Scientists at Cornell University have demonstrated a novel quantum sensing technique that directly predicts a target property, circumventing the need to initially measure the signal itself. Sridhar Prabhu and colleagues report the experimental realisation of quantum computational displacement sensing (QCDS) utilising a superconducting circuit. Their work represents a fusion of quantum sensing and quantum computing, achieving demonstrably improved accuracy in binary classification tasks when contrasted with conventional quantum sensing methodologies followed by classical post-processing. By employing parameterised quantum circuits, incorporating up to 24 entangling gates, and subsequently training these circuits via classical optimisation, the team achieved a classification accuracy advantage of up to 15 percentage points for specific, defined tasks. These findings underscore the potential of integrating quantum computation and sensing to enhance performance when estimating properties of signals, rather than merely estimating the signals themselves. Direct classification via single qubit measurement enhances quantum sensing precision A fifteen-percentage-point improvement in classification accuracy is now achievable with the new quantum computational displacement sensing (QCDS) protocol, exceeding the performance benchmarks of conventional quantum sensing techniques. QCDS directly predicts a class label from a single qubit measurement, effectively overcoming a fundamental limitation inherent in prior methodologies. Traditional approaches necessitate an initial estimation of signal displacement, followed by classical processing to infer the corresponding class label. This two-step process introduces potential inaccuracies and inefficiencies. QCDS, however, leverages the principles of quantum computation to directly map the input signal to a classification outcome, streamlining the process and enhancing precision. The displacement being sensed represents a shift in the signal’s amplitude, and accurately determining this shift is crucial in many sensing applications, such as gravitational wave detection or magnetic field mapping. The protocol utilises superconducting circuits, fabricated using established microfabrication techniques, with up to 24 entangling gates, enabling a quantum computational-sensing advantage for specific binary classification