Complex systems are characterized by multiple spatial and temporal scales. A natural
framework to capture their multiscale nature is that of multilayer networks, where different …

Biological and living organisms sense and process information from their surroundings,
typically having access only to a subset of external observables for a limited amount of time …

Generalized empirical currents represent a vast class of thermodynamic observables of
mesoscopic systems. Their fluctuations satisfy the thermodynamic uncertainty relations …

Biochemistry, ecology, and neuroscience are examples of prominent fields aiming at
describing interacting systems that exhibit nontrivial couplings to complex, ever-changing …

Biological and living systems possess the inherent capacity to process information across
spatiotemporal scales, displaying the hallmark ability to constantly adapt their responses to …

Real-world systems are shaped by both their complex internal interactions and the changes
in their noisy environments. In this work, we study how a shared active bath affects the …

The properties of an active fluid, for example, a bacterial bath or a collection of microtubules
and molecular motors, can be accessed through the dynamics of passive particle probes …

Understanding how the complex connectivity structure of the brain shapes its information-
processing capabilities is a long-standing question. Here, by focusing on a paradigmatic …

Complex systems with multiple processes evolving on different temporal scales are naturally
described by multilayer networks, where each layer represents a different timescale. In this …

This Thesis explores how tools from Statistical Physics and Information Theory can help us
describe and understand complex systems. In the first part, we study the interplay between …