arXiv subjects

Noam Abadi

Publications and source records attributed to Noam Abadi.

3 recordsLinked to original sources

arXiv2026

Energy pathway variety and the progress of the energy transition in European countries

The integration of new energy forms into existing energy infrastructure has emerged as a critical challenge in the context of the pursuit of a sustainable energy transition. One of the main challenges is understanding how this integration takes place not only from the introduction, but also as energy follows existing paths or creates new ones through which it is transformed and used by different activities. Here we introduce techniques from network science to analyse this process for the case of 29 European countries between 1992 and 2021. We study how new energy forms increase or decrease the variety (heterogeneity) of paths through the system of each country by establishing new ones and replacing or phasing out existing ones. We find that the transition to systems based on renewable energy is characterised by an initial increase in the variety of paths while the heterogeneity of paths decreases at the end of the transition, when the proportion of non-renewables in the system tends to zero. We then demonstrate that greater heterogeneity (complexity) is associated with larger annual fluctuations in the proportion of non-renewable sources in the system, establishing a direct relationship between the progress of the transition and the complexity of the energy system in which it occurs. This contributes to the understanding of general properties of the dynamics of the energy transition and effects that accelerate or deter it.

physics.soc-ph↗

arXiv2025

Maximum entropy for dynamic processes on networks

Dynamic processes on networks are fundamental to understanding modern-day phenomena such as information diffusion and opinion polarization on the internet or epidemics spreading through society. However, such processes are notoriously difficult to study broadly as small changes in initial conditions, the process, or the network can lead to very different evolution trajectories. Here we apply the information-theoretic framework of maximum caliber to study the statistics of such systems analytically, focusing on processes that can be interpreted as driven by interactions between populations of different types of individuals in the network. We verify the dynamics deduced from maximum caliber by using simulations of different processes on different networks, introduce an approximation of the dynamics that significantly simplifies the problem, and show that the approximation can be used to recover well-established models of population dynamics that are typically not thought of as taking place on networks.

physics.soc-ph↗

arXiv2024

Maximum entropy in dynamic complex networks

The field of complex networks studies a wide variety of interacting systems by representing them as networks. To understand their properties and mutual relations, the randomisation of network connections is a commonly used tool. However, information-theoretic randomisation methods with well-established foundations mostly provide a stationary description of these systems, while stochastic randomisation methods that account for their dynamic nature lack such general foundations and require extensive repetition of the stochastic process to measure statistical properties. In this work, we extend the applicability of information-theoretic methods beyond stationary network models. By using the information-theoretic principle of maximum caliber we construct dynamic network ensemble distributions based on constraints representing statistical properties with known values throughout the evolution. We focus on the particular cases of dynamics constrained by the average number of connections of the whole network and each node, comparing each evolution to simulations of stochastic randomisation that obey the same constraints. We find that ensemble distributions estimated from simulations match those calculated with maximum caliber and that the equilibrium distributions to which they converge agree with known results of maximum entropy given the same constraints. Finally, we discuss further the connections to other maximum entropy approaches to network dynamics and conclude by proposing some possible avenues of future research.

cond-mat.stat-mech↗