adsabs/AstroCLIMB huggingface dataset:
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Periodogram analysis of a simulated light curve with Gaussian white noise together with an injected planetary transit with a depth of 200 ppm. The light curve cadence and duration are similar to a single-sector TESS FFI observation. The injected planet has an orbital period of 2 days and a transit duration of 2 hr. The top row shows the simulated light curve (left) and its autocorrelation function (right). The second row shows the BLS (left) and TCF (right) periodograms. The red curve gives the cobs median fit to the periodogram powers. A rug plot (small vertical marks on the x-axis) shows the location of the knots used for the median fit. Annotations give the S/N, period, and depth obtained from the periodogram. The third row gives histograms of the BLS (left) and TCF (right) power values. The fourth and fifth rows show the periodograms and the corresponding histograms after standardization. The annotation in the fourth row gives the FAP value of the peak in the standardized periodogram.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Periodogram analysis with autocorrelated noise and a smaller injected planet with 234 ppm. See Figure 1 for a description of the panels.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Periodogram analysis for Gaussian white noise and a smaller planet with injected transit depth 68 ppm. See Figure 1 for a description of the panels.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Periodogram analysis with autocorrelated noise. Here the injected transit depth is 400 ppm. See Figure 1 for a description of the panels.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: MDD (in percent of the stellar brightness) as a function of the number of transits. The injected planet has a 1 day period and a 2 hr transit duration. Two metrics are shown: FAP based on EVT on standardized periodograms (top row) and S/N on detrended periodograms (bottom row). Light curves have Gaussian white noise (left column) and autocorrelated noise (right column). Each panel shows the MDDs for the BLS (blue curve) and TCF (orange curve) periodograms. The horizontal dashed line corresponds to MDD = 0.005% to guide the eye.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Illustration of BLS (left panels) and TCF (right panels) analysis of a simulated light curve with a P = 2 days transiting planet superposed on autocorrelated noise. First row: zoom of several days of the light curve with the Gaussian process regression fit overlaid (left) and the same light curve after differencing with the ARMA fit overlaid (right). Second row: periodograms of the entire simulated light curve with two BLS false peaks “A” and “B” marked. Third row: folded light curves for the true transit period. Fourth and fifth rows: folded light curves of the original (left) and differenced (right) data for false spectral peaks A and B.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Example 1 of a TESS year 1 light curve for a star with smaller confirmed transiting planets. The panels are similar to those in Figure 1 with the normalized light curve, autocorrelation function, BLS and TCF periodograms with median trend fit and their histograms, standardized periodograms, and histograms. Scalar results are provided in Table 1.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: MDD as a function of transit period (top rows) and duration (bottom rows). Simulations assume 10 transits, transit duration = 2 hr for the comparison using period, and period = 1 day for the comparison using transit duration. See Figure 5 for panel details.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Example 4 of a TESS year 1 light curve and the corresponding periodograms and histograms. See Figure 7 for a description of the panels.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Decision tree outlining general suggestions for selecting a periodogram algorithm based on certain conditions.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Comparison of the execution times of BLS and TCF as a function of the number of data points in the light curve.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Example 3 of a TESS year 1 light curve and the corresponding periodograms and histograms. See Figure 7 for a description of the panels.
Paper: A Study of Two Periodogram Algorithms for Improving the Detection of Small Transiting Planets
Authors: Yash Gondhalekar, Eric D. Feigelson, Gabriel A. Caceres, Marco Montalto, Snehanshu Saha
Figure caption: Example 2 of a TESS year 1 light curve and the corresponding periodograms and histograms. See Figure 7 for a description of the panels.
Paper: Star Formation and AGN Activity 500 Myr after the Big Bang: Insights from JWST
Authors: Jordan C. J. D'Silva, Simon P. Driver, Claudia D. P. Lagos, Aaron S. G. Robotham, Jake Summers, Rogier A. Windhorst
Figure caption: Left: SFMS at z ≈ 3.5 → 12.5. Blue points and lines show the results from STELLAR, while red shows the results from STELLAR+AGN. Gray dots are the z ≥ 5 SFR − M ⋆ from the DEVILS survey (e.g., Thorne et al. 2021). The gray shaded region shows the exclusion range up to M ⋆ = 108 M ⊙ where the stellar masses may not be robust. The inset panel in the highest-redshift bin shows a zoom-in of the data points and the SFMS. Right: SFR density distributions per unit stellar mass at z ≈ 3.5 → 12.5. The color scheme is the same as in the left panels.
Paper: Relating Intermittency and Inverse Cascade to Stochastic Entropy in Solar Wind Turbulence
Authors: Mirko Stumpo, Simone Benella, Tommaso Alberti, Oreste Pezzi, Emanuele Papini, Giuseppe Consolini
Figure caption: Local scaling exponent ζ 2 related to the S 2 structure function (top panel) and flatness F (bottom panel) as functions of the scale parameter r in units of d  i  (purple dashed lines). Orange (cyan) curves indicate ζ 2 and F conditioned to ΔS > 0 (ΔS < 0). Typical values of the scaling exponent ζ 2 expected in solar wind are indicated by horizontal black lines, ζ 2 = 0.5 being the Iroshnikov–Kraichnan scaling predicted for MHD turbulence (Kraichnan 1965) and ζ 2 = 1.7 a typical value measured at sub-ion scales. The power law ﹩{r}^{{\zeta }_{4}-2{\zeta }_{2}}﹩, expected to be representative of the trend of F(r) due to anomalous scaling, is reported as a reference.
Paper: Star Formation and AGN Activity 500 Myr after the Big Bang: Insights from JWST
Authors: Jordan C. J. D'Silva, Simon P. Driver, Claudia D. P. Lagos, Aaron S. G. Robotham, Jake Summers, Rogier A. Windhorst
Figure caption:  PROSPECT fit to CEERS_1019, a confirmed broad-line AGN at z = 8.679 first presented in Larson et al. (2023). The black points with error bars show the PROFOUND photometry. The error bars show the 16th–84th percentile ranges of the photometry. The STELLAR fit is shown in blue, while the STELLAR+AGN fit is shown in red. The log-probability (LP), being the maximum of the log-posterior distribution, is also included. The blue and red squares show the fit photometry for STELLAR and STELLAR+AGN. We show the relevant filter transmission curves from HST+JWST with rainbow colors. Larson et al. (2023) report LAGN ≈ 1045.1±0.2 erg s−1, while we find LAGN ≈ 1045.02±2.35 erg s−1. The bottom panel shows the error weighted difference between the observed and fitted photometry, with the same color scheme used for the fitted SED curves above.
Paper: Relating Intermittency and Inverse Cascade to Stochastic Entropy in Solar Wind Turbulence
Authors: Mirko Stumpo, Simone Benella, Tommaso Alberti, Oreste Pezzi, Emanuele Papini, Giuseppe Consolini
Figure caption: A set of four trajectories b  r  retrieved from PSP data set (top panel). The amplitude of the signal is here normalized to the magnetic field standard deviation and compared with the power spectral density (PSD; bottom panel). The scale parameter is given in units of d  i  in order to highlight the transition from the inertial toward the sub-ion regimes. The vertical dotted line indicates the spectral break located at ∼10 d  i .
Paper: Relating Intermittency and Inverse Cascade to Stochastic Entropy in Solar Wind Turbulence
Authors: Mirko Stumpo, Simone Benella, Tommaso Alberti, Oreste Pezzi, Emanuele Papini, Giuseppe Consolini
Figure caption: Average behavior of the absolute value of fluctuations conditioned to ΔS as a function of the scale (left panel) and the scaling exponent ζ 1(ΔS) as a function of ΔS (right panel). The vertical dotted lines mark the end of the inertial range (r = 10d  i , left) and the crossing of ΔS = 0 (right), respectively.
Paper: Relating Intermittency and Inverse Cascade to Stochastic Entropy in Solar Wind Turbulence
Authors: Mirko Stumpo, Simone Benella, Tommaso Alberti, Oreste Pezzi, Emanuele Papini, Giuseppe Consolini
Figure caption: Probability distribution of the total entropy production ΔS. The inset shows the computation of the IFT by varying the number N of randomly selected trajectories.
Paper: Star Formation and AGN Activity 500 Myr after the Big Bang: Insights from JWST
Authors: Jordan C. J. D'Silva, Simon P. Driver, Claudia D. P. Lagos, Aaron S. G. Robotham, Jake Summers, Rogier A. Windhorst
Figure caption: CSFH at z ≈ 0–15. Blue triangles show the z ≈ 3.5–12.5 STELLAR results, while red inverted triangles show the results for STELLAR+AGN. The error bars show the 16th–84th percentiles from the SFMS fits in Figure 2. The arrows indicate where the results are upper limits. The blue and red points are offset by 0.05 in z for clarity. The brown dashed line shows the Madau & Dickinson (2014) fitted CSFH. The brown solid line shows the constant star formation efficiency model of the CSFH from Harikane et al. (2022). The brown shaded region shows the CSFH calculated at z ≈ 0–4 using the SFMSs and SMFs from Thorne et al. (2021). The gray points show previous literature results of the CSFH from Bouwens et al. (2015), Adams et al. (2023a), Bouwens et al. (2023b), D’Silva et al. (2023a), and Harikane et al. (2023b).
Paper: Star Formation and AGN Activity 500 Myr after the Big Bang: Insights from JWST
Authors: Jordan C. J. D'Silva, Simon P. Driver, Claudia D. P. Lagos, Aaron S. G. Robotham, Jake Summers, Rogier A. Windhorst
Figure caption: Left: STELLAR M ⋆ against STELLAR+AGN M ⋆ at z ≈ 3.5–12.5. The color of the points corresponds to the AGN bolometric luminosity determined by PROSPECT, where blue is weaker AGN and red is stronger. The purple line and shading show the third-order spline fit. The gray shaded region shows exclusion range up to M ⋆ = 108 M ⊙ where the stellar masses may not be robust. The dashed line shows the one-to-one relation. The inset panel in the highest-redshift bin shows a zoom-in of the data points and fitted relation. Right: Δ M ⋆ = STELLAR+AGN − STELLAR. The color scheme is the same as the left panels. The horizontal dashed line shows Δ M ⋆ = 0.
Paper: Star Formation and AGN Activity 500 Myr after the Big Bang: Insights from JWST
Authors: Jordan C. J. D'Silva, Simon P. Driver, Claudia D. P. Lagos, Aaron S. G. Robotham, Jake Summers, Rogier A. Windhorst
Figure caption: ΔSFR = STELLAR+AGN − STELLAR as a function of AGN bolometric luminosity. We show the results binned in 2 dex intervals of STELLAR+AGN stellar mass from M ⋆ ≈ 104.5 M ⊙ → 1010.5 M ⊙. The color of points indicates the redshift, where blue corresponds to low redshift and red to high. The horizontal dashed line shows ΔSFR = 0.
Paper: Constraints on the Alfvénicity of Switchbacks
Authors: O. V. Agapitov, J. F. Drake, M. Swisdak, K.-E. Choi, N. Raouafi
Figure caption: Two switchbacks encountered by PSP on 2018 November 6: (a)—magnetic field components in the RTN coordinate system (R-red; T-blue; N-green). The magnitude of the magnetic field is shown by the black curve; (b)—proton bulk velocity components in the RTN coordinate system (the same color coding as for panel (a)); (c)—proton density; (d)—the angle of magnetic field rotation θ (relative to the magnetic field  B  SW recorded before the SB); (e)—the Alfvénicity parameter α (﹩| {\rm{\Delta }}{\boldsymbol{V}}| /| {\rm{\Delta }}{\boldsymbol{B}}| {\left(4\pi {n}_{i}{m}_{i}\right)}^{-1/2}﹩) (for aligned Δ V  and Δ B ). The red points indicate the geometrical limit for α: α  c  = ∣ B  SW∣/∣ B  SB −  B  SW∣ based on the assumption that ﹩\left|{\rm{\Delta }}{\boldsymbol{V}}\right|﹩ is limited by the local value of V A. (f)—the cross-helicity σ  c . The red points indicate perfect alignment of the magnetic field and proton bulk velocity perturbations, so that σ  c  depends only on α as σ  c α  = 2α/(1 + α 2). Panels (g)–(l) present the second switchback parameters in the same format.
Paper: Constraints on the Alfvénicity of Switchbacks
Authors: O. V. Agapitov, J. F. Drake, M. Swisdak, K.-E. Choi, N. Raouafi
Figure caption: The distributions of SBs’ averaged parameters (a)—in the α − θ domain and (b)—the distribution of perturbations of solar wind parameters from Encounter 1 (∼2 · 106 points, corresponding to ∼1 measurement per second) in the α − θ domain (switchback intervals are contoured by blue and nonswitchback solar wind intervals are contoured by red; the distribution on θ is in the right subpanel with the same color coding); (c)—the distribution of SBs and (d)—the distribution of perturbations of solar wind parameters from Encounter 1 in the α − σ  c  domain (the distribution on σ  c  is in the right subpanel). The black dashed curve presents the case of the perfect alignment of Δ V  and Δ B  when σ  c  is a function of α: σ  c α  = 2α/(1 + α 2); (e)—the distribution of SBs and (f)—the distribution of perturbations of solar wind parameters from Encounter 1 in the α − σ  r  domain (the distribution on σ  r  is in the right subpanel). The black dashed curve presents the case of the perfect alignment of Δ V  and Δ B  when σ  r  is a function of α: σ  c α  = (α 2 − 1)/(1 + α 2); (g)—the distribution of ﹩{\left\langle \alpha \right\rangle }_{\mathrm{SB}}﹩ values inside SBs (one value from each SB); and (h)—the distribution of α values from solar wind perturbations recorded from Encounter 1 (black), the distribution inside SBs (blue), the distribution in the pristine solar wind (red).
Paper: Constraints on the Alfvénicity of Switchbacks
Authors: O. V. Agapitov, J. F. Drake, M. Swisdak, K.-E. Choi, N. Raouafi
Figure caption: Schematic of the magnetic field (black) and plasma bulk velocity perturbation (red) in SBs in the de Hoffman–Teller frame (a)—for the Alfvénic perturbation, which is characterized by ﹩{\rm{\Delta }}{\boldsymbol{V}}={\rm{\Delta }}{{\boldsymbol{V}}}_{{\rm{A}}}={\rm{\Delta }}{\boldsymbol{B}}/\sqrt{4\pi n}﹩, ∣ V  SB −  V  HT∣ = V A, and ∣ V  SW −  V  HT∣ = V A; and (b)—when the value Δ V  is limited by the local V A. The velocity values are correspondingly scaled by the parameter α:Δ V  = αΔ V  A, ∣ V  SB −  V  HT∣ = α V A, and ∣ V  SW −  V  HT∣ = α V A, with α = ∣ B  SW∣/∣ B  SB −  B  SW∣.
Paper: Constraints on the Alfvénicity of Switchbacks
Authors: O. V. Agapitov, J. F. Drake, M. Swisdak, K.-E. Choi, N. Raouafi
Figure caption: (a)—Transverse to the SB axis component of dHT speed in the solar wind frame ( V  HT −  V  SW) vs. the transverse component of the corresponding SB velocity ( V  SB −  V  SW). The SB axis is estimated as the average direction of magnetic field inside the SB (Krasnoselskikh et al. 2020); (b)—plasma flow velocity in the dHT frame ∣ V  SW −  V  HT∣ vs. V A and α V A—better alignment with α V A (the filled circles) than with V A (the empty circles) is observed; (c)—V A (the blue filled circles) and ΔV A (the red filled circle) plotted vs. ∣ΔV∣. Note that ∣ΔV∣ < ΔV A if ΔV A < V A so α can reach 1, and ∣ΔV∣ < V A so ∣ΔV∣ is limited by V A, so α < 1 for this regime.
Paper: Correlation between Supergranular Lane Widths and Sunspot Number; A Simple Way to Predict the Amplitude of Sunspot Cycle
Authors: K P Raju, Jagdev Singh, Belur Ravindra, Muthu Priyal
Figure caption: The image and the autocorrelation function. The Kodaikanal Ca II K image on 1914 Nov 1 and a few representative windows are shown on the left. The autocorrelation curve as a function of lag is shown on the right. The dotted lines give the supergranular lane width and size.
Paper: Bridging Scales in Black Hole Accretion and Feedback: Magnetized Bondi Accretion in 3D GRMHD
Authors: Hyerin Cho, 혜린 조, Ben S. Prather, Ramesh Narayan, Priyamvada Natarajan, Kung-Yi Su, Angelo Ricarte, Koushik Chatterjee
Figure caption: Time-averaged radial profiles of selected quantities for our HD (red) and MHD (black) Bondi accretion simulations with R B = 1.8 × 105 r  g  (gray vertical dashed line). In this and forthcoming plots, negative values are plotted with dotted rather than solid lines. While most naturally expressed in gravitational units (lower x-axis), we also present distances scaled to M87 (upper x-axis). Where available, analytic solutions of relativistic Bondi accretion are plotted with thick gray lines. Magnetic fields lead to a shallower density slope, a dramatically suppressed accretion rate, and positive energy feedback.
Paper: Bridging Scales in Black Hole Accretion and Feedback: Magnetized Bondi Accretion in 3D GRMHD
Authors: Hyerin Cho, 혜린 조, Ben S. Prather, Ramesh Narayan, Priyamvada Natarajan, Kung-Yi Su, Angelo Ricarte, Koushik Chatterjee
Figure caption: Top: accretion rate (black) and magnetic flux parameter (blue) as a function of time for our MHD simulation. The mean accretion rate of ﹩{\overline{\dot{M}}}_{10}\sim 5\,\times \,{10}^{-3}{\dot{M}}_{{\rm{B}}}﹩ and the mean magnetic flux at the horizon ﹩\overline{{\phi }_{b}}\sim 30﹩ are plotted in gray and blue horizontal lines, respectively. We average values over the second half of the simulations (pink background), when the simulation has reached a steady state. Bottom: slices of β (left) and ρ (right) in our simulation, spanning 8 orders of magnitude in spatial scale. Lines of constant magnetic flux representing φ-averaged magnetic fields are overlaid in black.
Paper: Bridging Scales in Black Hole Accretion and Feedback: Magnetized Bondi Accretion in 3D GRMHD
Authors: Hyerin Cho, 혜린 조, Ben S. Prather, Ramesh Narayan, Priyamvada Natarajan, Kung-Yi Su, Angelo Ricarte, Koushik Chatterjee
Figure caption: Top: dissecting contributions to the total energy outflow (η tot), including the fluid contribution (η fl), the advective outflow efficiency (η adv), and the convective outflow efficiency (η conv). Since η fl ≈ η tot, the electromagnetic field does not contribute much directly to the energy outflow. Instead, the energy is transported primarily via convection until near the Bondi radius (gray vertical dashed line). Positive (negative) values are shown in solid (dotted) lines. Bottom: azimuthally averaged energy fluxes in the r, θ plane, normalized by the accretion rate at 10 r  g . Outflowing energy is shown in red and inflowing energy in blue.
Paper: Correlation between Supergranular Lane Widths and Sunspot Number; A Simple Way to Predict the Amplitude of Sunspot Cycle
Authors: K P Raju, Jagdev Singh, Belur Ravindra, Muthu Priyal
Figure caption: Plots of supergranular lane width during the sunspot minima years vs. maximum sunspot number of the following solar cycle. The latitude, correlation coefficient, and percentage probability that the correlation coefficient arises from two random distributions are mentioned in each plot. A probability ≤1 is considered highly significant (99% confidence level). The continuous line represents a straight-line fit. The error bar and the sunspot cycle number are given at every data point. sunspot data from the World Data Center SILSO, Royal Observatory of Belgium, Brussels.
Paper: Bridging Scales in Black Hole Accretion and Feedback: Magnetized Bondi Accretion in 3D GRMHD
Authors: Hyerin Cho, 혜린 조, Ben S. Prather, Ramesh Narayan, Priyamvada Natarajan, Kung-Yi Su, Angelo Ricarte, Koushik Chatterjee
Figure caption: Comparison between simulations with varying resolutions, coordinate systems, and initial magnetic strength, described in Table 1. Each profile is averaged between t run(R B) = 4.5 t B − 9 t B measured at the Bondi radius (gray vertical dashed line). Positive (negative) values are shown in solid (dotted) lines. Overall, we find good agreement between these simulations.
Paper: Correlation between Supergranular Lane Widths and Sunspot Number; A Simple Way to Predict the Amplitude of Sunspot Cycle
Authors: K P Raju, Jagdev Singh, Belur Ravindra, Muthu Priyal
Figure caption: Plots of correlation coefficient between supergranular lane width and the sunspot number maximum vs. solar latitude for three epochs. The panels represent a year before the solar minimum, the solar minimum year, and a year after the solar minimum. The dotted line gives the 99% confidence level. The continuous line represents a smoothed curve. The data are provided in a machine-readable format as the data behind the Figure; it is also accessible from Harvard Dataverse, doi:10.7910/DVN/IRN90W. (The data used to create this figure are available.)
Paper: A New Covariant Formalism for Kinetic Plasma Simulations in Curved Spacetimes
Authors: Tyler Trent, Pierre Christian, Chi-kwan Chan, Dimitrios Psaltis, Feryal Özel
Figure caption: Fractional difference between the average drift velocity calculated numerically in the guiding center limit and the analytic drift velocity for a charged particle in a constant electromagnetic field as a function of the gyroradius ρ divided by the macroscopic scale R of the system in a flat spacetime (see insert for the setup). In this configuration, the only drift experienced by the particle is proportional to  E  ×  B . Different points show different magnetic field strengths (blue) and particle velocities (orange), both of which alter the gyroradius. The truncation error in the drift velocity introduced by the guiding center equations depends linearly on gyroradius, as expected.