T3QUBO-EAerospace & Space
Launch / orbit trajectory optimization
Continuous trajectory optimization under constraints — embedding-taxed; classical optimal control is strong.
Sector
Space / aerospace
Likely buyer
Launch providers
Hardware gate
FTQC-era for real advantage
Taxonomy
cost-prohibitive × accelerating
No live demo yet — continuous optimal control embeds poorly on near-term hardware. The paradigm-honest position: this use case is demonstrated with crossover analysis, not theater.
GTM talk track
Track as research; lead with the MIS space cluster instead.
OGSM — product operating frame
Objective
Keep a watching brief; do not lead.
Goals
- Understand where classical optimal control wins
Strategies
- Monitor FTQC roadmap
Measures
- N/A near-term
OBR — outcome-based roadmap
| Horizon | Outcome we create | Buyer behavior change | Result we measure |
|---|---|---|---|
| Now | Educate on paradigm boundary | Prospect runs the emulated demo on their own instance data | Booked QPU-time evaluation or paid pilot |
| Next | Revisit at FTQC | Prospect co-designs a scoped benchmark against their incumbent solver | Documented crossover curve; expansion to production instances |
| Later | Reassess | Prospect standardizes on the workflow or buys an on-prem system | Recurring QPU consumption / system sale; reference case |
Fit notes (honesty gate)
Continuous control embeds poorly; honest answer is usually classical.
Ready to run this on real hardware?
Emulation-verified today — the same program runs on a Pasqal QPU unchanged.