Quantum computational displacement sensing with trained parameterized circuits achieves up to 15 percentage points higher binary classification accuracy than conventional quantum sensing plus classical postprocessing on superconducting hardware.
The advantage of this technique is its simplicity: based on the estimate, further postprocessing tasks can be performed, as illustrated in Fig
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Quantum computational displacement sensing
Quantum computational displacement sensing with trained parameterized circuits achieves up to 15 percentage points higher binary classification accuracy than conventional quantum sensing plus classical postprocessing on superconducting hardware.