It all started with Nicolas Roy's trip to Stanford. Nicolas is a PhD student in the Department of Physics and a member of the NISM and NaXys Institutes. The purpose of the visit to Stanford was to develop expertise at UNamur on a new method of simulating twisted photonic crystals, recently published by the prestigious university. Following discussions during the stay at Stanford, avenues for collaboration emerged, notably that of continuing research related to one of their publications in order to try to make a device that allows the direction of the light beam to be manipulated as efficiently and compactly as possible.  The gamble paid off, as the theoretical study predicts a device measuring 6 microns (the size of a hair)!  What's more, it is very energy efficient.  In practical terms, it could be used to track satellites, for example, without moving the transmitter or receiver, which is complicated in a photonic circuit.  Another practical application is being studied for Meta, a company that wants to reduce the size of virtual reality headsets to a simple pair of glasses... 

During his PhD, and based on a Stanford team publication entitled "Theory for Twisted Bilayer Photonic Crystal Slabs", Nicolas reproduced the simulation method and developed an analytical model of the numerical simulations. The use of these inexpensive simulations has made it possible to find the photonic structures most capable of deflecting light in a controlled manner. The analytical model, in turn, provides an explanation for what has been observed, and thus a better understanding of what's going on. In short, it opens up prospects for simpler fabrication of future devices.

The research teams collaborating on this study are working on twisted photonic crystals, i.e. two-dimensional materials formed, for example, from two superimposed and structured layers of silicon, and their interaction with light. 

In designing an analytical model, Nicolas Roy also used a theory that has been known since the 1960s: lattice networks. A lattice network is a plane diffraction network with a sawtooth profile.  In concrete terms, it resembles the roofs of old factories.  The novelty he brought to this concept is that it allows us to understand the mechanism that controls the angle of the light beam's exit thanks to the twist between the two layers. In doing so, he identified that the system acted similarly to a lattice grating. The team, using meta-models, was able to concentrate the light in a very specific direction with 90% efficiency.

What is the purpose of this type of twisted structure? To control light and ultimately create systems that can slow it down or even stop it.

This twist technique therefore opens up many unexplored possibilities in photonics by adding a degree of control over light. The researchers are continuing their work in this area, continuing their fruitful collaboration with Professor Fan's team, Stanford University.  

It looks like there's no end in sight to the twisting at the University of Namur! 

The Belgian team

• Professor Michael Lobet (UNamur, Harvard University)
• Professor Alexandre Mayer (UNamur)
• Dr Nicolas Roy (UNamur)

The American team

• Professor Shanhui Fan (Stanford University)
• Dr Beicheng Lou

The researchers thank UNamur, and more specifically the Department of Physics and the NISM Institute for funding Nicolas Roy's trip, the Institut naXys for its support in this project, the PTCI technology platform, whose supercomputers made this study possible, as well as the FNRS for funding the research mandates of Michaël Lobet and Alexandre Mayer.

• Michaël Lobet, the physicist of the invisible who makes light twist
• Following in Einstein's footsteps: old theories, new perspectives
• Publication on light observation in Nature Communications

The study of complex systems published in Physical Reviews Letters supports a growing trend that focuses more on analyzing the collective behavior of a system rather than discovering the underlying mechanisms of interaction.

When we observe a flock of starlings swirling through the sky in perfect coordination - a phenomenon known as murmuration - we witness the elegant interplay of individual actions creating collective behavior. In trying to understand these fascinating patterns, researchers can isolate simple rules based on an individual bird's field of view and the distance separating it from its neighbors, but there's always the question of whether the model actually captures the processes driving interactions between birds (Fig. 1).

This is a general problem in complex systems research, which comes down to distinguishing mechanisms (the rules governing interactions) from behaviors (the observable patterns that emerge).

Representative networks of interacting individuals, or nodes, are a good way to study mechanisms versus behaviors. Until now, researchers have focused on pairwise interactions, but many systems also include higher-order interactions between several nodes. The impact of these higher-order mechanisms on behavior has not been clearly established. Thomas Robiglio, from the Central European University in Vienna, and his colleagues, including Maxime Lucas (CR FNRS - UNamur) addressed this question. They considered networks with higher-order interactions and evaluated the resulting behaviors in terms of statistical dependencies between node values.

The researchers identified higher-order behavioral signatures which, unlike their pairwise counterparts, reveal the presence of higher-order mechanisms. Their findings open up new avenues for distinguishing mechanisms and behaviors when studying complex systems - a distinction that is crucial for the study of inference in network science, neuroscience, the social sciences and beyond.

This study is also the subject of a "Featured in Physics" and "Editor's suggestion" article, and a "commentary" article at the journal's request, available on their website in English in full.

The study, entitled "Topology shapes dynamics of higher-order networks" proposes a theoretical framework specifically designed to understand complex higher-order networks where several agents interact at the same time and thus generalize networks with their interactions in pairs. More precisely, the study shows how topology shapes dynamics, how dynamics learns topology and how topology evolves dynamically.

The aim of this work is to introduce physicists, mathematicians, computer scientists and network scientists to this emerging research field, as well as to define future research challenges where discrete topology and nonlinear dynamics mix.

With the data in their possession, the researchers show that real-life complex systems such as the brain, chemical reactions and neural networks can be easily modeled as higher-order networks, characterized by multi-body connections indicating the fact that several elements of the system interact simultaneously.

This international team is convinced that the visibility of their work through this publication in Nature Physics will open the door to new collaborations with other disciplines that rely on network analysis to study real complex systems.

Kudos to the team for this publication!

After a Master's degree in physics (University of Florence, June 1995), Timoteo Carletti pursued his doctoral studies in Florence (Italy) and Paris (France) at IMCCE, finally defending his doctoral thesis in mathematics in February 2000.

He moved to Belgium in 2005, and was hired at the University of Namur as a lecturer, then as a professor (2008), and finally as a full professor (2011) in the Mathematics Department of the Faculty of Science. In 2010, he was one of the founders of the Namur Center for Complex Systems (now the Namur Institute for Complex Systems - naXys), which he headed until December 2014.

Elio Tuci is a professor at the Faculty of Computer Science and a member of UNamur's Institut naXys (axe Robotics). He has just been awarded Crédit de Recherche (CDR) du F.R.S - FNRS funding following calls whose results were published in December 2024.

His research falls within the interdisciplinary field of bio-inspired robotics and computational intelligence. In his research activity, he draws inspiration from nature to design control mechanisms enabling artificial agents to operate in a complex environment and learn autonomously from their experience.

The aim of his work is twofold. On the one hand, it seeks to design autonomous adaptive systems by developing control mechanisms that underpin complex behavioral, social, cognitive and communication capabilities. On the other, he designs computational and robotic models to generate new and alternative hypotheses concerning the operational principles of cognition and learning in natural organisms: macroscopic (i.e. mathematical) and microscopic (i.e. computational based on computer-simulated agents) models.

The FNRS funding will be used to extend the computing resources available to our team already working on the BABots collaborative project, with a powerful server unit that will enable us to exploit the advantages of parallel computing to carry out advanced research and analysis.

Researchers are implementing the first BABot system in C. elegans. The worm's BABots will be programmed to act as a collective to detect, localize and attack invasive pathogens in a confined agricultural environment.

The BABots project has received funding from the European Innovation Council's Horizon Europe - EIC PathFinder work program under the Project 101098722 agreement.

The Action de Recherche Concertée (ARC) AUTOMATic project

This project aims to develop and test, in a simulation environment, a content-aware urban traffic management system based on a swarm of unmanned aerial vehicles (UAVs).

More info on the ARC projects website.

The EU-C2W Fellowship - On the study of firefly synchronisation using robots

"Connect with Wallonia - Come 2 Wallonia" (C2W) is a European postdoctoral program (Marie Skłodowska Curie COFUND action) open to postdoctoral researchers in all fields of research. The project, led by Dr Marcelo Avida and Cinzia Tomaselli, involves implementing what is known as synchronization response in a population of e-puck robots. It is inspired by behavior observed in certain species of fireflies as part of courtship.

More info on the C2W website.

The SPW's Win4Doc project is researching Monaster - Failure monitoring system with a preventive and autonomous maintenance strategy based on robotics and artificial intelligence for space applications.

This project led by Antoine Hubermont aims to create a platform for visualizing and predicting information about the condition of terrestrial assets, assessing the risk level of their failure, identifying anomalies and initiating a process to restore their functions. The platform integrates and combines the detection and prediction capabilities of artificial intelligence-based solutions with the technical capabilities of robotic solutions. The project is being carried out in collaboration with Telespazio Belgium.

The SPW BEWARE fellowship is researching ILabBot - Intelligent Laboratory Autonomous Mobile Robot for Pharmaceutical Industry

The aim of this project led by Dr. Muhanad Alkilabi is to equip the HelMO mobile robot with all the necessary control mechanisms and possibly additional sensors to enable the robot to operate autonomously in a pharmaceutical laboratory environment in order to automate production processes currently carried out by human operators. This project is being carried out in collaboration with CISEO.

• BABots | A European biorobotics project
• Synthetic choirs| A choir of robots created at UNamur