|Project Leader: Jan Kołodyński, PhD||Project period: 2020 - 2024|
|Project funding: QuantERA I, NCN|
Acquiring and interpreting data about physical processes is vital for science and technology. The targeted breakthrough of the project “Continuously Monitored Quantum Sensors: Smart Tools and Applications”―in short, C’MON-QSENS!―is to develop tools to interpret data acquired from quantum sensors. Indeed, quantum-enhanced ultra-precise sensors are among the most disruptive quantum technologies with near-term applications in several disciplines, but with a limited reach so far. Most efforts are devoted to the measurement of static properties by single-shot or repeated measurement schemes, while many real-world applications are concerned with dynamical signals.
Extracting information from time-series of data needs sensors operating in the continuously monitored regime, and here is where the interdisciplinary approach of C’MON-QSENS! emerges. The final concrete aim of the project is to develop sensors based on hot atomic ensembles and optomechanical device and make them operational in real time, what, however, requires close collaboration between leading experimentalists and theory researchers in quantum information theory, statistical inference and classical signal processing. In particular, the project will create a unique synergy to close this interdisciplinary gap, so modern methods of (classical) signal processing and data inference can be incorporated within the context of quantum metrology. On one hand, the result will allow advanced sensing tasks to be explicitly demonstrated in experiments. On the other, thanks to the outcomes of the project researchers will gain a deeper understanding of quantum information processing in the real-time regime, and develop practical approaches to quantum sensing and interpretation of real-time signals.
In summary, C’MON-QSENS! will advance the current frontiers of fundamental and applied knowledge on continuously monitored quantum systems by focusing on fulfilling the following three important tasks:
A. Constructing advanced dynamical models that will allow for an accurate description of realtime quantum sensors, including relevant decoherence mechanisms, non-linearities, sources of stochastic noise, and quantum back-action resulting from continuous-time measurements.
B. Developing (i): signal processing and statistical inference techniques (Bayesian filtering, compressed sensing, sequential analysis) for highly controlled scenarios when the quantum sensor and signal dynamics can be accurately modelled and (ii): model-free machine learning methods for real-world complex scenarios. This will advance fundamental theory on continuously monitored quantum systems and provide ultimate bounds on the performance for the relevant sensing tasks.
C. Building actual quantum sensors based on continuously monitored atomic vapours and optomechanical systems such that the dynamical models and inference techniques can be applied and verified in practice. In particular, after optimisation of sensors’ operating regimes, this will allow for tracking real-life signals (e.g. neuron, brain, heart, and acceleration) and validate experimentally advanced sensing tasks such as “wave-form estimation”, “model selection” and “change-point/anomaly detection”.
Quantum Information and Inference (QI2) Laboratory