Quantum Computing Enhanced Sensing

The main goal of quantum metrology is to leverage quantum mechanical objects such as atoms and molecules to improve sensing in any on of various aspects including sensitivity, speed, spatio-temporal resolution, and economic cost. A paradigmatic example is the use of entangled quantum particles to improve upon the standard quantum limit and achieve an improved sensitivity only limited by the Heisenberg uncertainty principle.

In this talk, we consider a novel setting, where the quantum sensor particles are connected to a small quantum computer or register capable of executing elementary algorithms. We show that such a setting can drastically improve sensing for a specific task that we call quantum search sensing (QSS): the detection of a weak oscillating signal at an unknown frequency. QSS problems are pervasive in physical sciences, ranging from the detection of gravitational waves and the search for dark matter to applications in nuclear magnetic resonance (NMR) spectroscopy. By constructing an explicit algorithm, we show that having a quantum computer can improve the scaling of both sensitivity (the minimal detectable strength of a signal) and bandwidth (the maximum frequency range over which a signal is sought) in QSS as a function of total measurement time; this improvement directly originates from a quantum algorithmic speed-up. Furthermore, we demonstrate that our approach is optimal, saturating a fundamental limit set by quantum mechanics up to logarithmic corrections. We discuss the implementation of our algorithms in real-world experimental platforms such as an NV-center interacting with nearby nuclear spins.