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Motivated by recent advances in realizing quantum information processors, we introduce and analyse a quantum circuit-based algorithm inspired by convolutional neural networks, a highly effective model in machine learning. However, its direct application to problems in quantum physics is challenging due to the exponential complexity of many-body systems. Neural network-based machine learning has recently proven successful for many complex applications ranging from image recognition to precision medicine. Quantum error correction in scrambling dynamics and measurement-induced phase transition ( ).Theory of the phase transition in random unitary circuits with measurements, Editor's suggestion ( ).The nature of the phase transition can be understood from two complementary perspectives: firstly, by using the quantum error-correcting properties of scrambling unitary dynamics and secondly, by using a mapping to ordering transitions in classical statistical mechanics. The interplay between unitary evolution and measurements leads to a phase transition: at high measurement rates, any coherent information in the system is completely lost, while at sufficiently low rates, an extensive amount of information is robustly protected. We consider a generic quantum many-body system coupled to a noisy environment, which we model with random unitary circuits interspersed by projective measurements. Recently, we have studied a novel phenomenon that arises in this regime: a phase transition in the dynamics of quantum entanglement and information. Quantum information science seeks to understand and control quantum systems with high entanglement and complexity, defining a new frontier of physics. This research topic is extremely rich and often involves a wide variety of interdisciplinary approaches to study: from analytic theory and numerical computations to experiments with controlled quantum degrees of freedom.īelow are brief descriptions of a few recent research topics: I am interested in exploring dynamical phenomena that occur in strongly interacting quantum many-body systems in out of equilibrium and designing their novel applications for quantum information science.