Talks

Density and pressure fluctuations in proliferating cell layers

Tissue growth is pivotal in embryonic development, tissue regeneration and disease progression. To ensure that tissue growth is properly controlled, cell growth and death is regulated by mechanical and biochemical feedback. However, cell proliferation is inherently stochastic. In this work, we introduce a new framework to model the feedback between stochastic tissue growth and regulation of proliferation. Using one-dimensional numerical simulations and theoretical analysis, we show that proliferating tissues show non-trivial statistical properties in the fluctuations of the density and pressure fields, including long-range correlations and different universality classes. These properties are controlled by the interplay between the statistical characteristics of the proliferation noise, the type of mechanical regulation, and the tissue size. Our results highlight new connections between non-equilibrium statistical mechanics and tissue dynamics, and provide insights into how small-scale non-equilibrium fluctuations impact the large-scale mechanical state of living tissues.

Quantum Dynamics Seminar: tba

Attractor reconstruction in attracting subspaces for robust reproduction of chaotic dynamics

Data-driven models of dynamical systems achieve time-series prediction and reproduction of a target chaotic system by reconstructing its attractor within their representation state space. This talk focuses on where in the representation space the attractor should be reconstructed. We present a method that reconstructs the attractor in an attracting low-dimensional subspace (slow submanifold), and show that it achieves robust reproduction of chaotic dynamics.

Slow dynamics, kinetic constraints and large deviations, from classical to quantum

Classical many-body systems that display slow collective relaxation (the typical example being glass formers) do so due to effective constraints in their dynamics, the simplest manifestation being kinetically constrained models. This approach highlights the relevance of rare events and of the properties of stochastic trajectories. I will review this perspective on slow dynamics, and describe what can be learnt by studying trajectory ensembles using the framework of large deviations. I will also discuss how this way of thinking can extend to quantum systems, highlighting the crossover of ideas and methods between classical and quantum non-equilibrium.

QUANT26 Colloquium

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colcel26 Colloquium

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