Namur Institute For Complex Systems

Joseph O'Brien (MACSI, University of Limerick, Ireland)
2020-11-05 13:00 - 14:00 (Europe/Paris) | Online Event
Title: Branching Processes and their Application to Popularity Dynamics
Abstract: Arising from a desire to understand the likelihood of a family name becoming extinct, branching processes have a rich history and have been shown to be applicable to a wide range of domains. The simplest description of these processes is the case where a parent has a random number of children during their lifetime who themselves proceed to have a similarly distributed number of children. In this talk I demonstrate how the processes may be used to describe social spreading phenomena whereby the parents are now online pieces of information (tweets, online threads, …) while their children correspond to interactions with these pieces (retweets, comments,…) and as such may represent social contagion dynamics. Two specific examples will be considered in detail, the first being a mathematical model of online spreading across multiple social media platforms and the effect said network structure has upon the dynamics [2]. Second, I will demonstrate how a branching process approach can allow a unified understanding of the well-studied Hawkes process (which has itself been shown to accurately describe social spreading features [3]) and may in fact allow one to make predictions regarding future dynamics of such processes [4].
[1] K. B. Athreya and P. E. Ney, Branching Processes (Springer Science + Business Media, New York, 2013).
[2] J. D. O’Brien, I. K. Dassios, and J. P. Gleeson. Spreading of memes on multiplex networks. New Journal of Physics, 21(2):025001, 2019.
[3] A. N. Medvedev, R. Lambiotte, and J.-C. Delvenne. The anatomy of Reddit: An overview of academic research. In Dynamics on and of Complex Networks, pages 183–204. Springer, 2017.
[4] J. D. O’Brien, A. Aleta, Y. Moreno, and J. P. Gleeson. Quantifying uncertainty in a predictive model for popularity dynamics. Physical Review E, 101(6):62311, 2020.

Link to the teams group “naXys Seminars” (unamur members) here
Link to the seminar here
For any problem with the links, write to riccardo.muolo@unamur.be

Delivering your presentation remotely by Principiae
2020-11-13 14:00 - 16:00 (Europe/Paris) | Online Event
Abstract: When circumstances oblige you to deliver your presentation remotely from your office, your home, or even a hotel room, you face additional challenges, technological and otherwise. This remote lecture discusses and demonstrates the necessary adaptations to your tools, your environment, and your delivery so as to focus the attention of the audience, minimize distractions, and get your message across optimally.
Speaker: An engineer (UCLouvain) and PhD in applied physics (Stanford), Jean-luc Doumont is acclaimed worldwide for his no-nonsense approach, his highly applicable, often life-changing recommendations on a wide range of topics, and Trees, maps, and theorems, his book about “effective communication for rational minds.” For additional information, visit www.principiae.be.
Registration
Registration is free but mandatory through the following web form.
PhD students will receive a certificate with ECTS mention for their doctoral training.

Benedetta Franceschiello (University of Lausanne, Switzerland)
2020-11-19 13:00 - 14:00 (Europe/Paris) | Online Event
Title: MIME – Magnetic resonance Imaging of the Moving Eye
Abstract: Vision is arguably the most important of our senses and it relies on the synchronous functioning of the eyes and the brain. These organs are highly interdependent: pathologies of the eyes can impact brain functionality [1], and brain impairments affect how the visual information is encoded at the eye-level [2], [3]. While nowadays ophthalmic biomedical devices are able to extract high-resolution anatomical measurements and behavioral measurements of the eyes, no technology is able to perform anatomical assessments of the eye while it moves, yet eye-movements are a behavioral readout encompassing valuable biomarkers in brain disorders [4], [5]. Magnetic Resonance Imaging (MRI) is a particularly promising non-invasive and versatile technique because it provides measurements related both to the tissue/organ structure and to the regional neural activity. However, the image artefacts arising from eye motion prevent the applicability of MR techniques to eye imaging, therefore impeding the investigation of the interplay between anatomical structures and their motion.
In this talk I will present our patented structural MRI protocol [6], [7] that allows dynamic acquisitions of the eye while it moves during quasi-naturalistic vision. To test the efficacy of this method, eye-movements and eye-axial lengths – as extracted from the MR images – were compared with eye-tracker measurements and optical biometry, respectively. This new non-invasive technology can estimate the rotation axes from the MR images with up to 97% accuracy with respect to the eye-tracker hardware. The high-resolution MRI scans of the human eye (1 mm3) – acquired during natural movement – permit to quantify the optical axial length with an accuracy having the same order of magnitude of the one obtained with ocular biometry. Finally, I will discuss the possible applications of this technique and the new frontiers it opens both in the field of ophthalmic MRI and vision neuroscience.
[1] Zheng, D. D. et al. Longitudinal Associations Between Visual Impairment and Cognitive Functioning. JAMA Ophthalmol. 136, 989 (2018).
[2] Ciuffreda, K. J. et al. Occurrence of oculomotor dysfunctions in acquired brain injury: A retrospective analysis. Optom. – J. Am. Optom. Assoc. 78, 155–161 (2007).
[3] DeBuc, D. C. et al. Seeing the Brain Through the Eye: What Is Next for Neuroimaging and Neurology Applications. in OCT and Imaging in Central Nervous System Diseases 55–82 (Springer International Publishing, 2020). doi: 10.1007/978-3-030-26269-3_5
[4] MacAskill, M. R. & Anderson, T. J. Eye movements in neurodegenerative diseases. Curr. Opin. Neurol. 29, 61–68 (2016).
[5] Anderson, T. J. & MacAskill, M. R. Eye movements in patients with neurodegenerative disorders. Nat. Rev. Neurol. 9, 74–85 (2013).
[6] Franceschiello, B. et al. 3-Dimensional magnetic resonance imaging of the freely moving human eye. Prog. Neurobiol. 101885 (2020). doi:10.1016/j.pneurobio.2020.101885
[7] Franceschiello, B. et al. WO2020178397 – Magnetic Resonance Imaging Methods and device. (2020). Available at: https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2020178397&tab=PCTBIBLIO.
Benedetta Franceschiello
Laboratory for Investigative Neurophysiology,
Ophthalmology Department, Fondation Asile des aveugles, Lausanne, Switzerland
Radiology Department, University Hospital Center and University of Lausanne, Switzerland
Link to the teams group “naXys Seminars” (unamur members) here
Link to the seminar here

Greta Malaspina (University of Novi Sad, Serbia)
2020-12-03 13:00 (Europe/Paris)
Title: A modified Levenberg-Maquardt method for large scale network adjustment
We present a numerical optimization approach for the solution of large scale Network Adjustment Problems that arise in localization problems such as GPS positioning, surveying and large scale Wireless Sensors Networks localization. We consider a modification of Levenberg Marquardt method that attempts to deal with the non-convex nature of the objective function and the large number of variables.
At each iteration of the classical method the search direction is computed by solving a linear system of equations, which is an expensive procedure when the number of unknowns in the problem that we consider is large, and represents the major obstacle to the solution of realistic, large scale, problems. We develop a scheme for the decomposition of the linear system, which consist in computing an approximation of the Levenberg Marquardt direction by solving a number of independent linear systems of smaller size, and we propose a correction strategy of the right sides that improves the quality of the approximated direction while retaining separability of the linear systems. The convergence analysis of the resulting method is studied under standard regularity assumptions of the objective function. Moreover, the algorithm we propose is tested on realistic adjustment problems and compared with Levenberg Marquardt in terms of both accuracy and computational cost.
Link to the teams group “naXys Seminars” (unamur members) here
Link to the seminar here

Jean Teyssandier (Université de Namur)
2020-12-17 13:00 - 14:00 (Europe/Paris)
Title: An overview of astrophysical disc dynamics
Astrophysical discs appear at all scales in the Universe, from rings around planets to galactic discs. Despite the differences in scales and building blocks, they all share similar underlying physical processes. In this talk I will review some of these processes and explain the origin of certain features, such as the spiral arms of galaxies, the fine structures in the rings of Saturn, or the recent observations of gaseous discs where planetary systems are born.
Link to the teams group “naXys Seminars” (unamur members) here
Link to the seminar here

Rodrigo Martínez (University of the Balearic Islands, Spain)
2021-02-04 13:00 - 14:00 (Europe/Paris)
Title: Dynamical Phase Transitions in Quantum Reservoir Computing
Closed quantum systems may exhibit different dynamical regimes, such as Many-Body Localization or thermalization, that can affect their ability to process information. Specifically, we establish the role of dynamical phases of Ising spin networks in the field of quantum reservoir computing.
Reservoir computing is an unconventional computing paradigm that consists in exploiting classical or quantum dynamical systems to solve nonlinear and temporal tasks. We observe that the thermal phase of the spin model is naturally adapted to the requirements of reservoir computing while the localized phase is detrimental for the purposes of this computational approach, finding an improved performance for linear and mildly nonlinear tasks in the transition regime. We uncover the physical mechanisms behind optimal information processing capabilities of the spin networks, essential for future experimental implementations.

Link to the teams group “naXys Seminars” (unamur members) here
Link to the seminar here

International Day of Women and Girls in Science at UNamur
2021-02-11 14:00 - 17:00 (Europe/Paris)
Join to the online scientific & outreach conferences held at UNamur in the framework of the International Day of Women and Girls in Science to attend the scientific presentations of two naXys members, Morgane Dumont and Anne-Sophie Libert.
The International Day of Women and Girls in Science takes place every 11th of February, following the declaration by the General Assembly of the United Nations on 22nd of December 2015. It aims at promoting the access of women and girls to science and technology as well as their full and fair participation. This event reminds the important role of women in the scientific community. It constitutes a great opportunity to encourage girls and young women to participate in scientific developments. This year, the University of Namur takes fully part in this day. In this context, a scientific conference [in English] will highlight the research contributions of women from UNamur and promote the interaction among them and our fellow colleagues.
Check out our invited speakers. The programme is available online: https://cds.unamur.be/activites/femmesenscience/university
Please take a minute to register (it’s free!) in order to help us in terms of logistics: https://www.billetweb.fr/womeninscience
In the evening, an outreach conference [in French] is organised in collaboration with Confluent des Savoirs: https://cds.unamur.be/activites/femmesenscience/public. Do not hesitate to spread the word, specifically to non-scientists and younger generations!
Looking forward to welcoming you to our conferences!
An initiative by Lorena Ballesteros Ferraz, Aishwarya Saxena, and Sébastien R. Mouchet from the Faculty of Sciences with the support of Confluent des Savoirs (CDS) and Unité d’Appui à la Recherche (UAR).

Maxime Lucas (Aix-Marseille University, France)
2021-02-18 13:00 - 14:00 (Europe/Paris)
Title: The cell cycle as a temporal network of protein interactions
Biological systems often operate over multiple timescales and their temporal organisation is often crucial to their functioning. The cell cycle illustrates this well: before dividing into two cells, the cell must go through 4 consecutive phases. Each of these phases corresponds to specific and well-timed physiological processes, driven by protein-protein interactions (PPIs), necessary to the cycle progression. Any deviation from this temporal organisation can indicate a change in cell fate, behaviour, or a malfunction which can lead to diseases. Identifying, predicting, and understanding this temporal organisation can thus yield important insight into their behaviour.
Here, we infer phases of the cell cycle by modelling it as a temporal network of protein-protein interactions and clustering the network’s snapshots. First, we build our temporal network by integrating time series of protein concentrations to a static PPI network. Second, we group snapshots at different times that have a similar structure by clustering them. We show that the obtained clusters recover the 4 known phases of the cell cycle. Moreover, we identify the temporal organisation across a range of timescales by clustering the snapshots for different number of clusters. Results are in agreement with biological knowledge, and we show how robust they are against method changes. Finally, we explore how the input time series affect the results. For example, we investigate the effect of having only partial temporal information in the networks, i.e. not for all edges, which is a common situation in biology. Finally, we show that gene expression data from RNA-seq, widely available for many biological systems, can be used too. This method can be used to further our understanding of the multiscale temporal organisation of many biological networks.
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

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

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

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

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

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

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

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

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

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

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)

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)

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)

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

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

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

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

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).

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

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.

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.

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.
