Registration / Coffee & Cake Room: 122:026

Opening

• Ralf Eichhorn (Nordita)
• Alberto Imparato (Department of Physics and Astronomy University of Aarhus)

Room: 122:026

Quantum Statistical Geophysics

• John Wettlaufer (Yale University & Nordita)

Room: 122:026 We derive a generalized description of the ice thickness distribution in the polar ice pack using concepts from stochastic dynamics. This geophysical problem can be cast in terms of a Bessel-like process with a negative constant drift, described by a Fokker-Planck equation with a logarithmic potential.The problem belongs to a family of Fokker-Planck equations with logarithmic potentials closely related to the Bessel process that has been extensively studied for its applications in physics, biology, and finance. The Bessel-like process we consider can be solved by seeking solutions through an expansion into a complete set of eigenfunctions. The associated imaginary-time Schrödinger equation exhibits a mix of discrete and continuous eigenvalue spectra, corresponding to the quantum Coulomb potential describing the bound states of the hydrogen atom. We demonstrate this technique by solving the Brownian motion problem and the Bessel process both with a constant negative drift. The use of this approach allows one to study Earth’s polar climate using a single equation and/or two equations for each of the seasons.

A unified nonlinear stochastic time series analysis for climate science

• Woosok Moon (SU & Nordita)

Room: 122:026 Earth’s orbit and axial tilt imprint a strong seasonal cycle on climatological data. Climate variability is typically viewed in terms of fluctuations in the seasonal cycle induced by higher frequency processes. We can interpret this as a competition between the orbitally enforced monthly stability and the fluctuations/noise induced by weather. Here we introduce a new time-series method that determines these contributions from monthly-averaged data. We find that the spatio-temporal distribution of the monthly stability and the magnitude of the noise reveal key fingerprints of several important climate phenomena, including the evolution of the Arctic sea ice cover, the El Nio Southern Oscillation (ENSO), the Atlantic Nio and the Indian Dipole Mode. In analogy with the classical destabilising influence of the ice-albedo feedback on summertime sea ice, we find that during some time interval of the season a destabilising process operates in all of these climate phenomena. The interaction between the destabilisation and the accumulation of noise, which we term the memory effect, underlies phase locking to the seasonal cycle and the statistical nature of seasonal predictability.

Lunch Room: Restaurant

Orientation patterns of non-spherical particles in turbulence

• Bernhard Mehlig (Gothenburg University)

Room: 122:026 In experiments and numerical simulations we measured angles between the orientations of small spheroids in turbulence. Since turbulent strains tend to align nearby spheroids, one might think that their relative angles are quite small. We show that this intuition fails in general: the distribution of relative angles has heavy power-law tails, and the dynamics evolves to a fractal attractor despite the fact that the fluid velocity is spatially smooth at small scales. The fractal geometry depends on particle shape, and it determines the power-law exponents. This talk is based on joint work with L. Zhao, K. Gustavsson, R. Ni, S. Kramel, G. A. Voth, and H. I. Andersson.

Recent Progress on the Experimental Study of Active Matter

• Giovanni Volpe (Gothenburg University)

Room: 122:026 After a brief introduction of active particles, I’ll present some recent advances on the study of active particles in complex and crowded environments. First, I’ll show that active particles can work as microswimmers and microengines powered by critical fluctuations and controlled by light. Then, I’ll discuss some examples of behavior of active particles in crowded environments: a few active particles alter the overall dynamics of a system; active particles create metastable clusters and channels; active matter leads to non-Boltzmann distributions and alternative non-equilibrium relations; and active colloidal molecules can be created and controlled by light. Finally, I’ll present some examples of the behavior of active particles in complex environments: active particles often perform 2D active Brownian motion; active particles at liquid-liquid interfaces behave as active interstitials or as active atoms; and the environment alters the optimal search strategy for active particles in complex topologies.

Coffee Break Room: 122:026

Aspects of open quantum systems

• Hans Fogedby (Aarhus University)

Room: 122:026 After a brief review of some of the methods used in the treatment of open quantum systems: the quantum Langevin equation, the quantum master equation and the Lindblad equation, we discuss in some detail a recent study of an autonomous quantum rotator model.

Friction Fluctuations of Gold Nanoparticles in the Superlubric Regime

• Astrid de Wijn (Trondheim University)

Room: 122:026 Superlubricity, or alternatively termed structural (super)lubrictiy, is a concept where ultra-low friction is expected at the interface between sliding surfaces if these surfaces are incommensurate and thus unable to interlock. In this work, we now report on sudden, reversible, friction changes that have been observed during AFM based nanomanipulation experiments of gold nanoparticles sliding on highly oriented pyrolythic graphite. These effects are can be explained by rotations of the gold nanoparticles within the concept of structural superlubricity, where the occurrence of ultra-low friction candepend extremely sensitively on the relative orientation between the slider and the substrate. From our theoretical simulations it will become apparent how even miniscule magnitudes of rotation are compatible to the observed effects and how size and shape of the particles can influence the dependence between friction and relative orientation.

How glasses break

• Stefano Zapperi (University of Milano)

Room: 122:026 Glasses represent the quintessential brittle materials and yet at the nanoscale they become ductile, as experimentally observed in amorphous silica nanofibers as the sample size is reduced. I will discuss the results of extensive molecular dynamics simulations at low and room temperatures for a broad range of sample sizes, with open and periodic boundary conditions. Our results show that small sample size enhanced ductility is primarily due to diffuse damage accumulation, that for larger samples leads to brittle catastrophic failure. Surface effects such as boundary fluidization contribute to ductility at room temperature by promoting necking, but are not the main driver of the transition. Our results suggest that the experimentally observed size-induced ductility of silica nanofibers is a manifestation of finite-size criticality, as expected in general for quasi-brittle disordered networks. In the rest of the talk, I will discuss our recent results on the plasticity of glasses based on molecular dynamics simulations and meso-scale models.

Coffee Break Room: 122:026

Phase diagram of Kob-Andersen type binary Lennard-Jones mixtures

• Ulf Pedersen (Roskilde University, Denmark)

Room: 122:026 The binary Kob-Andersen (KA) Lennard-Jones mixture is the standard model for computational studies of viscous liquids and the glass transition. For very long runs the viscous KA system crystallizes, however, by phase separating into a pure A particle phase forming an FCC crystal. We present the phase diagram for KA-type mixtures showing, in particular, that the freezing temperature of the standard KA system at liquid density 1.2 is 1.028(3). At large B particle concentrations the system crystallizes into the CsCl crystal structure. The eutectic corresponding to the FCC and CsCl structures is cut-off in a narrow interval of B particle concentrations around 25% at which the PuBr3 structure is the thermodynamically stable phase. The melting temperature's variation with B particle concentration at two other pressures, as well as at the constant density 1.2, are predicted from the simulations using isomorph theory. Interface-pinning simulations confirm these predictions. Our data demonstrate approximate identity between the melting temperature and the onset temperature below which viscous dynamics appears.

Iso-Flux Tension Propagation Theory and Its Application to Driven Polymer Translocation

• Tapio Ala-Nissilä (Aalto and Loughborough University)

Room: 122:026 The translocation dynamics of polymers though nanopores driven by external fields is a far-from-equilibrium process, which can be understood based on the tension propagation (TP) theory of Sakaue [1]. In particular, the Brownian Dynamics TP theory within the iso-flux (IFTP) assumption [2] allows a self-consistent derivation of analytic equations of motion for the dynamics, including an explicit form for the chain length dependence of the average translocation time [3]. In this talk I will discuss various applications of the IFTP theory to translocation dynamics of semi-flexible [4] and end-pulled polymer chains [5]. 1. T. Sakaue, Phys. Rev. E 76, 021803 (2007). 2. P. Rowghanian and A. Y. Grosberg, J. Phys. Chem. B 115, 14127 (2011). 3. J. Sarabadani, T. Ikonen and T. Ala-Nissila, J. Chem. Phys. 141, 214907 (2014) 4. J. Sarabadani, Timo Ikonen, Harri Mökkönen, Tapio Ala-Nissila, Spencer Carson, and Meni Wanunu, Sci. Reps. 7, 7423 (2017). 5. J. Sarabadani, B. Ghosh, S. Chaudhury, and T. Ala-Nissila, EPL 120, 38004 (2017).

Lunch Room: Restaurant

Structural constrains on the emergence of temporal patterns in neuronal networks

• Arvind Kumar (KTH)

Room: 122:026 Spatial and temporal patterns of neuronal activity in the brain are thought to underlie every meaningful behavior. Consistent with this idea, spatio-temporal sequences have been observed in different conditions across the brain in the form of travelling waves and spike patterns. Three somewhat related mechanisms have been proposed to explain the existence of temporal sequences. First, it is assumed that the feedforward networks are embedded in an otherwise random network. Second, temporal sequences reflect a systematic transition of the network activity from one attractor state to another. Such transitions are governed by specific connectivity rules or neuron and synapse properties. Third, randomly connected networks learn to generate sequences using a supervised learning algorithm. All these mechanisms are untenable given the known anatomy of the brain and the biological implausibility of supervised learning. Thus, despite the ubiquity of sequential activity of neurons, the underlying mechanisms have remained obscure. To better understand the spatio-temporal patterns in neuronal activity we investigated the dynamics of neuronal network with spatial connectivity. We found that to form spatial pattern in the network activity, spatial connectivity should vary non-monotonically as a function of distance between neurons. On the other hand when the spatial connectivity is asymmetric and inhomogeneous in the network space, the spatial patterns become unstable and result in the emergence of temporal patterns. Finally, we derive the constraints on the asymmetry and inhomogeneity of the connectivity that results in spatio-temporal sequences resembling the sequential neuronal activity in the brain.

Can machines learn to solve football? A look at how we model complex systems

• David JT Sumpter (Uppsala University, Sweden)

Room: 122:026 Football is the most mathematical of sports. Passing networks, the geometry of player positioning and randomness are all important. There are lots of people—coaches and players---who understand football intuitively. Can we train a computer to understand the game and generate insights these people have missed? I argue that we can, but we can’t just throw away these people’s knowledge and start from scratch. I explain how studies of collective behaviour can be used to help improve our analysis and understanding of the beautiful game, and how the problem of modelling football should inform the way we approach all complex systems.

Coffee Break Room: 122:026

Virus attack on a Bacterial Colony: Transition from Death to Persistent Survival

• Namiko Mitarai (Niels Bohr Institute)

Room: 122:026 Bacteriophages are viruses that infect bacteria. A virulent phage infection to a host bacterial cell results in lysis of the cell and possibly hundreds of phage particle release after a latency time. It is important for the survival of bacteria to develop defense mechanisms against phages, while also for phages it is important not to completely eliminate their host since bacteria are needed for their propagation. In this talk, we demonstrate that bacteria growing as a dense colony provides a spatial refuge by exposing only the bacterial cells on the surface of the colony to a phage attack. When the colony size is below a critical size at the time of exposure to phages, bacteria will be eliminated, while when the colony size is above the critical size, the colony can survive and grow despite the persistent phage attack on the surface. We show that experimental result using the virulent version of phage P1 and the host Escherichia Coli is consistent with this prediction. We study the parameter dependence of the critical size by numerical simulation, and predict that the phage with lower adsorption rate will actually kill a colony better. Our findings indicate that the spatial structure of the bacterial population plays an important role in phage-bacteria coexistence. Reference: Rasmus Skytte Eriksen, Sine Lo Svenningsen, Kim Sneppen, and Namiko Mitarai, “A Growing Microcolony can Survive and Support Persistent Propagation of Virulent Phages”, Proc. Natl. Acad. Sci. USA. (2018) 115(2):337-342.

Conference Dinner Room: Cypern

Statistical physics of PLC

• Mikko Alava (HUT, Espoo, Finland)

Room: 122:026 The Portevin - LeChatelier effect is a signature of collective behavior in the deformation of metal alloys. I will describe a set of experiments to elucidate this, and the modeling we have done to account (almost) quantitatively for the results. This is put into context: why the PLC is thought to ensue, and what does that have to do with the collective dislocation dynamics.

Coarsening and mechanics in a mesoscale model of wet foams

• Antti Puisto (Aalto University, Helsinki, Finland)

Room: 122:026 Aqueous foams are an important model system that displays coarsening dynamics. Coarsening in dispersions and foams is well understood in the dilute and dry limits, where the gas fraction tends to zero and one, respectively. However, foams are known to undergo a jamming transition from a fluid-like to a solid-like state at an intermediate gas fraction, $\phi_c$. Much less is known about coarsening dynamics in wet foams near jamming, and the link to mechanical response, if any, remains poorly understood. In this talk, we discuss coarsening and mechanical response using numerical simulations of a mesoscale model for wet foams. As in other coarsening systems we find a steady state scaling regime with an associated particle size distribution. We relate the time-rate of evolution of the coarsening process to the wetness of the foam and identify a characteristic coarsening time that diverges approaching jamming. In addition, we probe the mechanical response of the system to strain while undergoing coarsening. We find two competing time scales, namely the coarsening time and the mechanical relaxation time. We relate these to the evolution of the elastic response and the mechanical structure.

Coffee Break Room: 122:026

Membrane curvature sensing by symmetric proteins

• Martin Linden (Uppsala University, Sweden)

Room: 122:026 Many proteins and peptides have an intrinsic capacity to sense and induce membrane curvature, and play crucial roles for organizing and remodeling cell membranes. However, neither the molecular driving forces behind these processes nor the physical models capable of connecting molecular mechanisms to their large-scale consequences are well understood. I will describe recent work to develop computational methods to study these phenomena, and focus on the relationship between structural symmetry and curvature sensing. Structural symmetry is ubiquitous in membrane proteins, since many of them form symmetric multimeric complexes. Using coarse-grained simulations and theoretical arguments, we show that symmetry can greatly influence membrane curvature sensing. In particular, the potential for anisotropic membrane curvature sensing is limited to asymmetric proteins, dimers, and tetramers, but strongly suppressed by odd and higher-order symmetries. This classification provides a new perspective on structure-function relation for membrane proteins, suggests a correlation between multimer multiplicity and certain types of membrane deformations, and can simplify the task of constructing mesoscopic models of curvature sensing.

Biomechanics as a driver of stem cell differentiation, segregation and development

• Lene Oddershede (Niels Bohr Institute)

Room: 122:026 Early in embryonic development the blastocyst consists of a mix of two different cell populations, one primed towards the epiblast which will later develop into the fetus, and one primed for the endoderm, which will develop into the amniotic sac. Initially, those two populations are mixed and later they segregate into the fetus and amniotic sac. Using embryonic stem cells as a relevant model system, we use optical tweezers to quantify the physical properties of those two populations and demonstrate that their viscoelastic properties are significantly different. By modeling we also show that the difference in viscoelasticity in those two cell populations is actually enough to cause a segregation of the two populations, hence, the biomechanical properties alone can drive the process. Mechanical forces and biophysical properties of cells are also vital for the morphogenesis of organs and embryos. However, how mechanical force and biophysical properties specifically contribute to tissue formation is poorly understood, predominantly due to a lack of tools to measure and quantify biomechanical parameters deep within living developing organisms without causing severe physiological damage. Using an adapted version of optical tweezers, we mechanically probe the developing gut region deep within living zebrafish and show that the mechanical properties of developing organs differ significantly. We hypothesize that these biomechanical differences serve as a segregation mechanism and might drive development.

Lunch Room: Restaurant

Free Discussion / Closing Room: 122:026