Abstracts

Abstracts of the talks in order of appearance in the Program:

• Luis Dinis (UCM), Bet-hedging. A story of horses, bacteria and desert plants. Kelly's solution to allocating bets in a horse race, or other gambling games, maximizes the long-term growth rate, but is known to be risky. Here, I will describe optimal betting strategies that give the highest capital growth rate while keeping a certain low value of risk, that is, an optimal trade-off between the average and the fluctuations. This trade-off is also embodied in a general bound similar to thermodynamic uncertainty relation (TUR). Finally, I will discuss possible applications in biology, in growing populations or seed germination. This trade-off is believed to operate in situations known generically in biology as "bet-hedging". Organisms may exchange a reduction of their present fitness for increased fitness in a possible future stressful condition. Some type of bet-hedging mechanism is believed to operate in the production of seeds by plants or in the resistance to antibiotics.

• Miguel Ruiz-García(UCIIIM), Learning the forces in active matter from the trajectories: a graph-neural-network approach. Active particles exhibit complex collective phenomena that emerges from their local interactions. To model such systems, one would usually propose some inter-particle interactions and active forces, simulate the dynamics of a system with many individual elements and finally compare the results with experiments via, for instance, an order parameter. However, not only choosing one order parameter might introduce a bias, but also it is difficult to assess how well the model describes the experimental system. In our work we suggest a completely different approach. What if we could learn the inter-particle interactions and the active forces directly from the data? We propose a graph-neural-network-based scheme that learns the interactions between particles and the active forces to predict the correct particle dynamics. After training the network, one can extract both passive and active interactions between particles and use them (analytically or numerically) to make new predictions or unravel dynamical features of experiments of active particles.

• Aniello Lampo (UCIIIM), Congestion Phase Transitions in Urban Street Networks. Cities exhibit different organizational patterns as a consequence of historical, political or economical circumstances, and constitute a paradigmatic example of complex system. In this context, network theory stands out as a fundamental tool facilitating the quantitative modeling of the main urban features and the analysis of the resulting dynamical processes, such as mobility and city growth. Our work focuses on street networks, which edges represent city roads, while the nodes portray the points where such roads cross. In the literature, the topic has been addressed following different points of views according to the purpose and the system characteristics. For instance, the dynamics related to inter-urban roads (also known as arterial roads or high capacity roads), characterized by long segments and limited inter-connection, has been approached employing fluids models, or the fundamental diagram of traffic flow. On the contrary, phenomenology of intra-urban streets is ruled by the underlying network structure and has been traditionally treated by means of graph models. These two types of street networks, which are usually studied independently, are increasingly entangled as cities sprawl over suburban areas. So far, only a few works dealt with street networks from an intertwined perspective, and the effects induced by such an interaction have been mostly overlooked. The analysis of the spatial interplay of intra and inter roads networks is the main motivation of the current work. We focus on monocentric cities and consider the situation in which arterial roads and urban local ones operate on separate geographic spaces. Specifically, local roads are located at the city center, and arterial ones at the urban periphery. Along this line, we introduce a family of random planar network models composed by a dense center surrounded by an arboreal periphery. Such a class of models reproduces previous results in terms of betweenness distribution and, at the same time, offers a considerable advantage in terms of analytical tractability. In this way, we are able to unveil several unexpected properties of road networks with respect to the congestion phenomena. In particular, it evidences that cities may experience a set of multiple abrupt phase transitions in the spatial localization of congested areas. These transitions define a set of congestion regimes that correspond to the emergence of congestion in the city center, its periphery or in urban arterial roads, and regards the way in which different road classes are entangled to form a unique transportation system. In other words, traffic bottlenecks shift away from the center towards the periphery, as larger areas are incorporated in the urban setting. The detection of congestion abrupt transition is performed both numerically and analytically and constitutes the main finding of our work. Importantly, this is validated by looking into real road networks. Empirical analysis is carried out over almost a hundred of cities worldwide, and relies on automatic and unsupervised methods. Results show that the multiple abrupt transitions exist in real cities, confirming the prediction performed with our model. The phase transitions we detect, represents an important resource to improve the efficiency of road networks. The displacement of the traffic bottlenecks towards the peripheral zones, indeed, is crucial to reduce the pressure on the city center, and to avoid the degradation of the transportation system. Therefore, the possibility to control and manipulate such an effect constitutes a notable task which has never been performed before.

• Daniel Villarubia (UCIIIM), First-passage percolation under extreme disorder and beyond: a brief introduction to the k-th passage percolation model Geometry on random manifolds presents both applied and fundamental interest, with applications ranging from the physics of polymers and membranes to quantum gravity. It was recently shown that in the case of random surfaces which are flat in average and with short-range correlations in the curvature, geodesics present fractal structure, governed by exponents corresponding to the Kardar-Parisi-Zhang universality class (KPZ). When the manifold is discretized, the problem is called first-passage percolation (FPP). In our FPP model we have an undirected lattice of nodes where a link-time is assigned randomly to each edge between nodes by a common probability distribution. Considering the statistical properties of arrival times to nodes, we showed a crossover between Gaussian and KPZ universality in the weak disorder regime. But now we have considered the strong-disordered regime, where a new crossover length appears below which FPP displays bond-percolation universality class. Moreover, the interplay between the correlation length intrinsic to percolation and this new characteristic length, whose behavior can be explained just through properties of the probability distribution, determines the crossover between initial percolation-like growth and asymptotic KPZ scaling. The Kth-Passage Percolation (KPP) is the natural generalization of FPP, which considers the whole set of paths and not just the geodesic one. Its first results and its similarity with energy levels in quantum systems will be introduced.

• Juan J. Mazo (UCM), Física no lineal y problemas de fricción. El fenómeno de la fricción es un problema complejo que ha desafiado a la física durante siglos. Hoy contamos con nuevas técnicas experimentales que permiten su estudio a escalas atómicas y con recursos computacionales capaces de realizar simulaciones a todos los átomos. Estos trabajos han renovado el interés en este problema fundamental. En este esfuerzo, el uso de modelos sencillos, modelos minimalistas, podría parecer marginal para algunos en comparación con los complejos y poderosos métodos mencionados. Sin embargo, los modelos más sencillos han jugado un papel esencial en el desarrollo de muchas ramas de la física y están jugando también en la actualidad un papel clave en la comprensión del problema de la fricción a las escalas más pequeñas. En este contexto, el “celebrado” modelo Prandtl-Tomlinson, un sencillo modelo no lineal, juega un papel primordial. En esta charla hablaremos fundamentalmente del fenómeno de "stick-slip", ubicuo en problemas de fricción a bajas velocidades y su comprensión, mediante el modelo Prandtl-Tomlinson, a escalas nanométricas.

• Luis F. Seoane (CNB), (A)symmetry and complexity in neural systems. In brains, symmetry, asymmetry, and complexity are brought together -- and involve both structure and function. Symmetric structures, thanks to their redundancy, might aid in computing with faulty parts and under noisy conditions. Mirror symmetric counterparts in the brain might also act as backups when a circuit fails. This redundancy, however, might be costly in metabolic terms. It might also require the coordination of parallel, independent computations, which can take a toll as well. In this talk I discuss complexity, symmetry, and symmetry breaking in the brain. The insights presented stem from a series of recent papers: "Fate of duplicated neural structures", "Modeling brain reorganization after hemispherectomy", and "Evolutionary paths to lateralization of complex brain functions".

• Christian C. Cortes (CNB), Dynamics of conjugation in the Bacillus subtilis plasmid pLS20. Bacterial conjugation is one of the horizontal gene transfer processes in which a donor bacterium transfers its conjugative plasmid to a recipient bacterium to become, for example, resistant to an antibiotic. Several experimental studies carried out in recent years have shown that three proteins are involved in the regulation of the conjugation genes present in the pLS20 conjugative plasmid of Bacillus subtilis. In this case, the main promoter that enables conjugation is repressed by a regulatory protein, called RcopLS20, that induces the formation of a DNA loop. However, an anti-repressor of RcopLS20, which enables activation of the conjugation promoter, called RappLS20, is inactivated by a plasmid-encoded signaling peptide, Phr*pLS20. This peptide needs to be exported out of the cell to be modified into its active form and is therefore a quorum-sensing signal that allow cells to receive information from their environment. With the aim of deepen the understanding of this system, this work proposes a mathematical model, using a system of differential equations, which describes the dynamics between the concentration of the conjugative gene and the proteins involved during the conjugation process, contrasted with experimental data.

• Jorge Tabanera (UCM), Self-oscillation and bistability in hybrid systems. Non-linear feedback between electric transport and mechanical degrees of freedom in nanomechanical systems gives place to different phenomenology in systems far from equilibrium. In this talk we explore the spontaneous generation of Self-oscillations in nanomechanical devices as well as their associated bistability and thermodynamic consequences.

• Yuriko Baba (UCM), Rashba coupling and spin switchingin Dirac semimetals. Topological semimetals, such as Weyl and Dirac 3D semimetals, have attracted much interest in the last decade due to the promising new properties, especially those related to their robust metallic surface states, called Fermi arcs. The robustness of the Fermi Arcs can be exploited to design chiral-switch devices owing to the possibilities of control by external fields. In particular, perturbations such as an electric field enable the control of the transport properties of the states by an external input. In this work, we study the rotation of the spin induced by a Rashba spin-orbit coupling generated by the breaking of the inversion symmetry and enhanced by the interaction with the substrate and controlled by an external electric field. We present a detailed analysis of the spin-dependent two-terminal conductance in the clean limit and with the addition of a random distribution of impurities. In this way, we show the potential of the system for spintronic applications.

• Marina Fernández (CAB), Interstellar phosphorus chemistry as a complex system: a theoretical approach to the formation of the simplest building blocks of life. In this work, we apply complex networks theory to phosphorus chemistry in the Interstellar Medium to understand how PO and PN (the most relevant phosphorus-bearing molecules in astrobiology) are formed. We developed a simplified model that studies the dynamics of the chemical species abundances as a complex system, simulating the conditions of different astrophysical environments within molecular clouds. It allowed us to show how each chemical species abundance affects the abundances of molecules PO and PN, solving the so-called `interstellar phosphorus problem’, which is the up-to-now discrepancy between the observational data and most existing astrochemical models. In addition, the comparison of our theoretical results with those obtained in radioastronomical surveys will be of use to detect which chemical reactions are the most relevant ones in the phosphorus chemistry, and which kinetic rates should be measured in the laboratory to improve the precision of the already existing models.

*This work has been developed as my master thesis and is being continued as a PhD thesis at Centro de Astrobiología CSIC-INTA under the supervision of Jacobo Aguirre.

• Juan Ozaita (UCIIIM), Why do structural measures of personal networks predict migrant's countries of origin? An explanation from the grid/group theory. Drawing on a rich dataset about migrants in two countries (the USA and Spain), we predict the country of origin of individual migrants reliably using three different methods. This finding shows that structural and cultural dimensions are somehow intertwined, as suggested by the Grid/Group Analysis or Cultural Theory. Moreover, each group of migrants exhibits a particular network pattern or "signature" after the "social signature" that individuals uniquely exhibit in their structure of social interactions. This finding opens new avenues for studying the interdependence between social and cultural phenomena, and the study of cultural diversity through a structural lens.

• Leonor Chico (UCM), One-dimensional moiré superlattices and magic angle physics in collapsed chiral carbon nanotubes. The discovery of superconducting and correlated insulating behavior in twisted bilayer graphene has shaken up the field of two-dimensional materials, reinvigorating the study of graphene-based systems. We demonstrate that one-dimensional moiré patterns, analogous to those found in twisted bilayer graphene, can arise in collapsed chiral carbon nanotubes. Resorting to a combination of approaches, namely, molecular dynamics to obtain the relaxed geometries and tight-binding calculations validated against ab-initio modeling, we find that magic angle physics occur in collapsed carbon nanotubes. Velocity reduction, flat bands, and localization in AA regions with diminishing moiré angle are revealed, showing a magic angle close to 1°.

• José Martín-Roca (UCM), The effect of two repulsive length scales on the structural and dynamic features of active Brownian particles. In this work we study a two-dimensional system composed by Active Brownian Particles (ABP) interacting via two-length scale repulsive potential. Unlike a one-length scale potential, the interplay between the second length scale and activity affects the structural behaviour of the suspension, leading to very rich phenomena. When the strength of the second length scale is comparable with the activity of the particles it can produce an anomalous dynamic in the system, that is avoid for a certain conditions.

• Ángel L. Corps (UCM), Dynamical phase transitions driven by excited-state quantum phase transitions in collective systems. During recent years there has been a growing interest in the different kinds of phase transition that many-body quantum systems may exhibit as well as in the thermodynamic properties associated to the resulting quantum phases. Besides the well-known quantum phase transition, occurring in the ground-state of a physical system as a certain control parameter is varied, and its generalization to high-lying levels, excited-state quantum phase transitions (ESQPTs), two new forms of non-analytic behavior have been explored, especially in models with long-range and infinite-range interaction: they have been termed dynamical phase transitions (DPTs). The first kind, which we call DPT-I, is characterized by an abrupt change of a given order parameter after a quench from an initial value of a control parameter to a final value. The second kind of DPT, which we call DPT-II, consists in non-analytic point in the return probability at certain critical times after a quench from an initial state in a broken-symmetry phase where the eigenlevels are pairwise degenerate. In this talk I will present a theory for the two kinds of dynamical quantum phase transitions in a large class of collective many-body systems. These two DPTs are shown to be rooted in excited-state quantum phase transitions. For quenches below the critical energy of the ESQPT, the existence of an additional conserved charge identifying the corresponding broken-symmetry phase means that the dynamical order parameter of DPTs-I can take on a non-zero value, while it becomes zero for quenches leading the initial state above the ESQPT. This same conserved charge forbids the appearance of non-analyticities in the return probability after a quench ending in the broken-symmetry phase demarcated by the ESQPT, meaning that DPTs-II are forbidden in this phase. The long-time averages of order parameters associated with DPTs-I are described by a generalization of the standard microcanonical ensemble, and we provide an analytical proof for the absence of DPTs-II within the symmetry-broken phase.

• Jorge Quereda (UCM), Nonlinear optoelectronics in 2D semiconductors. In this talk I will review my recent work on nonlinear optoelectronic processes in 2D material based phototransistors.

• Javier M. Byuldú (URJC), From complex systems to sports. En esta charla explicaré el motivo principal por el cual ya no veo series en Netflix. Básicamente, en mi tiempo libre, me dedico a analizar datos de fútbol desde la perspectiva de los sistemas complejos. Explicaré como un sistema tan complejo como es la dinámica de 11 jugadores cooperando entre ellos, y compitiendo contra otros 11, se estudia tradicionalmente mediante hojas de Excel. Finalmente daré un breve repaso sobre como un análisis más profundo puede generar información muy útil pero que no interesa a casi ningún cuerpo técnico.