Data + abstraction layer over ultra-sensitive quantum sensors — a device registry, high-rate reading ingest, a time-series / spatial store, and a calibration + anomaly analysis pipeline.
A data and abstraction layer over ultra-sensitive quantum sensors — a device registry, high-rate reading ingest, a time-series and spatial store, and a calibration and anomaly-analysis pipeline. The provider seam is dormant until real hardware and credentials are configured.
What's included
Sensor registry across quantum magnetometry (NV-center / OPM), gravimetry (cold-atom), timing (optical / atomic clock), quantum imaging, and quantum radar / lidar
A typed CapabilityDescriptor per sensor class — what it measures, canonical unit, sample-rate class (the same MCP-tool shape the Fabric uses)
Provider seam that is DORMANT by default — a sensor does nothing until real hardware + credentials are configured; no vendor is hardcoded
Reading ingest as a class-agnostic time-series; spatial readings carry lat/lng and overlay the location fabric
Readings project into the Data Lake as a queryable quantumReadings dataset — no export loop
Analysis pipeline — calibration + bias/drift correction, noise filtering, and rolling-baseline anomaly detection (honest DSP stubs where the real physics plugs in)
About this module
Quantum Sensing lives at /quantum-sensing and is the data, abstraction, and visualization layer over a new class of instrument — not the physics itself. The sensor registry spans quantum magnetometry, cold-atom gravimetry, optical and atomic timing, quantum imaging, and quantum radar or lidar, and each sensor class carries a typed capability descriptor: what it measures, its canonical unit, and its sample-rate class, in the same tool shape the rest of the Fabric uses.
Readings come in as a class-agnostic time series, with spatial readings carrying latitude and longitude so they overlay the location fabric. Those readings project into the Data Lake as a queryable dataset — no export loop — and an analysis pipeline handles calibration and bias-drift correction, noise filtering, and rolling-baseline anomaly detection, with honest DSP stubs where the real physics plugs in.
It is built to stay dormant until it is real. No vendor is hardcoded; a sensor does nothing until actual hardware and credentials are configured, and writes route through the quantum domain service. From there it can be directed at a concrete application — GPS-denied positioning, geophysical survey, magnetic-anomaly detection, or medical magnetometry.
What you can do with it
Register quantum magnetometers, gravimeters, clocks, and imagers by capability
Ingest high-rate readings as a class-agnostic time series
Overlay spatial readings on the location fabric
Project readings into the Data Lake for querying with no export loop
Run calibration, drift correction, and rolling-baseline anomaly detection
Get this module
Free for all Turtini organizations.
Who it's for
- Research and defense teams operating quantum-sensor hardware
- Programs needing GPS-denied positioning or magnetic-anomaly detection
- Anyone who needs a data and abstraction layer over ultra-sensitive sensors
Details
- Category
- Frontier
- Pricing
- Free
- Built by
- Badge
- Beta