adsabs/AstroCLIMB huggingface dataset:
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of water−carbon dioxide (H2O−13CO2) ice mixtures before (top) and after (middle) irradiation at 10 K. The infrared spectra of the irradiated sample warmed up to 320 K are shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 6. L and d indicate libration and dangling, respectively.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of water−carbon dioxide (H2O−13CO2) ice mixtures before (top) and after (middle) irradiation at 40 K. The infrared spectra of the irradiated sample warmed up to 320 K are shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 6. L and d indicate libration and dangling, respectively.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of water−carbon monoxide (H2O−13CO) ice mixtures before (top) and after (middle) irradiation at 10 K. The infrared spectra of the irradiated sample warmed up to 320 K are shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 5. L and d indicate libration and dangling, respectively.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of water−carbon monoxide (H2O−13CO) ice mixtures before (top) and after (middle) irradiation at 20 K. The infrared spectra of the irradiated sample warmed up to 320 K are shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 5. L and d indicate libration and dangling, respectively.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of water−methane (H2O−13CH4) ice mixtures before (top) and after (middle) irradiation at 20 K. The infrared spectra of the irradiated sample warmed up to 320 K are shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 3. L indicates libration.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of water−methane (H2O–13CH4) ice mixtures before (top) and after (middle) irradiation at 10 K. The infrared spectra of the irradiated sample warmed up to 320 K are shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 3. L indicates libration.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of water−ammonia (H2O−NH3) ice mixtures before (top) and after (middle) irradiation at 40 K. The infrared spectra of the irradiated sample warmed up to 320 K are shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 4. L indicates libration.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of water−ammonia (H2O−NH3) ice mixtures before (top) and after (middle) irradiation at 10 K. The infrared spectra of the irradiated sample warmed up to 320 K are shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 4. L indicates libration.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of water−methanol (H2O−13CH3OH) ice mixtures before (top) and after (middle) irradiation at 40 K. The infrared spectra of the irradiated sample warmed up to 320 K are shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 7. L indicates libration.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of carbon dioxide−methanol (13CO2−13CH3OH) ice mixtures before (top) and after (middle) irradiation at 10 K. The infrared spectra of the irradiated sample warmed up to 320 K are also shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 17.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Functional groups identified from the infrared spectra of irradiated TNO ice analogs. These groups can be combined into various compounds, suggesting complex species in the outer solar system. Carbon atoms in all groups are the isotopically labeled 13-carbon.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of carbon dioxide−methanol (13CO2−13CH3OH) ice mixtures before (top) and after (middle) irradiation at 40 K. The infrared spectra of the irradiated sample warmed up to 320 K are also shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 17.
Paper: Spectroscopic Study of Ice Analogs of Trans-Neptunian Objects Exposed to Ionizing Radiation. II. Infrared Spectra and Functional Groups
Authors: Chaojiang Zhang, Jia Wang, Andrew M. Turner, Leslie A. Young, Ralf I. Kaiser
Figure caption: Infrared spectra of carbon monoxide−methanol (13CO−13CH3OH) ice mixtures before (top) and after (middle) irradiation at 10 K. The infrared spectra of the irradiated sample warmed up to 320 K are also shown at the bottom. The experimental spectra are plotted in black, the deconvoluted peaks are in blue, and the sums are in red. Only noticeable peaks are labeled for clarity, and detailed peak assignments are listed in Table 16.
Paper: Deep Active Learning–Based Classification of Solar Radio Spectrogram Data
Authors: Yan Liu, 岩 刘, HongQiang Song, 红强 宋, FaBao Yan, 发宝 严, YanRui Su, 艳蕊 苏
Figure caption: Distribution histograms of frequency drift rate for type II and type III bursts.
Paper: A 50–55 GHz Millimeter-wave Radiometer Spectrometer for Solar Flare Detection
Authors: XiaoFeng Xu, 晓峰 徐, ZhanFeng Zhao, 占锋 赵, Qian Liu, 乾 刘, QinZheng Li, 钦正 李, Zhao Wu, 昭 武, Guang Lu, 光 路, YanRui Su, 艳蕊 苏, Yao Chen, 耀 陈, FaBao Yan, 发宝 严
Figure caption: Panel (a) illustrates the LCP channel, highlighting the nonuniform linearity caused by the switching of the output power source of the vector network analyzer. Linear fitting was applied to this region to achieve a smoother input–output curve. Panel (b) illustrates the RCP channel, with the linear region of the system marked. The left half of the −70 dBm level represents the small-signal region of the system input. The right half, indicated by the dashed line, shows a decrease in slope, which is attributed to the nonlinear effects of the microwave components. From these two figures, it can be inferred that the system exhibits linearity within the range of −70 to −35 dBm, where the input–output relationship is more accurately represented.
Paper: A 50–55 GHz Millimeter-wave Radiometer Spectrometer for Solar Flare Detection
Authors: XiaoFeng Xu, 晓峰 徐, ZhanFeng Zhao, 占锋 赵, Qian Liu, 乾 刘, QinZheng Li, 钦正 李, Zhao Wu, 昭 武, Guang Lu, 光 路, YanRui Su, 艳蕊 苏, Yao Chen, 耀 陈, FaBao Yan, 发宝 严
Figure caption: The following information presents the observations of the X1.5-class solar flare on 2024 December 30. The system captured this event with a time resolution of 0.2 s, and the observed flare peak in the frequency range of 50.5–51.5 GHz reached approximately 450 SFU. For comparison, CBSmm has a time resolution of 0.13 s and observed a flare peak of around 1170 SFU at the 35.75 GHz frequency point. The three red dashed lines in the figure indicate the time points used for spectral analysis, specifically 04:08:58, 04:09:58, and 04:11:11.
Paper: A 50–55 GHz Millimeter-wave Radiometer Spectrometer for Solar Flare Detection
Authors: XiaoFeng Xu, 晓峰 徐, ZhanFeng Zhao, 占锋 赵, Qian Liu, 乾 刘, QinZheng Li, 钦正 李, Zhao Wu, 昭 武, Guang Lu, 光 路, YanRui Su, 艳蕊 苏, Yao Chen, 耀 陈, FaBao Yan, 发宝 严
Figure caption: The spectral index map obtained from observations at 35–54 GHz shows a significant evolution of soft–hard–harder during flares.
Paper: A 50–55 GHz Millimeter-wave Radiometer Spectrometer for Solar Flare Detection
Authors: XiaoFeng Xu, 晓峰 徐, ZhanFeng Zhao, 占锋 赵, Qian Liu, 乾 刘, QinZheng Li, 钦正 李, Zhao Wu, 昭 武, Guang Lu, 光 路, YanRui Su, 艳蕊 苏, Yao Chen, 耀 陈, FaBao Yan, 发宝 严
Figure caption: Information before and after data calibration. Panel (a) shows the strength before calibration. It should be noted that the signal strength of the 50.5–51.5 GHz right channel is much higher than that of other channels due to the use of high-sensitivity detectors. Panel (b) shows the radiation flow intensity data of this system after relative calibration.
Paper: A 50–55 GHz Millimeter-wave Radiometer Spectrometer for Solar Flare Detection
Authors: XiaoFeng Xu, 晓峰 徐, ZhanFeng Zhao, 占锋 赵, Qian Liu, 乾 刘, QinZheng Li, 钦正 李, Zhao Wu, 昭 武, Guang Lu, 光 路, YanRui Su, 艳蕊 苏, Yao Chen, 耀 陈, FaBao Yan, 发宝 严
Figure caption: The comparison photo shows data pointing toward the Sun and data pointing toward the cold air. This comparison demonstrates the effectiveness of the system’s observation. The SNR of the system is calculated based on the values obtained from the cold air and the Sun. The actual observed SNR is between 2 and 9 dB.
Paper: SageNet: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation
Authors: Fan Zhang, Yifang Luo, Bohua Li, Ruihan Cao, Wenjin Peng, Joel Meyers, Paul R. Shapiro
Figure caption: Example emulation results. Each panel corresponds to a distinct type of GW spectra. The emulator consistently predicts the correct evolutionary trends, variations, frequency limits, and specific ﹩{{\mathrm{log}}}_{10}\,{{\rm{\Omega }}}_{{\rm{GW}}}({f}_{i})﹩ values, regardless of the variability in the spectral shapes. Surprisingly, it also reproduces the density distribution of the sample points along the frequency axis, accurately reconstructing the sampling patterns in both high-variation and quasi-linear segments of the curves. The gray areas represent the predicted error distribution, for which the errors in both fi and ﹩{{\mathrm{log}}}_{10}\,{{\rm{\Omega }}}_{{\rm{GW}}}({f}_{i})﹩ are combined to obtain a more rigorous assessment than standard methods. In sparsely sampled segments, although the positions of the predicted points (blue) deviate from the original data (red), these points lie on almost the same curve as the original ones.
Paper: SageNet: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation
Authors: Fan Zhang, Yifang Luo, Bohua Li, Ruihan Cao, Wenjin Peng, Joel Meyers, Paul R. Shapiro
Figure caption: Error distribution of test emulations. This histogram illustrates the performance of the emulator predictions against the ground truth of the test samples. The horizontal axis represents the dimensionless SMAPE, and the vertical axis represents the normalized frequency counts (bin areas standardized to 1). Notably, 90.9% of predictions achieve a SMAPEEval of under 4%, and 86.0% of the samples have an SMAPEEval of less than 3%, highlighting the accuracy and robustness of our emulator. A small fraction of the predicted samples exhibit higher SMAPE values, attributed to the fact that the predicted {fi} sequence is not necessarily in ascending order, as is the true GW spectrum sequence. These errors are hence not real and can be eliminated by reordering the predicted ﹩\{{f}_{i},\,{{\mathrm{log}}}_{10}\,{{\rm{\Omega }}}_{{\rm{GW}}}({f}_{i})\}﹩ sequence.
Paper: SageNet: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation
Authors: Fan Zhang, Yifang Luo, Bohua Li, Ruihan Cao, Wenjin Peng, Joel Meyers, Paul R. Shapiro
Figure caption: Error density distribution across predicted points. Errors are normalized to the interval [0, 1] and color coded. High error points (yellow) are concentrated in sparsely sampled segments of the curves. Nevertheless, these errors do not undermine the overall accuracy of the GW spectra reconstructed by SageNet.
Paper: SageNet: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation
Authors: Fan Zhang, Yifang Luo, Bohua Li, Ruihan Cao, Wenjin Peng, Joel Meyers, Paul R. Shapiro
Figure caption: Wall times for producing 100 random samples using three methods. The brute-force numerical method shows significant variabilities in the computation times, for which even low-demand cases (<100 points) take ﹩{ \mathcal O }(10)﹩ s. By contrast, our neural network approach can output results within ∼7 ms on an Intel Core i7-11800H CPU, with the potential for further GPU acceleration.
Paper: SageNet: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation
Authors: Fan Zhang, Yifang Luo, Bohua Li, Ruihan Cao, Wenjin Peng, Joel Meyers, Paul R. Shapiro
Figure caption: Three-dimensional error density distribution. This visualization highlights that larger errors occur at sparsely sampled segments of the curves, while the densely sampled segments exhibit minimal residuals.
Paper: SageNet: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation
Authors: Fan Zhang, Yifang Luo, Bohua Li, Ruihan Cao, Wenjin Peng, Joel Meyers, Paul R. Shapiro
Figure caption: Training loss curve of the SageNet model. The model initially produces random predictions and learns rapidly within the first 10 epochs (upper panel). After the 10th epoch, the learning curve gradually stabilizes, though the loss continues to decrease. By the 80th epoch (lower panel), the validation loss curve flattens out at ∼0.01.
Paper: SageNet: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation
Authors: Fan Zhang, Yifang Luo, Bohua Li, Ruihan Cao, Wenjin Peng, Joel Meyers, Paul R. Shapiro
Figure caption: Comparison between the distribution of the original numerical samples and that of the predicted samples from emulations. The apparent resemblance demonstrates that SageNet can learn both physical information and artificial sampling patterns simultaneously.
Paper: SageNet: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation
Authors: Fan Zhang, Yifang Luo, Bohua Li, Ruihan Cao, Wenjin Peng, Joel Meyers, Paul R. Shapiro
Figure caption: Architecture of SageNet.
Paper: SageNet: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation
Authors: Fan Zhang, Yifang Luo, Bohua Li, Ruihan Cao, Wenjin Peng, Joel Meyers, Paul R. Shapiro
Figure caption: Structure of an LSTM unit.
Paper: The TESS Ten Thousand Catalog: 10,001 Uniformly Vetted and Validated Eclipsing Binary Stars Detected in Full-frame Image Data by Machine Learning and Analyzed by Citizen Scientists
Authors: Veselin B. Kostov, Brian P. Powell, Aline U. Fornear, Marco Z. Di Fraia, Robert Gagliano, Thomas L. Jacobs, Julien S. de Lambilly, Hugo A. Durantini Luca, Steven R. Majewski, Mark Omohundro, Jerome Orosz, Saul A. Rappaport, Ryan Salik, Donald Short, William Welsh, Svetoslav Alexandrov, Cledison Marcos da Silva, Erika Dunning, Gerd Gühne, Marc Huten, Michiharu Hyogo, Davide Iannone, Sam Lee, Christian Magliano, Manya Sharma, Allan Tarr, John Yablonsky, Sovan Acharya, Fred Adams, Thomas Barclay, Benjamin T. Montet, Susan Mullally, Greg Olmschenk, Andrej Prša, Elisa Quintana, Robert Wilson, Hasret Balcioglu, Ethan Kruse
Figure caption: The distributions of the TESS magnitudes, orbital periods, photocenter offsets, and number of sectors observed for the 7936 new EBs in our catalog. A darker shade represents a higher number of targets. Most of the EBs are faint, have short orbital periods, have detected eclipses that originate within ∼1″–2″ of the respective target star, and have been observed by TESS in at least three sectors.
Paper: The TESS Ten Thousand Catalog: 10,001 Uniformly Vetted and Validated Eclipsing Binary Stars Detected in Full-frame Image Data by Machine Learning and Analyzed by Citizen Scientists
Authors: Veselin B. Kostov, Brian P. Powell, Aline U. Fornear, Marco Z. Di Fraia, Robert Gagliano, Thomas L. Jacobs, Julien S. de Lambilly, Hugo A. Durantini Luca, Steven R. Majewski, Mark Omohundro, Jerome Orosz, Saul A. Rappaport, Ryan Salik, Donald Short, William Welsh, Svetoslav Alexandrov, Cledison Marcos da Silva, Erika Dunning, Gerd Gühne, Marc Huten, Michiharu Hyogo, Davide Iannone, Sam Lee, Christian Magliano, Manya Sharma, Allan Tarr, John Yablonsky, Sovan Acharya, Fred Adams, Thomas Barclay, Benjamin T. Montet, Susan Mullally, Greg Olmschenk, Andrej Prša, Elisa Quintana, Robert Wilson, Hasret Balcioglu, Ethan Kruse
Figure caption: The distributions of Gaia’s AEN, AENS, RUWE, and effective temperatures for the 7936 new EBs presented here. The vertical dashed lines represent AENS = 3 (left panel) and RUWE = 1.4 (middle panel), potentially suggesting unresolved companions.
Paper: The TESS Ten Thousand Catalog: 10,001 Uniformly Vetted and Validated Eclipsing Binary Stars Detected in Full-frame Image Data by Machine Learning and Analyzed by Citizen Scientists
Authors: Veselin B. Kostov, Brian P. Powell, Aline U. Fornear, Marco Z. Di Fraia, Robert Gagliano, Thomas L. Jacobs, Julien S. de Lambilly, Hugo A. Durantini Luca, Steven R. Majewski, Mark Omohundro, Jerome Orosz, Saul A. Rappaport, Ryan Salik, Donald Short, William Welsh, Svetoslav Alexandrov, Cledison Marcos da Silva, Erika Dunning, Gerd Gühne, Marc Huten, Michiharu Hyogo, Davide Iannone, Sam Lee, Christian Magliano, Manya Sharma, Allan Tarr, John Yablonsky, Sovan Acharya, Fred Adams, Thomas Barclay, Benjamin T. Montet, Susan Mullally, Greg Olmschenk, Andrej Prša, Elisa Quintana, Robert Wilson, Hasret Balcioglu, Ethan Kruse
Figure caption: Left panel: distribution of the detected secondary eclipses as a function of the orbital phase. Middle and right panels: the two EBs with the most extreme secondary phases, TIC 149673382 with phase ≈0.87 (middle) and TIC 337097515 with phase ≈0.11 (right panel), both exhibiting a heartbeat “bump.”
Paper: The TESS Ten Thousand Catalog: 10,001 Uniformly Vetted and Validated Eclipsing Binary Stars Detected in Full-frame Image Data by Machine Learning and Analyzed by Citizen Scientists
Authors: Veselin B. Kostov, Brian P. Powell, Aline U. Fornear, Marco Z. Di Fraia, Robert Gagliano, Thomas L. Jacobs, Julien S. de Lambilly, Hugo A. Durantini Luca, Steven R. Majewski, Mark Omohundro, Jerome Orosz, Saul A. Rappaport, Ryan Salik, Donald Short, William Welsh, Svetoslav Alexandrov, Cledison Marcos da Silva, Erika Dunning, Gerd Gühne, Marc Huten, Michiharu Hyogo, Davide Iannone, Sam Lee, Christian Magliano, Manya Sharma, Allan Tarr, John Yablonsky, Sovan Acharya, Fred Adams, Thomas Barclay, Benjamin T. Montet, Susan Mullally, Greg Olmschenk, Andrej Prša, Elisa Quintana, Robert Wilson, Hasret Balcioglu, Ethan Kruse
Figure caption: TESS FFI ELEANOR lightcurve of TIC 173706211 for all available sectors at the time of writing. Sector 84 is completely dominated by systematics. As a result, the ephemeris measured from Sectors 16 and 17 is not significantly improved with the addition of the latest data.
Paper: The TESS Ten Thousand Catalog: 10,001 Uniformly Vetted and Validated Eclipsing Binary Stars Detected in Full-frame Image Data by Machine Learning and Analyzed by Citizen Scientists
Authors: Veselin B. Kostov, Brian P. Powell, Aline U. Fornear, Marco Z. Di Fraia, Robert Gagliano, Thomas L. Jacobs, Julien S. de Lambilly, Hugo A. Durantini Luca, Steven R. Majewski, Mark Omohundro, Jerome Orosz, Saul A. Rappaport, Ryan Salik, Donald Short, William Welsh, Svetoslav Alexandrov, Cledison Marcos da Silva, Erika Dunning, Gerd Gühne, Marc Huten, Michiharu Hyogo, Davide Iannone, Sam Lee, Christian Magliano, Manya Sharma, Allan Tarr, John Yablonsky, Sovan Acharya, Fred Adams, Thomas Barclay, Benjamin T. Montet, Susan Mullally, Greg Olmschenk, Andrej Prša, Elisa Quintana, Robert Wilson, Hasret Balcioglu, Ethan Kruse
Figure caption: TESS FFI ELEANOR lightcurve of TIC 5232381 for Sector 9 (left) and Sector 62 (right). The vertical span is the same for both panels. The eclipse depths are different between the two sectors due to systematic effects caused by contamination from TIC 5232374.