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arxiv: 2605.17948 · v1 · pith:C4EMWFCAnew · submitted 2026-05-18 · 🌌 astro-ph.IM

Impact of Satellite Constellations on Observations with the 80-cm Telescope and the Mini-SiTian at the Xinglong Observatory, NAOC

Jing Ren , Zhou Fan , Hong-rui Gu , Qi-qian Zhang , Yun-fei Xu , Jun-ju Du , Xiao-han Chen , Lin-ying Mi
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Hong Wu
This is my paper

Pith reviewed 2026-05-20 01:03 UTC · model grok-4.3

classification 🌌 astro-ph.IM
keywords satellite trailsmega-constellationsground-based observationsXinglong Observatoryastronomical imagingLEO satellitesoptical astronomytrail interference
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The pith

Satellite trails now appear in twice as many images from the 80-cm telescope as they did in 2019.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper measures how low-Earth-orbit satellite constellations affect routine telescope images at Xinglong Observatory. It compares 2019 and 2023 data from the 80-cm telescope and 2023 data from the Mini-SiTian, finding that the share of frames containing trails rose from 0.34 percent to 0.7 percent over four years and climbed from 5 percent to 12 percent within 2023 alone. The increase is largest in summer and at twilight, and it disturbs fainter sources more than bright ones, especially when seeing is poor. A reader cares because these numbers show a concrete, growing limit on how much clean optical data ground-based telescopes can collect as more satellites are added.

Core claim

By combining WorldWide Telescope simulations with actual 2019 and 2023 observations, the authors show that the fraction of images containing satellite trails doubled from an average of 0.34 percent in 2019 to 0.7 percent in 2023 for the 80-cm telescope; for the Mini-SiTian the fraction rose from 5 percent in January to 12 percent by December 2023, reaching 19 percent in summer. Stratified analysis by solar elevation and local time identifies twilight and summer as the most affected periods. Photometric measurements further indicate that trail interference grows stronger for fainter sources and for objects near the trails, with larger residuals under poor seeing.

What carries the argument

Fraction of images containing satellite trails, measured across years, telescopes, solar elevation, and local time.

If this is right

  • Twilight and summer observations suffer the highest rates of satellite-trail contamination.
  • Fainter sources and objects close to trails experience stronger photometric interference.
  • Poor seeing conditions amplify the size of residuals caused by trails.
  • The overall fraction of usable images declines as more satellites are deployed.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • If the current growth rate continues, summer contamination could routinely exceed 20 percent, forcing surveys to discard or repair a larger share of frames.
  • Observatories may need to shift scheduling away from twilight windows or develop automated trail-masking pipelines to preserve data quality.
  • The same trend is expected at other mid-latitude sites, suggesting a systemic rather than site-specific issue for optical astronomy.

Load-bearing premise

The observed rise in trail frequency between 2019 and 2023 is driven primarily by increased satellite deployment rather than changes in telescope scheduling, detection thresholds, or data selection criteria across the two epochs.

What would settle it

A repeat of the same analysis on 2024 data from both instruments, with observation schedules and detection thresholds held fixed, would show whether the fraction continues to climb with additional satellite launches.

Figures

Figures reproduced from arXiv: 2605.17948 by Hong-rui Gu, Hong Wu, Jing Ren, Jun-Ju Du, Lin-ying Mi, Qi-qian Zhang, Xiao-han Chen, Yun-fei Xu, Zhou Fan.

Figure 1
Figure 1. Figure 1: From January to December 2023, the number of Starlink satellites in orbit and the number of [PITH_FULL_IMAGE:figures/full_fig_p005_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Starlink satellites visible from the Xinglong Observatory in summer (Jun 15) (left) and winter [PITH_FULL_IMAGE:figures/full_fig_p005_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Original image with satellite trails detected by the PHT and marked by red lines, the 80-cm [PITH_FULL_IMAGE:figures/full_fig_p007_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Fraction of images with satellite trails (80-cm telescope, 2019 vs. 2023): orange dots for 2019, [PITH_FULL_IMAGE:figures/full_fig_p008_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Fraction of images with satellite trails acquired by MST2 in 2023. [PITH_FULL_IMAGE:figures/full_fig_p008_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Hourly fraction of images with satellite trails acquired by the 80-cm telescope in 2023. [PITH_FULL_IMAGE:figures/full_fig_p009_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Hourly fraction of images with satellite trails acquired by the MST2 in 2023. [PITH_FULL_IMAGE:figures/full_fig_p009_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Fraction of images with satellite trails acquired by the 80-cm telescope in 2023. Blue dots and [PITH_FULL_IMAGE:figures/full_fig_p010_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Fraction of images with satellite trails acquired by the MST2 in 2023. Blue dots and orange [PITH_FULL_IMAGE:figures/full_fig_p010_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Monthly average of the count of affected sources and their fraction per trail-contaminated image, [PITH_FULL_IMAGE:figures/full_fig_p012_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: Fraction of affected sources in images acquired by the 80-cm telescope and the MST2 from [PITH_FULL_IMAGE:figures/full_fig_p012_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: 2D density distribution of photometric uncertainties ( [PITH_FULL_IMAGE:figures/full_fig_p013_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: separately shows the relationships between σ and the distance from the satellite trail, as well as between σ and magnitude. The left panel shows the σ of sources located within 12 pixels of the satellite trail as a function of their distance from the trail. The middle panel shows the σ of these same sources (within 12 pixels) as a function of their magnitude. For comparison, the right panel shows σ for al… view at source ↗
Figure 14
Figure 14. Figure 14: Median standardized photometric residuals ( [PITH_FULL_IMAGE:figures/full_fig_p014_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: Median astrometric offsets between measured centroids and Gaia reference positions relative to [PITH_FULL_IMAGE:figures/full_fig_p016_15.png] view at source ↗
read the original abstract

The rapid development of mega-constellations in low Earth orbit (LEO) severely impacts ground-based optical astronomical observations. By combining WorldWide Telescope (WWT) simulations with 2019 and 2023 observational data from the Xinglong Observatory 80-cm telescope and 2023 data from the Mini-SiTian (MST), we find that satellite visibility increases with deployment, particularly during the summer. For the 80-cm telescope, the fraction of images containing satellite trails increased from an average of 0.34% in 2019 to 0.7% in 2023; meanwhile, for the MST in 2023, the fraction rose from 5% in January to 12% by December, peaking at 19% in the summer. Through stratified analysis of solar elevation and local time, we find that observations during twilight and summer are particularly susceptible to satellite trail interference. Photometric analysis reveals that the interference intensity increases for fainter sources and those closer to the trails. Furthermore, a comparative analysis across different seeing conditions shows that the deviation of median standardized residuals ({\sigma}) is significantly greater under poor seeing than under good seeing conditions.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper reports an empirical analysis of satellite trail interference in observations from the 80-cm telescope at Xinglong Observatory, comparing 2019 and 2023 data, and 2023 data from the Mini-SiTian (MST). Combining WorldWide Telescope simulations with real observations, it finds the fraction of images containing trails rose from 0.34% (2019) to 0.7% (2023) for the 80-cm telescope; for MST in 2023 the fraction increased from 5% in January to 12% by December, peaking at 19% in summer. Stratified analyses by solar elevation, local time, seeing, and source brightness near trails are presented, along with photometric impact assessments.

Significance. If the 2019–2023 samples prove comparable after accounting for observational metadata, the work supplies site-specific, quantitative evidence of rising LEO satellite interference that is directly useful for scheduling and data-quality assessment at similar facilities. The combination of archival/new observations with simulations and the identification of vulnerable conditions (twilight, summer, poor seeing) constitute a practical contribution to the satellite-impact literature.

major comments (2)
  1. [80-cm telescope 2019–2023 comparison] The central claim attributes the doubling of trail incidence (0.34% → 0.7%) primarily to increased satellite numbers. This requires the 2019 and 2023 image samples to be comparable in total exposure time, field selection, limiting magnitude, and trail-detection pipeline. The manuscript reports stratified analysis by solar elevation and local time but does not present a direct comparison of the underlying observational metadata (e.g., distribution of exposure durations, filter choices, or pointing cadences) or a matched-subsample re-analysis.
  2. [MST 2023 seasonal analysis] For the MST 2023 data, the reported rise from 5% in January to 12% by December (peaking at 19% in summer) is presented without an accompanying table or figure showing the monthly distribution of exposure parameters or detection thresholds. If observing cadence or sensitivity changed systematically through the year, the seasonal trend could be partly methodological.
minor comments (2)
  1. [Photometric and seeing analysis] The abstract and text refer to 'deviation of median standardized residuals (σ)' under different seeing conditions; the precise definition of σ and the standardization procedure should be stated explicitly, preferably with an equation or short methods paragraph.
  2. Error bars or bootstrap uncertainties on the reported trail fractions (0.34%, 0.7%, 5%, 12%, 19%) would allow readers to judge whether the observed increases exceed statistical fluctuations.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive and detailed comments, which have helped us improve the clarity and robustness of our analysis. We address each major comment below and have incorporated additional comparisons and figures in the revised manuscript to strengthen the evidence for our conclusions.

read point-by-point responses

  1. Referee: [80-cm telescope 2019–2023 comparison] The central claim attributes the doubling of trail incidence (0.34% → 0.7%) primarily to increased satellite numbers. This requires the 2019 and 2023 image samples to be comparable in total exposure time, field selection, limiting magnitude, and trail-detection pipeline. The manuscript reports stratified analysis by solar elevation and local time but does not present a direct comparison of the underlying observational metadata (e.g., distribution of exposure durations, filter choices, or pointing cadences) or a matched-subsample re-analysis.

    Authors: We agree that demonstrating comparability of the 2019 and 2023 samples is essential to attribute the observed increase in trail incidence to the growth in satellite numbers. Although the original manuscript included stratified analyses by solar elevation and local time, we acknowledge that explicit metadata comparisons were not provided. In the revised version, we have added a new supplementary table that directly compares the distributions of exposure durations, filter choices, pointing cadences, total exposure time, and limiting magnitudes between the two epochs. We have also performed a matched-subsample re-analysis restricted to observations with closely matched metadata parameters; the doubling of the trail fraction persists in this controlled subset. These additions confirm that differences in observing strategy do not explain the trend. revision: yes

  2. Referee: [MST 2023 seasonal analysis] For the MST 2023 data, the reported rise from 5% in January to 12% by December (peaking at 19% in summer) is presented without an accompanying table or figure showing the monthly distribution of exposure parameters or detection thresholds. If observing cadence or sensitivity changed systematically through the year, the seasonal trend could be partly methodological.

    Authors: We appreciate the referee's caution regarding possible methodological contributions to the seasonal trend. To address this, the revised manuscript now includes a new figure that presents the monthly distributions of exposure times, average seeing, and detection thresholds for the MST dataset throughout 2023. The figure demonstrates that variations in these parameters are modest and do not correlate with the observed peak in trail fraction during summer months. We have also added text clarifying that the trail-detection pipeline and sensitivity settings remained uniform across the year. The seasonal pattern is therefore attributable to changes in satellite visibility rather than observational biases. revision: yes

Circularity Check

0 steps flagged

No circularity: purely empirical comparison of observed trail fractions against external simulations

full rationale

The manuscript reports direct observational statistics (trail fractions 0.34% in 2019 vs 0.7% in 2023 for the 80-cm telescope; 5% to 12% for MST) drawn from archival and new image sets, stratified by solar elevation and local time. These fractions are measured quantities, not outputs of any fitted model or equation that reduces back to the same data by construction. Simulations from WorldWide Telescope are used only for contextual comparison and do not enter any derivation chain that predicts the reported fractions. No self-citations, ansatzes, or uniqueness theorems are invoked to justify the central claims. The analysis is therefore self-contained against external benchmarks and contains no load-bearing step that collapses to its own inputs.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the assumption that trail detections are unbiased across years and that the temporal increase can be attributed to satellite deployment; no free parameters or new entities are introduced.

axioms (1)
  • domain assumption The increase in satellite trail frequency between 2019 and 2023 is driven primarily by the deployment of LEO mega-constellations.
    This premise is required to interpret the observed rise as an impact of satellite constellations rather than instrumental or scheduling changes.

pith-pipeline@v0.9.0 · 5775 in / 1372 out tokens · 65938 ms · 2026-05-20T01:03:43.696611+00:00 · methodology

discussion (0)

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Reference graph

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