adsabs/AstroCLIMB huggingface dataset:
Paper: Dynamical Architectures of S-type Transiting Planets in Binaries. I. Target Selection Using Hipparcos and Gaia Proper Motion Anomalies 
Authors: Jingwen Zhang, 婧雯 张, Lauren M. Weiss, Daniel Huber, Eric L. N. Jensen, Timothy D. Brandt, Karen Collins, Dennis M. Conti, Howard Isaacson, Pablo Lewin, Giuseppe Marino, Bob Massey, Felipe Murgas, Enric Palle, Don J. Radford, Howard M. Relles, Gregor Srdoc, Chris Stockdale, Thiam-Guan Tan, Gavin Wang
Figure caption: Gaia differential velocity distribution of TOIs with significant proper motion anomalies (red) compared to field stars (blue). The field star sample consists of all stars with significant proper motion anomalies from HGCA within 300 pc. The differential velocities are in log scale. We exclude TOIs with FP/FA disposition.
Paper: Dynamical Architectures of S-type Transiting Planets in Binaries. I. Target Selection Using Hipparcos and Gaia Proper Motion Anomalies 
Authors: Jingwen Zhang, 婧雯 张, Lauren M. Weiss, Daniel Huber, Eric L. N. Jensen, Timothy D. Brandt, Karen Collins, Dennis M. Conti, Howard Isaacson, Pablo Lewin, Giuseppe Marino, Bob Massey, Felipe Murgas, Enric Palle, Don J. Radford, Howard M. Relles, Gregor Srdoc, Chris Stockdale, Thiam-Guan Tan, Gavin Wang
Figure caption: Observed and fitted absolute astrometry for the LTT 1445 system. The two panels show the position angle and relative separation of LTT 1445 BC. The thicker black lines represent the best-fit orbit in the MCMC chain while the other 20 lines represent random draws from the chain.
Paper: Dynamical Architectures of S-type Transiting Planets in Binaries. I. Target Selection Using Hipparcos and Gaia Proper Motion Anomalies 
Authors: Jingwen Zhang, 婧雯 张, Lauren M. Weiss, Daniel Huber, Eric L. N. Jensen, Timothy D. Brandt, Karen Collins, Dennis M. Conti, Howard Isaacson, Pablo Lewin, Giuseppe Marino, Bob Massey, Felipe Murgas, Enric Palle, Don J. Radford, Howard M. Relles, Gregor Srdoc, Chris Stockdale, Thiam-Guan Tan, Gavin Wang
Figure caption: Gaia color-absolute magnitude diagram for our targets (star signs) and stars in HGCA within 300 pc (gray dots). TOI/KOI/K2 planet candidate hosts with significant proper motion anomalies are color coded by the S/N of their proper motion anomalies at the Gaia epoch (S/NG).
Paper: Direct Exoplanet Detection using Convolutional Image Reconstruction (ConStruct): A New Algorithm for Post-processing High-contrast Images
Authors: Trevor N. Wolf, Brandon A. Jones, Brendan P. Bowler
Figure caption: Pixel-wise speckle prediction residuals in a fixed spatial patch ﹩{\mathbb{Y}}﹩ accumulated over all frames in an ADI sequence. Each of the samples is first linearly scaled between 0 and 1. The orange distributions are residuals after subtracting the time-averaged pixel-wise intensity from each frame; the purple distributions are the autoencoder prediction residuals; and the green distributions are the prediction residuals augmented with an additional linear regression. The vertical dashed lines indicate the ±1σ bounds on the residuals. The autoencoder prediction and regularized least-squares regression in ConStruct progressively improves the prediction accuracy, yielding the most accurate speckle prediction, shown in the green distribution.
Paper: Direct Exoplanet Detection using Convolutional Image Reconstruction (ConStruct): A New Algorithm for Post-processing High-contrast Images
Authors: Trevor N. Wolf, Brandon A. Jones, Brendan P. Bowler
Figure caption: The partitioning of regions ﹩{\mathbb{X}}﹩, ﹩{\mathbb{Y}}﹩, and ﹩{\mathbb{D}}﹩ in an ADI frame. Each region can in principle be any shape and size. In forming the partitions, the region ﹩{\mathbb{Y}}﹩ is hypothesized to contain a point source, and ﹩{\mathbb{X}}﹩ contains only speckle noise.
Paper: Direct Exoplanet Detection using Convolutional Image Reconstruction (ConStruct): A New Algorithm for Post-processing High-contrast Images
Authors: Trevor N. Wolf, Brandon A. Jones, Brendan P. Bowler
Figure caption: Autoencoder prediction of the speckle noise intensity in a masked region of an ADI sequence. The image patch is extracted from a frame in Sequence 9 in Table 1. It is linearly scaled to values between 0 and 1 before being fed into the autoencoder. Panels (a) and (b) are the masked autoencoder input and the ground-truth region of interest, respectively. Panel (c) is the ground truth, with an injected Gaussian signal with a peak scaled intensity of 0.2. Panel (d) is the prediction formed by passing the masked input into our network. Panels (e) and (f) are the residual images produced by subtracting the predicted image region from the ground truth without and with the injected source, respectively. ConStruct can accurately reconstruct the ground truth over the mask, and recover the injected source.
Paper: Direct Exoplanet Detection using Convolutional Image Reconstruction (ConStruct): A New Algorithm for Post-processing High-contrast Images
Authors: Trevor N. Wolf, Brandon A. Jones, Brendan P. Bowler
Figure caption: Graphical illustration of the autoencoder architecture used in ConStruct. From left to right, an image region of interest is fed into the network, with the central region ﹩{\mathbb{Y}}﹩ masked. In this example, the autoencoder is constructed such that it is compatible with a 32 × 32 pixel image patch. The encoder and decoder portions of the network act sequentially to first transform the masked image into a low-dimensional feature space, then back into the original input space. By training the network with many examples, the network learns to accurately predict the masked central region. Here, we include the sizes for the output from each encoder and decoder block.
Paper: Direct Exoplanet Detection using Convolutional Image Reconstruction (ConStruct): A New Algorithm for Post-processing High-contrast Images
Authors: Trevor N. Wolf, Brandon A. Jones, Brendan P. Bowler
Figure caption: Graphical illustration of how sector regions are extracted and processed by ConStruct on ADI sequences. Each plane represents a frame in the ADI sequence. Sectors are extracted from each frame, and geometrically transformed into square arrays for processing. The center of each array is masked before being fed into the autoencoder.
Paper: Searching the SN 1987A SETI Ellipsoid with TESS
Authors: Bárbara Cabrales, James R. A. Davenport, Sofia Sheikh, Steve Croft, Andrew P. V. Siemion, Daniel Giles, Ann Marie Cody
Figure caption: Gaia (G bp − G rp, M  G ) color–magnitude diagram (CMD) for the 32 stars that we find intersect the SN 1987A Ellipsoid (black stars with error bars). The entire sample of 329,176 TESS 2 minute targets is shown for reference, with point colors indicating the Gaia colors. The theoretical location of the Sun is also shown (orange star). Ellipsoid targets in TESS Cycles 1–3 include main-sequence, subgiant, and giant branch stars. Three stars are found with near-solar locations in the CMD.
Paper: Searching the SN 1987A SETI Ellipsoid with TESS
Authors: Bárbara Cabrales, James R. A. Davenport, Sofia Sheikh, Steve Croft, Andrew P. V. Siemion, Daniel Giles, Ann Marie Cody
Figure caption: Galactocentric Y-Z plane for TESS stars, color-coded to show the location of the southern CVZ and their designation within the SETI Ellipsoid framework for SN 1987A. A total of 214,995 stars have seen SN 1987A (dashed line) but are outside of the Ellipsoid (green points). A total of 97,514 stars have not observed SN 1987A (gray points). A total of 23,148 stars are inside the SN 1987A Ellipsoid (yellow points), implying that any coordinated beacon has already passed the Earth. A total of 736 stars are laying on the SN 1987A Ellipsoid (orange points). The 7850 southern CVZ stars are shown in pink. A total of 37 targets are both on the Ellipsoid and in the southern CVZ (black stars) and are our targets of interest. The contour of the SETI Ellipsoid in the YZ plane is shown as a solid line. The Sun is also plotted (blue cross).
Paper: Searching the SN 1987A SETI Ellipsoid with TESS
Authors: Bárbara Cabrales, James R. A. Davenport, Sofia Sheikh, Steve Croft, Andrew P. V. Siemion, Daniel Giles, Ann Marie Cody
Figure caption: Normalized light curves for six selected SN 1987A Ellipsoid crossing targets that exhibit interesting behavior related to stellar variability, described in the main text. Common “Time” and “Flux” labels are displayed for the entire figure. Each light curve is color-coded by TESS sector to aid in viewing. The vertical red line in each plot indicates the crossing time with the SN 1987A Ellipsoid. The vertical black lines show the uncertainty window of the crossing time calculated in Section 3. None of these objects show any change in their light-curve behavior coincident with the Ellipsoid crossing times.
Paper: Searching the SN 1987A SETI Ellipsoid with TESS
Authors: Bárbara Cabrales, James R. A. Davenport, Sofia Sheikh, Steve Croft, Andrew P. V. Siemion, Daniel Giles, Ann Marie Cody
Figure caption: Histogram of simulated distances of the Cycle 1 Ellipsoid candidates (top) and the Cycle 3 Ellipsoid candidates (bottom) to the SN 1987A Ellipsoid using a Monte Carlo method of random draws in a Gaussian distribution calculated from Gaia's distance errors. Common "Distance to Ellipsoid" and "Frequency" labels are displayed for the entire figure. Even when including all sources of uncertainty, all 32 of these targets have a standard deviation smaller than 0.5 lt-yr. The peaks of these distributions are also within 0.5 lt-yr, as expected from the etol value chosen in Section 3.3.
Paper: Searching the SN 1987A SETI Ellipsoid with TESS
Authors: Bárbara Cabrales, James R. A. Davenport, Sofia Sheikh, Steve Croft, Andrew P. V. Siemion, Daniel Giles, Ann Marie Cody
Figure caption: Distance to the Ellipsoid in time for targets on Cycles 1 (top) and 3 (bottom). The slope of these lines corresponds to 99.9% the speed of light. The Ellipsoid crossing times are the zeros in each line. Targets with lines that start and end later than the rest belong to targets whose first observation was not in Cycle 3's first sector.
Paper: A Combined Ground-based and JWST Atmospheric Retrieval Analysis: Both IGRINS and NIRSpec Agree that the Atmosphere of WASP-77A b Is Metal-poor
Authors: Peter C. B. Smith, Michael R. Line, Jacob L. Bean, Matteo Brogi, Prune August, Luis Welbanks, Jean-Michel Desert, Jonathan Lunine, Jorge Sanchez, Megan Mansfield, Lorenzo Pino, Emily Rauscher, Eliza Kempton, Joseph Zalesky, Martin Fowler
Figure caption: Top: the median spectrum from 2000 random draws from the IGRINS pre-eclipse retrieval (red line) and 1σ distribution about the median (red shaded region). The median spectrum from 2000 draws from the NIRSpec retrieval is in blue, and the 1σ distribution is so tightly around this median it is not visible in this figure. The NIRSpec data are plotted with diamonds, with the color indicating the difference in the median log-likelihood. While the predictions from the IGRINS retrieval are largely consistent with the NIRSpec data, they struggle to predict the data around 4 μm the most. Middle: similar to the top panel, but now in red is the median spectrum resulting from combining random draws from the IGRINS gas posteriors but the NIRSpec P-T posteriors. Bottom: draws from the combined IGRINS+NIRSpec retrieval. Similar to the NIRSpec retrieval, the 1σ contours are not visible.
Paper: A Combined Ground-based and JWST Atmospheric Retrieval Analysis: Both IGRINS and NIRSpec Agree that the Atmosphere of WASP-77A b Is Metal-poor
Authors: Peter C. B. Smith, Michael R. Line, Jacob L. Bean, Matteo Brogi, Prune August, Luis Welbanks, Jean-Michel Desert, Jonathan Lunine, Jorge Sanchez, Megan Mansfield, Lorenzo Pino, Emily Rauscher, Eliza Kempton, Joseph Zalesky, Martin Fowler
Figure caption: Marginalized posterior distributions for the abundances of H2O and CO, as well as posterior draws of the P-T profile when removing three (red) and four (blue) PCs from the post-eclipse data. For comparison, shown are the same marginalized posteriors for the pre-eclipse data when 12 PCs are removed.
Paper: A Combined Ground-based and JWST Atmospheric Retrieval Analysis: Both IGRINS and NIRSpec Agree that the Atmosphere of WASP-77A b Is Metal-poor
Authors: Peter C. B. Smith, Michael R. Line, Jacob L. Bean, Matteo Brogi, Prune August, Luis Welbanks, Jean-Michel Desert, Jonathan Lunine, Jorge Sanchez, Megan Mansfield, Lorenzo Pino, Emily Rauscher, Eliza Kempton, Joseph Zalesky, Martin Fowler
Figure caption: The first four left singular vectors for order 26 (1.69–1.71 μm) from the sequence taken on December 21 compared to the continuum level, air mass, and humidity. Each column corresponds to the nth singular value, indicated at the top. For each left singular vector, we search for both linear (blue) and quadratic (red) correlations with these. The correlation coefficients for linear and quadratic fits are shown, with a value of ≥0.5 being considered a significant correlation. In this particular order, it appears that effects from humidity are captured in the first two singular vectors, whereas the continuum takes the first three, and there still remains a correlation with air mass in the fourth.
Paper: A Combined Ground-based and JWST Atmospheric Retrieval Analysis: Both IGRINS and NIRSpec Agree that the Atmosphere of WASP-77A b Is Metal-poor
Authors: Peter C. B. Smith, Michael R. Line, Jacob L. Bean, Matteo Brogi, Prune August, Luis Welbanks, Jean-Michel Desert, Jonathan Lunine, Jorge Sanchez, Megan Mansfield, Lorenzo Pino, Emily Rauscher, Eliza Kempton, Joseph Zalesky, Martin Fowler
Figure caption: Marginalized posterior distributions of relevant parameters from retrievals on the post-eclipse data with four PCs removed (red), NIRSpec (blue), and the two combined (purple). Only lower limits would be placed on the abundances of H2O and CO from the post-eclipse data alone. By combining it with the NIRSpec data, we are able to use what gas abundance information there was in that data and gain more precise estimates for these values than afforded by NIRSpec alone.
Paper: A Combined Ground-based and JWST Atmospheric Retrieval Analysis: Both IGRINS and NIRSpec Agree that the Atmosphere of WASP-77A b Is Metal-poor
Authors: Peter C. B. Smith, Michael R. Line, Jacob L. Bean, Matteo Brogi, Prune August, Luis Welbanks, Jean-Michel Desert, Jonathan Lunine, Jorge Sanchez, Megan Mansfield, Lorenzo Pino, Emily Rauscher, Eliza Kempton, Joseph Zalesky, Martin Fowler
Figure caption: Top: cross-correlation map for the post-eclipse data calculated as described in Section 3 when removing the first four PCs from the data. Bottom: similar cross-correlation map but when removing only the first three PCs.
Paper: A Combined Ground-based and JWST Atmospheric Retrieval Analysis: Both IGRINS and NIRSpec Agree that the Atmosphere of WASP-77A b Is Metal-poor
Authors: Peter C. B. Smith, Michael R. Line, Jacob L. Bean, Matteo Brogi, Prune August, Luis Welbanks, Jean-Michel Desert, Jonathan Lunine, Jorge Sanchez, Megan Mansfield, Lorenzo Pino, Emily Rauscher, Eliza Kempton, Joseph Zalesky, Martin Fowler
Figure caption: The first four eigenvectors (columns) from the SVD on order 26 for each night (rows). In this particular echelle order, all three nights have a common first eigenvector, while December 6 appears to have an extra eigenvector associated with the second singular value. The third eigenvector on December 6 resembles the second eigenvectors on December 14 and December 21.
Paper: A Combined Ground-based and JWST Atmospheric Retrieval Analysis: Both IGRINS and NIRSpec Agree that the Atmosphere of WASP-77A b Is Metal-poor
Authors: Peter C. B. Smith, Michael R. Line, Jacob L. Bean, Matteo Brogi, Prune August, Luis Welbanks, Jean-Michel Desert, Jonathan Lunine, Jorge Sanchez, Megan Mansfield, Lorenzo Pino, Emily Rauscher, Eliza Kempton, Joseph Zalesky, Martin Fowler
Figure caption: Left: marginalized posterior distributions of the H2O and CO gas abundances from retrievals on the full post-eclipse sequence (red), the first half only (blue), and the second half only (purple). Right: median retrieved day- and nightside P-T profiles from the two P-T retrieval in Section 6.6.
Paper: A Combined Ground-based and JWST Atmospheric Retrieval Analysis: Both IGRINS and NIRSpec Agree that the Atmosphere of WASP-77A b Is Metal-poor
Authors: Peter C. B. Smith, Michael R. Line, Jacob L. Bean, Matteo Brogi, Prune August, Luis Welbanks, Jean-Michel Desert, Jonathan Lunine, Jorge Sanchez, Megan Mansfield, Lorenzo Pino, Emily Rauscher, Eliza Kempton, Joseph Zalesky, Martin Fowler
Figure caption: Cumulative variance projected onto each PC for each night of IGRINS data. Because the number of PCs is determined by the rank of a matrix, sequences with fewer frames have fewer PCs; therefore, a higher fraction of variance is projected onto a given component compared to a longer sequence.
Paper: The Inner Disk Rim of HD 163296: Linking Radiative Hydrostatic Models with Infrared Interferometry
Authors: Ondřej Chrenko, Mario Flock, Takahiro Ueda, Antoine Mérand, Myriam Benisty, Raúl O. Chametla
Figure caption: Temperature profile (represented by filled contours) in the meridional plane of the disk models M1 (top), M2 (middle), and M3 (bottom). Individual curves show where: the dust grains start to condense (solid gray), the dust is fully condensed (solid black), the radially integrated optical depth to stellar irradiation becomes unity (solid white), and the vertically integrated optical depth to infrared emission becomes unity (dashed green). Blue arrows delimit the radial range of the inner disk rim. As we plot z/r on the vertical axis (where z is the height above the midplane and r is the spherical radius), we point out that radially propagating irradiating rays would appear as horizontal lines.
Paper: The Inner Disk Rim of HD 163296: Linking Radiative Hydrostatic Models with Infrared Interferometry
Authors: Ondřej Chrenko, Mario Flock, Takahiro Ueda, Antoine Mérand, Myriam Benisty, Raúl O. Chametla
Figure caption: Half-light radius (top) and fractional disk flux (bottom) as functions of the wavelength. We show synthetic data corresponding to models M1 (blue), M2 (red), and M3 (black), as well as data corresponding to previous morphological studies of the inner disk emission (black points and error bars; Lazareff et al. 2017; GRAVITY Collaboration et al. 2019; Varga et al. 2021). The wavelength range at the bottom panel is limited to λ < 5 μm in order to highlight the differences at shorter wavelengths (the dependence at larger wavelengths is asymptotic and therefore less interesting).
Paper: The Inner Disk Rim of HD 163296: Linking Radiative Hydrostatic Models with Infrared Interferometry
Authors: Ondřej Chrenko, Mario Flock, Takahiro Ueda, Antoine Mérand, Myriam Benisty, Raúl O. Chametla
Figure caption: Top: Opacity of dust grains as a function of the wavelength λ. We show the absorption opacity κ abs (solid black curve) and the scattering opacity κ sca (dashed gray curve). Dotted blue horizontal lines mark the values of Planck-averaged opacities to thermal emission κ d(T s) and to stellar irradiation κ d(T ⋆). Planck-averaged opacities are utilized in our hydrostatic models with radiative diffusion, while the wavelength-dependent opacities are used to ray trace synthetic images using RADMC-3D. Bottom: Stellar spectrum used in RADMC-3D. Individual points represent the frequency sampling.
Paper: The Inner Disk Rim of HD 163296: Linking Radiative Hydrostatic Models with Infrared Interferometry
Authors: Ondřej Chrenko, Mario Flock, Takahiro Ueda, Antoine Mérand, Myriam Benisty, Raúl O. Chametla
Figure caption: Comparison of ﹩{B}_{\tfrac{1}{2}}\times {R}_{\mathrm{hl}}﹩ for various analytical profiles of I  ν . Each radial profile (left) is plotted as a function of r/R hl. For each profile, the visibility is computed as a function of ﹩B/{B}_{\tfrac{1}{2}}﹩ (center). Finally, we compare (right) ﹩{B}_{\tfrac{1}{2}}\times {R}_{\mathrm{hl}}﹩ as a function of k (which parameterizes the various intensity profiles) and find that it is fairly independent of the function used to represent I  ν .
Paper: The Inner Disk Rim of HD 163296: Linking Radiative Hydrostatic Models with Infrared Interferometry
Authors: Ondřej Chrenko, Mario Flock, Takahiro Ueda, Antoine Mérand, Myriam Benisty, Raúl O. Chametla
Figure caption: Visibility ∣V∣ as a function of the deprojected spatial frequency. Colored areas represent bundles of synthetic visibility curves in bands H (blue), K (green), and L (red) that are derived from our models M1 (top), M2 (middle), and M3 (bottom). Data points show the VLTI observations from the 2019 epoch taken with the PIONIER (circles), GRAVITY (triangles), and MATISSE (crosses) instruments. The wavelength intervals of synthetic visibilities and observations are the same and are given in the plot legend.
Paper: The Inner Disk Rim of HD 163296: Linking Radiative Hydrostatic Models with Infrared Interferometry
Authors: Ondřej Chrenko, Mario Flock, Takahiro Ueda, Antoine Mérand, Myriam Benisty, Raúl O. Chametla
Figure caption: Synthetic images (emission intensity maps) derived from models M1 (top), M2 (middle), and M3 (bottom) at wavelengths λ = 1.75 and 3.5 μm (left and right column, respectively). We point out that the intensity is shown in the linear scale and the range of color bars slightly differs between the left and right column. The emission of the central star is masked. The blue arrow marks the approximate radial range of the disk rim defined in Figure 3. The white scale bar corresponds to 0.5 au.
Paper: The Inner Disk Rim of HD 163296: Linking Radiative Hydrostatic Models with Infrared Interferometry
Authors: Ondřej Chrenko, Mario Flock, Takahiro Ueda, Antoine Mérand, Myriam Benisty, Raúl O. Chametla
Figure caption: Radial profiles of the midplane temperature (top), IR photospheric temperature (middle), and gas surface density Σ (bottom) for models M1 (blue curve), M2 (red curve), and M3 (black curve). The top panel distinguishes four characteristic regions of dusty inner rims (see Flock et al. 2016; Ueda et al. 2017, for details).
Paper: The Inner Disk Rim of HD 163296: Linking Radiative Hydrostatic Models with Infrared Interferometry
Authors: Ondřej Chrenko, Mario Flock, Takahiro Ueda, Antoine Mérand, Myriam Benisty, Raúl O. Chametla
Figure caption: Summary of results for model M3Fe. Top: temperature distribution in the meridional plane of the disk (compare with Figure 3). Middle: fractional disk flux as a function of the wavelength (compare with Figure 5). Bottom: synthetic visibility curves compared to observations (compare with Figure 6).
Paper: Large Interferometer For Exoplanets (LIFE). XII. The Detectability of Capstone Biosignatures in the Mid-infrared—Sniffing Exoplanetary Laughing Gas and Methylated Halogens
Authors: Daniel Angerhausen, Daria Pidhorodetska, Michaela Leung, Janina Hansen, Eleonora Alei, Felix Dannert, Jens Kammerer, Sascha P. Quanz, Edward W. Schwieterman
Figure caption: Results for TRAPPIST-1 type star in 100 days.
Paper: Large Interferometer For Exoplanets (LIFE). XII. The Detectability of Capstone Biosignatures in the Mid-infrared—Sniffing Exoplanetary Laughing Gas and Methylated Halogens
Authors: Daniel Angerhausen, Daria Pidhorodetska, Michaela Leung, Janina Hansen, Eleonora Alei, Felix Dannert, Jens Kammerer, Sascha P. Quanz, Edward W. Schwieterman
Figure caption: Results for TRAPPIST-1 type star in 10 days.
Paper: Revised Architecture and Two New Super-Earths in the HD 134606 Planetary System
Authors: Zhexing Li, Stephen R. Kane, Timothy D. Brandt, Tara Fetherolf, Paul Robertson, Jinglin Zhao, Paul A. Dalba, Robert A. Wittenmyer, R. Paul Butler, Matías R. Díaz, Steve B. Howell, Jeremy Bailey, Brad Carter, Elise Furlan, Crystal L. Gnilka, Jonathan Horner, Hugh R. A. Jones, Simon O'Toole, Chris Tinney
Figure caption:  RVSearch result of the HD 134606 system. The upper panels show the best fit along with residuals to the model. Individual fits to each of the five signals are shown in the lower panels along with their periodograms. Panel (m) shows a running periodogram for the five signals. No more significant signal is found in the residual as shown in panel (n).