There is no English translation for this web page.
Workshop: Perspectives on Complex Systems 2018
- © SFB910
Title: Perspectives on Complex Systems
The aim of this workshop is to provide a platform for scientific exchange on most recent topics and future perspectives of complex systems. It will bring together experts from various fields at the end of the 2nd funding period of Collaborative Research Center 910. A number of invited presentations (25+5min) will offer insights into both past advancements and promising leads for future research. The second day of the workshop is reserved for 2 PhD defenses from project B10 "Control of networks with time-varying topologies and applications to epidemiology".
Students interesting in attending the workshop as block seminar (3233 L 515) should contact Dr. Philipp Hövel (firstname.lastname@example.org ) for further details.
For directions to TU Berlin see https://www.itp.tu-berlin.de/ag_empirische_netzwerke_und_neurodynamik/hoevel/kontakt/anfahrt_tu/parameter/en/ "
Monday, December 17, 2018
|9:00 - 9:30||Physics of the immune
of Sussex, UK|
10:00||Physics of Disease
of Theoretical Physics, TU Berlin|
|10:00 - 10:30||Dynamics of systems
with distributed delays||Yuliya
of Sussex, UK|
11:30||Multi-cluster structures in
networks of adaptively coupled|
of Mathematics & Theoretical Physics, TU Berlin|
12:00||Operational stochastic thermodynamics: From
quantum backaction to time-delayed feedback
Strasberg||Université du Luxembourg|
|12:00 - 12:30||Emergent
hierarchies and social stability||Marton
|12:30 - 14:30||--Lunch
|14:30 - 15:00|| Network
Science Perspective on Hollywood
15:30||Bio‐inspired Information Processing: The
Future of Artificial Intelligence?||Hermann
zu Kiel, Germany|
16:00||Nation-Wide Supply Chain Data and
Inoue||University of Hyogo, Kobe,
Tuesday, December 18, 2018
- 11:00 ||Computational and Anaytical
Approaches Towards Epidemic Spread Containment of Temporal Animal
Bassett||Institute of Theoretical
16:00||Dynamics of collective attention:
Competition for ephemeral popularity and the impact of modern
communication pathways ||Philipp
Lorenz-Spreen||Institute of Theoretical
Wednesday, December 19, 2018
- 9:30 ||Controlling current on the quantum
|9:30 - 10:00||Integrating Network
Modeling and Emerging Data Sources to Approach Large-Scale Problems in
Public Health||Abigail Horn||1)
Federal Institute for Risk Assessment (BfR), Berlin, Germany, |
2) Kühne Logistics University, Hamburg, Germany
10:30||Temporal network approaches for human and
veterinary public health||Beatriz
of Bern, Switzerland|
11:30||Cascade dynamics on
of Limerick, Ireland|
12:00||Entropic selection of concepts unveils
hidden topics in documents corpora||Alessio
of Bristol, UK|
Overview of the talks in chronological order.
Monday, December 17
Affiliation: University of Sussex, UK
Affiliation: Institute of Theoretical Physics, TU Berlin
Title: Dynamics of systems with distributed delays
Affiliation: University of Sussex, UK
Title: Controlling current on the quantum scale
Affiliation: Newcastle University, UK
Control of the emission and flow of electrons forms the basis of electronics and with it much of modern technology. As we shrink and cool electronic circuits, we enter a regime where the granularity and wave-particle duality of electrons become important. Learning to control electron behaviour in this quantum-transport regime presents significant challenges, but also opens up opportunities for new physics and device functionalities.
In this talk, I will give an overview of the nascent field of feedback control in quantum transport. I will discuss how feedback can give rise to a range of interesting effects, such as noise suppression, quantum-state stabilisation, and Maxwell's daemon. Finally, I will also future developments and the prospect of coherent quantum control.
Title: Operational stochastic thermodynamics: From quantum backaction to time-delayed feedback control
Affiliation: Université du Luxembourg
The theory of stochastic processes describes noisy systems which
are perfectly and passively observed. Unfortunately, it can be no
longer used whenever an external agent passively or actively intervenes
the process (e.g., via measurement disturbance or feedback control).
The lack of a formal understanding of such processes has also
hindered progress in understanding the thermodynamics of feedback
controlled classical and, in general, quantum systems.
After briefly reviewing how to generalize stochastic processes to
arbitrary interventions, I will show how to define the basic
thermodynamic quantities internal energy, heat, work and entropy
along a single observed trajectory. The validity of the first and
second law is established. Based on a recent experiment I
demonstrate the versatility of the framework to describe even time-
delayed quantum feedback control.
Title: Emergent hierarchies and social stability
Affiliation: UC Davis, USA
Hierarchy of social organization is a ubiquitous property of animal and human groups, linked to resource allocation, collective decisions, individual health, and even to social instability. In my talk, I will discuss aspects of modelling the dynamics of hierarchy formation. I will first focus on the role of talent versus social feedback in obtaining rank. Experimental evidence shows that both impact hierarchies; existing mathematical models, however, focus on the latter. I will introduce a rigorous model that incorporates both features, and show effects that arise from the interaction of the two.
In the second half of my talk, I will discuss our collaboration with the California National Primate Research Center, this joint work aims to model the social structure and stability of rhesus macaque groups. Rhesus macaques live in cohesive hierarchically-structured groups of approximately one hundred individuals. Their social organization is regulated by a multiplex network defined by kinship and a number of interactions including grooming, fighting and formal submission. A notable property of macaque societies is that they can become unstable: the hierarchical organization may collapse, culminating in large-scale fighting, dissolution of social order and disbanding of entire groups. I will briefly describe the structure of their social networks and how modelling their dynamics help us understand social collapse.
Vitaly Belik1 und Kathleen Loock2
Title: Network Science Perspective on Hollywood Remakes
1AG System Modeling, Institute for Veterinary Epidemiology and Biostatistics, Department of Veterinary Medicine, Freie Universität Berlin
Title: Bio‐inspired Information Processing: The Future of Artificial Intelligence?
Affiliation: Institute for Electrical Engineering and Information
Kiel University, Germany
Information processing in biological nerve system is characterized
by highly parallel,
energy efficient and adaptive architectures in contrast to clock driven digital Turing
machines. Even simple creatures outperform supercomputers when it comes to pattern
recognition, failure tolerant systems and cognitive tasks. Fundamental building blocks
leading to such remarkable properties are neurons as central processing units, which are
(with variable strengths) interconnected by synapses to from a complex dynamical three
dimensional network. The field of neuromorphic engineering aims to mimic such biological
inspired information pathways by electronic circuitries. Up to today, this approach is
hindered by an inadequate understanding how to link the information pathways on the
local, synaptic and neuron level to the global functionality of the entire brain network. One
of the central pillars in science (for example in solid state physics) the so‐called
“reductionism” smilingly reaches its limits and nourishes a longstanding conflict between
natural science and spiritual science.
In the talk I will show restrictions of conventional IT and present alternative
computing architectures, which are currently under investigations. The challenges and
possible limitations of bio‐inspired computing approaches will be discussed.
Affiliation: University of Hyogo, Kobe, Japan
Titel: Multi-cluster structures in networks of adaptively
Affiliation: Institute of Mathematics, TU Berlin
Institute of Theoretical Physics, TU Berlin
Dynamical systems on networks with adaptive couplings appear naturally
in real-world systems such as power grid networks, social networks as
well as neuronal networks. We investigate collective behaviour in a
paradigmatic network of adaptively coupled phase oscillators. The
coupling topology of the network changes slowly depending on the
dynamics of the oscillators. We show that such a system gives rise to
numerous complex dynamics, including relative equilibria and
hierarchical multi-cluster states. An analytic treatment for equilibria
and multi-cluster solutions as well as the existence of continuous
families of these states is presented and parameter regimes of high
multi-stability are found. In addition, we give an interpretation for
equilibria as functional units which are building blocks in
multi-cluster structures. Our results contribute to the understanding of
mechanisms for pattern formation in adaptive networks, such as the
emergence of multi-layer structure in neural systems.
Wednesday, December 19
Title: Complexity and infectious disease epidemics
Affiliation: Inserm & Sorbonne Université Paris, France
Our understanding of infectious diseases prevention and control is rooted in the theory of host population transmission dynamics. Contacts between hosts (along which transmission can occur) and contacts between populations of hosts (along which spatial diffusion can take place) drive the epidemiology of infectious diseases, determining if and how quickly they spread, and who gets infected. Mathematical epidemiology has made great progress in this area in the last decades, moving from approximations where every host is in contact with anyone else with equal probability (i.e. the homogeneous mixing assumptions) to frameworks where patterns of contacts between hosts or population of hosts are explicitly accounted for through networks, made of nodes representing hosts/populations of hosts and connections representing potential transmission/diffusion links. This talk will present recent findings on the role that complexity of host population structure has on the resulting disease spreading dynamics and discuss future perspectives on the use of epidemic modeling approaches in the realm of public health.
Title: Integrating Network Modeling and Emerging Data Sources to Approach Large-Scale Problems in Public Health
1 Federal Institute for Risk Assessment (BfR), Berlin, Germany
2 Kühne Logistics University, Hamburg, Germany
∗ E-mail: email@example.com
My research focuses on modeling network structure and dynamics to better understand how disease and
behavior spread through physical and social systems, to inform and develop interventions for preventing,
mitigating, and controlling both infectious and chronic diseases. Research problems and approaches are
motivated by and evaluated on large-scale real-world network data from physical systems including trans-
port, logistics, and infrastructure, as well as digital trace data from social networks, mobile phone records,
credit card transactions, and other emerging sources. The questions I am researching can be categorized
into three primary areas: (i) How do network structure and dynamics influence transmission of disease or
behaviors; (ii) Can we develop accurate predictions and forecasts for real-time outbreak response and risk
assessment; and (iii) What are network-based interventions and mitigation strategies for preventing diseases.
In this talk I will discuss a few current research activities within these themes, including: modeling food
supply network structure to identify the source of large-scale outbreaks of foodborne disease [1-3]; tracing
the source of network-based disease diffusion processes more generally including infectious diseases spread
through the global air traffic network and cholera spread through water distribution networks; and integrat-
ing digital trace data to quantify the impact of mobility on food consumer behavior, nutrition, and health.
I will also provide a perspective on current themes and opportunities for integrating emerging data sources
to model social network structure for public health applications.
 Balster, A., and Friedrich, H. (2018). “Dynamic freight flow modelling for risk evaluation in food supply,”
Transportation Research E, doi.org/10.1016/j.tre.2018.03.002 .
 Horn, A., Friedrich, H. (2018). “Locating the Source of Large-scale Diffusion of Foodborne Contamina-
tion.” arXiv preprint arXiv:1805.03137.
 Liu, X., Horn, A., Su, J., Jiang, J. (2018).“A Universal Measure for Network Traceability.” Omega: The
International Journal of Management Science. 10.1016/j.omega.2018.09.004.
Both human and veterinary public health aim to the wellbeing of human populations. Their perspective and therefore the challenges they face are, however, very different. Network approaches have become, for both disciplines, state of the art methods for modelling infectious disease spread. I will summarize a first case study of a bioterror attack on a human population, and the most effective way to control it (Vidondo et al 2012); and a second case study of a generic infectious process spreading on a livestock population and a very effective way to detect it (Vidondo and Voelkl 2018; Schirdewahn et al in prep). In both case studies, social contacts (for disease transmission) are realistically specified using single layer temporal networks. I will finally outline the prospect of multilayer temporal networks to answer research questions in what epidemiologists call a "one-health" approach (humans, their livestock and the environment they live in, including wildlife).
Vidondo, B. Voelkl. B. 2018. Dynamic network measures reveal the impact of cattle markets and alpine summering on the risk of epidemic outbreaks in the Swiss cattle population. BMC Vet Res 14(1):88
Schirdewahn, F., Vidondo, B. Koher, A., Lentz, HHK, Colizza, V., Hövel, P. Outbreak detection in livestock networks. In preparation.
Title: Cascade dynamics on networks
Affiliation: University of Limerick, Ireland
Network models may be applied to describe many complex systems, and in the era of online social networks the study of dynamics on networks is an important branch of computational social science. Cascade dynamics can occur when the state of a node is affected by the states of its neighbours in the network, for example when a Twitter user is inspired to retweet a message that she received from a user she follows, with one event (the retweet) potentially causing further events (retweets by followers of followers) in a chain reaction. In this talk I will review some simple models that can help us understand how social contagion (the spread of cultural fads and the viral diffusion of information) depends upon the structure of the social network and on the dynamics of human behaviour. Although the models are simple enough to allow for mathematical analysis, I will show examples where they can also provide good matches to empirical observations of cascades on social networks.
Title: Entropic selection of concepts unveils hidden topics in
Affiliation: University of Bristol, UK
The organization and evolution of science has recently become itself
an object of scientific quantitative investigation, thanks to the
wealth of information that can be extracted from scientific documents,
such as citations between papers and co-authorship between
researchers. However, only few studies have focused on the concepts
that characterize full documents and that can be extracted and
analyzed, revealing the deeper organization of scientific knowledge.
Unfortunately, several concepts can be so common across documents that
they hinder the emergence of the underlying topical structure of the
document corpus, because they give rise to a large amount of spurious
and trivial relations among documents. To identify and remove common
concepts, I will introduce a method to gauge their relevance according
to an objective information-theoretic measure related to the
statistics of their occurrence across the document corpus. After
progressively removing concepts that, according to this metric, can be
considered as generic, I will show how the topic organization of the
corpus under scrutiny displays a correspondingly more refined