adsabs/AstroCLIMB huggingface dataset:
Paper: Improving Power Spectrum Estimation Using Multitapering: Efficient Asteroseismic Analyses for Understanding Stars, the Milky Way, and Beyond
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 佳士 沈, David J. Thomson
Figure caption: Comparison between LS, mtNUFFT, and the true spectrum used to simulate an asteroseismic time series (refer to Section 2.3 for more details of the simulation). The top and bottom panels show the NW = 3, K = 5 and NW = 4, K = 7 mtNUFFT periodograms, respectively. The insets at the top right of the two panels zoom into two p-modes; mtNUFFT is able to estimate the PSD more accurately than the LS by reducing both bias and variance. We also see that the resolution slightly reduces as we increase NW, but it does not affect mode estimation in this case.
Paper: Improving Power Spectrum Estimation Using Multitapering: Efficient Asteroseismic Analyses for Understanding Stars, the Milky Way, and Beyond
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 佳士 沈, David J. Thomson
Figure caption: Comparison between 95% jackknife confidence intervals of the classical multitaper (transparent orange) and mtNUFFT (transparent blue) power spectrum estimates of regular and quasi-regular AR(4) process (N = 44544) time series respectively. The confidence intervals are consistent with each other showing that interpolation of DPSS tapers to Kepler-like time series introduces minor nonorthogonality, and allows us to compute the jackknife variance. Note that the high-frequency power spectrum estimates have larger differences because of spectral leakage due to uneven time sampling.
Paper: Improving Power Spectrum Estimation Using Multitapering: Efficient Asteroseismic Analyses for Understanding Stars, the Milky Way, and Beyond
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 佳士 沈, David J. Thomson
Figure caption:  PBjam peakbagging fit for the Kepler-91 time series using the LS (top panel) and mtNUFFT (bottom panel) periodograms. Both panels show an SNR power spectrum estimate (data) in gray along with its smoothed version using a 1D Gaussian filter kernel in black. The panels also show the model fits (red) to the radial l = 0 and quadrupole l = 2 modes obtained in Step 2 of PBjam. It is evident that the variance of the mtNUFFT SNR power spectrum estimate is much smaller than that of the LS periodogram, which leads to more efficient peakbagging than LS.
Paper: Improving Power Spectrum Estimation Using Multitapering: Efficient Asteroseismic Analyses for Understanding Stars, the Milky Way, and Beyond
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 佳士 沈, David J. Thomson
Figure caption: Comparison between distributions of LS and multitaper power spectrum estimates. LS is χ 2 distributed with degrees of freedom df = 2 as shown by the dashed line in black. mtLS and mtNUFFT are ﹩{\chi }_{2K}^{2}﹩ distributed, where K is the number of tapers. We show the K = 2 (df = 4) and K = 7 (df = 14) distributions in blue and dark pink curves. As K (or df) increases, the ﹩{\chi }_{2K}^{2}﹩ approaches a normal distribution with symmetric values around the mean, leading to better noise properties for the mtNUFFT periodogram.
Paper: Improving Power Spectrum Estimation Using Multitapering: Efficient Asteroseismic Analyses for Understanding Stars, the Milky Way, and Beyond
Authors: Aarya A. Patil, Gwendolyn M. Eadie, Joshua S. Speagle, 佳士 沈, David J. Thomson
Figure caption: Comparison between the NUFFT and the mtNUFFT periodograms of the Kepler-91 time series. The parameters of the multitaper periodograms are NW = 4 and K = 7. The mtNUFFT periodogram in blue has smaller variance compared to the untapered counterpart in gray. The inset shows the zoomed-in mtNUFFT periodogram along with its 95% jackknife confidence interval.
Paper: Gemini High-resolution Optical Spectrograph (GHOST) at Gemini South: Instrument Performance and Integration, First Science, and Next Steps
Authors: V. M. Kalari, R. J. Diaz, G. Robertson, A. McConnachie, M. Ireland, R. Salinas, P. Young, C. Simpson, C. Hayes, J. Nielsen, G. Burley, J. Pazder, M. Gomez-Jimenez, E. Martioli, S. B. Howell, M. Jeong, S. Juneau, R. Ruiz-Carmona, S. Margheim, A. Sheinis, A. Anthony, G. Baker, T. A. M. Berg, T. Cao, E. Chapin, T. Chin, K. Chiboucas, V. Churilov, E. Deibert, A. Densmore, J. Dunn, M. L. Edgar, J. Heo, D. Henderson, T. Farrell, J. Font, V. Firpo, J. Fuentes, K. Labrie, S. Lambert, J. Lawrence, J. Lothrop, R. McDermid, B. W. Miller, G. Perez, V. M. Placco, P. Prado, C. Quiroz, F. Ramos, R. Rutten, K. M. G. Silva, J. Thomas-Osip, C. Urrutia, W. D. Vacca, K. Venn, F. Waller, L. Waller, M. White, S. Xu, R. Zhelem
Figure caption: Top: cutout of a standard-resolution slit unit flat from the dual IFU (SRIFU1 and SRIFU2). The microlenses are arranged horizontally, with seven IFU1 microlenses, three sky microlenses, and seven IFU2 microlenses from left to right. The pseudo-slit is captured in the slit-viewing unit (receiving 1% of the light entering the spectrograph), where it is split into red and blue pseudo-slits. The filter bandpasses of the slit-viewing camera are given in Table 3. The top reconstructed slit is seen through a blue filter and the bottom one through a red filter. Bottom: cutout of a high-resolution slit unit flat from a single high-resolution IFU. The slits are reversed in the vertical direction for display purposes, and there are 19 IFU1 microlenses and seven sky microlenses visible. Microlens 62 is the final internal arc lamp microlens (not shown) and is separated from microlens 61 by an empty microlens. The final pseudo-slit image is tilted by 11°. Microlens nomenclature is the same as in Figure 3.
Paper: Gemini High-resolution Optical Spectrograph (GHOST) at Gemini South: Instrument Performance and Integration, First Science, and Next Steps
Authors: V. M. Kalari, R. J. Diaz, G. Robertson, A. McConnachie, M. Ireland, R. Salinas, P. Young, C. Simpson, C. Hayes, J. Nielsen, G. Burley, J. Pazder, M. Gomez-Jimenez, E. Martioli, S. B. Howell, M. Jeong, S. Juneau, R. Ruiz-Carmona, S. Margheim, A. Sheinis, A. Anthony, G. Baker, T. A. M. Berg, T. Cao, E. Chapin, T. Chin, K. Chiboucas, V. Churilov, E. Deibert, A. Densmore, J. Dunn, M. L. Edgar, J. Heo, D. Henderson, T. Farrell, J. Font, V. Firpo, J. Fuentes, K. Labrie, S. Lambert, J. Lawrence, J. Lothrop, R. McDermid, B. W. Miller, G. Perez, V. M. Placco, P. Prado, C. Quiroz, F. Ramos, R. Rutten, K. M. G. Silva, J. Thomas-Osip, C. Urrutia, W. D. Vacca, K. Venn, F. Waller, L. Waller, M. White, S. Xu, R. Zhelem
Figure caption: Overview of major systems within the telescope (adapted from A. I. Sheinis et al. 2016). 1 and 2 represent the Cassegrain unit mounted on either the side or the up-looking port respectively, with the ballast frame also shown. 3 indicates the instrument support structure. 4 marks the fiber cable, 5 shows the cable passing through the anchor and to the pier lab, and 6 marks the location of the hole in the Gemini South pier lab that allows the fiber cable to pass through and land in the pier lab indicated by 7. Additionally, the locations of the fiber agitator and the acquisition and guiding unit (which includes the internal ThXe lamp) outside the bench thermal enclosure are shown by 8 and 9 respectively. 10 marks the outer enclosure, which is thermally enclosed, and a pressure-monitored chamber containing the bench spectrograph inside the inner enclosure. A human being is shown for scale.
Paper: Gemini High-resolution Optical Spectrograph (GHOST) at Gemini South: Instrument Performance and Integration, First Science, and Next Steps
Authors: V. M. Kalari, R. J. Diaz, G. Robertson, A. McConnachie, M. Ireland, R. Salinas, P. Young, C. Simpson, C. Hayes, J. Nielsen, G. Burley, J. Pazder, M. Gomez-Jimenez, E. Martioli, S. B. Howell, M. Jeong, S. Juneau, R. Ruiz-Carmona, S. Margheim, A. Sheinis, A. Anthony, G. Baker, T. A. M. Berg, T. Cao, E. Chapin, T. Chin, K. Chiboucas, V. Churilov, E. Deibert, A. Densmore, J. Dunn, M. L. Edgar, J. Heo, D. Henderson, T. Farrell, J. Font, V. Firpo, J. Fuentes, K. Labrie, S. Lambert, J. Lawrence, J. Lothrop, R. McDermid, B. W. Miller, G. Perez, V. M. Placco, P. Prado, C. Quiroz, F. Ramos, R. Rutten, K. M. G. Silva, J. Thomas-Osip, C. Urrutia, W. D. Vacca, K. Venn, F. Waller, L. Waller, M. White, S. Xu, R. Zhelem
Figure caption: The microlenses in the two probe arms are labeled and shown in the instrument’s focal plane, with their distance translated to the on-sky scale. The microlenses for scientific purposes are indicated in black, those for guiding in red, and those for capturing sky information in blue. These labeled microlenses can be matched with the pseudo-slit image and echellogram. To maintain clarity, the guide microlenses are not labeled.
Paper: Gemini High-resolution Optical Spectrograph (GHOST) at Gemini South: Instrument Performance and Integration, First Science, and Next Steps
Authors: V. M. Kalari, R. J. Diaz, G. Robertson, A. McConnachie, M. Ireland, R. Salinas, P. Young, C. Simpson, C. Hayes, J. Nielsen, G. Burley, J. Pazder, M. Gomez-Jimenez, E. Martioli, S. B. Howell, M. Jeong, S. Juneau, R. Ruiz-Carmona, S. Margheim, A. Sheinis, A. Anthony, G. Baker, T. A. M. Berg, T. Cao, E. Chapin, T. Chin, K. Chiboucas, V. Churilov, E. Deibert, A. Densmore, J. Dunn, M. L. Edgar, J. Heo, D. Henderson, T. Farrell, J. Font, V. Firpo, J. Fuentes, K. Labrie, S. Lambert, J. Lawrence, J. Lothrop, R. McDermid, B. W. Miller, G. Perez, V. M. Placco, P. Prado, C. Quiroz, F. Ramos, R. Rutten, K. M. G. Silva, J. Thomas-Osip, C. Urrutia, W. D. Vacca, K. Venn, F. Waller, L. Waller, M. White, S. Xu, R. Zhelem
Figure caption: Field of view of the Cassegrain unit overlaid on a simulated sky image, with the dimensions marked. The total diameter subtended on the sky is 7.′34, beyond which the probes suffer from vignetting. The field of view of each IFU semicircle is marked, with the overlapping region also shown. The labels are offset from the center for display. The closest separation between the two IFUs (not shown) is 102″.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: The MAC sends the state transfer diagram of the state machine.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: UWLPIPE process flow.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: J0332+5434's subband dynamic spectrum diagram. (a) subband0, (b) subband1, (c) subband2, (d) subband3, (e) subband4, and (f) subband5.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: GPU node configuration.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: Observation information.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: Multiple subbands splicing broadband signals.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: Multichannel coherent dispersion process.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: J0332+5434's dynamic spectrum diagram.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: NSRT pulsar observation test scheme.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: J1935+1616's subband dynamic spectrum diagram. (a) subband0, (b) subband1, (c) subband2, (d) subband3, (e) subband4, and (f) subband5.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: J2022+5154's subband dynamic spectrum diagram. (a) subband0, (b) subband1, (c) subband2, (d) subband3, (e) subband4, and (f) subband5.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: Dynamic spectrum of J2022+2854. (a) subband0, (b) subband1, (c) subband2, (d) subband3, (e) subband4, and (f) subband5.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: J1935+1616's dynamic spectrum diagram.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: J2022+5154's dynamic spectrum diagram.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: J2022+2854's dynamic spectrum diagram.
Paper: An Ultrawide Bandwidth Digital Backend System Based on PFB Algorithm for QTT
Authors: Hai-long Zhang, Ya-zhou Zhang, Shao-cong Guo, Xu Du, Na Wang, Jie Wang, Xin-chen Ye, Han Wu, Jian Li, Xin Pei, Qiao Meng
Figure caption: J0332+5434 bandpass spectrum.
Paper: Submillimeter and Mid-Infrared Variability of Young Stellar Objects in the M17SWex Intermediate-mass Star-forming Region
Authors: Geumsook Park, Doug Johnstone, Carlos Contreras Peña, Jeong-Eun Lee, Sheng-Yuan Liu, Gregory Herczeg, Steve Mairs, Zhiwei Chen, Jennifer Hatchell, Kee-Tae Kim, Mi-Ryang Kim, Keping Qiu, Yao-Te Wang, Xu Zhang
Figure caption: Summary flowchart outlining the mid-IR sample selection and light-curve variability classification process. Our methodology, based on the approach used by Park et al. (2021), identifies six types of variables, secular (linear, periodic, curved) and stochastic (burst, drop, irregular), among known YSO candidates in the WISE W1 and W2 bands (refer to Section 3.3 for additional details). The quantity Δ(mag) represents the difference between the maximum and minimum values of the magnitude, while SD and σ(mag) (or simply σ) denote the standard deviation and mean uncertainty of magnitudes across all epochs for a given source, respectively. This methodology was applied to each band separately. The number of objects that satisfy each flowchart criteria is indicated in the figure. Where two numbers are provided, the first is for W1 and the second for W2.
Paper: Submillimeter and Mid-Infrared Variability of Young Stellar Objects in the M17SWex Intermediate-mass Star-forming Region
Authors: Geumsook Park, Doug Johnstone, Carlos Contreras Peña, Jeong-Eun Lee, Sheng-Yuan Liu, Gregory Herczeg, Steve Mairs, Zhiwei Chen, Jennifer Hatchell, Kee-Tae Kim, Mi-Ryang Kim, Keping Qiu, Yao-Te Wang, Xu Zhang
Figure caption: Scatter plots of mean peak flux at 850 μm against (a) the standard deviation of the peak flux normalized by the fiducial model and (b) the absolute value of slope S ratioed to its uncertainty ΔS for submillimeter sources identified in M17 SWex. Sources with a mean peak flux greater than 100 mJy beam−1 are shown in red, while all others are in gray. The dashed lines in each panel indicate thresholds used to identify variable candidates. The dashed vertical line indicates a mean peak flux of 100 mJy beam−1, the threshold for sources bright enough for statistical significance. The dashed horizontal line in Panel (a) indicates 2.5 times the fiducial expectation, a threshold for reliability for stochastic variability. The dashed horizontal line in Panel (b) indicates where ∣S/ΔS∣ = 3, which is the threshold for reliability for linear variability as defined by Johnstone et al. (2018). The sources that are marked in red in the upper-right corners are considered to be robust variables. There is one robust stochastic variable in (a) and there are two robust linear secular variables in (b).
Paper: Submillimeter and Mid-Infrared Variability of Young Stellar Objects in the M17SWex Intermediate-mass Star-forming Region
Authors: Geumsook Park, Doug Johnstone, Carlos Contreras Peña, Jeong-Eun Lee, Sheng-Yuan Liu, Gregory Herczeg, Steve Mairs, Zhiwei Chen, Jennifer Hatchell, Kee-Tae Kim, Mi-Ryang Kim, Keping Qiu, Yao-Te Wang, Xu Zhang
Figure caption: Positions of target source peaks within the M17 SWex observation area at submillimeter (a) and mid-IR (b)–(c). The 850 μm image in (a) is a coadded image from 23 epochs, with a 30 mJy beam−1 contour overlaid. Target source peaks with a mean peak flux greater than 100 mJy beam−1 are marked with pink circles, while those with a mean peak flux less than 100 mJy beam−1 are shown with gray triangles. Three submillimeter robust variables are highlighted with teal and orange diamonds. The mid-IR images in (b–c) show WISE W1 and W2 data acquired during the first epoch used (2014 March), overlaid with the 850 μm contour shown from the (a) image. YSOs within our JCMT-observed area are marked: pink circles indicate those identified with WISE data, while gray crosses indicate those not identified. Additionally, royal-blue crosses mark YSOs cataloged by Kuhn et al. (2021) that were not included in any group in their study. Colored squares highlight mid-IR variables identified in this study. The color scales are displayed on the right side of each map, and the units are (a) mJy beam−1 and (b), (c) arbitrary counts.
Paper: Submillimeter and Mid-Infrared Variability of Young Stellar Objects in the M17SWex Intermediate-mass Star-forming Region
Authors: Geumsook Park, Doug Johnstone, Carlos Contreras Peña, Jeong-Eun Lee, Sheng-Yuan Liu, Gregory Herczeg, Steve Mairs, Zhiwei Chen, Jennifer Hatchell, Kee-Tae Kim, Mi-Ryang Kim, Keping Qiu, Yao-Te Wang, Xu Zhang
Figure caption: The light curve of potential stochastic (a) or linear (b) variable submillimeter candidates based on the 23 epochs of JCMT observations. The black solid and dotted lines represent the mean and ±1σ standard deviations, while the red dotted lines show the expected fiducial standard deviations. The upper x-axis indicates the time relative to the first epoch.
Paper: Submillimeter and Mid-Infrared Variability of Young Stellar Objects in the M17SWex Intermediate-mass Star-forming Region
Authors: Geumsook Park, Doug Johnstone, Carlos Contreras Peña, Jeong-Eun Lee, Sheng-Yuan Liu, Gregory Herczeg, Steve Mairs, Zhiwei Chen, Jennifer Hatchell, Kee-Tae Kim, Mi-Ryang Kim, Keping Qiu, Yao-Te Wang, Xu Zhang
Figure caption: Overview of YSO classification and data selection: (a) Distribution of mean magnitudes for the final sample of YSOs across different evolutionary stages: Class 0/I, Class II, Class III, and ambiguous classifications, shown in magenta, orange, blue, and gray, respectively. (b) Nested pie charts representing population statistics for YSOs at various stages of data collection and analysis for both WISE W1 and W2 bands. Each segment within the charts corresponds to a distinct YSO type, with the outer ring representing the total count of that type, the middle ring showing those with WISE data, and the innermost ring indicating the count in the final sample. The percentages on the pie charts reflect the proportion of each YSO type within the respective layer and the percentage of the total count for each YSO type.
Paper: Submillimeter and Mid-Infrared Variability of Young Stellar Objects in the M17SWex Intermediate-mass Star-forming Region
Authors: Geumsook Park, Doug Johnstone, Carlos Contreras Peña, Jeong-Eun Lee, Sheng-Yuan Liu, Gregory Herczeg, Steve Mairs, Zhiwei Chen, Jennifer Hatchell, Kee-Tae Kim, Mi-Ryang Kim, Keping Qiu, Yao-Te Wang, Xu Zhang
Figure caption: Representative light curves of several sources, observed in both the WISE W1 (green) and W2 (blue) bands. The source identifier is provided in the bottom right corner of each panel.
Paper: Submillimeter and Mid-Infrared Variability of Young Stellar Objects in the M17SWex Intermediate-mass Star-forming Region
Authors: Geumsook Park, Doug Johnstone, Carlos Contreras Peña, Jeong-Eun Lee, Sheng-Yuan Liu, Gregory Herczeg, Steve Mairs, Zhiwei Chen, Jennifer Hatchell, Kee-Tae Kim, Mi-Ryang Kim, Keping Qiu, Yao-Te Wang, Xu Zhang
Figure caption: Comparison of SD/SDfid and Δmag for all sources in the final samples of W1 (a) and W2 (b). The dashed vertical line indicates the commonly used threshold value of SD/SDfid equal to 3 for identifying sources with brightness variability. The classification of YSOs is indicated by the filled circle colors, which are consistent with those used in Figure 5. Variable candidates among the YSOs are denoted by a bordered circle, with the color of the border circle indicating the type of variability, while sources that were excluded during the analysis because they have a Δmag/σ(mag) < 3 are marked with the gray bordered circle.
Paper: Submillimeter and Mid-Infrared Variability of Young Stellar Objects in the M17SWex Intermediate-mass Star-forming Region
Authors: Geumsook Park, Doug Johnstone, Carlos Contreras Peña, Jeong-Eun Lee, Sheng-Yuan Liu, Gregory Herczeg, Steve Mairs, Zhiwei Chen, Jennifer Hatchell, Kee-Tae Kim, Mi-Ryang Kim, Keping Qiu, Yao-Te Wang, Xu Zhang
Figure caption: Comparison of the FAPs for linear and periodic fits for all sources in the final samples of W1 (a) and W2 (b). The dashed vertical line represents a FAP of 10−4 for the linear fit, while the dashed horizontal line represents a FAP of 10−2 for the periodic fit. Symbols and colors used in this figure are consistent with those presented in Figure 6, representing different evolutionary stages and the five types of mid-IR flux variability identified in our study.
Paper: Submillimeter and Mid-Infrared Variability of Young Stellar Objects in the M17SWex Intermediate-mass Star-forming Region
Authors: Geumsook Park, Doug Johnstone, Carlos Contreras Peña, Jeong-Eun Lee, Sheng-Yuan Liu, Gregory Herczeg, Steve Mairs, Zhiwei Chen, Jennifer Hatchell, Kee-Tae Kim, Mi-Ryang Kim, Keping Qiu, Yao-Te Wang, Xu Zhang
Figure caption: Coadded 850 μm image of M17 SWex using 23 epochs and with contours overlaid at (1100, 2000, 4000, 9000) mJy beam−1.
Paper: Submillimeter and Mid-Infrared Variability of Young Stellar Objects in the M17SWex Intermediate-mass Star-forming Region
Authors: Geumsook Park, Doug Johnstone, Carlos Contreras Peña, Jeong-Eun Lee, Sheng-Yuan Liu, Gregory Herczeg, Steve Mairs, Zhiwei Chen, Jennifer Hatchell, Kee-Tae Kim, Mi-Ryang Kim, Keping Qiu, Yao-Te Wang, Xu Zhang
Figure caption: Mid-IR light curves for sources in the final WISE sample, included in either the W1 or W2 analysis, are presented. The total number of sources is 179. Sources shown in Figure 9 are not included here. The first 40 sources exhibit flux variability in either the W1 or W2 band. The subsequent panels display sources that were not observed to vary in this study. The source identifier is provided in the bottom right corner of each panel.