Optimized for Light-curve Extraction
Authors: Martin Millon, Kevin Michalewicz, Frédéric Dux, Frédéric Courbin, Philip J. Marshall
Figure caption: Lensed quasar light curves extracted with STARRED using the deconvolved model shown in the second row of Figure 7 (θ  E  = 1″). Aperture photometry obtained after annulus background subtraction is shown with triangles. The bottom panels show the residuals from each lensed image.
Paper: A Volume-limited Radio Search for Magnetic Activity in 140 Exoplanets with the Very Large Array
Authors: Kevin N. Ortiz Ceballos, Yvette Cendes, Edo Berger, Peter K. G. Williams
Figure caption: Luminosity upper limits as a function of system distance. A dashed line shows the intended sensitivity of the survey at L  ν  ≲ 1012.5 erg s−1 Hz−1. Each data set studied is shown in a different color, and upper limits on luminosity as a function of distance are presented as markers with dotted lines pointing downward. Results from the literature are also shown for reference; these correspond to the four systems in the unobserved portion of the sample that have published radio observations in the 4–8 GHz range, taken from Bower et al. (2009), Bastian et al. (2018), Pineda & Hallinan (2018), and Cendes et al. (2021).
Paper: A Volume-limited Radio Search for Magnetic Activity in 140 Exoplanets with the Very Large Array
Authors: Kevin N. Ortiz Ceballos, Yvette Cendes, Edo Berger, Peter K. G. Williams
Figure caption: Luminosity limits as a function of planet mass. Here, each planet in the sample is plotted, with the luminosity measurement corresponding to its system. We include the same four literature systems as in Figure 1. We also include the measured luminosities and estimated masses for the available radio-detected T dwarfs in the literature: SIMP J013656.5+093347.3, 2MASS J10475385+2124234, 2MASS J12373919+6526148, 2MASS J12545393-0122474, and WISE J062309.94-045624.6. These literature measurements are taken from Kao et al. (2016, 2018) and Rose et al. (2023).
Paper: A Volume-limited Radio Search for Magnetic Activity in 140 Exoplanets with the Very Large Array
Authors: Kevin N. Ortiz Ceballos, Yvette Cendes, Edo Berger, Peter K. G. Williams
Figure caption: The GBR between X-ray and radio luminosities. The red arrows indicate upper limits on GBR placement obtained from our radio luminosity upper limits and X-ray luminosity values from Stelzer et al. (2013). The red star indicates the placement of GJ 3323 in the GBR from our detection. Gray circles are from the original result of Benz & Guedel (1994), and green circles and arrows are detections and upper limits, respectively, of early M dwarfs (M0–M6) from Williams et al. (2014). The inset plot shows the distribution of offsets perpendicular to the GBR fit in units of dex for the original Güdel–Benz sample (gray) and for the Williams et al. (2014) sample (green), with GJ 3323 as the red line.
Paper: A Volume-limited Radio Search for Magnetic Activity in 140 Exoplanets with the Very Large Array
Authors: Kevin N. Ortiz Ceballos, Yvette Cendes, Edo Berger, Peter K. G. Williams
Figure caption: Stacked images for targets from three of the VLA programs reported in this paper. Each stack is made using a weighted average of a 31 x 31 pixel region centered on each target star. The center pixel is marked with a red outline. Images were made with a cell size of 1/3 the synthesized beam size, but there may be more than one beamwidth per stack. The resulting rms values for the stacks are 2.1 μJy (18B-048), 1.1 μJy (22A-186), and 1.0 μJy (23A-270).
Paper: A Volume-limited Radio Search for Magnetic Activity in 140 Exoplanets with the Very Large Array
Authors: Kevin N. Ortiz Ceballos, Yvette Cendes, Edo Berger, Peter K. G. Williams
Figure caption: VLA images of the region centered on the Gaia DR3 proper-motion-corrected position of GJ 3323. The contour levels are −3, 3, 5, 7, 9σ, where σ is the rms of the image as shown in each cutout. GJ 3323 is detected with a flux density of 86 ± 10 μJy in Stokes I and 35 ± 9 μJy in Stokes V.
Paper: A Volume-limited Radio Search for Magnetic Activity in 140 Exoplanets with the Very Large Array
Authors: Kevin N. Ortiz Ceballos, Yvette Cendes, Edo Berger, Peter K. G. Williams
Figure caption: Luminosity limits as a function of planet orbital separation. The literature values correspond to the same four systems from Figures 1 and 2.
Paper: A Volume-limited Radio Search for Magnetic Activity in 140 Exoplanets with the Very Large Array
Authors: Kevin N. Ortiz Ceballos, Yvette Cendes, Edo Berger, Peter K. G. Williams
Figure caption: Flux predictions from Turnpenney et al. (2018) for six nearby exoplanets and our measured upper limits. We establish upper limits more stringent than their predicted fluxes for three planets. Two of these planets belong to the same system, GJ 876.
Paper: A Volume-limited Radio Search for Magnetic Activity in 140 Exoplanets with the Very Large Array
Authors: Kevin N. Ortiz Ceballos, Yvette Cendes, Edo Berger, Peter K. G. Williams
Figure caption: Spectral-type distribution of our observed sample of stellar systems. The spectral type for each observed star is taken from the NASA Exoplanet Archive’s Planetary Systems Composite Planet Data Table.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Azimuthally averaged PS of simulated noiseless speckle cubes for a 0.″8 seeing: an ideal (instantaneous and monochromatic) speckle at 800 nm, a monochromatic exposure of 30 ms (dashed line), and imaging in the I band (dashed–dotted). The vertical dotted line marks 0.5f  c , and the red dotted line is a linear approximation of the I-band PS.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Signal-to-noise ratio in the simulated HRCam with an EM CCD detector vs. stellar magnitude in the instrumental system I. Full lines and upper axis correspond to the 30 ms exposure, and dashed lines correspond to the 60 ms exposure, both with 400 frames per data cube. The curves are computed for seeing values of 0.″6, 0.″8, 1.″0, 1.″2, and 1.″4. The asterisk shows the observation of V1311 Ori D in 2021.7983 (see text).
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Example of processing the data cube EK.021 recorded on 2021.79. The binary star WDS 05321−0305 (separation 0.″165, ΔI = 0.87 mag) was observed in the I filter with standard parameters (ROI 200 × 200 pixels, exposure time 24 ms, 400 frames per cube). The speckle PS is shown in a negative logarithmic stretch. The central 40 × 40 pixels (0.″63) fragments of the ACF and SAA images are displayed. The FWHM of the average image is 0.″58. Under good seeing, residual aberrations of the telescope are manifested as asymmetric details of the average image, as a cross-like feature in the PS, and as faint spurious details in the ACF.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Comparison between real and simulated data in the I filter. Left: PS averaged in angular coordinate; right: individual speckle images (top) and the average images in negative rendering (bottom). Note that the linear fit to PS between 0.2f  c  and 0.8f  c  (not plotted) is a poor approximation in this case.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Power spectra of a simulated binary star with equal components displayed on a negative logarithmic scale. The SNR and N ph are indicated. An EM CCD with CIC = 0.02, A = 10, and a threshold of 10 ADU is simulated. An ideal speckle data cube was used as input.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Illustration of the standard signal processing in HRCam. Signal in a single row of the bias-subtracted image at various processing stages is plotted by thick black lines, the thresholds are shown in red; see the text.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Dependence of the speckle signal S (solid line and squares) and the PS slope p 1 (dashed line) on the exposure time according to simulations. Asterisks show results for the real image cube EA.009.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Cumulative histograms of the speckle signal S in the I filter without binning in the speckle runs of 2021a and 2023a with good and average seeing, respectively. The median S values are −4.19 and −4.42 and the median PS slopes p 1 are −3.78 and −3.61.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Dependence of the speckle signal S (solid line and squares) and the PS slope p 1 (dashed line) on seeing. Simulations with a 30 ms exposure time and the I filter.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Errors in the position (top: the solid and dashed lines correspond to two orthogonal directions) and magnitude difference (bottom) of simulated binary star measurements depending on the SNR. Approximate magnitudes are indicated in the lower plot, where the dashed line shows the errors, while squares with error bars show the mean fitted Δm and their scatter.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Signal-to-noise ratio (SNR) in the PS at half of the cutoff frequency vs. magnitude in the I band for a 0.″8 seeing and three simulated detectors: an EM CCD, a scientific CMOS (RON of 0.5 e−), and a qCMOS (RON of 0.3 e−). The upper axis gives the number of photons per frame in a 30 ms exposure; the SNR assumes 400 frames per data cube.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Simulated single noisy frames with N ph = 3000 corresponding to an EM CCD (left, SNR = 1.7), and a CMOS with RON = 0.5 e− (right, SNR = 3.3). The central region of 100 × 100 pixels is shown in negative linear stretch.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Quantum efficiency of three detectors for speckle interferometry according to the vendor’s data: EM CCD iXon X3 888 from Andor, ASI462 from ZWO, and ORCA Quest from Hamamatsu.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Effective loss of flux 1/(P bias N ph) vs. threshold for a qCMOS with RON of 0.3 e− (marked by the vertical dotted line) and for two levels of the flux.
Paper: Performance of the SOAR Speckle Instrument
Authors: Andrei Tokovinin
Figure caption: Scheme of the speckle simulation code (see text).