adsabs/AstroCLIMB huggingface dataset:
Paper: The TESS-Keck Survey. VII. A Superdense Sub-Neptune Orbiting TOI-1824 
Authors: Sarah Lange, Joseph M. Akana Murphy, Natalie M. Batalha, Ian J. M. Crossfield, Courtney D. Dressing, Benjamin Fulton, Andrew W. Howard, Daniel Huber, Howard Isaacson, Stephen R. Kane, Erik A. Petigura, Paul Robertson, Lauren M. Weiss, Aida Behmard, Corey Beard, Sarah Blunt, Casey L. Brinkman, Ashley Chontos, Fei Dai, Paul A. Dalba, Tara Fetherolf, Steven Giacalone, Michelle L. Hill, Rae Holcomb, Jack Lubin, Mason G. MacDougall, Andrew W. Mayo, Teo Močnik, Daria Pidhorodetska, Alex S. Polanski, Malena Rice, Lee J. Rosenthal, Ryan A. Rubenzahl, Nicholas Scarsdale, Emma V. Turtelboom, Judah Van Zandt, David R. Ciardi, Andrew W. Boyle
Figure caption: Top: the SIP is shown in black. The vertical red dashed line represents the highest peak found in the GLS periodogram of the SAP light curve. The SIP shows a similar peak to the one seen in the GLS periodogram, suggesting that the feature is not necessarily a product of TESS systematics. Bottom: the periodogram of the flux from the pixels outside of the SAP aperture. There is little power in the background flux at the supposed stellar rotation period.
Paper: The TESS-Keck Survey. VII. A Superdense Sub-Neptune Orbiting TOI-1824 
Authors: Sarah Lange, Joseph M. Akana Murphy, Natalie M. Batalha, Ian J. M. Crossfield, Courtney D. Dressing, Benjamin Fulton, Andrew W. Howard, Daniel Huber, Howard Isaacson, Stephen R. Kane, Erik A. Petigura, Paul Robertson, Lauren M. Weiss, Aida Behmard, Corey Beard, Sarah Blunt, Casey L. Brinkman, Ashley Chontos, Fei Dai, Paul A. Dalba, Tara Fetherolf, Steven Giacalone, Michelle L. Hill, Rae Holcomb, Jack Lubin, Mason G. MacDougall, Andrew W. Mayo, Teo Močnik, Daria Pidhorodetska, Alex S. Polanski, Malena Rice, Lee J. Rosenthal, Ryan A. Rubenzahl, Nicholas Scarsdale, Emma V. Turtelboom, Judah Van Zandt, David R. Ciardi, Andrew W. Boyle
Figure caption: Keck-HIRES RVs—with the Keplerian signal of TOI-1824 b removed—plotted as a function of their associated S HK value. The RV residuals and the S HK values have a slight linear correlation, suggesting that the RV time series is contaminated by stellar activity.
Paper: The TESS-Keck Survey. VII. A Superdense Sub-Neptune Orbiting TOI-1824 
Authors: Sarah Lange, Joseph M. Akana Murphy, Natalie M. Batalha, Ian J. M. Crossfield, Courtney D. Dressing, Benjamin Fulton, Andrew W. Howard, Daniel Huber, Howard Isaacson, Stephen R. Kane, Erik A. Petigura, Paul Robertson, Lauren M. Weiss, Aida Behmard, Corey Beard, Sarah Blunt, Casey L. Brinkman, Ashley Chontos, Fei Dai, Paul A. Dalba, Tara Fetherolf, Steven Giacalone, Michelle L. Hill, Rae Holcomb, Jack Lubin, Mason G. MacDougall, Andrew W. Mayo, Teo Močnik, Daria Pidhorodetska, Alex S. Polanski, Malena Rice, Lee J. Rosenthal, Ryan A. Rubenzahl, Nicholas Scarsdale, Emma V. Turtelboom, Judah Van Zandt, David R. Ciardi, Andrew W. Boyle
Figure caption: The results of our exploratory TTV analysis for TOI-1824 b. Differences in the observed and expected transit times are shown as the blue points with 1σ error bars for the five transits in the 2 minute cadence TESS SAP data. We find no evidence of TTVs for TOI-1824 b.
Paper: The TESS-Keck Survey. VII. A Superdense Sub-Neptune Orbiting TOI-1824 
Authors: Sarah Lange, Joseph M. Akana Murphy, Natalie M. Batalha, Ian J. M. Crossfield, Courtney D. Dressing, Benjamin Fulton, Andrew W. Howard, Daniel Huber, Howard Isaacson, Stephen R. Kane, Erik A. Petigura, Paul Robertson, Lauren M. Weiss, Aida Behmard, Corey Beard, Sarah Blunt, Casey L. Brinkman, Ashley Chontos, Fei Dai, Paul A. Dalba, Tara Fetherolf, Steven Giacalone, Michelle L. Hill, Rae Holcomb, Jack Lubin, Mason G. MacDougall, Andrew W. Mayo, Teo Močnik, Daria Pidhorodetska, Alex S. Polanski, Malena Rice, Lee J. Rosenthal, Ryan A. Rubenzahl, Nicholas Scarsdale, Emma V. Turtelboom, Judah Van Zandt, David R. Ciardi, Andrew W. Boyle
Figure caption: The mass–radius diagram in the sub-Neptune regime. Gray dots show planets from the NASA Exoplanet Archive (NEA; accessed on 2023 June 8; NASA Exoplanet Archive 2023) that were confirmed using RVs and have better than 50% and 15% fractional measurement precision in mass and radius, respectively. TOI-1824 b is shown as the green star. Blue triangles represent planets with M p > 12 M ⊕ and R p < 3 R ⊕ whose RV data sets have >30 measurements. Red octagons represent planets in the same mass and radius range whose RV data sets have <30 measurements. We plot various density profiles for reference. The dashed–dotted gray lines represent Earth-like cores surrounded by a 0.1%, 1%, or 2% solar metallicity H/He envelope by mass for a 10 Gyr old planet receiving 10× Earth’s instellation (Lopez & Fortney 2014). The dashed blue lines represent either a planet composed of 100% condensed H2O or a planet made up of a 1:1 mixture of condensed H2O and Earth-like silicates (Zeng et al. 2016). Both are calculated under the assumption of constant specific entropy for a fixed temperature of 700 K at 100 bars. Additional composition curves come from Zeng et al. (2016). TOI-1824 b is emblematic of the degenerate nature of inferring sub-Neptune bulk composition—its mass and radius are consistent with either a 1:1 mixture of water and rock or an Earth-like core surrounded by a 1%–2% H/He envelope by mass.
Paper: Low-frequency Radio Recombination Lines Away from the Inner Galactic Plane
Authors: Akshatha K. Vydula, Judd D. Bowman, David Lewis, Kelsie Crawford, Matthew Kolopanis, Alan E. E. Rogers, Steven G. Murray, Nivedita Mahesh, Raul A. Monsalve, Peter Sims, Titu Samson
Figure caption: Integrated spectrum (top) and residuals following a five-term polynomial fit subtraction (middle) and a nine-term polynomial fit subtraction (bottom) for the 2 hr bin centered at LST 18 hr, when the Galactic center is at zenith. A five-term polynomial fit fails to capture all the bandpass features, whereas a nine-term polynomial fit removes all the structures, giving continuum-removed residuals. In the middle and bottom panels, the 85 vertical red lines represent the Cα frequencies that are expected within the observed frequency range of 50–87 MHz. Many of the most extreme negative deviations align with RRL frequencies. The lines are strongest at low frequencies, reaching about 2 K below 55 MHz, and weaker at higher frequencies with amplitudes of about 1 K at 60 MHz and less than 0.5 K above 70 MHz.
Paper: Low-frequency Radio Recombination Lines Away from the Inner Galactic Plane
Authors: Akshatha K. Vydula, Judd D. Bowman, David Lewis, Kelsie Crawford, Matthew Kolopanis, Alan E. E. Rogers, Steven G. Murray, Nivedita Mahesh, Raul A. Monsalve, Peter Sims, Titu Samson
Figure caption: Stacked Cα line profile relative to the continuum for each LST bin (blue) and best-fit double-Gaussian model (orange). Each stacked profile is created from 85 individual lines with principal quantum numbers 423 ≤ n ≤ 507 and has an effective line center of 66.1 MHz. The small emission feature about 35 kHz below the Cα absorption in each panel is from Hα. The lines are strong when the Galactic center is in the beam, peaking at LST 18 hr when the center is at the zenith. They are weak when higher Galactic latitudes are in the beam (e.g., LST 2–6 hr). The best-fit Gaussian profile parameters for each LST bin are listed in Table 1.
Paper: Low-frequency Radio Recombination Lines Away from the Inner Galactic Plane
Authors: Akshatha K. Vydula, Judd D. Bowman, David Lewis, Kelsie Crawford, Matthew Kolopanis, Alan E. E. Rogers, Steven G. Murray, Nivedita Mahesh, Raul A. Monsalve, Peter Sims, Titu Samson
Figure caption: Observed C503α absorption line centered at 51.5 MHz (top) and the stacked average line profile from all 85 RRLs across the band 423 ≤ n ≤ 507 (bottom) for the LST 18 hr bin. The effective frequency of the stacked profile is 66.1 MHz. The significance of detection improves from about 4σ for the individual line to 28σ for the stacked profile.
Paper: Low-frequency Radio Recombination Lines Away from the Inner Galactic Plane
Authors: Akshatha K. Vydula, Judd D. Bowman, David Lewis, Kelsie Crawford, Matthew Kolopanis, Alan E. E. Rogers, Steven G. Murray, Nivedita Mahesh, Raul A. Monsalve, Peter Sims, Titu Samson
Figure caption: Same as Figure 3, but for C β lines. Each stacked profile is created from 95 individual lines between 533 ≤ n ≤ 638 and has an effective line center of 66.3 MHz. The presence of any contribution from hydrogen is less clear here compared to the α lines; hence, we have fit only a single Gaussian to the main Cβ profile in each bin.
Paper: Low-frequency Radio Recombination Lines Away from the Inner Galactic Plane
Authors: Akshatha K. Vydula, Judd D. Bowman, David Lewis, Kelsie Crawford, Matthew Kolopanis, Alan E. E. Rogers, Steven G. Murray, Nivedita Mahesh, Raul A. Monsalve, Peter Sims, Titu Samson
Figure caption: Simulated all-sky RRL proxy maps for the center of each LST bin. The images are orthographic projections of the Planck 2015 CO map at 115.27 GHz (Adam et al. 2016; Ade et al. 2016), which provides a rough proxy for the location of carbon in the Galaxy. The CO line emission is tightly concentrated along the Galactic plane, similar to RRL surveys of the plane.
Paper: Low-frequency Radio Recombination Lines Away from the Inner Galactic Plane
Authors: Akshatha K. Vydula, Judd D. Bowman, David Lewis, Kelsie Crawford, Matthew Kolopanis, Alan E. E. Rogers, Steven G. Murray, Nivedita Mahesh, Raul A. Monsalve, Peter Sims, Titu Samson
Figure caption: Cγ line profiles, with 122 individual lines stacked, 610 ≤ n ≤ 731, and an effective frequency of 66.1 MHz. The Gaussian model in the top panel gives the best-fit Cγ amplitude of −171.5 ± 34.4 mK when the Galactic plane is in the beam at LST 18 hr, and the bottom panel shows a nondetection when the Galactic plane moves away from the beam at LST 06 hr with a noise level of ∼4 mK.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Age distributions of Gaia open clusters as predicted by CG20, D21, HR23, and in this work. Left panel: differential age distribution. Right panel: cumulative age distribution.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Comparison between parameters derived in this work with the ones present in literature. In the top left corners is reported the value of the root main square error. Top row: comparison of age, extinction, and distance for clusters that are in common with CG20. Middle row: comparison of age, [Fe/H], extinction, and distance for clusters in common with D21. Bottom row: comparison of age, extinction, and distance for clusters contained in HR23.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Predicted isochrones for three open clusters UBC 276 (left panel), UBC 562 (middle panel), and Teutsch 30 (right panel) from CG20 (dotted–dashed green line), D21 (dashed orange line), HR23 (solid purple line), and this work (solid red line). In the top right, we annotate the ages that correspond to the plotted isochrones (colored accordingly). With blue and full dots we plot the members of the clusters retrieved by HR23, and with empty black dots we plot the ones of D21.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Synthetic CMDs generated by the code described in Section 2.2. The mock clusters are generated with N star = 400, [Fe/H]  =  0, A v = 2, dMod =12 mag, and logAge between 7.9 and 8.2. Single members of simulated clusters are plotted with dots colored according to their age. With dotted lines, we plot the theoretical isochrones used to generate the synthetic CMDs. Left panel: synthetic CMDs superimposed to the grid used by HR23. Right panel: synthetic CMDs superimposed to the Quadtrees of the simulated clusters with logAge   =  7.9 (blue) and logAge   =  8.2.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Isochrones and parameters for UBC 1516 inferred by HR23 (solid purple line), our single-band ANN (dotted red line), and multiband ANN (solid red line). The predicted isochrones are superimposed on the corresponding CMDs of the cluster. Note that the isochrone inferred by HR23 is at solar metallicity. This value is fixed and not actually derived by their ANN.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Example of the computation of the quality metric developed in this work. With blue dots, the members of the open cluster UBC 1016 on which we superimpose the isochrone inferred by the ANN (plotted with a solid red line). In the top right corner, we plot the histogram of the distances between the inferred isochrone and the members of the cluster. On the histogram, we plot with a vertical dotted orange line the mean value of the distribution of distances.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Difference between the parameters estimated by our ANN and the true ones as a function N stars for ∼2000 synthetic clusters contained in the test sample (black dots). In orange, we plot the mean and standard deviations of Y pred − Y true.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Left: fraction of clusters contained in gold (82.3%), silver (11.0%), bronze (3.5%), and wood (3.2%) samples. Right: distribution of μ dist for the 6413 clusters analyzed in this work. Clusters are colored according to their “quality” sample (gold, silver, bronze, or wood).
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: QuadTrees of Gaia CMD of four clusters contained in HR23. Note that magnitudes and colors are standardized as described in Section 3.1.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Spatial distribution of intrinsically bright open clusters divided into age bins superimposed on the overdensity map (in gray) measured by Poggio et al. (2021). The Sun is located in (X, Y) = (0, 0), the Galactic Center is to the right, and Y is taken as positive in the direction of Galactic rotation.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Predicted isochrones for three open clusters UBC 518 (left panel), COIN-Gaia 41 (middle panel), and BH 217 (right panel) from CG20 (dotted–dashed green line), D21 (dashed orange line), HR23 (solid purple line), and this work (solid red line). With blue dots, we plot the members of the clusters retrieved by HR23.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Distribution of heights above the Galactic midplane for intrinsically bright open clusters in different age bins.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Values of [Fe/H] as a function of the distance from the Galactic center (R Gal). With black dots, we plot the clusters analyzed in this work and selected as reported in Section 5.2 and their respective uncertainties. With a red solid line, we plot the relation obtained by the mean values of α and β while a 68% confidence interval is plotted with a red-shaded area. We also superimpose the metallicity gradient obtained by Spina et al. (2022), mean with a solid blue line and 68% confidence interval with a blue-shaded area.
Paper: Parameter Estimation for Open Clusters using an Artificial Neural Network with a QuadTree-based Feature Extractor
Authors: Lorenzo Cavallo, Lorenzo Spina, Giovanni Carraro, Laura Magrini, Eloisa Poggio, Tristan Cantat-Gaudin, Mario Pasquato, Sara Lucatello, Sergio Ortolani, Jose Schiappacasse-Ulloa
Figure caption: Comparison between [Fe/H] derived in this work and the one obtained from spectroscopic data by Spina et al. (2022). Clusters are color coded based on logAge as determined by our ANN. The average posterior of the fitted relation is plotted by a dashed red line, while the red-shaded areas represent the 68% and 90% confidence intervals. In the top left corner, we provide the mean and standard deviations for the three free parameters. With a dotted black line, we plot the relation with α = 1 and β = 0.08.
Paper: Low-frequency Radio Recombination Lines Away from the Inner Galactic Plane
Authors: Akshatha K. Vydula, Judd D. Bowman, David Lewis, Kelsie Crawford, Matthew Kolopanis, Alan E. E. Rogers, Steven G. Murray, Nivedita Mahesh, Raul A. Monsalve, Peter Sims, Titu Samson
Figure caption: Frequency dependence of Cα and Cβ absorption lines. The top panels shows LST 18 hr after correcting for beam dilution and spectral smearing. The middle panels shows the average over LST 0–12 hr assuming that the lines are due to diffuse gas filling the beam; hence, no beam dilution correction is applied. In both cases, EDGES low-band data (blue circles) have a strong frequency dependence. A single mid-band point (green square) for Cα represents the average across its analyzed data. For LST 18 hr, the Oonk et al. (2019) data (red diamonds) and a composite of the Erickson et al. (1995) data (blue square) are shown after adjusting to brightness temperature units as described in Section 3.6. 1σ error bars are plotted for all points but do not include dilution uncertainty in the LST 18 hr case, which is conservatively estimated as a 50% error in undiluted ﹩{T}_{\mathrm{RRL}}^{u}﹩. Overall, there is good agreement between this work and Oonk et al. (2019). The black solid and dashed lines show best-fit models in the LTE limit of Equation (7) as described in Section 3.6. The black dashed–dotted lines show the best-fit model when the departure coefficient product, b  n  β  n , is modeled as a third-order polynomial in frequency and included in the parameter estimation with the strong priors. The best-fit departure coefficient models are shown in the bottom panel. For LST 18 hr, the best-fit b  n  β  n  for Cα qualitatively resembles the curves in Salgado et al. (2017b).
Paper: Low-frequency Radio Recombination Lines Away from the Inner Galactic Plane
Authors: Akshatha K. Vydula, Judd D. Bowman, David Lewis, Kelsie Crawford, Matthew Kolopanis, Alan E. E. Rogers, Steven G. Murray, Nivedita Mahesh, Raul A. Monsalve, Peter Sims, Titu Samson
Figure caption: Frequency dependence of Hα emission lines for the LST 18 hr case. We show the undiluted line amplitude of EDGES low band and EDGES mid-band, along with the results from Oonk et al. (2019) after adjusting to brightness temperature units following the same process as for Cα and Cβ in Figure 10. Again, we see reasonable agreement between the EDGES and Oonk et al. (2019) observations. The green dashed line shows the best-fit model in the LTE limit. The blue dashed line shows the best-fit model for a non-LTE case using the strong priors described in Section 3.6 and with b  n  = 1 and b  n  β  n  modeled as a first-order (linear) polynomial. The black solid and dashed lines show the best-fit models in the non-LTE limit of Equation (7), where β  n  is further expanded as a third-order polynomial. The bottom panel shows the derived models of b  n  β  n  in the non-LTE cases.
Paper: Low-frequency Radio Recombination Lines Away from the Inner Galactic Plane
Authors: Akshatha K. Vydula, Judd D. Bowman, David Lewis, Kelsie Crawford, Matthew Kolopanis, Alan E. E. Rogers, Steven G. Murray, Nivedita Mahesh, Raul A. Monsalve, Peter Sims, Titu Samson
Figure caption: Top: simulated RRL spectrum, similar to Figure 12 but for LST 0–12 hr, away from the inner Galactic plane. Cα, Cβ, and Hα lines are modeled in the 50–100 MHz band with 1 kHz resolution. No other foreground contributions are included. Middle: the simulated spectrum rebinned to 100 kHz, which is approximately the spectral resolution used by HERA. Bottom: delay spectra calculated from the simulated RRLs for three different spectral binnings. These are equivalent to delay spectra from a notional zero-length baseline in an interferometer. Most of the power contributed by the RRLs is above 2 μs delay, corresponding to spectral scales smaller than 500 kHz. The 100 kHz spectral resolution of HERA couples power from smaller scales to larger scales of order 1 MHz. An intermediate spectral resolution of 40 kHz removes much of the coupling to large scales. Even with coupling, the power from scales larger than 500 kHz (<2 μs) contributes less than 10 mk2 to the total 36 mk2 variance in the simulated spectrum with HERA-like resolution.