Quantum information

Quantum information is a central research direction for understanding how information is stored, processed, and transformed in quantum systems [1]. One important area in this field is the study of entropy and entanglement in complex quantum systems, especially monitored quantum circuits [2].

Monitored quantum circuits provide a powerful framework for studying the competition between unitary quantum evolution and measurement. In these systems, quantum gates generate entanglement, while measurements can reduce or restructure it. This interaction creates rich dynamical behavior and can lead to entanglement phase transitions, where the system changes between different entanglement-scaling regimes.

A key research interest is the investigation of entropy in complex quantum systems. Entropy provides important information about the structure of quantum states, the distribution of information across subsystems, and the growth of entanglement over time. By studying entropy in monitored circuits, it becomes possible to analyze how measurement affects information spreading and how quantum correlations survive under repeated observation [3].

Another important direction is the use of quantum machine learning to study monitored quantum circuits. Machine learning models may help identify patterns in entropy growth, detect signatures of entanglement phase transitions, and classify different dynamical phases of quantum systems. This approach can be useful when direct analytical methods become difficult due to the complexity of many-body quantum dynamics [4].

The goal is to explore whether quantum machine learning can extract meaningful information about entropy and entanglement growth in monitored circuits. Such models could be trained to recognize phase-transition behavior, estimate entanglement properties, or learn effective representations of quantum dynamics. This may provide a new computational tool for studying complex quantum systems and their information-theoretic properties.

References

[1] M. A. Nielsen and I. L. Chuang, Quantum Computation and Quantum Information, Cambridge University Press (2010).

[2] B. Skinner, J. Ruhman, and A. Nahum, “Measurement-Induced Phase Transitions in the Dynamics of Entanglement,” Physical Review X 9, 031009 (2019).

[3] X. Turkeshi, “Measurement-Induced Criticality in Random Quantum Circuits,” Physical Review B 10, 104302 (2020).

[4] V. Dunjko and H. J. Briegel, “Machine Learning & Artificial Intelligence in the Quantum Domain,” Reports on Progress in Physics 81, 074001 (2018).

Author: Yousef Mafi

Published date: 31 May 2026

Location: Tampere. Finland