Abstracts

Abstracts

1. Biosensors based on upconversion nanoparticles

Elena Díaz García

UCM

The design of new heterostructures based on several optically active nanoparticles that get assembled due to the presence of short sequences of nucleotides as those expressed in a viral processes like the so called miRNAs, has a huge potential in bionanotechnology to detect certain infections. This approach allows us to design biosensors as molecular switchers whose functioning (on or off) depends on the presence of the miRNA in the biological sample. The efficiency of these biosensors is closely related to the proper selection of the nanoparticles (fluorescent, metallic, quantum dots…) acting as donors and acceptors within the heterostructure.

In the last years upconversion nanoparticles have acquired a lot of attention in this regard due to their optical and chemical properties. In this seminar some proposals of biosensing platforms based on upconversion nanoparticles will be discussed.

2. Two notes on the foundations of statistical mechanics: objectivity and the origin of giant fluctuations

Juan Manuel Rodríguez Parrondo

UCM

Boltzmann’s explanation of irreversibility is based on the concept of macro-states and the definition of entropy as the logarithm of the volume in phase space of the region of micro-states compatible with a given macro-state. The explanation, however, lacks an objective (i.e. non arbitrary) definition of macro-states and of the crossover between micro- and macro-scales. Here we show that this problem can be solved by reformulating Boltzmann’s explanation in terms of observables relaxing from giant fluctuations. We show that the irreversible behavior of an observable is a fully objective property and has nothing to do with its micro- or macroscopic nature. In fact, we will show a situation where a system exhibits irreversibility at the micro-scale and reversibility at the macro-scale. In the second part of the talk, we propose a mechanism for creating giant fluctuations of an observable (hence, irreversibility) based on metastable states induced by symmetry breaking.

3. Free-energy density functional for Strauss's model of transitive networks (applied to social networks)

Diego Escribano

UC3M

Ensemble models of graphs are one of the most important theoretical tools to study complex networks. Among them, exponential random graphs (ERGs) have proven to be very useful in the analysis of social networks. In this talk I will present a technique, borrowed from the statistical mechanics of lattice gases, to solve Strauss's model of transitive networks. This model was introduced long ago as an ERG ensemble for networks with high clustering and exhibits a first-order phase transition above a critical value of the triangle interaction parameter, where two different kinds of networks with different densities of links (or, alternatively, different clustering) coexist. Compared to previous mean-field approaches, this method describes accurately even small networks and can be extended beyond Strauss's classical model---e.g.~to networks with different types of nodes. This allows to tackle, for instance, models with node homophily. I provide results for the latter and show that they accurately reproduce the outcome of Monte Carlo simulations.

4. Vaccination strategies in structured populations under partial immunity and reinfection

Iker Atienza Diez

CNB

The enormous effects of infectious diseases in humankind through history could only be counteracted through massive vaccination campaigns. Optimal protocols of vaccine administration to minimize the effects of infectious diseases depend on several variables that admit different degrees of control: the characteristics of the disease and its impact on different groups of individuals, controlled non-pharmaceutical interventions and, critically, vaccine roll-out. It is often very difficult to assess a priori the importance and effect of such different factors. Here we study a compartmental model of infection propagation and analyze the effect that variations in the vaccination and reinfection rates have on the progression of the disease and on the number of fatalities. The model considers five different classes: Susceptible (S), Infected (I), Reinfected (Y), Recovered (R) and Dead (D). As a practical example, we study COVID-19 dynamics in various countries using real demographic data and contact matrices between different groups. We first divide the population into two age groups to highlight the overall effects on disease caused by vaccination rates and demographic structure. We observe, first, that the higher the fraction of reinfected individuals, the higher the likelihood that the disease becomes quasi-endemic and, second, that optimal vaccine roll-out depends on demographic structure and disease fatality. Therefore, there is no unique vaccination protocol, valid for all countries, that minimizes the effects of a specific disease. Our second analysis focused on the dynamics of COVID-19 in Spain using nine age groups. We explored the space of all possible combinations (9!) for the order in the vaccination protocol as a function of age and evaluated its performance in terms of the number of fatalities and infections, comparing with the baseline case of vaccination in strict decreasing age order. We conclude that, at least for COVID-19 in Spain, there is no strategy significantly better than age ordered vaccination.

5. Species interactions reproduce abundance correlations in microbial communities

José Manuel Camacho Mateu

UC3M

During the last decades macroecology has established itself as a prominent approach to investigate the behavior of microbes. Such a point of view allowed to recognize broad-scale patterns of abundances and diversity, as well as to argue some potential causes, but this does not parallel with a full understanding of the dynamical processes behind them. Particularly, abundance fluctuations over communities are found to be correlated but current models fail in reproducing their distributions. The present paper tackles with this problem and points to species interactions as a fundamental requirement to reproduce those distributions. We design a Metropolis-Hastings algorithm to build interaction networks which yield abundance correlations that best fit the experimental distributions. Importantly, the dynamics induced by the obtained networks still reproduces the experimental laws

detected in the previous literature, concerning the abundance fluctuations over both species and communities, as well as their mutual relationship. Endorsed by the agreement with experimental patterns, we employ this method to get information about microbial interactions and find that they may be treated in terms of principal components, namely there is a small number of interactions pivoting the whole biome dynamics. We argue that the result helps to shed light on microscopic origins of coarse-grainability.

6. Twister Bilayer Graphene at magic angles and Casimir effect

Pablo Rodríguez López

URJC

Twisted bilayered graphenes at magic angles are systems housing long ranged periodicity of Moiré pattern together with short ranged periodicity associated with the individual graphenes. Such materials are a fertile ground for novel states largely driven by electronic correlations. Here we find that the ubiquitous Casimir force can serve as a platform for macroscopic manifestations of the quantum effects stemming from the magic angle bilayered graphenes properties and their phases determined by electronic correlations. By utilizing comprehensive calculations for the electronic and optical response, we find that Casimir torque can probe anisotropy from the Drude conductivities in nematic states, while repulsion in the Casimir force can help identify topologically nontrivial phases in magic angle twisted bilayered graphenes.

7. Relating genotype and phenotype during cell division in a genomically minimal cell

James Pelletier

CNB

Engineered to have as few genes as possible, genomically minimal cells offer a simplified system to study relationships between genotype and phenotype. We here describe the development of the genomically minimal cell JCVI-syn3.0, which has the smallest genome of any free-living cell. Even in the minimal genomic context of JCVI-syn3.0, fundamental physiological processes often depend on many genes. For example, cell division depends on multiple genes of known and unknown function. To guide future experiments, we consider a physical description of cellular mechanics as an interlayer between genotype and phenotype. We review current knowledge of genes contributing to two physical parameters relevant to cell division, namely, the surface-area-to-volume ratio and membrane curvature. This physical view of JCVI-syn3.0 may inform the attribution of gene functions and conserved processes in bacterial physiology, as well as whole-cell models and the engineering of synthetic cells.

8. Shape fluctuations in random balls

Iván Álvarez Domenech

UNED

First passage percolation is a lattice model of a random metric on a surface, for which geodesics can be shown to present Kardar-Parisi-Zhang (KPZ) statistics under some conditions. We will present new results regarding the characterization of balls, also known as isochrone curves. Indeed, their average shape is known to depend on the level of noise in the metric. For low levels of noise the average shape is a diamond, while for larger levels we obtain circumferences, recovering the isotropic result. As we will show, previous difficulties to characterize shape fluctuations are due to the fact that they should be measured with respect to the corresponding average shape. As we will show, when this procedure is done correctly we recover KPZ statistics.

9. Human subjects do not know their centrality in social networks

Juan Ozaita Corral

UC3M

Do human subjects know their centrality and influence in their social network? We show with a sample of 500 students in a novel experimental method that centrality is difficult to perceive by a subject and the subjective general tendencies that exist when individuals try to guess their position in the network, generally, overestimating their influence.

10. On how to describe the emergence of interstellar molecular complexity with a network model... and get astrochemists (at least a little) interested.

Jacobo Aguirre

CAB

The road to life is punctuated by transitions toward complexity, from astrochemistry to biomolecules and eventually, to living organisms. Disentangling the origin of such transitions is a challenge where the application of complexity and network theory has not been fully exploited. In this talk, I will present you a computational framework named NetWorld in which simple networks simulate the most basic building bricks of life and interact to form complex structures, leading to an explosion of diversity when the parameter representing the environment reaches a critical value. While this model is abstract and unrelated to chemical theory, its predictions surprisingly (at least for us!) mimic the molecular evolution in the interstellar medium during the transition toward chemical complexity, suggesting that some rules leading to the emergence of complexity may be universal.

11. La evolución no ve los mejores diseños... pero no importa

José Cuesta

UC3M

En la evolución molecular (y en la evolución en general) hay una enorme redundancia entre los genotipos que expresan un mismo fenotipo. Y no solo eso: hay una enorme disparidad (de órdenes de magnitud) entre las fracciones del genoma que corresponden a cada uno de esos fenotipos. En esta charla daré argumentos que justifiquen las distribuciones observadas del número de fenotipos que ocupan una fracción dada del genoma y explicaré por qué el 99.9% del genoma se concentra en una pequeña fracción de dichos fenotipos (que además tiende a cero exponencialmente con la longitud de las moléculas). Los mejores diseños quedan, pues, ocultos en un inmenso océano de fenotipos inaccesibles a la evolución. Explicar cómo se resuelve esta paradoja, esto es, justificar por qué esto no es relevante en absoluto, es el objetivo de esta charla.

12. Non-equilibrium criticality in the synchronization of oscillator lattices

Ricardo Gutiérrez

UC3M

The main focus on the study of synchronous dynamics has been the identification of threshold parameter values for the transition to synchronization, and the nature of such transition. In this talk we will show that considering an oscillator lattice as a discrete growing interface provides unique insight into the dynamical process whereby the lattice synchronizes for long times, a much less studied aspect of synchronization. Working on a generalization of the Kuramoto model, we elucidate synchronization as an instance of generic scale invariance, whereby the system displays space-time criticality, largely irrespective of parameter values. The critical properties of the system fall into universality classes of kinetically rough interfaces with columnar disorder, namely, those of the Edwards-Wilkinson equation (equivalently, the Larkin model of an elastic interface in a random medium), for Kuramoto coupling, or the Kardar-Parisi-Zhang (KPZ) equation, generically. The critical properties include fluctuations that follow the celebrated Tracy-Widom distribution associated with the KPZ nonlinearity, which brings synchronizing oscillator lattices into a large class of strongly-correlated, low-dimensional systems with strong universal fluctuations.

13. Information and Thermodynamics in the nanoscale: from Landauer's principle to the information fuelled engine

Jorge Tabanera-Bravo

UCM

At the nanometric scale, the laws of Thermodynamics have been a challenge since Maxwell's time. Since he proposed the Demon paradox, there has been an intuition of the importance of Information Theory in these laws, but we still need to improve our control of experiments at the nanoscale. Hybrid systems combine quantum and classical degrees of freedom in such a way that we can directly observe both energy flows between the two and dissipation phenomena. This makes them excellent experimental platforms for thermodynamic analysis. In this work we use the information flow formalism to evaluate entropy generation on a realistic devices and propose a particular experimental implementation based on Landauer’s principle.

14. Persistence of symmetry-protected Dirac points in topological crystalline insulator SnTe

Olga Arroyo Gascón

ICMM

We study the effect of a non-magnetic impurity located at the surface of the SnTe topological crystalline insulator. Specifically, the changes on the surface states due to a Sb impurity atom are analyzed by means of first-principles simulations, and minimal and Green’s function continuum models. We compare slab and semi-infinite geometries, demonstrating that in the doped semi-infinite system the surface states remain gapless and their spin textures are unaltered. Besides its fundamental interest, tuning the Dirac cones of topological insulators can be of interest for transport and spintronic applications.

15. Simulating Microswimmers Under Confinement With Dissipative Particle (hydro)Dynamics

C. Miguel Barriuso Gutiérrez

UCM

In this work we study active "agents" of different shapes (a colloid and a polymer chain), embedded in bulk or in confinement. We explicitly consider hydrodynamic interactions and simulate the swimmers via an implementation inspired by the squirmer model. Concerning the surrounding fluid, we employ a Dissipative Particle Dynamics scheme. Differently from the Lattice-Boltzmann technique, on the one side this approach allows us to properly deal not only with hydrodynamics but also with thermal fluctuations. On the other side, this approach enables us to study microwimmers with complex shapes, ranging from spherical colloids to polymers. To start with, we study a simple spherical colloid. We analyze the features of the velocity fields of the surrounding solvent, when the colloid is a pusher, a puller or a neutral swimmer either in bulk or confined in a cylindrical channel. Next, we characterise its dynamical behaviour by computing the mean square displacement and the long time diffusion when the active colloid is in bulk or in a channel (varying its radius) and analyze the orientation autocorrelation function in the latter case. While the three studied squirmer types are characterised by the same bulk diffusion, the cylindrical confinement considerably modulates the diffusion and the orientation autocorrelation function. Finally, we focus our attention on a more complex shape: an active polymer. We first characterise the structural features computing its radius of gyration when in bulk or in cylindrical confinement, and compare to known results obtained without hydrodynamics. Next, we characterise the dynamical behaviour of the active polymer by computing its mean square displacement and the long time diffusion. On the one hand, both diffusion and radius of gyration decrease due to the hydrodynamic interaction when the system is in bulk. On the other hand, the effect of confinement is to decrease the radius of gyration, disturbing the motion of the polymer and thus reducing its diffusion.