#qubit #Quantum #Algorithms #Benchmarking #Machine #Learning.

Entangled quantum probes promise Heisenberg-limited precision, with estimation error scaling inversely with the number of probes rather than as the inverse square root. This quadratic gain shortens measurement times and reduces resource cost in quantum sensing. The advantage is fragile under decoherence, and conventional quantum error correction restores robustness only with noiseless ancilla qubits and gate-level recovery overhead beyond near-term hardware. We describe a route built on quantum error detection: auxiliary measurements that flag errors without acting back on the probe, supplying classical side information to the estimator rather than triggering a recovery operation. The syndrome conditions the estimator likelihood, isolating signal from noise without the gate cost of active correction. The framework places no recovery cost on the probe, opening a route to quantum-enhanced sensing on near-term hardware relevant applications.