News & Insights
Milestones and short notes on building NV-diamond quantum sensors.
The public layer of our digital twin is now open to everyone, in the browser, no account needed. Fly a full mission where satellites cannot help, attack your own instrument three different ways, and watch it refuse to be fooled: every figure recomputed live, every layer's contribution decomposed in the debrief, and the science behind each panel one click away. Every number is honestly labelled model-derived.
Fly the Instrument →Three patent families were filed in ten days at the turn of June and July, bringing the portfolio to sixteen. One protects how the sensing architecture rejects the host platform's own magnetic interference on board; one covers the onboard inference layer that turns the cleaned signal into navigation data the system can vouch for; and one extends that attribution across networks of sensors. All were filed before any public disclosure, and the details stay confidential until publication.
A physics engine is only as good as its confrontation with the literature. Every coherence prediction the engine makes is benchmarked against a registry of more than 100 published experimental results, curated anchor by anchor and re-checked as the model evolves. When the model and an experiment disagree, the experiment wins and the model changes.
Before our first device is built, our sensor flies an end-to-end synthetic mission: magnetic terrain, a vehicle with its own interference, the full sensor model and the navigation filter. Every figure is honestly labelled model-derived, and our hardware milestones will be judged against the twin’s own predictions. The interactive twin is live; access is granted on request.
Every magnetometer flying today is a lab instrument strapped onto a vehicle, corrected by external compensation models dating back to 1953. We took the opposite path: design the sensor for the vehicle from the first principle, so the measurement stays true under way, with the platform’s own magnetic noise rejected on board.
Our modelling work is documented in eight public preprints on Zenodo: timestamped, DOI-referenced and citable. Publishing the reasoning behind the engine is part of how we build credibility, in the open, against the literature.
We’re now a member of NVIDIA Inception, the programme supporting deep-tech startups. It strengthens our compute and ecosystem foundation as we scale the SF-QSim engine.
Satellite navigation is increasingly jammed, spoofed and denied. A passive magnetic reference that emits nothing and cannot be switched off is the missing layer, and it is exactly what NV-diamond is good at.
Before a sensor reaches the cleanroom, it lives in SF-QSim. Simulating coherence and sensitivity across decoherence channels lets a lean team explore the design space at deep-tech speed.
Follow the build.
We share progress and insights regularly, keeping the same cadence we keep on LinkedIn. Want the behind-the-scenes?