Invited talk by G. Volpe at the 10th Nordic Workshop on Statistical Physics, Stockholm, 20-22 Mar 2019

Soft Matter Meets Deep Learning
Giovanni Volpe
The 10th Nordic Workshop on Statistical Physics: Biological, Complex and Non-equilibrium Systems, NORDITA, Stockholm, Sweden
20-22 March 2019

I will present an overview of recent projects where we have proposed new approaches to the experimental study of active matter. In particular, I will present a new algorithm for the measurement of microscopic force fields and a deep-learning approach to the tracking of microscopic particles.

Presentation by F. Schmidt at the Gothenburg Nanophotonic Symposium, 26 Mar 2019

Gothenburg Nanophotonic Symposium 2019

The first symposium on the topic of Nanophotonics brings together researchers from physics and chemistry departments in Gothenburg to present their work and share ideas.

Organised by Dr. R. Verre from the Bionanophotonic group at Chalmers University of Technology seven different groups will be present among which F. Schmidt will represent our Softmatter division of Gothenburg University.

The symposium will take place on the 26th of March 2019 at Kollektorn in MC2, Chalmers Campus. Everybody is welcome to attend!

Jalpa Soni and Falko Schmidt at the Lindau Nobel Laureate Meeting

Jalpa Soni and Falko Schmidt have been nominated by the Marie-Curie association and the Ragnar-Söderbergs foundation to attend the 69th Lindau Nobel Laureate Meeting from the 30 June till 5 July 2019. Congratulations to both!

The Lindau Nobel Laureate Meeting is an annual scientific conference that brings together Nobel laureates and young scientists to encourage scientific exchange among different generations and cultures.
The 69th meeting will be dedicated to Physics, where 580 young scientist from 88 countries will be present.

Seminar on reinforcement learning in photonics networks by Daniel Brunner from FEMTO-ST, France, Nexus, 13 May 2018

Reinforcement Learning in a Large Scale Photonic Network
Seminar by Daniel Brunner
from FEMTO-ST Institute/Optics Department, CNRS & University Bourgogne Franche-Comté, Besançon Cedex, France

We experimentally create a neural network via a spatial light modulator, implementing connections between 2025 in parallel based on diffractive coupling. We numerically validate the scheme for at least 34.000 photonic neurons. Based on a digital micro-mirror array we demonstrate photonic reinforcement learning and predict a chaotic time-series via our optical neural network. The prediction error efficiently converges. Finally, we give insight based on the first investigation of effects to be encountered in neural networks physically implemented in analogue substrates.

Place: Nexus
Time: 13 May 2019, 14:00

Active Colloidal Molecules published in J. Chem. Phys.

Light-controlled Assembly of Active Colloidal Molecules
Light-controlled Assembly of Active Colloidal Molecules

Light-controlled Assembly of Active Colloidal Molecules
Falko Schmidt, Benno Liebchen, Hartmut Löwen & Giovanni Volpe
Journal of Chemical Physics 150(9), 094905 (2019)
doi: 10.1063/1.5079861
arXiv: 1801.06868

Thanks to a constant energy input, active matter can self-assemble into phases with complex architectures and functionalities such as living clusters that dynamically form, reshape, and break-up, which are forbidden in equilibrium materials by the entropy maximization (or free energy minimization) principle. The challenge to control this active self-assembly has evoked widespread efforts typically hinging on engineering of the properties of individual motile constituents. Here, we provide a different route, where activity occurs as an emergent phenomenon only when individual building blocks bind together in a way that we control by laser light. Using experiments and simulations of two species of immotile microspheres, we exemplify this route by creating active molecules featuring a complex array of behaviors, becoming migrators, spinners, and rotators. The possibility to control the dynamics of active self-assembly via light-controllable nonreciprocal interactions will inspire new approaches to understand living matter and to design active materials.

Ordering of binary colloidal crystals by random potentials on ArXiv

Ordering of binary colloidal crystals by random potentials

Ordering of binary colloidal crystals by random potentials
André S. Nunes, Sabareesh K. P. Velu, Iryna Kasianiuk, Denys Kasyanyuk, Agnese Callegari, Giorgio Volpe, Margarida M. Telo da Gama, Giovanni Volpe & Nuno A. M. Araújo
arXiv: 1903.01579

Structural defects are ubiquitous in condensed matter, and not always a nuisance. For example, they underlie phenomena such as Anderson localization and hyperuniformity, and they are now being exploited to engineer novel materials. Here, we show experimentally that the density of structural defects in a 2D binary colloidal crystal can be engineered with a random potential. We generate the random potential using an optical speckle pattern, whose induced forces act strongly on one species of particles (strong particles) and weakly on the other (weak particles). Thus, the strong particles are more attracted to the randomly distributed local minima of the optical potential, leaving a trail of defects in the crystalline structure of the colloidal crystal. While, as expected, the crystalline ordering initially decreases with increasing fraction of strong particles, the crystalline order is surprisingly recovered for sufficiently large fractions. We confirm our experimental results with particle-based simulations, which permit us to elucidate how this non-monotonic behavior results from the competition between the particle-potential and particle-particle interactions.

Seminar by G. Volpe at Tel Aviv University, 6 Mar 2019

Emergent Complex Behaviour in Active Matter
Giovanni Volpe
Light Matter Interaction Center, Tel Aviv University, Israel
6 March 2019

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.

Controlling Colloidal Dynamics by Critical Casimir Forces published in Soft Matter

Controlling the dynamics of colloidal particles by critical Casimir forces

Controlling the dynamics of colloidal particles by critical Casimir forces
Alessandro Magazzù, Agnese Callegari, Juan Pablo Staforelli, Andrea Gambassi, Siegfried Dietrich & Giovanni Volpe
Soft Matter 15(10), 2152—2162 (2019)
doi: 10.1039/C8SM01376D
arXiv: 1806.11403

Critical Casimir forces can play an important role for applications in nano-science and nano-technology, owing to their piconewton strength, nanometric action range, fine tunability as a function of temperature, and exquisite dependence on the surface properties of the involved objects. Here, we investigate the effects of critical Casimir forces on the free dynamics of a pair of colloidal particles dispersed in the bulk of a near-critical binary liquid solvent, using blinking optical tweezers. In particular, we measure the time evolution of the distance between the two colloids to determine their relative diffusion and drift velocity. Furthermore, we show how critical Casimir forces change the dynamic properties of this two-colloid system by studying the temperature dependence of the distribution of the so-called first-passage time, i.e., of the time necessary for the particles to reach for the first time a certain separation, starting from an initially assigned one. These data are in good agreement with theoretical results obtained from Monte Carlo simulations and Langevin dynamics.