*Report by Matt Garrod*

The Institute of Physics’ Nonlinear and Complex Physics Group held their Spring meeting on Wednesday the 30th of May. The event which was entitled “Graph Theory and Physics” and was held at Imperial College London. The event attracted approximately 30 attendees from a wide variety of disciplines, both from Imperial College and other institutions around the country.

Many physicists are active researchers in the field of complex networks, which often makes use of tools from statistical physics and graph theory to study networks which crop up in fields of research such as biology, economics and the social sciences. However, as it turns out, there are a plethora of different applications of graph theory even within physics itself. The aim of the event was to explore these connections and provide an opportunity for those working in physics to be introduced to mathematical ideas from graph theory and vice versa.

The morning mostly focused on applications of graph theory to quantum physics. The first talk from Svenn Gnutzmann of University of Nottingham discussed the applications of graph theory in the study of quantum chaos while UCL’s Professor Simone Severini discussed the application of graphs to quantum information theory. These ideas were explored further later in the day by Loughborough University’s Brian Winn.

The following two talks showcased how the interdisciplinary nature of graph theory make it a rich source for collaboration. Dhruv Saxena and Alexis Arnaudon are both postdoctoral researchers at Imperial College from the departments of physics and mathematics respectively. Dhruv is physicist based in the Complex Nanophotonics group within Imperial who’s work concerns so called “random networks of optical lasers”. Dhruv’s talk introduced the physics of the problem and the experimental setup of photonic lasers. Following this, Alexis introduced his own mathematical of the model of the system created in order to gain some insight into how such systems behave and how they might be controlled.

Many of the talks focused on using graph theory to study physics at small scales. The next talk given by Stav Zalel, a PhD student in theoretical physics at Imperial College provided a contrast to this. Stav spoke about her work in studying “causal sets” which are one candidate approach to quantum gravity. This research is relevant for modelling and understanding the large scale structure of the universe. Following this, David Reutter, a PhD student at the University of Oxford, provided a talk showcasing his work which lies at the intersection of quantum information, compact quantum groups and category theory.

The rest of the Afternoon saw several talks concerning some of the applications of graph theory and network science to fields other than Physics. Oliver Smith spoke about the analysis of flows in complex networks with respect to a metric known as the Price of Anarchy. While the final student speaker of the day, Imperial College’s Ronan Macadam described the analysis of transport of plastic through the “connectivity network” of different regions in the ocean using a Markov-Chain based model.

The final talk of the day was given by Professor Ernesto Estrada, a prominent researcher in the field of network science, who has published numerous papers as well as two text books on the subject. In his talk he introduced the idea of communicability on networks. Researchers commonly use the average shortest path between nodes in a graph to measure how well connected the system is. Communicability provides an alternative measure which is motivated by how information or messages are actually known to pass through a graph, which is not necessarily by using the shortest path or most efficient route. Following the final talk was a drinks reception which provided an opportunity for researchers to network and discuss the topic further.

]]>**Artificial Intelligence and Complexity: ****What can AI do for physics and what can physics do for AI?**

AI isn’t magic, but to many physicists working in complexity science it might as well be! This all-day meeting is an opportunity for non-specialists to experience an introduction to the central concepts and open research questions in this fast-progressing field. The aim of the event was to explore links between approaches in the field of complexity science and those in AI, and to consider how AI could play a role in solving the hardest problems in physics.

**Key Themes**:

- Elucidating the underlying principles of AI, giving concrete examples which bring them to life.
- Cutting edge problems in AI from a physicist’s perspective.
- Applications of AI to problems in physics: opportunities, challenges and limitations.

**Speakers included**:

- Professor Tobias Preis (University of Warwick)
- Ilya Feige (ASI Data Science)
- Marc Deisenroth (Imperial College London)

**Event Report**

On the Wednesday the 6th of December 2017 the Institute of Physics’ Nonlinear and Complex Physics Group held its annual winter meeting in the EPSRC CDT space. The theme for the day long meeting was “Artificial Intelligence and Complexity.” The event attracted over 40 people from a range of backgrounds in physics, applied mathematics and computer science.

The morning centred around two 50 minute talks given by Ilya Fiege, head of research at ASI data science. He covered the mathematical background behind neural networks: starting from linear regression and moving to the more general approach of training neural networks. In addition, as a seasoned data scientist, he was able to articulate the theoretical issues in the subject that may plague mathematicians but do not actually make an important difference in practice.

The second keynote speaker of the day was March Deisenroth, a lecturer in statistical machine learning at Imperial College. He gave an introduction to the theory of Gaussian processes. He reported on the application of these techniques to study data from high energy physics experiments at the LHC. Secondly, he reported on using similar techniques for data efficient learning in robotics. This included video demonstrations of robots learning to walk and balance.

The final keynote talk of the day was given by Professor Tobias Preis of the University of Warwick. His talk focused on methodologies for measuring and predicting human behavior using online data. This included using google searches to predict the behavior of the stock market, using geotagged photos from the photo sharing website Flickr to identify global travel flows and a study of how the visual beauty of different landscapes in the UK can influences people’s health.

Contributed talks from PhD students and Postdoctoral researchers covered a range of topics including the use of neural networks for data assimilation in ocean and weather models, machine learning techniques applied to remove noise in optical fiber transmissions and the thermodynamics of statistical inference.

Also see https://mpecdt.org/artificial-intelligence-and-complexity-event/

]]>**Michael Kitromilidis, Imperial College London**

The conference took place from June 19th to June 23rd and was organised by Indiana University, Bloomington in conjunction with the Network Science Society. It was the 12th annual instalment of NetSci, which has been organised around the world, bringing together network scientists from a wide range of disciplines. This year’s conference was attended by 680 participants.

My participation in the conference consisted of a talk on a satellite meeting centred around the theme of “Social Influence in Networks” on Monday, June 19th and a poster contribution, whose main plenary presentation was Wednesday, June 21st.

My talk was entitled “Network structure in artistic influence”, and was based on one of the two main projects of my PhD research, where I form a social network of Western art painters and am using community detection methods, standard and generalised centrality measures, and measures of brokerage to identify and quantify artistic influence. What makes me particularly motivated about this project is how it finds a novel area where networks become relevant and can be used to bridge yet another discipline with applications of physics. The talk also got a few interesting questions and comments about my definition and construction of the network, which I can certainly use in later work.

My poster, entitled “Preferential attachment in container shipping” was based on the second main project of my PhD work, which is modelling container shipping networks by models incorporating the concept of exogenous intrinsic fitness. The objective is to understand how a port’s attractiveness impacts its capability to attract edges in a growing network, which in turn motivates the more theoretical discussion of how a latecomer node in a growing network can depend on its fitness to eventually dominate the network. My work attracted interest from young researchers who were working with the fitness model theoretically, and mainly from a post-doc from Dalian University in China, who was also working on container shipping networks and found the inclusion of fitness quite promising.

Apart from presenting my own work, I had the opportunity to listen to world authorities on the field of networks, such as A.L. Barabási, S. Borgatti, A. Clauset and R. Lambiotte. Possibly one of the most interesting talks I heard in the conference was by one of the youngest authorities in networks, D. Bassett, whose applications of networks in neuroscience I found fascinating and deeply inspiring. I was also delighted to meet other young researchers in the field of networks, whose community drive definitely seems to keep the field growing.

I am deeply grateful to the IOP, and in particular the Nonlinear and Complex Physics Group for their very significant contribution towards my travel costs, which definitely made my attendance of NetSci 2017 possible. I was also quite honoured to be able to acknowledge the contribution on my talk and poster, making me feel deeply integrated within the physics community of the UK. Thank you for making this possible.

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**Sarah Morgan, University of Cambridge**

From telecommunication networks to social networks and gene regulatory networks, network science is now routinely applied in a wide range of fields. NetSci has emerged as the main annual conference for the network science community. NetSci 2017 was the 12th edition of the conference and was held in Indianapolis, USA, with over 600 attendees. The highly interdisciplinary nature of network science was reflected in the backgrounds of the attendees which covered a wide range of disciplines including physics, mathematics, computer science, engineering, biological sciences, social sciences and the humanities.

The event began with two days of satellite meetings, covering a diverse range of topics from Machine Learning in Network Science to Urban networks and the Statistical Physics of Financial and Economic networks. On the first morning, I attended the Network Medicine satellite on ‘Quantitative interactome and multilayer networks taking medicine beyond the genome’. I particularly enjoyed the keynote lecture given by Prof. Nitesh Chawla on his work trying to go from disease centred medicine to patient focused medicine, combining different data types to predict a patients’ susceptibilities to diseases. His comments that ‘maths is easier than people’ and that often the difficulties lie in the nuances of obtaining and understanding the data resonated strongly with my own research. On Tuesday, I attended the Network Neuroscience satellite, which was the first edition of this satellite meeting and started with an excellent keynote talk from Prof. John Beggs. Prof. Beggs discussed his work studying the functional connectivity of around 300 neurons and presented intriguing results suggesting that 20% of neurons are responsible for around 70% of information transfer. The rest of the morning provided an opportunity to learn more about different methods and data available, for example data from the Allen Brain Institute mapping the mouse brain in unprecedented detail. In the afternoon, I presented a poster on my work so far combining graph theory and machine learning approaches to diagnose and predict schizophrenia as part of the PSYSCAN project. Whilst this work is still ongoing, it was extremely helpful to get feedback on the various approaches we are taking and I came away with several ideas for future directions.

The main part of the conference began on Wednesday, with a keynote from Prof. Dani Bassett on her work on a range of structural and functional brain networks. In the afternoon, I gave a talk on my research using network motifs (small subgraphs of networks) to study the key driving factors underlying the global topological properties of functional MRI brain networks. The rest of the conference covered a wide range of talks and discussions, including for example the challenges around defining network measures to fully exploit the characteristics of a problem but not overfitting a particular dataset. The networking sessions provided great opportunities to meet other researchers in the field and I was able to meet many brain network researchers for the first time.

At the end of the conference, I also took opportunity to visit Prof. Olaf Sporns’ lab in nearby Bloomington. The group were extremely welcoming and the visit provided an ideal opportunity to discuss my research in more detail with group members and to discuss how some of the methods developed in Prof. Sporns’ group could be applied to the schizophrenic datasets I am working on as part of PSYSCAN (for example work on path ensembles by Dr Andrea Avena-Koenigsberger).

Overall the conference succeeded in bringing together network scientists from a wide range of disciplines and gave me many ideas to further my own research. The conference organisers should also be commended on the number of female speakers; with over 50% of keynote talks given by women this was certainly one of the most forward-thinking conferences I have attended.

]]>Further details can be found here: https://www.bera.ac.uk/event/complexity-and-education

The event attracted more than 40 people from across disciplines and from across Europe, and a broad range of issues was discussed, in education and beyond.

The submitted papers can be found here. Please note that speakers went beyond these papers in the seminar however.

*Outline:*

Anyone familiar with education knows that it is a complex undertaking, involving the interaction of myriad influences and concerns. Over the last few decades however, the term ‘complex’ has taken on new meaning in both the natural and social sciences, denoting how the interplay of dynamic elements results in the emergence of patterns and meanings that cannot be predicted by considering those elements in isolation.

13.00 | Welcome and introductions, refreshments |

13.20 | Paper 1: An Introduction – The Case for Complexity inEducation, followed by 10 mins initial questions |

14.00 | Paper 2: Curriculum and Complexity: A DifferentImaginary, followed by 10 mins initial questions |

14.40 | Refreshments |

15.10 | Paper 3: Complexity and the Characterisation of Learning Complexity and the Characterisation of Learning,followed by 10 mins initial questions |

15.50 | Paper 4: Assessment Policy, ‘ Readiness for School ’ and aComplexity View of Time, followed by initial questions |

16.30 | Chaired questions and discussion |

17.55 | Completion of evaluation forms |

18.00 | Wine reception and networking event |

20.00 | Close of event |

**Further reading**

A number of delegates have asked about further reading in complexity in education, and in the social sciences more broadly. Some good starting places might be:

Complexity in Education

Cilliers, P. (1998) *Complexity and postmodernism: understanding complex systems. *London: Routledge. (available as a pdf here) – Paul was a key figure in bringing together complexity and insights from social discourses.

Stacey, R. (2003) *Complexity and Group Processes. *Hove: Brunner-Routledge. – Ralph Stacey is a leading figure in the consideration of complexity in organisations.

[I would propose that there are subtle differences in the way that Cilliers, Byrne and Stacey have interpreted complexity in social systems, and these different strands are reflected in contemporary research].

The E: Co Journal is an open access journal which hosts a wide ranging discussion about the applications of complexity theory to organisations: https://journal.emergentpublications.com/

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*Early career members are invited to attend this exciting town meeting to shape an IOP special interest group which will support members working across the whole community, in academia, business and education.*

*The proposed group will enable early career members to build a network of peers, develop an effective mentoring scheme and to ensure members understand the different career options available to them as well providing access to the development of vital skills.*

*Attending the town meeting will enable you to:*

*Be inspired by a panel of leaders who have experienced different career paths across academia, business and education**Identify barriers for early career members and help shape the group to meet your needs**Connect with likeminded early career members**Get the opportunity to be actively involved*

*If you are interested in attending but cannot because of your geographical location the afternoon session will be live streamed on YouTube. Please indicate on the registration form if you would like to take part through this format.*

Please take a look at their website, which details their aims as below:

**Aims**

The objective of the Statistical and Nonlinear Physics Division (SNPD) is the advancement of research in statistical and nonlinear physics, the dissemination of key results in this area to the general public, and the promotion and coordination of interdisciplinary research. More specifically, the SNPD aims to form an umbrella organization for coordination of research in statistical physics, nonlinear physics, complex systems and interdisciplinary applications and

- to promote studies and dissemination in this general research area
- to facilitate contacts between members
- to encourage collaboration and exchange of knowledge between different disciplines
- to stimulate the interest of young scientists in the field of statistical physics, nonlinear physics, and complex systems
- to organize and support conferences and workshops
- to maintain contacts with related divisions within EPS
- to communicate with similar organizations worldwide

**Areas of research**

Research areas represented by the division include (but are not restricted to)

- nonequilibrium statistical physics .
- complex networks
- nonlinear dynamical system
- chaos and turbulence
- stochastic modelling
- spin glasses and disordered quantum systems
- pattern formation
- long-range interacting systems
- phase transitions and critical phenomena
- interdisciplinary applications in physics, biology, economics, and social sciences

This school is aimed at young researchers and it offers a series of engaging lectures about several aspects of network theory, ranging from statistical mechanics to game theory, from ecological applications to multi-layer models. More details about the invited speakers from this year are available here: http://mediterraneanschoolcomplex.net/

The early bird conference rate is available until 15th March 2017

]]>**The winning image** was submitted by Finn Box, who took the image whilst completing a PhD with Tom Mullin at the University of Manchester. He received the £100 prize:

*The image is concerned with transition to turbulence in the flow along a pipe, which is considered to be one of the greatest challenges of classical Physics. Theory predicts that the flow should be smooth and laminar for all flow rates, however, the most common flow in practice is rough and turbulent. The image illustrates the transition process where dye lines show the complex structures that exist between laminar and turbulent flows.*

**Runner up** James Christian from the University of Salford sent a fantastic image also, which made the work of the judging panel difficult:

*Complexity in laser optics: two-dimensional virtual-source predictions of the light intensity for lowest-loss (left) and next-lowest-loss (right) fractal modes in an unstable resonator. The feedback mirror has a shape corresponding to the fourth iteration of a Gosper Island curve, and its edge is marked by the white line.*

**Runner up** Massimo Stella also sent us a picture from his doctoral studies, at the University of Southampton:

*Nonlinear and complexity physics is about non-local and non-trivial interactions, as reported in the idealised network representation (left) of a subsample of a bird flock (right). Nodes are reported as boids and they represent birds, influencing each other either via local coordination with nearby birds (blue links) or through long range speed correlations (green links). The blue skeleton of spatial interactions is represented here as a Bethe lattice, whose regular topology allows to formulate several models of statistical mechanics as exactly solvable. When modelling non-linearities in real-world systems, the ordered structure of a Bethe lattice is only an approximation. Complexity physics is distinctively characterised by non-local interactions, which can ultimately give rise to emergent phenomena at the scale of observation of the whole system. For instance, long range correlations on speed allow for birds to influence each other over long distances, thus giving rise to the fascinating shapes of bird flocks (cf. Cavagna et al., Scale-free correlations in starling flocks, (PNAS, 107(26), 11865-11870, 2009).*

Thank you again for all the entries.

]]>2016 Nonlinear and Complex Physics Group Yuletide Lecture

**Wednesday 7th December 2016; University of Machester**

**Dr Tobias Galla**

Tobias Galla is a theoretical physicist in the Complex Systems and Statistical Physics Group at the University of Manchester. His research interests include statistical mechanics of complex systems, stochastic dynamics in biological systems and the application of game theory and mathematical modelling in health care.

**Abstract**

The terms econophysics and sociophysics describe research in which physicists apply their ideas and methods to problems in economics and the social sciences. What do you have to know about the field to answer the question in the title? Similarly, what are the opportunities and dangers of working at the interface with the biological sciences? In this talk Dr Galla will give an assessment of what physicists can contribute to the field of economics, to biology and more generally to the science of complexity. He will discuss the main achievements of physicists in these fields as well as the things physicists have not achieved (despite occasional claims to the contrary). He will also discuss the potential hurdles young physicists may face moving into this area, and highlight the potentials and benefits of working in an interdisciplinary setting.

**Event report by Matt Garrod:**

This year’s Christmas lecture was given by Dr Tobias Galla from The University of Manchester’s Complex Systems and Statistical Physics Group. At the beginning of the talk Dr Galla posed the question *“You are a young and aspiring Physicist. Is working at the interface with economics and biology a good idea?”* Tobias is in a good position to answer this question; he wrote his PhD thesis on the application of path integral techniques from quantum mechanics to the study of the minority game from economics and has subsequently published research at the interface with both economics and biology.

The talk began with a brief introduction to how physicists became interested in tackling problems from other disciplines. Examples of physicists tackling problems related to economics go back decades. However, in recent decades, the number of physicists tackling interdisciplinary problems in fields such as economics and biology has increased dramatically. The 1990’s even saw the emergence of a discipline referred to as “econophysics.” Tobias, noted, however that “econophysics” is currently defined as the discipline where physicists work on problems in economics. This type of definition suggests that you can only do econophysics if you are a physicist!

After discussing the history of the field Tobias went on to discuss both the advantages and disadvantages of having physicists work at the interface with other disciplines. One thing he noted was that a great number of papers in the econophysics literature have a somewhat formulaic nature. For example, they often propose a slight alteration or addition to a Physics inspired model (perhaps related to the well studied Ising model). This is often followed by some numerical simulations, their results, and a claim that the results have relevance some given social or biological phenomena. However, the results of simulations like these, although they may show interesting behaviour from a physicist’s point of view, are not guaranteed to relate well to the intended physical application. (On the other hand, Tobias noted that, as a statistical physicist working close to economics, some of his own work be of a similar form to the above)

Another issue which appears when physicists work in the social sciences is that they are not typically used to dealing with data containing large amounts of noise. The result of this is that many physicists lack the statistical training required to properly analyse data of this type. As an example, most physicists (myself included) are unlikely to have been introduced to a p-value during the course of their undergraduate studies. The result of this is that physicists may do a poor job when interacting with real data in the field – this leads to a vast gap between theoretical models and data.

In contrast to the above, some physicists have had some great successes working in alongside the boundaries of physics and economics. For example, they have introduced the technique of agent-based modelling to the social sciences. Agent-based models are by no means predictive, however, they do allow researchers to career out sophisticated thought experiments which would usually be impossible for a single person. Another area that techniques inspired by physics have had some success is in nanoscale biology (reference this?), where techniques from nonequilibrium statistical mechanics have made some less unambiguous progress.

The lecture was concluded by attempting an answer to the question posed at the beginning: In general it is somewhat a matter of taste, however, if one is willing to properly get involved in understanding progress that has already been made in another discipline then your efforts may pay off. On the other hand, sometimes interesting results can come about when specialists in two disciplines come together and exchange ideas that neither of them would have come across independently.

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Energy security plays an essential role both in alleviating poverty in developing countries and in maintaining growth and prosperity in the developed world. Yet the national and global infrastructures that deliver energy are changing rapidly in the face of new and unprecedented challenges. The biggest of these stem from the need to meet ever-increasing global demand for energy services whilst simultaneously reducing CO2 emissions caused by burning fossil fuels. Responding to these challenges will likely involve increased deployment of renewables in the energy mix, perhaps combined with a growing reliance on transported natural gas, nuclear energy and carbon capture technologies. The risks to energy security associated with this new energy landscape will need to be understood from a number of perspectives, ranging from the effects of policy and regulation on energy price and availability to the impact of weather and climate change on energy supply and demand.

The aim of this free event was to bring together participants with an interest in understanding and modelling risks in the energy sector. There was a focus on how Integrated Assessment models and Energy Systems models can be used to understand risk.

The full programme can be found here: Programme

**Speakers have kindly shared their slides:**

Hannah Bloomfield, Reading: “The impact of climate variability on the GB power system” – Slides

Oluwamayowa Amusat, UCL: “Standalone renewable energy systems: inter-year variability in systems sizing” – Slides

Simon Tindeman, Imperial: “Managing risks in a bottom-up electricity system” – Slides

Paul Balcombe, Imperial: “Distribution of methane and CO2 emissions from the natural gas supply chain” – Slides

Ellen Webborn, Warwick: “Exploring the risk of synchronisation of distributed demand-side response resources” – Slides

Steven Steer et al, Cambridge “Power station design methods applied to commercialising novel nuclear plant” – Slides

Nick Watkins, Warwick: “On bunched black swans and return times in climate and other time series” – Slides

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