Distributed multi-parameter quantum metrology with a superconducting quantum network

TL;DR

This paper demonstrates scalable distributed multi-parameter quantum metrology using a superconducting quantum network, achieving significant precision improvements in estimating vector fields and gradients across spatially separated nodes.

Contribution

It introduces a modular superconducting quantum network platform capable of multi-parameter estimation with low-loss interconnects and deterministic entanglement, advancing scalable distributed quantum metrology.

Findings

Achieved up to 13.72 dB precision improvement in vector field estimation.

Realized 3.44 dB gain in gradient estimation over local strategies.

Demonstrated the platform's reconfigurability and potential for scalable quantum sensing.

Abstract

Quantum metrology has emerged as a powerful tool for timekeeping, field sensing, and precision measurements in fundamental physics. With the advent of distributed quantum metrology, its capabilities have extended to probing spatially distributed parameters across networked quantum systems. However, scalable implementations of distributed quantum metrology with multi-parameter estimation remain limited, particularly due to the challenges of generating and distributing entanglement across a quantum network and dealing with incompatibilities in multi-parameter quantum metrology. Here we demonstrate distributed multi-parameter quantum metrology on a modular superconducting quantum network with low-loss microwave interconnects, a platform that uniquely combines fast gate operations, adaptive control, and deterministic non-local entanglement generation. Using a control-enhanced sequential protocol, we estimate all three components of a remote vector field, achieving up to 13.72 dB improvement in precision over the individual strategy. We further perform direct estimation of vector field gradients along two directions across spatially separated nodes, realizing a 3.44 dB gain over local entanglement strategies. These results establish superconducting quantum networks as a competitive and reconfigurable platform for scalable multi-parameter distributed quantum metrology.