ISSN2320-2882
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Paper Title
Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit
Authors
Sahil ingale , Dr. A. P. Jadhao , Dr. D. S. Kalyankar , Prof. D. G. Ingale , Prof. Rohit Solanke
Keywords
Hybrid Quantum-Classical (HQC) Framework, Quantum Annealing (QA), Quantum Machine Learning (QML), Active Debris Removal (ADR), Space Situational Awareness (SSA), Low Earth Orbit (LEO), Optimal Routing Problem (ORP), Quadratic Unconstrained Binary Optimization (QUBO), Variational Quantum Algorithms (VQAs), Quantum Neural Networks (QNNs), Quantum Autoencoders (QAEs), Quantum K-Nearest Neighbor (QkNN), Space Traffic Management (STM), Collision Probability (Pc), Multi-Target Optimization, Combinator
Abstract
The proliferation of space debris poses an existential threat to the sustainability of operations in Low Earth Orbit (LEO). While classical Artificial Intelligence (AI) solutions have improved tracking and localized debris capture, they encounter significant computational intractability when planning large-scale, multi-target Active Debris Removal (ADR) missions. This paper proposes a Hybrid Quantum-Classical (HQC) framework specifically designed to overcome these combinatorial optimization bottlenecks. The framework leverages Quantum Annealing (QA) to efficiently solve the optimal routing problem (ORP), formulated as a high-fidelity Quadratic Unconstrained Binary Optimization (QUBO) model. This optimization is integrated with Quantum Machine Learning (QML) for accelerated Space Situational Awareness (SSA) and real-time collision risk assessment (Pc). Simulation results benchmarking the HQC optimizer against classical metaheuristics, such as Genetic Algorithms (GA) and Simulated Annealing (SA), demonstrate a superior solution quality
(98% near-optimal fuel consumption) and a substantial reduction in time-to-solution (a 10-fold speedup for N=50 targets). Furthermore, the application of Variational Quantum Algorithms (VQAs) for quantum-enhanced anomaly detection improves sensor data fidelity and strengthens autonomous decision-making robustness, validating the critical role of nascent quantum technologies in preserving the orbital environment against the escalating threat of Kessler Syndrome.
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IJCRT — journal style
"Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit", IJCRT - International Journal of Creative Research Thoughts (www.ijcrt.org), ISSN:2320-2882, Vol.13, Issue 10, page no.c756-c764, October 2025, Available :https://ijcrt.org/papers/IJCRT2510329.pdf
APA — 7th edition
ingale, S., Jadhao, A. P., Kalyankar, D. S., Ingale, D. G., & Solanke, R. (2025). Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit. International Journal of Creative Research Thoughts, 13(10), c756-c764. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510329
MLA — 9th edition
ingale, Sahil, et al. "Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit." International Journal of Creative Research Thoughts, vol. 13, no. 10, 2025, pp. c756-c764, https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510329.
Chicago — 17th, bibliography
ingale, Sahil, et al. "Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit." International Journal of Creative Research Thoughts 13, no. 10 (2025): c756-c764. https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510329.
Harvard — author–date
ingale, S. et al. (2025) 'Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit', International Journal of Creative Research Thoughts, 13(10), pp. c756-c764. Available at: https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510329
IEEE — numbered reference
S. ingale, A. P. Jadhao, D. S. Kalyankar, D. G. Ingale and R. Solanke, "Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit," IJCRT, vol. 13, no. 10, pp. c756-c764, Oct. 2025.
Vancouver — biomedical
ingale S, Jadhao AP, Kalyankar DS, Ingale DG, Solanke R. Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit. IJCRT. 2025 Oct;13(10):c756-c764.
AMA — 11th edition
ingale S, Jadhao AP, Kalyankar DS, Ingale DG, Solanke R. Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit. IJCRT. 2025;13(10):c756-c764. Accessed at https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510329
BibTeX — Zotero, Mendeley, LaTeX
@article{IJCRT2510329,
author = {Sahil ingale and A. P. Jadhao and D. S. Kalyankar and D. G. Ingale and Rohit Solanke},
title = {Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit},
journal = {International Journal of Creative Research Thoughts},
volume = {13},
number = {10},
pages = {c756-c764},
year = {2025},
month = {October},
issn = {2320-2882},
url = {https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510329}
}
RIS — EndNote, RefWorks
TY - JOUR
AU - ingale, Sahil
AU - Jadhao, A. P.
AU - Kalyankar, D. S.
AU - Ingale, D. G.
AU - Solanke, Rohit
TI - Hybrid Quantum-Classical Algorithms for Scalable Multi-Target Active Debris Removal Optimization in Low Earth Orbit
T2 - International Journal of Creative Research Thoughts
JA - IJCRT
VL - 13
IS - 10
PY - 2025
SN - 2320-2882
UR - https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510329
SP - c756-c764
ER -
Issue
Volume 13 Issue 10,
October-2025
Pages : c756-c764
Article Information
- Published In
- International Journal of Creative Research Thoughts — Volume 13, Issue 10, October 2025
- Pages
- c756-c764
- Published
- October 2025
- Registration ID
- IJCRT_295096
- Published Paper ID
- IJCRT2510329
- Research Area
- Science and Technology
- Author Type
- Indian Author
- Location
- Amravati, Maharashtra, India
- Peer Review
- Request Peer Review Report
- Licence
- CC BY 4.0 · Open Access
- ISSN & Impact Factor
- 2320-2882 · IF 9.17
- Downloads
- 217
- Permanent Link
- https://ijcrt.org/viewpaperforall.php?paper=IJCRT2510329
- Published Paper PDF
- https://ijcrt.org/papers/IJCRT2510329.pdf
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