There is a varied programme of minisymposiums organised by experts across the discipline of nonlinear dynamics.
Please note that the minisymposiums take place each day from 10.40am and 12.20pm.
Monday 22nd August
MS 01.01 - Early warning signatures of dynamical transitions
Several natural systems display abrupt transitions that bring the dynamics from a dynamical state to another, often undesirable. Examples in natural sciences range from ice ages to desertification transitions and population extinctions, as well as tipping points between clear and turbid water in a lake. In the human body, transitions to critical conditions such as epilepsy or fibrillation often occur without any apparent warning. Being able to anticipate these regime shifts is a crucial challenge in time series analysis. The ability to detect in advance such behavioral changes allows more time to prepare for the transition, mitigating its effects and increasing the overall system resilience. Oftentimes, these changes in the dynamics are related to the presence of a bifurcation, which is generally connected to the presence of the so-called "critical slowing down" (CSD) for which, as the system approaches the transition, its dynamics becomes slower, and the relaxation time to equilibrium increases. Indeed, the first attempts to anticipate regime shifts have been based on the detection of CSD. In this mini-symposium we would like to share advances in regime shift detection and characterization, bringing forward the current knowledge in this very active field. We'll analyze the problem not only from the perspective of CSD but also through new techniques based on functional network theory and time-series statistics.
| Minisymposium Title | Organisers |
Programme Code |
Speaker | Speaker Presentation Title |
|
Early warning signatures of dynamical transitions
|
Cristina Masoller Giulio Tirabassi |
MS 01.01.01 | Andrés Aragoneses | Forecasting Events in the Complex Dynamics of a Semiconductor Laser with Optical Feedback |
| MS 01.01.02 | Noémie Ehstand | Percolation framework to anticipate sudden shifts in irregular climate oscillations | ||
| MS 01.01.03 | Mathias Marconi | Testing Critical Slowing Down as a Bifurcation Indicator in a Low-Dissipation Dynamical System | ||
| MS 01.01.04 | Giulio Tirabassi | Correlation lag times provide a reliable early-warning indication of approaching bifurcations in spatially extended dynamical systems |
MS 01.02 - Data-driven modelling and analysis in weather and climate science
There are traditionally two modelling strategies in weather and climate science: the physics-based or forward approach and the data-driven or inverse approach. Recently, there has been a lot of research activity on a third, namely the hybrid approach which describes physics-based models augmented with data-driven elements. This session will be centred around nonlinear and stochastic data-driven modelling and analysis of atmospheric, oceanic and climate phenomena. It will touch on purely data-based as well as hybrid models. The talks will address deterministic and stochastic subgrid-scale parameterisations for atmosphere and ocean models, analysis and prediction of weather and climate extremes and other topics. While the applications here are geared towards weather and climate science the discussed methodologies are relevant also in a wider context of nonlinear dynamics.
| Minisymposium Title | Organisers | Programme Code | Speaker | Speaker Presentation Title |
|
Data-driven modelling and analysis in weather and climate science
|
Frank Kwasniok |
MS 01.02.01 | Frank Kwasniok | Data-driven deterministic and stochastic subgrid-scale parameterisation in atmosphere and ocean models |
| MS 01.02.02 | Nikki Vercauteren | Uncertain turbulent fluxes in the atmospheric boundary layer: a stochastic data-model fusion approach | ||
| MS.01.02.03 | Vera Melinda Galfi | On the typicality of persistent atmospheric extreme events | ||
| MS 01.02.04 | Abdel Hannachi | Towards mining weather and climate extremes via Riemannian optimization |
MS 01.03 - Adaptive dynamical networks (Parts i, ii, iii & iv)
It is a fundamental challenge to understand how the function of a network is related to its structural organization. Adaptive dynamical networks represent a broad class of systems that can change their connectivity over time depending on their dynamical state. The most important feature of such systems is that their function depends on their structure and vice versa. While the properties of static networks have been extensively investigated in the past, the study of adaptive networks is much more challenging. Moreover, adaptive dynamical networks are of tremendous importance for various application fields. For example, models for neuronal synaptic plasticity, adaptive networks in chemical, epidemic, biological, transport, and social systems, to name a few. In view of the significant growth and importance of the field, this minisymposium will present recent developments in the field of adaptive dynamical networks and serve as a discussion forum for open problems. The different parts of the minisymposium will have the following preliminary specializations: I. Theory of adaptive dynamical networks, mathematical aspects II. Theory of adaptive dynamical networks, nonlinear phenomena III. Applications, time-continuous models (neuroscience, phase-oscillator models) IV. Applications, agent-based models (social sciences, power grids, epidemic spreading, ecological networks, machine learning)
| Minisymposium Title | Organisers | Programme Code | Speaker | Speaker Presentation Title |
|
Adaptive dynamical networks (part i)
|
Rico Berner Thilo Gross Christian Kuehn Jürgen Kurths Serhiy Yanchuk |
MS 01.03.01 | Erik A. Martens | Complex dynamics in adaptive networks of phase oscillators |
| MS 01.03.02 | Luis Venegas-Pineda | Chimera States in a Coevolutive Multilayer Network framework via Geometric Singular Perturbation Theory | ||
| MS 02 03 02 |
Serhiy Yanchuk |
Asymmetric adaptivity induces recurrent synchronization in dynamical networks |
MS 01.04 - Dynamics & Life Sciences (Part i, ii, iii)
The rules governing living organisms exhibit exquisite organisation and complexity, leading to fascinating dynamical behaviour. Dynamics has been very successful at deciphering these rules in biological systems, ranging from biomolecules to ecosystems. This minisymposia will address a series of topics that make use of mathematical models to analyse and understand the dynamics of biological systems over a wide range of temporal and spatial scales.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Dynamics & Life Sciences (Part i)
|
Celso Grebogi Mamen Romano |
MS 01.04.01 | Stefan Hoppler | Computational Modelling of Wnt Signalling-Controlled Gene Regulatory Networks in Early Embryonic Development and Heart Muscle Differentiation |
| MS 01.04.02 | Celso Grebogi |
Tipping Point and Noise Induced Transients in Ecological Networks |
||
| MS 01.04.03 | Dimitra Blana | Using dynamic simulations of movement in the design of assistive devices for people with tetraplegia | ||
| MS 01.04.04 | Nicolas Rubido | Finding the resistance distance and eigenvector centrality from the network's eigenvalues |
Tuesday 23rd August
MS 02.01 - Transient Chaos (Part i)
The aim of this minisymposium is to discuss the most recent developments and tendencies in the field of transient chaos, showing examples of this complex behaviour in different applications, reporting new forms of transient chaos and describing basic mathematical tools used for their analysis. The minisymposium can be seen as a continuation of the activity reflected in the recently published special issue of J. Phys. Complexity, entitled "Focus on Transient Chaos'' and guest edited by us. Here we provide a cross section of the topics presented in this special issue, augmented with the results achieved after its completion, wherever possible.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Transient Chaos (Part i)
|
Oleh Omel'chenko Tamas Tel |
MS 02.01.01 | Oleh Omel'chenko | Non-monotonic Transients to Synchrony in Kuramoto Networks and Electrochemical Oscillators |
| MS.02.01.02 | Ying-Cheng Lai | Predicting Transient Chaos Using Machine Learning | ||
| MS 02.01.03 | Emilio Hernandez-Garcia | Flow-Network Characterization of Transient Chaos in Open Systems | ||
| MS 02.01.04 | Everton S. Medeiros | State-Dependent Vulnerability of Synchronization in Ecological Networks |
MS 02.02 - Recurrence-based Data Analysis
Recurrence plot (RP) is a robust nonlinear data analysis technique for time and spatial series introduced by Eckmann et al. (1987) to visualize the recurrence of states of a dynamical system of arbitrary dimension. RP constructs a square matrix where the matrix elements correspond to those times at which a system returns arbitrarily close to one of its past states. Recurrence of states is a fundamental property of dynamical systems and is typical for naturally occurring complex, nonlinear or chaotic systems. RP can distinguish the distinct dynamics from their recurrence patterns, such as domain-related periodicities or irregular cyclic dynamics. Recurrence plot analysis and its quantifications can also cope with large amounts of noise as well as non-stationarity behavior. As a result, RP has found applications in various fields such as geophysics, meteorology, physiology, astrophysics, genetics, psychology, and finance. As advances in recurrence quantification analysis (RQA) and its applications in these fields of science and technology are rapidly accumulating, it is essential to encourage the exchange of knowledge and novel ideas among scientists working in these scientific disciplines making use of time-and-spatial series analyses. This mini-symposium will provide a forum to facilitate the theoretical developments in recurrence-based data analysis with applications in different fields of inquiry and fathom the future potentials in spatio-temporal data analysis.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Recurrence-based Data Analysis
|
Tobias Braun Norbert Marwan Deniz Eroglu |
MS 02.02.01 | Norbert Marwan | Recent trends in recurrence analysis of dynamical systems |
| MS 02.02.02 | Tobias Braun | A recurrence flow based approach to state space reconstruction | ||
| MS 02.02.03 | Çelik Ozdes | Transformation cost spectrum for irregularly sampled time series WITHDRAWN | ||
| MS 02.02.04 | Deniz Eroglu | Multiplex Recurrence Networks | ||
| MS 02.02.05 | Thomas Stemler | Ordinal pattern analysis for physiological data with ties |
MS 02.03 - Adaptive dynamical networks (Part ii)
It is a fundamental challenge to understand how the function of a network is related to its structural organization. Adaptive dynamical networks represent a broad class of systems that can change their connectivity over time depending on their dynamical state. The most important feature of such systems is that their function depends on their structure and vice versa. While the properties of static networks have been extensively investigated in the past, the study of adaptive networks is much more challenging. Moreover, adaptive dynamical networks are of tremendous importance for various application fields. For example, models for neuronal synaptic plasticity, adaptive networks in chemical, epidemic, biological, transport, and social systems, to name a few. In view of the significant growth and importance of the field, this minisymposium will present recent developments in the field of adaptive dynamical networks and serve as a discussion forum for open problems. The different parts of the minisymposium will have the following preliminary specializations: I. Theory of adaptive dynamical networks, mathematical aspects II. Theory of adaptive dynamical networks, nonlinear phenomena III. Applications, time-continuous models (neuroscience, phase-oscillator models) IV. Applications, agent-based models (social sciences, power grids, epidemic spreading, ecological networks, machine learning)
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Adaptive dynamical networks (part ii)
|
Rico Berner Thilo Gross Christian Kuehn Jürgen Kurths Serhiy Yanchuk |
MS 02.03.01 | Sarika Jalan | Hebbian plasticity in simplicial complexes: Robustness to de-synchronization |
| MS 03.04.02 | Simona Olmi | Modelling the emergence of different frequency-coupled rhythms in rats' brainstem via mean-field models of spiking neural networks with adaptation | ||
| MS 01.03.03 | Francesco Sorrentino | Adaptive cluster synchronization in complex dynamical networks | ||
| MS 02.03.03 | Jan Fialkowski | Heterogeneous nucleation in finite size adaptive dynamical networks |
MS 02.04 - Dynamics & Life Sciences (Part i, ii, iii)
The rules governing living organisms exhibit exquisite organisation and complexity, leading to fascinating dynamical behaviour. Dynamics has been very successful at deciphering these rules in biological systems, ranging from biomolecules to ecosystems. This minisymposia will address a series of topics that make use of mathematical models to analyse and understand the dynamics of biological systems over a wide range of temporal and spatial scales.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Dynamics & Life Sciences (Part ii)
|
Celso Grebogi Mamen Romano |
MS 02.04.01 | Tom Hiscock | Mathematical models of tetrapod joint patterning: how does a finger get its knuckles? |
| MS 02.04.02 |
Alessandro Moura |
Natural selection and the spatial distribution of DNA replication origins |
||
| MS 02.04.03 | Paco Perez-Reche |
Random growth processes to model power-law and log-normal avalanche size statistics in solids and living cells |
||
| MS 02.04.04 | Ian Stansfield | Systems biology approaches to understanding human neurodevelopment diseases: a battle against homeostasis |
Wednesday 24th August
MS 03.01 - Mean-field dynamics in oscillatory and neural systems
Living brains display extraordinarily complex and rich dynamical behaviours. They can be described by their fundamental units, the neurons, coupled via an intricate web of interlinked connections. For macroscopic behaviour however, an argument can be made that due to a large number of units that are typically densely connected, a mean-field approach is the appropriate mathematical tool for understanding the large-scale dynamics of the brain, and similar large complex systems. Reformulating the dynamics in terms of a mean-field approximation often proves to be useful: the original single-unit variables are replaced by families of units with common properties, which depend on the type of approximation one is interested in. In practice, the idea is to omit unimportant microscopic details and shift the focus on average, i.e., mean-field-like, observables to confidently reproduce the global activity of the system. Mean field approximations commonly arise by considering the system’s thermodynamic limit taking the number of individual units tending to infinity, thus averaging out any stochastic effects and microscopic deviations. Thermodynamic limits can be analysed exactly and often allow natural simplifications of the dynamics, such as dimensionality reduction. This has been particularly fruitful in analysis of oscillatory ensembles where it has been shown that some common, neuroscience inspired models, such as the Kuramoto model, and even neural models such as quadratic integrate-and-fire, possess inherent low dimensional dynamics in the thermodynamic limit. This minisymposia will cover recent advances in mean-field approaches in oscillatory and neural dynamics, including novel generalisations of existing exact theories, with applications to decision-making and collective brain oscillations.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Mean-field dynamics in oscillatory and neural systems
|
Gloria Cecchini Pau Clusella |
MS 03.01.01 | Rok Cestnik | Exact finite-dimensional reduction for a population of noisy oscillators and its link to Ott-Antonsen and Watanabe-Strogatz theories |
| MS 03.01.02 | Pau Pomés Arnau | How phase resetting curves influence excitatory-inhibitory based rhythms | ||
| MS 03.01.03 | Pau Clusella | Regular and sparse neuronal synchronization are described by identical mean field dynamics | ||
| MS 03.01.04 | Gloria Cecchini | Mean-field model of consequential reward-driven decision making |
MS 03.02 - Transient Chaos (Part ii)
The aim of this minisymposium is to discuss the most recent developments and tendencies in the field of transient chaos, showing examples of this complex behaviour in different applications, reporting new forms of transient chaos and describing basic mathematical tools used for their analysis. The minisymposium can be seen as a continuation of the activity reflected in the recently published special issue of J. Phys. Complexity, entitled "Focus on Transient Chaos'' and guest edited by us. Here we provide a cross section of the topics presented in this special issue, augmented with the results achieved after its completion, wherever possible.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Transient Chaos (Part ii)
|
Oleh Omel'chenko |
|||
| MS 03.02.01 | Antonio Politi | Macroscopic Chaos in Mean-Field Models of Identical Phase Oscillators | ||
| MS 03.02.02 | Ulrich Parlitz | Chaotic Transients in Excitable Media | ||
| MS 03.02.03 | György Károlyi | The Transient Charm of Decay | ||
| MS 03.02.04 | Julia Cantisan | Transient Chaos in Systems Subjected to Parameter Drift |
MS 03.03 - Enhancing gender balance in nonlinear dynamics
Nonlinear dynamics is at the core of numerous fields such as epidemic dynamics, neurosciences, networks, etc. In spite of this diversification, there are underlying deep common problems awaiting to be solved. This workshop will bring together researchers on nonlinear dynamics working in diverse fields with the aim of identifying, discussing, and tackling these common challenges. However, since the goal of our mini-symposium is also to enhance gender balance in nonlinear dynamics, we are inviting preferably female speakers. In fact we believe that women are still under-represented in fields such as computing, mathematics and physics, therefore we are addressing the gender gap in this minisymposium, thus bringing a new point of view to the congress, while keeping intact the interest on up-to-date topics (such as epidemics, computational neuroscience or synchronization).
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Enhancing gender balance in nonlinear dynamics
|
Simona Olmi Anna Zakharova |
MS 03.03.01 | Sarika Jalan | Hebbian learning governed Robust desynchronization in pure simplicial complexes |
| MS 03.03.02 |
Johanne Hizanidis Withdrawn |
Dynamical properties of neuromorphic Josephson junctions | ||
| MS 03.03.03 | Mehrnaz Anvari | Destructive interaction of extreme wind events with electrical networks | ||
| MS 03.03.04 | Fakhteh Ghanbarnejad | Epidemic dynamics in different scales | ||
| Simona Olmi | Emergent excitability in non-excitable globally coupled units |
MS 03.04 - Adaptive dynamical networks (Part iii)
It is a fundamental challenge to understand how the function of a network is related to its structural organization. Adaptive dynamical networks represent a broad class of systems that can change their connectivity over time depending on their dynamical state. The most important feature of such systems is that their function depends on their structure and vice versa. While the properties of static networks have been extensively investigated in the past, the study of adaptive networks is much more challenging. Moreover, adaptive dynamical networks are of tremendous importance for various application fields. For example, models for neuronal synaptic plasticity, adaptive networks in chemical, epidemic, biological, transport, and social systems, to name a few. In view of the significant growth and importance of the field, this minisymposium will present recent developments in the field of adaptive dynamical networks and serve as a discussion forum for open problems. The different parts of the minisymposium will have the following preliminary specializations: I. Theory of adaptive dynamical networks, mathematical aspects II. Theory of adaptive dynamical networks, nonlinear phenomena III. Applications, time-continuous models (neuroscience, phase-oscillator models) IV. Applications, agent-based models (social sciences, power grids, epidemic spreading, ecological networks, machine learning)
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Adaptive dynamical networks (part iii)
|
Rico Berner Thilo Gross Christian Kuehn Jürgen Kurths Serhiy Yanchuk |
MS 03.04.01 | Christian Meisel | Adaptive self-organized criticality in cortical and artificial intelligence networks |
| MS 03.04.03 | Jakob Niehues | Resonant velocity tuning of solitary states in networks of coupled phase oscillators | ||
| MS 03.04.04 | Silja Sormunen | Neuroscience needs Bifurcation Theory: Neural criticality and critical drift in adaptive neural networks |
MS 03.05 - Dynamics & Life Sciences (Part iii)
The rules governing living organisms exhibit exquisite organisation and complexity, leading to fascinating dynamical behaviour. Dynamics has been very successful at deciphering these rules in biological systems, ranging from biomolecules to ecosystems. This minisymposia will address a series of topics that make use of mathematical models to analyse and understand the dynamics of biological systems over a wide range of temporal and spatial scales.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Dynamics & Life Sciences (Part iiI)
|
Celso Grebogi Mamen Romano |
MS 03.05.01 | Lionel Broche | Field cycling imaging: measuring water dynamics in vivo |
| MS 03.05.02 | Murilo Baptista | Real-world applications of the science devoted to understand from data the cause and effect relationship | ||
| MS 03.05.03 |
Ekkehard Ullner |
Collective irregular dynamics in spiking neuronal networks |
||
| MS 03.05.04 | Mamen Romano |
Translation dynamics |
Thursday 25th August
MS 04.01 - Global features of coupled dynamical systems
The dynamics of coupled systems has brought the attention to researchers from decades due to its connection with many physical models and the rich theory developed to understand them. Approaches from both theory and numerical methods have been used to understand the mechanisms organising emergent phenomena in coupled systems, such has synchrony and chimera states in coupled oscillators, and heteroclinic dynamics in more general coupled systems. The aim of this mini-symposium is to set a bridge between experts from theory and numerical methods to discuss contemporary ideas and recent developments along the line of global features that organise complex dynamics in coupled systems.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Global features of coupled dynamical systems
|
Jose Mujica |
MS 04.01.01 | Rob Sturman | Stability of heteroclinic cycles in rings of coupled oscillators |
| MS 04.01.02 | Ralf Toenjes | Low-dimensional description for ensembles of identical phase oscillators subject to Cauchy noise | ||
| MS 04.01.03 | Alejandro Barrera Moreno | Coupling of heterogeneous slow-fast systems with MMOs. New patterns and ROM simulations | ||
| MS 04.01.04 | Jose Mujica | Heteroclinic cycles under forced symmetry breaking: coupled oscillators, reduced dynamics, normal forms and invariant manifolds |
MS 04.02 - Estimating Stability Indicators from Data
Recently new approaches for the estimation of stability indicators based on various machine learning techniques have been proposed. The idea for the symposium is to bring together scientists who are working on the estimation of stability indicators from data.The goal is to have fruitful discussions on pros and cons of these new methods, examine potential pitfalls of each approach and maybe to set up numerical experiments for benchmark studies.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Estimating Stability Indicators from Data
|
Nahal Sharafi |
MS 04.02.01 | Sarah Hallerberg | Estimating covariant Lyapunov vectors from data |
| MS 04.02.02 | Nikki Vercauteren | Guidelines for data-driven approaches to study transitions in multiscale systems: the case of Lyapunov vectors | ||
| MS 04.02.03 | Yumeng Chen | Inferring the instability of a dynamical system from the skill of data assimilation exercises | ||
| MS 04.02.04 | George Datseris | Stability Indicators in DynamicalSystems.jl |
MS 04.03 - Metastability in neuron networks
Metastability of neuron dynamics is receiving growing recognition for its important role in cognition, sensory processing, or cortical computations. The term metastability, however, is often used in various contexts - ranging from the classical definition related to energy in physical systems via the dynamics of large but finite deterministic systems with quenched disorder to a hopping dynamics between different dynamical regimes or space-time patterns - rendering its interpretation for brain dynamics difficult. Addressing this issue, this minisymposium discusses metastability from the point of view of networked dynamical systems thereby highlighting the important role of "connectivity" (coupling structure) for an improved characterization of dynamical regimes and transitions between them. Special emphasis is given to the implications of metastability for neuron networks.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Metastability in neuron networks
|
Klaus Lehnertz |
MS 04.03.01 | Kalel Luiz Rossi | Towards a unifying view of metastability in neuroscience |
| MS 04.03.02 | Bastian Pietras | Mesoscopic description of metastability in networks of spiking neurons with short-term plasticity | ||
| MS 04.03.03 | Roberto C. Budzinski | Connecting individual network structures to collective behavior in oscillator systems | ||
| MS 04.03.04 | Tobias Fischer | Utilizing metastability to design a testbed for a data-driven estimation of resilience in networked dynamical systems |
MS 04.04 - Adaptive dynamical networks (Part iv)
It is a fundamental challenge to understand how the function of a network is related to its structural organization. Adaptive dynamical networks represent a broad class of systems that can change their connectivity over time depending on their dynamical state. The most important feature of such systems is that their function depends on their structure and vice versa. While the properties of static networks have been extensively investigated in the past, the study of adaptive networks is much more challenging. Moreover, adaptive dynamical networks are of tremendous importance for various application fields. For example, models for neuronal synaptic plasticity, adaptive networks in chemical, epidemic, biological, transport, and social systems, to name a few. In view of the significant growth and importance of the field, this minisymposium will present recent developments in the field of adaptive dynamical networks and serve as a discussion forum for open problems. The different parts of the minisymposium will have the following preliminary specializations: I. Theory of adaptive dynamical networks, mathematical aspects II. Theory of adaptive dynamical networks, nonlinear phenomena III. Applications, time-continuous models (neuroscience, phase-oscillator models) IV. Applications, agent-based models (social sciences, power grids, epidemic spreading, ecological networks, machine learning)
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Adaptive dynamical networks (part iv)
|
Rico Berner Thilo Gross Christian Kuehn Jürgen Kurths Serhiy Yanchuk |
MS 04.04.01 | Miguel C. Soriano | Inferring untrained dynamics of complex systems using adapted recurrent neural networks |
| MS 04.04.02 | Leonhard Lücken | Emergent Diversity and Persistent Turnover in Evolving Microbial Cross-Feeding Networks | ||
| MS 04.04.03 | Rico Berner | What adaptive neuronal networks teach us about power grids | ||
| MS 04.04.04 | Christian Bick | Coupled oscillators, dead zones, and networks with effective adaptivity |
Friday 26th August
MS 05.01 - Data-driven modelling and analysis of complex dynamical systems
The minisymposium is focused on theoretical, numerical, and experimental methodologies for the data-driven modelling and analysis of complex/ nonlinear dynamical systems. Presentations include the development and implementation of machine, manifold learning and numerical analysis methodologies for data and model reduction, the solution of the inverse and forward problems, the control and optimization of complex systems based on large-scale data produced by experiments and/or detailed high-fidelity microscopic simulations.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Data-driven modelling and analysis of complex dynamical systems
|
Constantinos Siettos Lucia Russo Yannick de Decker |
MS 05.01.01 | Jens Starke | Data-driven detection of unstable states, stability information and bifurcations in laboratory experiments |
| MS 05.01.02 | Felix Dietrich | Quantum Process Tomography from Time-Delayed Measurements | ||
| MS 05.01.03 | Jan Sieber | Finding nonlinear emergent behaviour in a spatial tropical forest model |
MS 05.02 - Extreme Events
Complex systems study is an important topic of research direction both from the dynamical systems perspective and network formalism, which receives tremendous attention from researchers, and now becomes an interdisciplinary field of science in its own rights. Extreme events are no doubt one the most important topics to be discussed for its recent trend of activities. It may provide clues on future prediction of devastating extreme phenomena in climate, earth, ecosystems, and the brain to mention a few. On the other hand, the study of extreme events in complex networks is another interesting topic of research, in particular, the origin of extreme events in engineering systems such as the power grid. Control of this devastative phenomenon in some man made systems in advance to save the loss. Recent works and review articles suggest that the use of extreme value theory for the understanding of extreme events in dynamical systems is another direction of research. Our proposed mini-symposium will arrange about 4/5 talks on recent progress in dynamical system studies and the network-theoretic approaches to extend our understanding on extreme events, in general, and how to use real data for the purpose of prediction using both network construction and machine learning.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Extreme Events
|
Dibakar Ghosh |
MS 05.02.01 | Syamal Kumar Dana | Extreme events in dynamical systems: Mechanisms and predictability |
| MS 05.02.02 | Neelima Gupte | Climate network analysis of extreme events: Tropical Cyclones | ||
| MS 05.02.03 | Timo Broehl | Characterizing predictive edges in complex networks that can generate extreme events | ||
| MS 05.02.04 | Dibakar Ghosh | Extreme events in complex networks and statistical analysis |
MS 05.03 - Critical transitions in nonlinear dynamical systems: theory and applications
Abrupt and large changes in the state of nonlinear dynamical systems when an external input (forcing) is varied can be characterized as tipping phenomena or a critical transition. Various types have been identified so far: bifurcation-induced, noise-induced, shock-induced, or rate-induced tipping. In many applications, the question of predictability or early warning of a critical transition is of prime importance, and constitutes a pressing problem particularly in climate and ecology. This minisymposium highlights recent advances in theory and applications of tipping phenomena and considers various notions of predictability of such transitions. We focus on applications in mathematical models from climate science and ecology to discuss new and counter-intuitive tipping phenomena that could occur in the real world. We examine limits to predictability in past abrupt transitions of the earth’s climate. Physical measures of autonomous systems can give us statistical predictability of the system. We consider a notion of natural measure for nonautonomous systems and how they can give rise to tipping probabilities.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Critical transitions in nonlinear dynamical systems: theory and applications
|
Ulrike Feudel Lea Oljaca |
MS 05.03.01 | Peter Ditlevsen | Are transitions in the climate predictable? Learning from the paleoclimatic records. |
| MS 05.03.02 | Calvin Nesbitt | Noise Induced Transitions in a Bistable Toy Model of Climate | ||
| MS 05.03.03 | Eoin Geoffrey O'Sullivan | Rate-Induced Tipping of the Compost Bomb: Sizzling Summers, Heteroclinic Canards and Metastable Zombie Fires | ||
| MS 05.03.04 | Julian Newman | Natural measures of asymptotically autonomous systems |
MS 05.04 - Dynamics of Urban Complexity: Infrastructural Entanglements
The complexity sciences have informed urban research conceptually and methodologically in a multitude of ways. The city has been metaphorically understood through ideas of equilibrium and the invisible hand from economic complexity, updated to non-linear systems from mathematics and systems on the edge of chaos from physics, eventually incorporating evolutionary aspects by borrowing complex adaptive systems from ecology.
In fact, cities cannot be reduced to quantifiable or observable phenomena since urban dynamics are transformative processes dependent on cognitive action undertaken by agents/agencies with differing motivations operating within differing structural parameters.
Urban sub-systems such as infrastructures are unavoidably dynamic, temporal and cognitive, requiring an interdisciplinary research framework from the complexity sciences and social systems. Methodological crossovers related to graph theory, social networks, spatial statistics and computational modelling have led to urban complexity research incorporating both the study of urban phenomena and the organisational complexity of influencing processes such as planning.
Design introduces a third disciplinary dimension to urban research, concerned more with how futures should be, rather than stopping at how cities and infrastructures operate now. A design science approach involves the development of computational tools to design alternative possibilities and test ex-ante performance criteria based on identified values and societal goals such as sustainability. The emerging field of urban complexity research explores the complex dynamics of change through an attempt to unravel and influence infrastructural entanglements.
In this mini-symposium, we examine the dynamics of urban complexity in infrastructural entanglements theoretically and empirically to identify where and how complexity science can be usefully applied in impactful urban research.
| Minisymposium Title | Organisers | Programme Code | Speakers | Speaker Presentation Title |
|
Dynamics of Urban Complexity: Infrastructural Entanglements
|
Deljana Iossifova Ulysses Sengupta |
MS 05.04.01 | Yahya Gamal | Infrastructuring as Caring: Transforming Infrastructural Entanglements |
| MS 05.04.02 |
Denise P Lozano Lazo / Alexandros Gasparatos |
Exploring the linkages between formal and informal solid waste management in developing countries through a system dynamics approach | ||
| MS 05.04.03 | Anas Alsharif | Where is the Complexity? Exploring the Theoretical Frameworks in Simulative Urban Modelling | ||
| MS 05.04.04 | Yahya Gamal | Land Market Preferences in Formal-informal Contexts: Urban Segregation Emergent Patterns | ||
| MS 05.04.05 | Norma Valencio | Uncovering the hidden social dynamics behind disaster decreeing in Brazil |