Alessandro Attanasi

Information transfer and behavioural inertia in starling flocks

Collective decision-making in biological systems requires all individuals in the group to go through a behavioural change of state. During this transition fast and robust transfer of information is essential to prevent cohesion loss. The mechanism by which natural groups achieve such robustness, though, is not clear. Here we present an experimental study of starling flocks performing collective turns. We find that information about direction changes propagates across the flock with a linear dispersion law and negligible attenuation, hence minimizing group decoherence. These results contrast starkly with current models of collective motion, which predict diffusive transport of information. Building on spontaneous symmetry breaking and conservation laws arguments, we formulate a new theory that correctly reproduces linear and undamped propagation. Essential to the new framework is the inclusion of the birds’ behavioural inertia. The new theory not only explains the data, but also predicts that information transfer must be faster the stronger the group’s orientational order, a prediction accurately verified by the data. Our results suggest that swift decision-making may be the adaptive drive for the strong behavioural polarization observed in many living groups.Alessandro Attanasi∗,‡, Andrea Cavagna∗,‡, Lorenzo Del Castello ∗,‡, Irene Giardina∗,‡, Tomas S. Grigera, Asja Jelić∗,‡, Stefania Melillo∗,‡, Leonardo Parisi∗,§, Oliver Pohl∗,‡, Edward Shen∗,‡, Massimiliano Viale∗,‡ ∗ Istituto Sistemi Complessi, Consiglio Nazionale delle Ricerche, UOS Sapienza, 00185 Rome, Italy ‡ Dipartimento di Fisica, Università Sapienza, 00185 Rome, Italy [ Instituto de Investigaciones Fisicoqúımicas Teóricas y Aplicadas (INIFTA) and Departamento de F́ısica, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, c.c. 16, suc. 4, 1900 La Plata, Argentina CONICET La Plata, Consejo Nacional de Investigaciones Cient́ıficas y Técnicas, Argentina and § Dipartimento di Informatica, Università Sapienza, 00198 Rome, Italy

Collective Behaviour without Collective Order in Wild Swarms of Midges

Collective behaviour is a widespread phenomenon in biology, cutting through a huge span of scales, from cell colonies up to bird flocks and fish schools. The most prominent trait of collective behaviour is the emergence of global order: individuals synchronize their states, giving the stunning impression that the group behaves as one. In many biological systems, though, it is unclear whether global order is present. A paradigmatic case is that of insect swarms, whose erratic movements seem to suggest that group formation is a mere epiphenomenon of the independent interaction of each individual with an external landmark. In these cases, whether or not the group behaves truly collectively is debated. Here, we experimentally study swarms of midges in the field and measure how much the change of direction of one midge affects that of other individuals. We discover that, despite the lack of collective order, swarms display very strong correlations, totally incompatible with models of non-interacting particles. We find that correlation increases sharply with the swarms density, indicating that the interaction between midges is based on a metric perception mechanism. By means of numerical simulations we demonstrate that such growing correlation is typical of a system close to an ordering transition. Our findings suggest that correlation, rather than order, is the true hallmark of collective behaviour in biological systems.

Emergence of collective changes in travel direction of starling flocks from individual birds' fluctuations

One of the most impressive features of moving animal groups is their ability to perform sudden coherent changes in travel direction. While this collective decision can be a response to an external alarm cue, directional switching can also emerge from the intrinsic fluctuations in individual behaviour. However, the cause and the mechanism by which such collective changes of direction occur are not fully understood yet. Here, we present an experimental study of spontaneous collective turns in natural flocks of starlings. We employ a recently developed tracking algorithm to reconstruct three-dimensional trajectories of each individual bird in the flock for the whole duration of a turning event. Our approach enables us to analyse changes in the individual behaviour of every group member and reveal the emergent dynamics of turning. We show that spontaneous turns start from individuals located at the elongated tips of the flocks, and then propagate through the group. We find that birds on the tips deviate from the mean direction of motion much more frequently than other individuals, indicating that persistent localized fluctuations are the crucial ingredient for triggering a collective directional change. Finally, we quantitatively verify that birds follow equal-radius paths during turning, the effects of which are a change of the flocks orientation and a redistribution of individual locations in the group.

Viscoelasticity and metastability limit in supercooled liquids

A supercooled liquid is said to have a kinetic spinodal if a temperature Tsp exists below which the liquid relaxation time exceeds the crystal nucleation time. We revisit classical nucleation theory taking into account the viscoelastic response of the liquid to the formation of crystal nuclei and find that the kinetic spinodal is strongly influenced by elastic effects. We introduce a dimensionless parameter lambda, which is essentially the ratio between the infinite frequency shear modulus and the enthalpy of fusion of the crystal. In systems where lambda is larger than a critical value lambda(c) the metastability limit is totally suppressed, independently of the surface tension. On the other hand, if lambda<lambda(c) a kinetic spinodal is present, and the time needed to experimentally observe it scales as exp([omega/(lambda(c)-lambda)2], where omega is roughly the ratio between surface tension and enthalpy of fusion.

GReTA-A Novel Global and Recursive Tracking Algorithm in Three Dimensions

Tracking multiple moving targets allows quantitative measure of the dynamic behavior in systems as diverse as animal groups in biology, turbulence in fluid dynamics and crowd and traffic control. In three dimensions, tracking several targets becomes increasingly hard since optical occlusions are very likely, i.e., two featureless targets frequently overlap for several frames. Occlusions are particularly frequent in biological groups such as bird flocks, fish schools, and insect swarms, a fact that has severely limited collective animal behavior field studies in the past. This paper presents a 3D tracking method that is robust in the case of severe occlusions. To ensure robustness, we adopt a global optimization approach that works on all objects and frames at once. To achieve practicality and scalability, we employ a divide and conquer formulation, thanks to which the computational complexity of the problem is reduced by orders of magnitude. We tested our algorithm with synthetic data, with experimental data of bird flocks and insect swarms and with public benchmark datasets, and show that our system yields high quality trajectories for hundreds of moving targets with severe overlap. The results obtained on very heterogeneous data show the potential applicability of our method to the most diverse experimental situations.

Elasticity and metastability limit in supercooled liquids: a lattice model

We present Monte Carlo simulations on a lattice system that displays a first-order phase transition between a disordered phase (liquid) and an ordered phase (crystal). The model is augmented by an interaction that simulates the effect of elasticity in continuum models. The temperature range of stability of the liquid phase is strongly increased in the presence of the elastic interaction. We discuss the consequences of this result for the existence of a kinetic spinodal in real systems.

A hybrid method for real-time short-term predictions of traffic flows in urban areas

Short-term traffic forecasting is driven by an increasing need of new services for user information and new systems for dynamic control. Our research focuses on reproducing anticipated traffic conditions by means of statistical methods traditionally applied in artificial intelligence problems. Although we strongly believe that the effects of specific traffic events can only be predicted through transportation model based simulations in real-time, yet the fluctuations affecting the ordinary traffic conditions of a day-type can well be forecasted without.

Real World Applications Using Parallel Computing Techniques in Dynamic Traffic Assignment and Shortest Path Search

As the range of applications for Intelligent Transport Systems (ITS) grows wider, the efficiency of the underlying tools for Big Data Analytics becomes of crucial importance. Smart Cities are able to monitor, forecast and (possibly) control the pulse of collective interactions involving networks and environment (such as traffic and pollution) by means of key performance indicators. Technology-guided solutions can proactively support the sustainable development and the optimal management of infrastructures and services, improving the quality of life for both city dwellers and commuters. This requires processing huge amounts of data, continuously streaming in from a variety of fixed sensors (e.g. loops, cameras) and mobile devices (GPS trajectories). In particular, Mobility Control Centres need effective software solutions and fast algorithms to deal with two major problems: Traffic Forecasting and Route Guidance. This paper presents real world examples of large scale applications where both tasks are addressed by implementing parallel computing algorithms, achieving high performances and allowing real time management operations and end-user services. The first test case examines the performance of a routing platform covering the entire Austria region, while the second concerns large instances of dynamic traffic assignment for real-time forecasting.