Enhancing the Dynamic Range of Quantum Sensing via Quantum Circuit Learning

TL;DR

This paper introduces a quantum circuit learning approach to extend the dynamic range of quantum sensors by training parameterized quantum circuits to produce monotonic responses, overcoming inter-qubit interaction challenges.

Contribution

It presents a novel quantum circuit learning framework that optimizes measurement responses to enhance sensing range in dense qubit systems.

Findings

Successfully trains quantum circuits to produce monotonic responses

Enhances dynamic range of quantum sensors in high-density qubit systems

Mitigates effects of inter-qubit interactions on measurement accuracy

Abstract

Quantum metrology is a promising application of quantum technologies, enabling the precise measurement of weak external fields at a local scale. In typical quantum sensing protocols, a qubit interacts with an external field, and the amplitude of the field is estimated by analyzing the expectation value of a measured observable. Sensitivity can, in principle, be enhanced by increasing the number of qubits within a fixed volume, thereby maintaining spatial resolution. However, at high qubit densities, inter-qubit interactions induce complex many-body dynamics, resulting in multiple oscillations in the expectation value of the observable even for small field amplitudes. This ambiguity reduces the dynamic range of the sensing protocol. We propose a method to overcome the limitation in quantum metrology by adopting a quantum circuit learning framework using a parameterized quantum circuit to approximate a target function by optimizing the circuit parameters. In our method, after the qubits interact with the external field, we apply a sequence of parameterized quantum gates and measure a suitable observable. By optimizing the gate parameters, the expectation value is trained to exhibit a monotonic response within a target range of field amplitudes, thereby eliminating multiple oscillations and enhancing the dynamic range. This method offers a strategy for improving quantum sensing performance in dense qubit systems.