Quantar Lab
(Quantum algorithms and technologies for advanced research)
HomeResearchQuantum Metrology & Sensing • Last updated: 2026

Quantum Metrology & Sensing

Time-dependent and networked quantum sensing protocols that push measurement precision beyond classical limits, with explicit attention to noise, control constraints, and experimental feasibility.

QFI / QFIM optimal control noise-robust networked sensors

What is quantum metrology?

Quantum metrology studies how quantum effects—such as superposition, entanglement, and squeezing—can be used to measure physical parameters with higher precision than is possible using classical strategies.

Key idea: the precision of any measurement is fundamentally limited, but quantum resources allow us to approach or surpass classical bounds.

Typical sensing workflow

In our work, a sensing protocol is treated as a controlled quantum process rather than a fixed experiment.

Quantum metrology workflow
Probe preparation → controlled evolution → optimized measurement → parameter estimation.

Core methods

  • Quantum Fisher information (QFI) and quantum Fisher information matrix (QFIM)
  • Time-dependent and optimal control of probe dynamics
  • Noise modeling and robustness analysis
  • Variational and learning-based optimization of states and measurements

Research topics

Time-dependent sensing

We design control schedules that maximize information gain within finite sensing times.

Networked quantum sensors

Distributed sensing using multiple nodes, optimized for scalability and realistic noise.

Multiphase and multiparameter estimation

Understanding trade-offs, compatibility conditions, and joint estimation limits.

Robust measurement design

Constructing POVMs that remain near-optimal under imperfect calibration and readout.

Selected results

  • Squeezing-induced quantum-enhanced multiphase estimation
  • Time-normalized quantum Fisher information
  • Noise-robust performance of networked quantum sensors

Why it matters

Precision measurement underpins modern science and technology. By explicitly accounting for noise, control, and finite resources, our work helps bridge the gap between fundamental limits and deployable quantum sensors.