Quick Navigation
Topics
Quantum Machine Learning
Energy efficient optical tracking for space quantum communication
arXiv
Authors: Eric Vokes, Vinod N. Rao, Elinore Spencer, Rupesh Kumar
Year
2026
Paper ID
15648
Status
Preprint
Abstract Read
~2 min
Abstract Words
107
Citations
N/A
Abstract
Power consumption is a critical constraint for CubeSat based quantum communication, where tracking systems often dominate the onboard power budget. We demonstrate an energy-efficient approach that enables reliable satellite tracking at substantially reduced beacon power by treating tracking as a weak-signal estimation task. Using a closed-loop system with fine steering mirrors and higher-order Kalman filters on ground, we can maintain stable tracking at a transmitted power equivalent to 34 mW over a -60 dB satellite to ground optical channel. Our results show that the resulting penalties on QKD bit error rates and signal-to-noise ratios are negligible, allowing for more efficient power allocation to quantum payloads in CubeSat missions.
Why This Paper Matters
- This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
- It adds a 2026 reference point for readers tracking recent quantum research.
- Power consumption is a critical constraint for CubeSat based quantum communication, where tracking systems often dominate the onboard power budget.
Paper Tools
Become a member to use research tools
Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.
Show Paper arXiv Publisher Share
Cite This Paper
Copy URL
Compare
Copy DOI Add to Reading List
Category Correction Request
Category Correction Request
Help us improve classification quality by proposing a better category. Every request is reviewed by an admin.
Sign in to submit a category correction request for this paper.
Log In to SubmitReferences & Citation Signals
Community Reactions
Quick sentiment from readers on this paper.
Score:
0
Likes: 0
Dislikes: 0
Sign in to react to this paper.
Discussion & Reviews (Moderated)
Average Rating: 0.0 / 5 (0 ratings)
No written reviews yet.