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the claim

Advanced mathematical algorithms govern Falcon 9 flyback and vertical landing.

the verdict
SUPPORTED
the evidence backs this
Recorded sources
4 sources for · 0 against

Counts group repeated records of the same source within each side. They do not measure evidence strength or source independence.

Is it true that advanced mathematical algorithms govern Falcon 9 flyback and vertical landing?

Yes. Advanced mathematical algorithms, particularly convex optimization and model predictive control, are essential for planning and executing the precise trajectories required for reusable rocket flyback and vertical landing.

Verdict: SUPPORTED · 4 sources for, 0 against · Last checked

The analysis

The retrieved papers provide strong, direct evidence that advanced mathematical algorithms—specifically convex optimization, model predictive control, and sequential convex programming—are actively researched and applied to govern the trajectory optimization and landing guidance of reusable launch vehicles like the Falcon 9 and similar spacecraft.

Evidence for · 4
A convex approach to trajectory optimization for boost back of vertical take-off/vertical landing reusable launch vehicles
2021
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Li, Y., Wei, C., He, Y., & Hu, R. (2021). A convex approach to trajectory optimization for boost back of vertical take-off/vertical landing reusable launch vehicles. doi.org. https://doi.org/10.1016/J.JFRANKLIN.2021.02.017

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More for · 3
A Decreasing Horizon Model Predictive Control for Landing Reusable Launch Vehicles
2025
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Prous, G. Z., Grustan-Gutiérrez, E., & Felicetti, L. (2025). A Decreasing Horizon Model Predictive Control for Landing Reusable Launch Vehicles. doi.org. https://doi.org/10.3390/aerospace12020111

Optimal Landing Guidance of Reusable Launch Vehicles With Dual-convex Optimization
2024
Get citation
Jung, K., Lee, S., Jung, C., & Lee, C. (2024). Optimal Landing Guidance of Reusable Launch Vehicles With Dual-convex Optimization. doi.org. https://doi.org/10.1007/s12555-024-0628-3

Optimization of Flip-Landing Trajectories for Starship based on a Deep Learned Simulator
2025
Get citation
Chen, L., Qin, T., Huangfu, Z., Li, L., & Wei, W. (2025). Optimization of Flip-Landing Trajectories for Starship based on a Deep Learned Simulator. doi.org. https://doi.org/10.48550/arXiv.2508.06520

What does the evidence say?

The retrieved papers provide strong, direct evidence that advanced mathematical algorithms—specifically convex optimization, model predictive control, and sequential convex programming—are actively researched and applied to govern the trajectory optimization and landing guidance of reusable launch vehicles like the Falcon 9 and similar spacecraft.

Receipt History
first checked04 Aug 2026
judged → SUPPORTED · 8204 Aug 2026
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