Work

Dynamic Estimation Loss Control in Variational Quantum Sensing via Online Conformal Inference

Year: 2026

Type: conference-paper

Abstract: Quantum sensing exploits non-classical effects to overcome limitations of classical sensors, with applications ranging from gravitational-wave detection to nanoscale imaging. However, practical quantum sensors built on noisy intermediate-scale quantum (NISQ) devices face significant noise and sampling constraints, and current variational quantum sensing (VQS) methods lack rigorous performance guarantees. This paper proposes an online control framework for VQS that dynamically updates the sensor’s variational parameters while providing deterministic error bars on the estimates. By leveraging online conformal inference techniques, the approach produces sequential estimation sets with a guaranteed long-term risk level. Experiments on a quantum magnetometry task confirm that the proposed dynamic VQS approach maintains the required reliability (e.g., 90% coverage) over time, while still yielding precise estimates.

Source: IEEE International Conference on Acoustics Speech and Signal Processing

DOI: 10.1109/icassp55912.2026.11463311

Authors: Ivana Nikoloska, Hamdi Joudeh, Ruud van Sloun, Osvaldo Simeone

Institutions: Eindhoven University of Technology, Northeastern University London

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green