Part VIII. Applications and Strategy · Chapter 70
Sensing, Navigation, and Adjacent Quantum Technologies
Some of the most fundable quantum products never run an algorithm. This chapter separates sensing, timing, navigation, and communication from gate-model computing, and shows how to diligence a device that has to survive the field rather than the lab.
In this chapter 9 sections
Evaluate the complete sensor by measurand, bandwidth, dynamic range, stability, calibration, environmental tolerance, size, power, cost, and field performance against the incumbent instrument; qubits and gate counts are usually irrelevant.
A quantum sensor is an instrument, and instruments live or die by mission conditions. Sensitivity quoted in a quiet laboratory is one parameter among bandwidth, dynamic range, bias stability, drift, calibration interval, warm-up, shock, temperature, size, power, and availability. A navigation system adds error propagation over time; no qubit count summarizes that behavior.
Name the measurand before the quantum effect
The acceptance sheet starts with a measurand and units. For inertial navigation it then allocates allowable position error across bias, scale factor, alignment, timing, and environmental terms over a mission duration. The quantum mechanism enters only where it changes a measured term. Laboratory sensitivity and accumulated mission error remain different columns.
Instrument evidence table with units and environments
The sensing review provides metrological concepts and modality examples. GAO and the National Academies separate sensing from computing and communications in their technology context. Bell and BB84 are included to prevent an adjacent quantum-information result from being used as sensor evidence. The full-stack source supports accounting for control and readout around the quantum element.
| Claim under review | Source chain |
|---|---|
| Quantum sensing uses quantum coherence, entanglement, or discrete transitions to estimate physical quantities under a metrological model. | |
| A technology assessment must separate quantum computing, communications, and sensing maturity and deployment paths. | |
| Bell correlations and quantum key distribution are adjacent quantum-information results, not evidence that a particular field sensor meets mission requirements. | |
| System suitability requires control, readout, environment, and integration costs beyond the quantum element. |
A GPS-denied navigation claim meets drift
| Requirement | Candidate record | Unit | Acceptance |
|---|---|---|---|
| Sensitivity | 1.0 | nT/sqrt(Hz) | pass |
| Mission drift | 180 | m over trial | fail: limit 100 |
| Power | 42 | W | pass: limit 50 |
| Temperature | -10 to 45 | degrees C | pending chamber test |
The illustrative instrument meets a 1.0 nanotesla-per-root-hertz sensitivity threshold and still fails the navigation mission because drift would accumulate to 180 meters against a 100-meter limit. Passing the laboratory row cannot override the system row. A field trial over the representative duration, motion profile, shock, and temperature range is the smallest evidence that can change the procurement decision.
EXPECTED_UNITS = {"sensitivity": "nT/sqrt(Hz)", "mission_drift": "m", "power": "W"}
def assess(sheet):
errors = []
if type(sheet.get("scenario")) is not str or not sheet.get("source_ids"):
errors.append("scenario_or_sources")
measurements = sheet.get("measurements", {})
passes = {}
for name, unit in EXPECTED_UNITS.items():
row = measurements.get(name, {})
if (type(row.get("value")) not in (int, float) or
type(row.get("limit")) not in (int, float) or row.get("unit") != unit or
not row.get("method") or type(row.get("incumbent")) not in (int, float)):
errors.append(name + "_schema")
else:
passes[name] = row["value"] <= row["limit"]
decision = "invalid" if errors else ("procurement-test" if all(passes.values()) else "field-trial")
return {"decision": decision, "errors": sorted(errors), "passes": passes,
"failed": sorted(name for name, passed in passes.items() if not passed)}
sheet = {"scenario": "GPS-denied 60-minute mission", "source_ids": ["gao-quantum"],
"measurements": {
"sensitivity": {"value": 1.0, "limit": 1.2, "incumbent": 1.1,
"unit": "nT/sqrt(Hz)", "method": "shielded calibration"},
"mission_drift": {"value": 180.0, "limit": 100.0, "incumbent": 95.0,
"unit": "m", "method": "one-hour blind route"},
"power": {"value": 42.0, "limit": 50.0, "incumbent": 35.0,
"unit": "W", "method": "battery-rail meter"}}}
base_result = assess(sheet)
bad = {**sheet, "measurements": {**sheet["measurements"],
"mission_drift": {key: value for key, value in sheet["measurements"]["mission_drift"].items()
if key != "method"}}}
bad_result = assess(bad)
improved = {**sheet, "measurements": {**sheet["measurements"],
"mission_drift": {**sheet["measurements"]["mission_drift"], "value": 90.0}}}
improved_result = assess(improved)
assert base_result["passes"]["sensitivity"] and base_result["failed"] == ["mission_drift"]
assert bad_result["decision"] == "invalid" and "mission_drift_schema" in bad_result["errors"]
assert improved_result["decision"] == "procurement-test"
print(f"PASS: 70 instrument dossier failed={base_result['failed']} invalid={bad_result['errors']} drift90m={improved_result['decision']}")Artifact contract. A units-bearing requirements table and executable pass/fail evaluator for sensitivity, bandwidth, drift, mass, power, and environmental range. The artifact rejects unitless thresholds, requires incumbent measurements, and never substitutes laboratory sensitivity for mission-level navigation error.
Exact validation command: python3 tools/validate_briefs.py --briefs data/editorial_briefs_64_87.json --from 64 --through 87 --check-rewritten-sources --execute-artifacts
Laboratory sensitivity is one term in field performance
Write the trial around the mission rather than the best sensor metric. Calibrate the incumbent and candidate under the same procedure, blind the analysis where practical, retain environmental logs, and predefine failure. Procurement remains pending until the drift and availability rows pass. A research contract may still be appropriate if it buys the missing field data at bounded cost.
Build an acceptance test around the mission
Prompt. Convert a GPS-denied navigation pitch into a mission acceptance test.
Deliverable. Measurand and units, incumbent performance, drift budget, calibration schedule, shock/temperature envelope, size-power-cost bounds, and field-trial decision rule.
Pass condition. Every threshold has units and a measurement method; sensitivity alone cannot pass; accumulated position error is evaluated over the mission duration.
Companion work
Artifacts for this chapter
These entries resolve to checked-in local source. Commands are reproduced exactly from the chapter manifest, and source-embedded fixtures are exported as direct downloads.
evidence dossier
Quantum-sensor mission acceptance sheet
Reproduce or test
python3 tools/validate_briefs.py --briefs data/editorial_briefs_64_87.json --from 64 --through 87 --check-rewritten-sources --execute-artifacts
Provenance
Sources and review
- C. L. Degen, F. Reinhard, and P. Cappellaro. Quantum sensing. Reviews of Modern Physics. 2017peer-reviewed review
- U.S. Government Accountability Office. Quantum Computing and Communications: Status and Prospects. GAO. 2021government technology assessment
- National Academies of Sciences, Engineering, and Medicine. Quantum Computing: Progress and Prospects. National Academies Press. 2019consensus study report
- Richard P. Feynman. Simulating physics with computers. International Journal of Theoretical Physics. 1982primary paper
- John S. Bell. On the Einstein Podolsky Rosen paradox. Physics Physique Fizika. 1964primary paper
- Charles H. Bennett and Gilles Brassard. Quantum cryptography: Public key distribution and coin tossing. Proceedings of the IEEE International Conference on Computers, Systems and Signal Processing / IBM Research. 1984primary conference paper
- OpenQASM Technical Steering Committee. OpenQASM 3 specification. Linux Foundation Joint Development Foundation. 2026official technical specification
- Lieven M. K. Vandersypen et al.. A look at the full stack. Nature Reviews Physics. 2021peer-reviewed perspective
The load-bearing claims in the chapter are mapped inline to this registered source set. A citation supports only the bounded claim beside it.