adsabs/AstroCLIMB huggingface dataset:
Paper: MOMOS: The Multi-Object MKID Optical Spectrometer Simulator and Data Reduction Package
Authors: Crystal S. Kim, John I. Bailey, Ronald A. López, W. Hawkins Clay, Benjamin A. Mazin
Figure caption: Example phase histogram in the on-blaze grating setup for ﹩{{\mathscr{R}}}_{{\rm{MKID}}}=15﹩ with the initial guess, converged fitting function Gi, and virtual pixel (order) boundaries.
Paper: MOMOS: The Multi-Object MKID Optical Spectrometer Simulator and Data Reduction Package
Authors: Crystal S. Kim, John I. Bailey, Ronald A. López, W. Hawkins Clay, Benjamin A. Mazin
Figure caption: Difference in bin width and distribution of photons between similar MOMOS simulations with ﹩{{\mathscr{R}}}_{\mathrm{MKID}}﹩ of 15 (top) and 60 (bottom), for the same pixel.
Paper: Chemical Abundance Gradients in Open Clusters from the Gaia/LAMOST Sample
Authors: Guochao Yang, Jingkun Zhao, Yong Yang, Nian Liu, Yangping Luo, Gang Zhao
Figure caption: Spatial distribution of OCs in this work in Galactocentric coordinates. Blue and red filled circles represent clusters younger and older than 1 Gyr, respectively. The Sun is positioned at (8.21, 0, 0.0208) kpc, while the Galactic center lies at (0, 0, 0) kpc. In the left and middle panels, the dashed circles, with a radius equal to the Sun-to-Galactic-center distance, are centered on the Galactic center.
Paper: Clouds and Hazes in GJ 1214 b’s Metal-rich Atmosphere
Authors: Isaac Malsky, Emily Rauscher, Kevin Stevenson, Arjun B. Savel, Maria E. Steinrueck, Peter Gao, Eliza M.-R. Kempton, Michael T. Roman, Jacob L. Bean, Michael Zhang, Vivien Parmentier, Anjali A. A. Piette, Tiffany Kataria
Figure caption: Revised phase-curve amplitudes for GJ 1214 b. Both Eureka! analyses (blue and orange points) are consistent; however, the 0.25 μm reduction shows significant scatter between adjacent bins. Compared to those reported by E. Kempton et al. (2023, black points), the revised Aobs values are generally lower. This is consistent with the warmer nightside flux seen in Figure 10 when fitting for the step function at 1.0278 days.
Paper: Orbital and Absolute Magnitude Distribution of Hilda Population
Authors: David Vokrouhlický, David Nesvorný, Miroslav Brož, William F. Bottke, Rogerio Deienno, Carson D. Fuls, Frank C. Shelly
Figure caption: Upper panel: histogram of the absolute magnitude H values for detections of Hildas during the CSS phase I (left panels) and II (right panels) operations (the ordinate is the number of such detections within the bin). The vertical dashed line shows the magnitude at the center of a bin in which number of detections dropped below 5% of the bin with maximum number of detections. This value is about  ≃17.2 for both phases. Bottom panel: correlation between the absolute magnitude H at the abscissa and visual magnitude m at the ordinate for Hilda detections during the CSS phase I and II operations. At an ideal opposition, when a high-eccentricity Hilda asteroid would be near perihelion, m − H ≃ 3.3 (neglecting the phase function correction) from simple distance arguments (slanted dotted line). In the opposite worst situation, when the same Hilda object would be near aphelion and high phase, m − H ≃ 7.7 (slanted dashed line). There are more than four magnitude difference between these cases. The reason is mainly due to the large eccentricity of some Hilda orbits and the possibility to observe them at phase angles up to  ≃20∘ (both values are larger than for Jupiter Trojans, for which the apparent magnitude spread is only about 2 mag, e.g., Figure 4 in D. Vokrouhlický et al. 2024). The horizontal dotted lines between visual magnitudes 20.5 and 21.5 indicate typical 50% photometric efficiency of detections. Some objects brighter than m ≃ 14.5 (lower dotted line) may saturate exposures and be undetected due to their slow motion.
Paper: Orbital and Absolute Magnitude Distribution of Hilda Population
Authors: David Vokrouhlický, David Nesvorný, Miroslav Brož, William F. Bottke, Rogerio Deienno, Carson D. Fuls, Frank C. Shelly
Figure caption: Osculating orbital eccentricity e (abscissa) vs. absolute magnitude H (ordinate) for 4316 Hildas detected during the CSS II period (a similar trend is seen also in the CSS I detections). The slanted lines show two different type of correlations: (i) the dashed line expresses an observational bias allowing us to detect fainter Hildas only when they are near perihelion of their orbit, while (ii) the dotted line indicates an intrinsic property of the Hildas having larger eccentricity orbits populated by fainter members. The latter is likely due to the Yarkovsky-driven diffusion of the resonant population like Hildas toward larger eccentricities.
Paper: Orbital and Absolute Magnitude Distribution of Hilda Population
Authors: David Vokrouhlický, David Nesvorný, Miroslav Brož, William F. Bottke, Rogerio Deienno, Carson D. Fuls, Frank C. Shelly
Figure caption: Detections of Hilda asteroids by the CSS operations in between 2013 January 2 and 2016 May 14 (phase I; left panel), and between 2016 May 31 and 2022 June 14 (phase II; right panel). There are 8686 detections of 2970 individual Hildas during the phase I, and 28,930 detections of 4317 individual Hildas during the phase II. The blue symbols are topocentric R.A. (abscissa) and decl. (ordinate) of the observations. The red line is the Jupiter track in the same period of time near the ecliptic plane (the sense of motion during the displayed period of time is along the increasing R.A. value). The solid black line is the projection of the galactic plane surrounded by the  ±15∘ latitude strip (gray region). The black star is the direction to the galactic center.
Paper: Orbital and Absolute Magnitude Distribution of Hilda Population
Authors: David Vokrouhlický, David Nesvorný, Miroslav Brož, William F. Bottke, Rogerio Deienno, Carson D. Fuls, Frank C. Shelly
Figure caption: Number of Hilda observations in the CSS operations (phases I and II separated by the vertical dashed line). Apart from the obvious annual variation (determined both by the seasonal changes and summer maintenance gaps) and more data collected during the phase II due to the camera upgrade, there is also a longer-term variation due to the Jupiter motion and its relative position to the galactic plane.
Paper: I-band Asymptotic Giant Branch (IAGB) Stars. II. A First Estimate of Their Precision and a Differential Zero Point 
Authors: Wendy L. Freedman, Barry F. Madore, Taylor Hoyt, In Sung Jang, Abigail J. Lee, Kayla A. Owens
Figure caption: NGC galaxies (cont.) See Figure 3 for description.
Paper: I-band Asymptotic Giant Branch (IAGB) Stars. II. A First Estimate of Their Precision and a Differential Zero Point 
Authors: Wendy L. Freedman, Barry F. Madore, Taylor Hoyt, In Sung Jang, Abigail J. Lee, Kayla A. Owens
Figure caption: Named galaxies. See Figure 3 for description.
Paper: I-band Asymptotic Giant Branch (IAGB) Stars. II. A First Estimate of Their Precision and a Differential Zero Point 
Authors: Wendy L. Freedman, Barry F. Madore, Taylor Hoyt, In Sung Jang, Abigail J. Lee, Kayla A. Owens
Figure caption: Same as Figure 1 except this sample has been downselected to remove 23 galaxies that were deemed to be suboptimal for TRGB measurements based on the placement of their points largely in the disks of these galaxies.
Paper: I-band Asymptotic Giant Branch (IAGB) Stars. II. A First Estimate of Their Precision and a Differential Zero Point 
Authors: Wendy L. Freedman, Barry F. Madore, Taylor Hoyt, In Sung Jang, Abigail J. Lee, Kayla A. Owens
Figure caption: European Southern Obserrvatory (ESO) galaxies. See Figure 3 for description.
Paper: I-band Asymptotic Giant Branch (IAGB) Stars. II. A First Estimate of Their Precision and a Differential Zero Point 
Authors: Wendy L. Freedman, Barry F. Madore, Taylor Hoyt, In Sung Jang, Abigail J. Lee, Kayla A. Owens
Figure caption: New General Catalogue (NGC) galaxies. See Figure 3 for description.
Paper: I-band Asymptotic Giant Branch (IAGB) Stars. II. A First Estimate of Their Precision and a Differential Zero Point 
Authors: Wendy L. Freedman, Barry F. Madore, Taylor Hoyt, In Sung Jang, Abigail J. Lee, Kayla A. Owens
Figure caption: ESO galaxies (cont.) See Figure 2 for description.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Mapping accuracy with different failure rates. The mapping success rate of different light-spot mapping methods in the overlapping area varies with the failure rate. The blue line represents DM, the purple line represents LM, and the green line represents PM. The probability potential field-based light-spot mapping method proposed in this paper has the highest fault stability in the overlapping area.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Mapping accuracy for different RFPs. Success rate of light-spot mapping for different types of RFPs. With an increasing failure rate, the success rate of using the light-spot mapping algorithm proposed in this article is higher than that of the nearest neighbor mapping method, and it can ensure a mapping accuracy of over 95% even with the 10% failure probability. Figure (b) enlarges the four curves of Figure (a).
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Schematic diagram of the second type of operation. Figure (a) shows a schematic diagram of the points, where the blue dot is the start point of operation, and the dark red is the target point of operation. Figure (b) shows a simulation diagram of the operation process. Figure (c) shows the construction of its probability field. The green dots are the target points of an adjacent RFP.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Schematic diagram of the fourth type of operation. Figure (a) shows a schematic diagram of the points, where the blue dot is the start point of operation, and the dark red is the target point of operation. Figure (b) shows a simulation diagram of the operation process. Figure (c) shows the construction of its probability field. The green dots are the target points of an adjacent RFP.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Schematic diagram of the third type of operation. Figure (a) shows a schematic diagram of the points, where the blue dot is the start point of operation, and the dark red is the target point of operation. Figure (b) shows a simulation diagram of the operation process. Figure (c) shows the construction of its probability field. The green dots are the target points of an adjacent RFP.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Schematic diagram of the first type of operation. Figure (a) shows a schematic diagram of the points, where the blue dot is the start point of operation, and the dark red is the target point of operation. Figure (b) shows a simulation diagram of the operation process. Figure (c) shows the construction of its probability field. The green dots are the target points of an adjacent RFP.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Variation in the mapping success rate of different light-spot mapping methods with the failure rate. The blue line represents the target-position-based DM, the purple line represents LM, and the green line represents PM.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: LAMOST fiber positioning photogrammetric system. Figure (a) shows a physical image of the focal plane of LAMOST. Figure (b) shows a schematic diagram of the installation of the LAMOST FVCs (K. Zhao et al. 2018). Figure (c) shows the field of view of the six LAMOST FVCs in the focal plane.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Workflow of the LAMOST closed-loop optical fiber positioning system. The light-spot mapping algorithm is incorporated in the third step of calculating the positions of RFPs.
Paper: The Lack of RR Lyrae Variables in Ultrafaint Dwarf Galaxy Sextans II
Authors: Chow-Choong Ngeow, Anupam Bhardwaj
Figure caption: Comparisons of the two α-enhanced synthetic CMD (red points, vertically shifted using μ0 = 20.8 mag), generated from using the BaSTI online tool (A. Pietrinferni et al. 2021), to the possible members of Sextans II (orange points). The input parameters for both of the synthetic CMD are: age of 13 Gyr, [Fe/H] = −2.2 dex, no binary fraction, and using the P. Kroupa et al. (1993) initial mass function. The integrated gr-band magnitudes of the synthetic CMD were converted to V band using the transformation given in S. Jester et al. (2005), and the resulting MV are given in the top-left corner of each panel. The vertical arrow on the right panel indicates the synthetic RR Lyrae identified from the synthetic CMD by BaSTI.
Paper: The Lack of RR Lyrae Variables in Ultrafaint Dwarf Galaxy Sextans II
Authors: Chow-Choong Ngeow, Anupam Bhardwaj
Figure caption: Color–magnitude diagram for Sextans II with possible members provided by M. Gatto (2024—private communication). The photometry for these possible members have been corrected for extinction (for details see M. Gatto et al. 2024). The dashed and dotted curves are the evolutionary tracks for two α-enhanced horizontal branch mass models (M in unit of solar mass) at [Fe/H] = −2.2 dex (M. Gatto et al. 2024; D. Homma et al. 2024), shifted with the distance moduli (μ0) of 20.5 mag (D. Homma et al. 2024) and 20.8 mag (M. Gatto et al. 2024). These models were taken from the BaSTI library (A. Pietrinferni et al. 2021). The vertical cyan dashed–dotted lines marked the (rough) boundaries of the RR Lyrae instability strip. Stars within the rectangle were selected to search for RR Lyrae (see Section 3).
Paper: The Lack of RR Lyrae Variables in Ultrafaint Dwarf Galaxy Sextans II
Authors: Chow-Choong Ngeow, Anupam Bhardwaj
Figure caption: Zoomed-in version of Figure 2. The color bar represents the r-band amplitudes, defined as the numerical difference between the maximum and minimum magnitudes of the observed data points. Note that the gr-band magnitudes are time-averaged values derived from the DECam light curves. Folded light curves for the six labeled stars, similar to Figure 3, are shown in Figure 4.
Paper: The Lack of RR Lyrae Variables in Ultrafaint Dwarf Galaxy Sextans II
Authors: Chow-Choong Ngeow, Anupam Bhardwaj
Figure caption: Top panel: the multiband Lomb–Scargle (LS) periodogram for BB Sex based on the DECam light-curve data, the vertical dashed line indicates the best period found by gatspy. Bottom panels: folded griz-band DECam light curves based on the best-found period of P = 0.52563 days. The black dashed curves are the best-fit template light curves adopted from B. Sesar et al. (2010). Note that the error bars are smaller than the size of the symbols.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Positioning results obtained with the light-spot mapping method. Figure (a) shows the residual statistical histogram of the RFPs and the target positions. Figure (b) shows the X-direction residual statistical histogram of the RFPs and the target positions. Gaussian fitting was used to obtain a mean of −2.0 um and a standard deviation of 9.4 um. Figure (c) shows the Y-direction residual statistical histogram of the RFPs and the target positions. Gaussian fitting was used to obtain a mean of −2.7 um and a standard deviation of 9.2 um.
Paper: The Lack of RR Lyrae Variables in Ultrafaint Dwarf Galaxy Sextans II
Authors: Chow-Choong Ngeow, Anupam Bhardwaj
Figure caption: Comparison of the histograms for UFDs with and without detected RR Lyrae, based on the list compiled in C.-C. Ngeow & A. Bhardwaj (2024). The vertical red dashed line marks the location of Sextans II.
Paper: The Lack of RR Lyrae Variables in Ultrafaint Dwarf Galaxy Sextans II
Authors: Chow-Choong Ngeow, Anupam Bhardwaj
Figure caption: CMD for stars in the vicinity of Sextans II, including possible members (red squares) and additional stars queried from the SDSS DR16 (gray points; photometry for all of these stars are in the SDSS system). We only search the potential RR Lyrae for SDSS stars located inside the rectangle, which is the same as in Figure 2. The HB tracks are the same as in Figure 2.
Paper: The Lack of RR Lyrae Variables in Ultrafaint Dwarf Galaxy Sextans II
Authors: Chow-Choong Ngeow, Anupam Bhardwaj
Figure caption: Similar to Figure 3, but for the six stars labeled in Figure 5. The period P referred to as the best period returned from gatspy, which might not be the true period.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Star observation results. The horizontal axis represents the magnitude of the celestial body, the vertical axis represents the logarithmic value of the flux count on the CCD of the spectrometer, and above the red line are the optical fibers with better flux for the celestial body.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Dual-rotation RFP of LAMOST. Figure (a) shows a schematic diagram of the LAMOST dual-rotation RFP, which is an equal-arm structure, with the central axis and eccentric axis having equal lengths of 8.25 mm, covering a patrol range of 33 mm in diameter. The central axis of the RFP can rotate 360°, and the eccentric axis can rotate 180°. Figure (b) shows a physical image of the LAMOST dual-rotation RFP head. The white color represents the ceramic head equipped with optical fibers, with the optical fibers located at the center of the ceramic head.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Schematic diagram of light-spot mapping. Figure (a) displays a front-illuminated image of the RFPs, with each RFP labeled by its corresponding number. Light green arrows indicate the ceramic heads of the RFPs, with the center of the ceramic head containing the optical fiber. Figure (b) presents a contrast-enhanced back-illuminated image of the RFPs, in which the white dots represent the optical fiber light spots of the RFPs. This study aims to achieve the mapping effect in Figure (b) similar to that in Figure (a), linking the RFP numbers to the light spots.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Back-illuminated light-spot diagram. Figure (a) shows the light-spot image of dual-rotation RFPs captured by FVC. Figure (b) shows the fiber backlight spot of a single RFP. Figure (c) shows the Gaussian distribution of the light-spot grayscale.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: Schematic diagram of the dual-rotation RFP of SDSS-V. Figure (a) shows the results of the β arm in the fully deployed state (β = 180°) and fully retracted state (β = 0°). Figure (b) shows the positioning interference between each RFP and its surrounding RFPs. The black point represents the center point of the RFP, the light-blue part represents the actual positioning area, and the dark blue part represents the nonlocatable area. Taking the central positioning RFP as an example, its dark blue part overlaps with the light-blue parts of the six surrounding RFPs, and positioning in this part can be achieved by the surrounding RFPs.
Paper: Back-illuminated Light-spot-mapping Algorithm for Dual Rotation Robotic Fiber Positioners Based on an Artificial Probability Potential Field Method
Authors: Yingfu Wang, Jiahao Zhou, Ziming Liu, Rongfeng Chen, Jiacheng Xie, Hongzhuan Hu, Jianping Wang, Zhigang Liu, Jiaru Chu, Feifan Zhang, Haotong Zhang, Yong Zhang, Zengxiang Zhou
Figure caption: LAMOST RFP structure. Figure (a) shows a schematic diagram of the LAMOST dual-rotation RFP structure, with the black dot indicating the center of the RFP. Figure (b) shows a schematic diagram of the light-spot safe area of the LAMOST RFP.