Quantum Information and Inference (QI2) Laboratory

Research Focus

 

Quantum information science is a research area that investigates quantum systems as natural and fundamental building-blocks for transmitting, storing and processing information. It explores how to exploit quantum properties of light and matter in order to perform tasks of communication, computation and sensing in the most efficient and, sometimes, also completely secure fashion.

However, as quantum mechanics is probabilistic by nature and, moreover, quantum systems are very fragile—being vulnerable to any external noise—advanced statistical inference and signal processing techniques turn out to be essential in order to exploit the full potential of any real-life quantum device. Quantum inference theory studies how to tailor such data inference tools so that quantum properties of systems can not only be accounted for but also extensively benefited from.

Within QI2-lab we primarily work on quantum metrology and sensing tasks. We develop the fundamental theory of quantum estimation protocols in order to focus on their optical implementations, with a particular interest in quantum sensors based on atomic-spin ensembles. We also seek novel practical solutions in quantum information tasks of cryptography and communication, while exploring the applicability of their state-of-art photonic implementations. Last but not least, we work on quantum software—our aim is to create an open-source library that will encompass various “quantum-tailored” data inference tools (such as filtering, compressive sampling or machine learning) so that they can be directly implemented in quantum control and sensing experiments that involve continuous-time measurements.

Jan Kołodyński, PhD
email: jan.kolodynski@cent.uw.edu.pl
room: 02.44

email: jan.kolodynski@cent.uw.edu.pl

website: www3.cent.uw.edu.pl/~jankolo/


Research experience:

2018-: Junior Group Leader, Centre for Quantum Optical Technologies (QOT), Warsaw, Poland.

2014-2018: Postdoctoral Researcher, Institute of Photonic Sciences (ICFO), Barcelona, Spain.

2010-2014: Research Assistant, Faculty of Physics, University of Warsaw, Poland.


Education:

2010-2014:  PhD in Physics (thesis), Faculty of Physics, University of Warsaw, Poland.

2008-2009:  MA Theor. Physics (CASM – Part III Maths), DAMTP, Cambridge, UK.

2007-2008:  Part II General in Computer Science, Comp. Labs, Cambridge, UK.

2004-2007:  BA in Natural Sciences (Physics), St John’s College, University of Cambridge, UK.


Selected prizes and scholarships:

2018-2020:  HOMING programme laureate, Foundation for Polish Science, Poland.

2015-2017:  Maria Skłodowska-Curie European Fellowship, ICFO, Spain.

2014-2015:  START Scholarship, Foundation for Polish Science, Poland.

2004-2008:  Cambridge European Trust Scholarship, Cambridge, UK.


Selected publications:


Selected invited talks:

2018.05 – “Observability and estimation in quantum dynamics” workshop, IHP, Paris, France; titled: “Bayesian filtering for quantum-enhanced atomic sensors” (video).

2017.09 – Quantum Optics IX conference, Gdansk, Poland.

2017.04 – SPIE: Optics+Optoelectronics conference, Prague, Czech Republic. Both titled: “Device-independent quantum key distribution with single-photon sources“.

2017.02   636. WE-Heraeus Seminar “Quantum-Limited Metrology and Sensing”, Bad Honnef, Germany. titled: “Random bosonic states for robust quantum metrology“.


Continuously Monitored Quantum Sensors: Smart Tools and Applications

Project Leader: Jan Kołodyński, PhD Project period: 2020 - 2024
Project funding: UNISONO, NCN
Project description:

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”.