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Programme for Wednesday 23rd June

13.00 -13.45

Emergent Behaviour across Lengthscales and Time

Robin Ball (Warwick)

In this talk I will reflect on some of the roadblocks and open questions in identifying and confirming the limiting behaviour of physical systems. In particular I will first focus on the dynamics of entangled polymers and the limiting behaviour of Diffusion Limited Aggregation. Later in the talk I will discuss how for emergence across scales the Renormalisation group can be directly measured, and how we can define and measure emergence across time.

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14.00 -14.30

Entanglement entropy as a measure for complexity of temporal networks

Debabrata Panja (Utrecht)

Networks provide the universal geometrical alphabet to describe complex systems, with agents and their interactions represented by nodes and links respectively. Many dynamical phenomena, e.g., pathogen transmission, disruptions in transport over networks, and (fake) news purveyance, concern spreading processes that play out on top of networks with changing architecture --- commonly known as temporal networks. Here we develop the concept of `entanglement entropy' in order to characterise topological structures and to measure complexity of temporal networks. Using a large number of publicly available datasets, we demonstrate that the metric naturally detects structures such as interaction bubbles, and allows for topological comparisons of vastly different systems. Importantly, we show that entanglement entropy is an excellent predictor for the systems' vulnerability to spreading phenomena, opening our methods up for quantifying relations between complexity, modularity and vulnerability (and for applications) in a wide variety of natural, social, biological and engineered systems.

14.30 – 15.00

Fracture of Colloidal Gels: New Insight into an Old System

David Weitz (Harvard)

When colloidal particles aggregate irreversibly, they ultimately form a solid gel network. The structure and properties of this network are vastly different depending on the nature of the aggregation process, something that Robin worked out early in his career. This talk will describe some surprising features of these colloidal gels, determined by the aggregation process that forms them. It will also discuss how these gels are fractured upon injection with either a fluid or a gas that displaces the continuous liquid phase of the gel.

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15.30 -16.00

"Proteins are rough - don't try doing physics with them" said Sam Edwards - how Robin Ball led me astray

Tom McLeish (York)

It is now almost obvious that a biology and biological molecules and their processes constitute a suitable field for doing physics, but even in the late 1980s this was by no means the case. Early movers into biological subject matter from physics were treated with suspicion, to say the least. Sam Edwards even rationalised why it might be a bad idea for the physicist (paradoxically from a theoretician who had pioneered ways of thinking about ‘rough’ landscapes. For me, this was never a problem – I had studiously avoided learning anything about biology from high-school onwards. Even the vocabulary scared me: ‘proteins’, ‘peptides’, ‘replication’, ‘ribosomes’ – the jargon was endless and avoidable. So, imagine my surprise when I heard that my former PhD supervisor had supervised some work [1] on protein folding. I was fascinated, but was certainly not going to follow. Until later I started working with biologists at the Astbury Centre at Leeds University, and with Sheena Radford in particular, and started reading (with some horror) the theoretical literature on protein folding. Very ill-advisedly, I wondered what the field would have looked like had the first theories been attempted by soft matter statistical physicists, rather than physical-chemists, and had the framework been that of high dimensional Brownian searches, rather than reaction-state kinetics. The answer is that, in terms of proteins, you get the rough with the smooth, or perhaps better, the smooth as well as the rough [2, 3].

[1] Thomas M. A. Fink and Robin C. Ball, ‘How Many Conformations Can a Protein Remember? Phys. Rev. Lett. 87, 198103 (2001).

[2] T.C.B. McLeish, “Protein Folding in High-Dimensional Spaces: Hypergutters and the Role of Nonnative Interactions”, Biophysical Journal, 88, 172–183 (2005).

[3] T.L. Rogers et al., “Modulation of Global Low-Frequency Motions Underlies Allosteric Regulation: Demonstration in CRP/FNR Family Transcription Factors”, PLOS-Biology, 11(9): e1001651 (2013).
 

16.00-16.30

Non-equilibrium interfaces

Margarida Telo da Gama (Lisbon)

An interface is the moving or static boundary between two bulk phases. These can be free or constrained by the presence of a third phase, boundaries or inhomogeneities in the medium. At and near equilibrium the field has matured and has led to the prediction and observation of a range of novel non-trivial phenomena. For non-equilibrium systems the situation is much less satisfactory, not least because distinct non-equilibrium systems do exist. Of these I will focus on interfaces of driven (passive) systems and active-passive interfaces. In the former, general continuous stochastic growth equations, such as the KPZ, have proved useful also in the presence of surfaces or quenched disorder, capturing the long-range statistical properties of microscopic models and of the experiments. Active matter is a much more recent field and work on active-passive interfaces has hardly begun. Concepts such as the surface tension of static interfaces are still open to debate. In addition, the nature of the bulk phases may be radically different (e.g. the existence of bubbly liquids in dry active matter and of active turbulence in wet nematics) raising fundamental questions on the effective descriptions that were so useful in driven passive systems.

In the first part of this talk I will review the non-equilibrium wetting phase diagram of driven passive systems based on effective interfacial models [1] and illustrate how the rougheness of a driven interface may depend (somewhat surprisingly) on the anisotropy of the particle interactions, as suggested by experiments on drying droplets [2]. In the second part of the talk I will address active-passive interfaces. I will present results on interfaces of the hydrodynamic model of wet active nematics, which describe a range of observations made on propagating interfaces of bacterial films [3]. If time permits, I will discuss preliminary results on the wetting of scalar (dry) active matter and the roughness of its growing interface, based on massive simulations of a lattice model of active Brownian particles [4].

[1] “Nonequilibrium Bound Interfaces”, F. de los Santos e M. M. Telo da Gama in Trends in Statistical Physics, (World Scientific, 2004).

[2] “Interaction anisotropy and the KPZ to KPZQ transition in particle deposition at the edges of drying drops”, C. S. Dias, P. J. Yunker, A. G. Yodh, N. A. M. Araújo and M. M. Telo da Gama, Soft Matter 14, 1903-1907 (2018).

[3] “Propagation of active nematic-isotropic interfaces on substrates”, R. C. V. Coelho, N. A. M. Araújo and M. M. Telo da Gama, Soft Matter 16, 4256-4266 (2020).

[4] “Wetting of a solid surface by active matter”, P. Neta, M. Tasinkevych, M. M. Telo da Gama, C. S. Dias, Soft Matter 17, 2468-2478 (2021).

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17.00 – 17.30

Self-organisation of dense granular matter: non-equilibrium entropy and detailed balance

Rafi Blumenfeld (Cambridge)

Working with Robin made me fall in love with the physics of granular systems and this is a great opportunity to show Robin where this has led me.

The large-scale behaviour of granular materials is very sensitive to the grain-scale structure. This structure self-organises in a way that depends on the driving dynamics, which is often regarded as history-dependence.

I will describe a recently-developed formalism to model structural organisation of dense granular matter. The formalism makes it possible to predict a number of structural characteristics under any quasi-static process. It also allowed us to show analytically that steady states of such dynamics satisfy both detailed balance. A set of experiments also shows that some properties can be predicted from a maximum entropy principle, constrained by mechanical stability. The theoretical predictions are supported by numerical and experimental observations. These results establish that dense granular systems can be modelled by statistical mechanics, supporting Sam Edwards’s suggestion.

 

17.30 – 18.00

Discussion