Namur Institute For Complex Systems

Aaron Bryan Rosengren (University of California San Diego, USA)
2022-07-12 13:00 - 14:00 (Europe/Brussels)
Title: Space-Manifold Dynamics for Small Solar-System Bodies
Abstract: Centaurs are a prominent group of small Solar-System bodies in highly dispersed orbits between the two main belts. They are a short-lived transient phase connecting their source reservoir in the Kuiper Belt to the Jupiter-family comets (JFCs) and Halley-type comets (HTCs), but the precise dynamical hand-off process between the Centaurs and these short-period comet (SPC) populations remains unclear. The recent finding of an orbital gateway between Jupiter and Saturn, funneling Centaurs into the inner Solar System, has cast some light on the orbital migration of these enigmatic bodies. Yet, no dynamical mechanism to explain the existence of this apparent conduit has hitherto been offered. The talk will link seminal research conducted over two decades ago on Jovian-induced space manifolds with our recent understanding of the orbital architecture of these gravitational structures to elucidate the nature of this and other dynamical channels for the rapid transport of planet-crossing small bodies of the outer Solar System. This work combines the well-developed techniques of astrodynamics for the study of space manifolds with the modern analytical and numerical tools of planetary dynamics, harnessing these in unique ways to probe for the first time the high time-resolution details of such strongly chaotic orbital evolution. Building from the notion and success of the interplanetary transport network, studying and understanding space-manifold dynamics in the planetary-science context may also give rise to new and unexpected results that could uncover new Centaur-mission concepts, motivate entirely new classes of missions, and amplify scientific return.
The seminar will take place in room S08 at the Faculty of Sciences

Corbinian Schlosser (LAAS-CNRS, Toulouse, France)
2022-06-16 13:00 - 14:00 (Europe/Brussels)
Title: Koopman and Perron-Frobenius operators on reproducing kernel Hilbert spaces
Abstract: Koopman operators and reproducing kernel Hilbert spaces (RKHS) share a common idea: Giving linear representations of non-linear tasks or objects. We follow the recent path of combining both concepts. The Koopman operator is a composition operator and therefore acts on a function space – in this talk we consider the underlying function space to be an RKHS. We give an introduction to the Koopman operator on an RKHS as well as to its adjoint, the so-called Perron-Frobenius operator. Both operators are linear but not necessarily bounded. Thus we focus on elementary properties of these operators including closedness and boundedness. We present a collection of known and new results on Koopman operators on RKHS. These results, with no further specifications on the RKHS, are restrained and we emphasize that the RKHS should be chosen accordingly to the problem at hand in order to flourish the interplay between the Koopman operator and the RKHS.
The seminar will take place in room CH12 at the Faculty of Sciences

Lluc Bono Rossello (Université Libre de Bruxelles)
2022-06-02 13:00 - 14:00 (Europe/Brussels)
Title: Modelling Music with Multilayer Networks
In this talk I will introduce our Multilayer Network Model for musical pieces. The goal of this model is to describe the dynamics and interactions occurring during the generative process of music: how each voice or instrument creates a new melody while interacting with other voices. In such a way, we establish a link between the properties of these networks and the music that is encoded in such networks. Then, I will present some of the applications of this model such as the generation of music via synchronized random walks.

The seminar will take place in room S08 at the Faculty of Sciences

naXys Research Day
2022-05-13 09:30 - 16:00 (Europe/Brussels)
CH01 (Rue Grafé 2, 5000 Namur)
Program
MORNING SESSION (9.30-12.30)

Registration
9.40-9.55: Welcome
9.55-10.40: Flash talks (Part I)
10.40-11.10: Coffee break
11.10-11.30: Discover AI Research Pole (E. Tuci)
11.30-11.40: Meet Jérôme Mallargé, ADRE ICT scientific advisor
11.40-12.30: Brainstorming “The post-it game”

LUNCH
AFTERNOON SESSION (14.00-16.00)

14.00-14.45: Flash talks (Part II)
14.45-15.30: Brainstorming “The puzzle game”
Conclusions

Registration
Registration is free but mandatory, before Friday, May 6th, through the following web form.
We strongly encourage submissions of flash talks for all PhD students. PhD students will receive a certificate with ECTS mention for their participation and/or presentation.

Ahmed Almansoori (Université de Namur)
2022-05-05 13:00 - 14:00 (Europe/Brussels)
Title: On the evolution of mechanisms for collective decision making in a swarm of robots
Abstract – A swarm of robots can collectively select an option among the available alternatives offered by the environment through a process known as collective decision-making. This process is characterised by the fact that once the group makes a decision, it can not be attributed to any of its group members. In the large majority of the swarm robotics literature, only a few types of mechanisms have been used to allow the robots of a swarm to make collective decisions. Namely, the mechanisms referred to as the Voter and the Majority model or variations of these two models. In this talk, we present an alternative solution based on the use of dynamical neural networks as individual decision-making mechanisms. This alternative solution proved effective in a perceptual discrimination task. We will show the results of extensive comparative tests that quantitatively evaluate the Voter model and the dynamic neural network model on a variety of operating conditions and for swarms that differ in their size on a perceptual discrimination task. The results of our study clearly indicate that the performances of a swarm employing dynamical neural networks as the decision-making mechanism are more robust, more adaptable to a dynamic environment, and more scalable to a larger swarm size than the performances of a swarm employing the Voter model as the decision-making mechanism.
The seminar will take place in room S08 at the Faculty of Sciences

Matteo Romano (Université de Namur)
2022-04-21 13:00 - 14:00 (Europe/Brussels)
Title:
Studying the topology of the space population using networks
Abstract:
With more than 23.000 tracked objects orbiting Earth, satellite operators find themselves dealing with hundreds of conjunctions at risk of collision per week, situation only getting worse due to the increasingly frequent satellite launches in recent years. Within the WALSAT project, in collaboration with the industrial partner Aerospacelab, we aim to represent the space population as a network in order to exploit its properties to study the topology of the population as a whole. The catalogue objects are represented as nodes and links between them are established whenever a close encounter occurs over a given time window. The resulting network is then analysed in terms of properties such as degree, centrality, and clustering to identify the most dangerous objects. Moreover, by weighting the links using the collision probability or the associated risk, we can identify the most sensitive orbital regions and the objects contributing the most to the overall collisional risk.

The seminar will take place in room S08 at the Faculty of Sciences

Alessio Franci (Universidad Nacional Autónoma de México, México)
2022-04-07 13:00 - 14:00 (Europe/Brussels)
Title: DECISION FROM INDECISION IN MULTI-AGENT MULTI-OPTION DYNAMICS
How does a group of agents break indecision about a set of options? Many biological and artificial multi-agent systems, from honeybees and bird flocks to bacteria and humans, face indecision when choosing between options in situations in which the fitness or even the survival of the group is at stake. Here, we develop a mathematical theory to study decision from indecision. Our approach is grounded in network bifurcation theory. We model decision from indecision as synchrony-breaking in influence networks in which each node is the value assigned by an agent to an option. We show that there are three generic types of value patterns emerging at synchrony-breaking bifurcations for influence networks: deadlock, consensus, dissensus. Deadlock and consensus value patterns are predicted by the symmetry of the influence networks. Conversely, we show that there are many “exotic” dissensus value patterns; that is, patterns that are not predicted by network symmetries, but are predicted by network architecture. Numerical simulations of a novel influence network model illustrate our theoretical results.

This is a joint work with Martin Golubitsky, Ian Stewart, Anastasia Bizyaeva, and Naomi E. Leonard.

The seminar will take place in room S08 at the Faculty of Sciences

Nicolas Franco (Université de Namur & Hasselt Universiteit)
2022-03-31 13:00 - 14:00 (Europe/Brussels)
Title: “Using social contact data to inform covid-19 epidemiological models and parameters”
Concerning SARS-CoV-2 transmission as well as many other infectious diseases, heterogeneity and age-related characteristics are crucial in order to correctly capture the dynamics. The use of social contact data is a modern method which has been widely used during the covid-19 pandemic in Belgium and other European countries thanks to the CoMix survey. In this talk, we present why and how those social contact data should be used. We develop the next generation principle based on Perron-Frobenius theory and derive a new numerical tool to estimate the time-evolution of heterogeneous susceptibility regarding SARS-CoV-2 infection and transmission.

The seminar will take place in room S08 at the Faculty of Sciences

Marvyn Gulina (Université de Namur)
2022-03-17 13:00 - 14:00 (Europe/Brussels)
Title: Spectral identification of networks with generalized diffusive coupling
Spectral network identification aims at inferring the eigenvalues of the Laplacian matrix of a network from measurement data. This allows to capture global information on the network structure from local measurements at a few number of nodes. In this paper, we consider the spectral network identification problem in the generalized setting of a vector-valued diffusive coupling. The feasibility of this problem is investigated and theoretical results on the properties of the associated generalized eigenvalue problem are obtained. Finally, we propose a numerical method to solve the generalized network identification problem, which relies on dynamic mode decomposition and leverages the above theoretical results.

Candy Sonveaux (Université de Namur)
2022-03-10 13:00 - 14:00 (Europe/Brussels)
Title: “Vaccination strategy design by a state-feedback control for an Age-Dependent epidemiologic model”
An age-dependent SIR epidemic model is studied with an input corresponding to the vaccination rate of susceptible individuals. The stability analysis of the equilibria highlights that, when the basic reproduction number is greater than one, the endemic equilibrium is stable whereas the disease-free one is unstable. According to this result, we aim to design a stabilizing state-feedback law of vaccination which eradicates the disease. This law is obtained for two different models. The first one consists in a nonlinear set of ordinary differential equations derived from the second one, a set of nonlinear partial integro-differential equation (PIDE), via a discretization by age. For the first model, Isidori’s theory allows us to design a linearizing stabilizing state-feedback. The second law is deduced from the first one and, using similar arguments as in Isidori’s theory, we show that the application of this law to the PIDE model results in a linear, positive and stable closed-loop system. Moreover, non-negativity conditions for the feedback law are obtained in both cases, ensuring real feasibility of the control law. Finally, numerical simulations complement theoretical arguments.

Frederik De Laender (Université de Namur)
2022-02-24 13:00 - 14:00 (Europe/Brussels)
The seminar will take place in person, Room S08, Faculty of Sciences
Title: Predicting the impact of environmental change on coexistence
I introduce a new approach to study effects of regional-scale environmental change on coexistence in ecological communities. The approach is based on the concept of feasibility, which measures how much one can change a model’s parameters while still maintaining positive species abundances.I will first present analyses in small consumer-resource communities, and simulations results for larger communities. Together, these analyses and simulations support the conclusion that simple summary statistics of direct species responses suffice to predict effects on the size of the feasibility domain. However, our results also reveal that these effects critically depend on the interaction strength between consumers and resources.I will then turn to food chains, confirming that simple summary statistics again predict environmental change effects on the size of the feasibility domain. In contrast to consumer-resource communities, however, these statistics do not scale up to larger food webs.I finally analyse an extensive set of field data of macroinvertebrate counts across thousands of sites along less and more polluted small streams across the USA. These analyses suggest that communities in more polluted sites can coexist across narrower environmental ranges than communities in less polluted sites.

Women and Girls in Science @ UNamur
2022-02-11 14:00 - 15:30 (Europe/Brussels)
11 February 2022 | 2nd edition
The UNamur is organizing the 2nd edition of the Women and Girls in Science day, in the framework of the 2015 declaration by the United Nations General Assembly.
This day aims at promoting the access of women and girls to science and technology as well as their full and fair participation.
Due to the sanitary situation, the main event is postponed to the Spring.
Instead, we will have two speakers in a hybrid event:
Dr. Antonella Fioravanti (VU Brussels, Belgium)
Prof. Petra Rudolf (RU Groningen, The Netherlands)
Registration is free but mandatory and can be done at this link.
Any questions? women-in-science@unamur.be

Leah Keating (University of Limerick, Ireland)
2022-02-10 13:00 - 14:00 (Europe/Brussels)
Online Seminar – Join by using this link
Title: “A Multi-Type Branching Process Method for Modelling Complex Contagion on Clustered Networks”
Online social networks such as Twitter, Facebook, Instagram and TikTok serve as a medium for the spread of information between their users, we are interested in developing models for this information diffusion to gain a greater understanding of how it spreads. Some models for the spread of online behaviour and information assume that the information behaves similarly to the spread of a virus, where infection is equally likely after each exposure, these dynamics are known as a simple contagion. In a simple contagion, the exposures are independent of each other. However, online adoption of some behaviour and content has been empirically observed to be more likely after multiple exposures from their network neighbours [1-2], the exposures are not independent of each other, we refer to this as a complex contagion. Analytically tractable descriptions of complex contagions have been developed for continuous-time dynamics. These extend mean-field and pair approximation methods to account for clustering in the network topologies [3]; however, no such analogous treatments for discrete-time cascade processes exist using branching processes. We describe a novel definition of complex contagion adoption dynamics and show how to construct multi-type branching processes which account for clustering on networks. We achieve this by tracking the evolution of a cascade via different classes of clique motifs which account for the different numbers of active, inactive and removed nodes. This description allows for extensive Monte Carlo simulations (which are faster than network-based simulations), accurate analytical calculation of cascade sizes, determination of critical behaviour and other quantities of interest. For more information see our preprint on arXiv.
[1] D. Centola, The spread of behavior in an online social network experiment, Science 329, 1194 (2010).
[2] D. M. Romero, B. Meeder, and J. Kleinberg, Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on twitter, in Proceedings of the 20th international conference on World wide web (2011) pp. 695–704.
[3] D. J. P. O’Sullivan, G. J. O’Keeffe, P. G. Fennell, and J. P. Gleeson, Mathematical modeling of complex contagion on clustered networks, Frontiers in Physics 3,10.3389/fphy.2015.00071 (2015).

FNRS Doctoral School - Introduction to dynamical systems on complex networks
2022-02-01 09:30 - 2022-02-03 12:45 (Europe/Brussels)
Doctoral School FNRS – Nonlinear phenomena, complex systems and statistical mechanics
Time: 1-2-3 February 2022 – 9h30-12h45
Location: Université de Namur, Faculty of Science, Room S08
Lecturers: Mattia Frasca (Università di Catania) & Timoteo Carletti (Université de Namur)

Slides:
– Carletti
– Lecture4
– Lecture5
– Lecture6
To attend the lectures it is mandatory to be in possession of the Covid Safe Ticket (CST)
Abstract: We live in an interconnected world, where “basic” units interact each other to produce unexpected emergent behaviors. Our society is for instance, the result of the interaction of many agents, we the human beings, that exchange information, news, opinions, etc., but also likes on Facebook or viruses. To a larger scale, the societies can be considered as agents interacting each other on a global stage, by exchanging goods to create the global economy, or fight each other and thus determine conflicts and wars. Our brain is made of about 100 billions of cells, i.e., the neurons, connected through even more synapses (millions of billions) allowing the signals to pass from one neuron to the others, and thus allowing us to think, act, remember, … Finally, our body is made by about 30 thousand billions of cells, basic blocks that determine our behavior, via synchronized processes, resulting from the exchanges among the cells. The cells are also organized into tissues and organs and so on to allow us to be alive. The following questions emerge thus straightforwardly. Is it possible to understand the behavior of a society ? How to understand the brain functioning, to distinguish between its regular or irregular behavior (disease) and thus control it to reduce / remove the unwanted behavior ? Can we determine the behavior of (part of) the human body? By using a reductionist approach we will divide the system into its constituting “elementary” parts, work hard to understand their behavior and then finally scale up the results to have a global picture. This approach has provided excellent results in many relevant cases (e.g., particle physics) but in other occasion it has shown its limits. A complementary approach is based on the study of the evolution of some average quantities, i.e., the mean field approach; this approach has been largely used in these last months to study the spreading of the COVID-19, i.e., the epidemic models SIR, where you group together all the agents with the same feature, being S, I or R, and you no longer make a distinction among each single agent. Modeling is always a matter of obtaining a reasonable trade-off between the details added to the model and its predictive or descriptive power; hence the level of details you add to a model depends on the research question you are dealing with. It is clear that in the above examples, reductionist or mean field, may fail to sufficiently well describe the whole system, indeed the resulting global behavior is not easily ascribed / predicted from the behavior of each single unit. How would it be possible from the behavior of a single human to extract the behavior of a society? Or, does a neuron has memory? To cope with these issues, network science and complex systems offer a reliable alternative approach. Let us observe that this is not a completely new research field. Physicists have been used it since long time but relying on regular couplings, e.g., the Ising model on square lattices. Nowadays the emphasis is on the use of coupling, i.e., networks, that better represent the reality; often such networks have been directly extracted from real data and thus the results better explain the empirical findings. The goal of these lectures is to propose a (personal) view of some interesting research questions arising once dealing with interconnected systems; we will in particular be interested in the study of the emergence of synchronous behavior or on the other hand of patchy, i.e. spatially heterogeneous, solutions. In the first part of these series of lectures, we will survey some basic results of dynamical systems theory, i.e., equilibria, their stability and bifurcation. The details provided in this first part will depend on the background of the students attending the lectures. Some notions of network theory will be provided and some of the most used models of network will be introduced and characterized (e.g., Erdős-Rényi, Small World, Scale Free). We will then introduce two interesting coupling among the basic units constituting the system, long range interaction and diffusive-like interaction. Starting from the behavior of the single isolated units we will study how the coupling will affect the global behavior and in particular the conditions ensuring the emergence of patchy solutions. We will conclude our lectures with some recent generalizations of network theory, where more complex structures have been considered to go beyond the pairwise interaction modeled by the network theory, e.g., multilayer networks, temporal networks and hypergraphs. The second part of the course will focus on synchronization of regular and chaotic dynamical systems defined on top of complex networks and on graph-based methods for multiagent systems. The major tool for the study of the stability of synchronization in complex networks (i.e., the master stability function) will be presented and then applied to paradigmatic examples. Then, synchronization in time-varying networks will be discussed. This is a particularly relevant case study where links may adapt in time as it occurs in many natural systems in response to different external conditions. The extension of the master stability function to such framework will be discussed and relevant examples of synchronization in adaptive networks and in networks of mobile agents will be dealt with. Finally, the course will discuss graph-based methods for multi-agent systems. In particular, typical multi-agent problems such as rendez-vous and formation control will be considered and solutions based on graph methods will be illustrated. Attention will be given to the communication protocols to set in order to reach the goals of the control, to the formalization of appropriate consensus methods to address these problems, and to simple models of interacting robots. This interdisciplinary doctoral course is aimed at PhD and Master students of nonlinear dynamics and complex system; because of the presented subjects and of the possible applications, students from physics, biology, chemistry or economics are warmly invited to attend the lectures. Some basic mathematical knowledge is required, however the topics will be introduced such in a way that it can be understandable and enjoyable by every researcher interested in collective dynamics and complexity, with more focus on the bigger picture and less on technical details.
For any information, write to riccardo.muolo@unamur.be

Jeong Min Jeon (KU Leuven & Université de Namur)
2021-12-16 13:00 - 14:00 (Europe/Brussels)
Title: Deconvolution estimation on hypersphere
This paper considers nonparametric estimation with contaminated data observed on the unit hypersphere $S^d$. For such data, we consider deconvolution density estimation and regression analysis. Our methodology and theory are based on harmonic analysis on $S^d$ which is not well considered in statistics. We establish novel deconvolution density and regression estimators, and study their asymptotic properties including the rates of convergence and asymptotic distributions. We also provide asymptotic confidence intervals. We present practical details on implementation as well as the results of simulation studies and real data analysis.

The seminar will be online at the following link

Camille Carpentier (Université de Namur)
2021-12-02 13:00 - 14:00 (Europe/Brussels)
Title: Using degree distribution of ecological networks to predict their responses to random and targeted species removals
Facing the current biodiversity crisis, it is becoming increasingly important to be able to understand – and predict – the consequences of species removal on ecological networks. These complex networks can be described using simple metrics such as the number of species (nodes), the number of interactions between them (edges) and their degree distribution. Coupling these three pieces of information allows us to predict the topological impacts of species removal and provides a first tool to identify the most fragile networks and which species removals would be most deleterious. A fundamental step for this approach is to describe the relationship between the number of species and the number of interactions as a network-specific property, whereas until now ecologists have assumed it as universal. The interaction-species relationship is based on the degree distribution of ecological networks (power-law, exponential or uniform) could therefore be generalised to other types of complex networks and provide a first understanding of their resistance to node removal.
The seminar is in hybrid mode:
_in person, Room S08 (Faculty of Sciences)
_online, at this link

BeNet21 - Belgian Network Research Meeting
2021-11-18 09:00 - 18:00 (Europe/Paris)
The 10th edition of the Belgian Network Research Meeting (BENet) will be organised by the naXys Institute at the University of Namur (UNamur). The event will be held at the University of Namur on November 18, 2021. The keynotes speakers, Ginestra Bianconi (Queen Mary University of London) and Alice C. Schwarze (University of Washington), will deliver their talks online.
The purpose of this annual event is to foster communication predominantly among Belgian researchers employing network science on their work, regardless of their discipline: sociology, economics, communication, history, biology, physics, medicine, computer science, mathematics and more.
For more information, visit the BENet 2021 page or contact riccardo.muolo@unamur.be.
BENet – HOME

Nicolas Herman (Université de Namur)
2021-11-09 13:00 - 14:00 (Europe/Brussels)
Title : Detecting High-Frequency Gravitational Waves with Resonant Electromagnetic Detectors

In this talk the possibility to detect gravitational waves (GW) from planetary-mass primordial black hole (PBH) binaries or the stochastic gravitational wave background (SGWB) with electromagnetic (EM) detectors of high-frequency GWs is investigated. We consider two patented experimental designs, based on the inverse Gertsenshtein effect, in which incoming GWs passing through a static magnetic field induce EM excitations inside either a TM cavity or a TEM waveguide. The frequency response of the detectors is computed for post-Newtonian GW waveforms. We find that such EM detectors based on current technology may achieve a strain sensitivity down to h ∼ 10−30, which generates an EM induced power of 10−10 W. This allows the detection of PBH binary mergers of mass around 10−5 M⊙ if they constitute more than 0.01 percent of the dark matter, as suggested by recent microlensing observations. We envision that this class of detectors could also be used to detect cosmological GW backgrounds and probe sources in the early Universe at energies up to the grand unified theory scale.

The seminar will take place in Room S08, Science Building (Rue Grafé 2)

Introduction to Git
2021-10-15 14:00 - 16:00 (Europe/Brussels)
Lecture open to all naXys researchers
Teacher: Juan Cabrera
Program: Why use git. Basic use of git and gitlab. Some good practices. Implementation (take your laptop).
Location: Room S06, Science Building (Rue Grafé 2)

Luca Gallo (University of Catania (Italy) & Université de Namur)
2021-10-14 13:00 - 14:00 (Europe/Brussels)
Title: Stability of synchronization in simplicial complexes
Various systems in physics, biology, social sciences and engineering have been successfully modeled as networks of coupled dynamical systems, where the links describe pairwise interactions. This is, however, a too strong limitation, as recent studies have revealed that higher-order many-body interactions are present in social groups, ecosystems and in the human brain, and they actually affect the emergent dynamics of all these systems. In this seminar I discuss the phenomenon of synchronization in higher-order networks. I describe a framework to study coupled dynamical systems accounting for the structure of their interactions at different orders. I show when complete synchronization exists and give the necessary condition for it to be observed as a stable state. Moreover, I consider the cases for which such a necessary condition takes the form of a Master Stability Function, thus generalizing the results valid for pairwise interactions to the case of simplicial complexes.
The seminar will take place in Room S08, Science Building (Rue Grafé 2)

Journée des Instituts (UNamur)
2021-10-05 08:00 - 17:00 (Europe/Brussels)
Information and registration: https://www.unamur.be/recherche/services-adre/journee-des-instituts

Lucien Hinderling (University of Bern, Switzerland)
2021-09-30 13:00 - 14:00 (Europe/Brussels)
Title: Live or die: Controlling the fate of cells in a tissue in real time using feedback-control microscopy
Abstract: Think of cells as tiny biological robots in a swarm. Working together in a self-organized fashion, they achieve complex tasks such as wound healing. We aim to study these emergent properties by artificially reprogramming the behaviour of selected cells, and then observing the response of the rest of the cells in the swarm. Using optogenetics, micro-projectors and computer vision, we developed an approach that allows us to control the cell fate (apoptosis, migration, signalling state) of single cells in real time.
The seminar will be online at this link

Federico Andres Stasyszyn (IATE & OAC, National University of Córdoba, Argentina)
2021-06-10 13:00 - 14:00 (Europe/Paris)
Title: Overview on Cosmic Magnetism Issues

We summarize some open questions around cosmic magnetic fields, from the theoretical and observational point of view. The use of Smoothed Particle Magneto Hydrodynamics (SPMHD) is getting nowadays more and more common to tackle these problems. From galaxy clusters to neutron stars, there are multiple applications already existing in the literature. I will quickly review some of the common methods used to evolve the MF, highlighting the successful approach of using vector potentials to describe them. Finally, I select a few applied astrophysical examples that will shed light on these issues in the near future.

Link to the seminar here
People outside Université de Namur with a Microsoft Teams account may join. For any questions, write to riccardo.muolo@unamur.be

Thomas Durt (Institut Fresnel, Ecole Centrale Marseille, France)
2021-06-03 13:00 - 14:00 (Europe/Paris)
Title: Applications of the Heisenberg-Weyl group to quantum state tomography with focus on dimensions 2 (quits) and 3 (qutrits)
Quantum state tomography aims at estimating an a priori unknown quantum state with maximal efficiency.The Heisenberg-Weyl group is obtained by composing phase-space displacements in position (translations) and momentum (boosts); it is a representation of the Galilei group. Heisenberg-Weyl displacement operators are intimately associated to the Wigner operators which are quantum localisation operators in phase-space. Mutually Unbiased Bases (MUBs) and Symmetric Informationally Complete POVMs (SICs) play a central role in relation with the tomographic applications associated to the aforementioned operators.Our goal is to define these objects, to describe the elegant symmetries and geometric structures associated to them, and to emphasize their relevance in the framework of quantum state tomography.
Link to the seminar here
People outside Université de Namur with a Microsoft Teams account may join. For any questions, write to riccardo.muolo@unamur.be

Horizon Europe by ADRE (event in French)
2021-05-25 12:30 - 13:15 (Europe/Paris)
Le nouveau programme-cadre de l’Union européenne pour la recherche et l’innovation “Horizon Europe” a été lancé depuis janvier 2021. Il représente un budget de 95 milliard € qui seront investis dans la recherche pour la période allant de 2021 à 2027.
Nous (ADRE) pensons que ce programme est une opportunité pour mettre en évidences les compétences de l’Université de Namur, en particulier celles de l’institut NAXYS. Nous proposons donc de vous en donner un aperçu et parcourir ensemble quelques opportunités pour NAXYS.
Points abordés :

Enjeux majeurs et nouveautés par rapport à Horizon 2020

Taux de financement des activités pour les Universités et autres partenaires

Au-delà de l’excellence scientifique, les autres aspects à prendre en compte pour une proposition réussie

Quelles opportunités pour NAXYS ?

Support ADRE et incitants institutionnels

La réunion aura lieu sur Teams le mardi 25/05 de 12h30 à 13h15 et sera accessible via ce lien

Carolina Charalambous (Université de Namur)
2021-05-20 13:00 - 14:00 (Europe/Paris)
Title: Dynamical analysis of resonant multi-planet systems
Throughout this seminar, I intend to cover some of the general problems observed in the extrasolar population as a consequence of their dynamical evolution.
For this purpose, I will first present some planetary features and discuss in which context the planets were formed to obtain the currently observed architectures.
The focus will be on systems with 3-planets. The interest comes after the discovery of the TRAPPIST-1 system.
To carry out this investigation, we used N-body numerical simulations to study in detail the evolution of planetary systems during the early stages of planet formation, that is, when there was still gas in the protoplanetary disk. We make dynamical maps from grids of initial conditions for systems with planets of different masses and compare the results of the N-body simulations with the analytical modeling to understand the evolutionary paths, on which parameters of the disk depend, and other physical characteristics. We dynamically analyze the TRAPPIST-1 planetary system that lies in a very complex resonant configuration. Results are consistent with the fact that systems were not formed in-situ but had to migrate to reach their current positions, without having to suppose ad-hoc dissipative effects, such as tidal effects by the star.

Link to the seminar here
People outside Université de Namur with a Microsoft Teams account may join. For any questions, write to riccardo.muolo@unamur.be

Ana Paula Millán Vidal (Amsterdam UMC, Netherlands)
2021-04-27 13:00 - 14:00 (Europe/Paris)
Title: Brain network models of epilepsy propagation and surgery
Clinical network neuroscience aims to apply the knowledge and tools from network science to study brain network topology in neurological and psychiatric diseases. This idea stems from the description of the brain as a complex network whose underlying structure and dynamics give rise to the emergent behaviour leading to cognition. How is this structure altered in different brain disorders [1]? And how can we apply this information to every-day clinical practice [2]? Here we will discuss the case of epilepsy, a neurological disorder that affects between 4 and 10 per 1000 people worldwide [3]. There is not one single cause of epilepsy: it often occurs as an associated symptom of an underlying disease, but many other times it is produced by unknown causes [4]. For patients who do not respond to medication (roughly 1 out of 3 people), epilepsy surgery is the treatment of choice if a focal origin can be found. However, seizure-freedom is currently achieved in only 2/3 of the patients after surgery. Brain networks in patients with epilepsy have been found to deviate significantly from the healthy brain, even when seizures have a local origin. In order to study how alterations in the underlying network and dynamics can lead and promote seizure propagation, computational models are used to mimic seizure generation and propagation. These allow us to test in silico different resections before the actual surgery, with the ultimate goal to improve surgery outcome and reduce side-effects. The choice of the network and dynamical model is the first step on this analysis. Simpler models allow for more computational tractability and theoretical analysis. In particular, we have modelled seizure propagation as an epidemic spreading process. Fitted with patient specific data, the model can capture the fundamental aspects of clinically observed seizure propagation, and can be used to test virtual resections in silico. Combined with optimization algorithms, smaller or alternative resection strategies, that are individually targeted for each patient, can be determined with the ultimate goal to improve surgery outcome.
[1] C. J. Stam. Nature Reviews Neuroscience 15.10 (2014), 683-695.
[2] L. Douw et al. Network Neuroscience 3.4 (2019), 969-993.
[3] P. N. Banerjee, D. Filippi, and W. A. Hauser. Epilepsy Research 85.1 (2009), 31-45.
[4] A. T. Berg et al. Epilepsia 51.4 (2010), 676-685.

Link to the seminar here
People outside Université de Namur with a Microsoft Teams account may join. For any questions, write to riccardo.muolo@unamur.be

Luca Gamberi (King's College London, UK)
2021-04-15 13:00 - 14:00 (Europe/Paris)
Title: Maximal modularity and the optimal size of parliaments: how big should your parliament be?
An important question in representative democracies is how to determine the optimal parliament size of a given country. According to an old conjecture, known as the cubic root law, there is a fairly universal power-law relation, with a 1/3 exponent, between the size of an elected parliament and the country’s population. Empirical data in modern European countries support such universality but are consistent with a larger exponent. In this seminar, I will introduce the audience to this intriguing regularity and discuss the current state of social science research on the topic. I will then move on to introducing our model, which is derived from fundamental complex network theory. We will see how modelling the population of a democratic country as a random network, drawn from a “clustered” growth model, enable us to determine an optimal number of constituencies – and thus of representatives – for a given population. In particular, I will briefly show how the modularity of the population can be calculated analytically and that its functional relation with the number of constituencies is strongly non-monotonic, exhibiting a maximum that depends on the population size. following a criterion of maximal modularity allows we are able to predict that the number of representatives and show that it naturally scales as a power-law in the size of the population – a finding that is qualitatively confirmed by the empirical analysis of real-world data.

Link to the seminar here
People outside Université de Namur with a Microsoft Teams account may join. For any questions, write to riccardo.muolo@unamur.be

Valentin Delchevalerie (Université de Namur)
2021-03-25 13:00 - 14:00 (Europe/Paris)
Title: Accelerating t-SNE using the Particle-Mesh Algorithm from Physics
t-Distributed Stochastic Neighbor Embedding (t-SNE) is a well-known dimensionality reduction technique used for the visualization of high-dimensional data. However, despite several improvements, t-SNE is not well-suited to handle large datasets. Indeed, for large datasets, the computation time required to obtain the visualizations is still too high to incorporate it in an interactive data exploration process. Since t-SNE can be seen as an N-body problem, this work presents a new variant of t-SNE based on a popular algorithm used in physics called Particle-Mesh (PM). The problem is solved by first computing a potential in space and deriving from it the force exerted on each body. As the potential can be computed efficiently using Fast Fourier Transforms (FFTs), this leads to a significant speed up.
Link to the seminar here
People outside Université de Namur with a Microsoft Teams account may join. For any questions, write to riccardo.muolo@unamur.be

François Lamoline (University of Luxembourg, Luxembourg)
2021-03-04 13:00 - 14:00 (Europe/Paris)
Title: Gene expression modelling from cell population snapshot data using optimal mass transport
Modelling gene expression is a central problem in systems biology. Accurate predictive models provide powerful tools for understanding cellular mechanisms and exploring the regulatory relations between genes. Perturbations of these regulatory structures affect the cellular functions. The ability to predict the effects of these perturbations is critical for finding sources of complex diseases and developing new treatments. Recently, single-cell techniques have enabled to perform sequencing at the level of individual cells for a large number of cells at a time. Unfortunately, the cells are destroyed in the measurement process, and so the data consist of population snapshots at different times. Traditional methods aim at modelling from time series data and cannot utilise the full information in the richer single-cell data. Therefore, these new sequencing techniques have raised the need of tailored computational methods for modelling the gene expression from single-cell data. In this talk we introduce new methods based on the 18th century problem of optimal mass transport. The idea consists in tracking the evolution of the distribution of cells over time and finding the dynamical system that minimises the transport cost between consecutive time points. The performance of the methods is compared in numerical experiments.
Link to the seminar here
People outside Université de Namur with a Microsoft Teams account may join. For any questions, write to riccardo.muolo@unamur.be
