arXiv subjects

Alessandro Rizzo

Publications and source records attributed to Alessandro Rizzo.

29 records · Page 2Linked to original sources

arXiv2021

The synchronized dynamics of time-varying networks

Over the past two decades, complex network theory provided the ideal framework for investigating the intimate relationships between the topological properties characterizing the wiring of connections among a system's unitary components and its emergent synchronized functioning. An increased number of setups from the real world found therefore a representation in term of graphs, while more and more sophisticated methods were developed with the aim of furnishing a realistic description of the connectivity patterns under study. In particular, a significant number of systems in physics, biology and social science features a time-varying nature of the interactions among their units. We here give a comprehensive review of the major results obtained by contemporary studies on the emergence of synchronization in time-varying networks. In particular, two paradigmatic frameworks will be described in details. The first encompasses those systems where the time dependence of the nodes' connections is due to adaptation, external forces, or any other process affecting each of the links of the network. The second framework, instead, corresponds to the case in which the structural evolution of the graph is due to the movement of the nodes, or agents, in physical spaces and to the fact that interactions may be ruled by space-dependent laws in a way that connections are continuously switched on and off in the course of the time. Finally, our report ends with a short discussion on promising directions and open problems for future studies.

physics.soc-ph↗

arXiv2021

Vector-based Pedestrian Navigation in Cities

How do pedestrians choose their paths within city street networks? Researchers have tried to shed light on this matter through strictly controlled experiments, but an ultimate answer based on real-world mobility data is still lacking. Here, we analyze salient features of human path planning through a statistical analysis of a massive dataset of GPS traces, which reveals that (1) people increasingly deviate from the shortest path when the distance between origin and destination increases, and (2) chosen paths are statistically different when origin and destination are swapped. We posit that direction to goal is a main driver of path planning and develop a vector-based navigation model that is a statistically better predictor of human paths than a model based on minimizing distance with stochastic effects. Our findings generalize across two major US cities with different street networks, hinting to the fact that vector-based navigation might be a universal property of human path planning.

q-bio.NC↗

arXiv2021

Game-theoretic modeling of collective decision-making during epidemics

The spreading dynamics of an epidemic and the collective behavioral pattern of the population over which it spreads are deeply intertwined and the latter can critically shape the outcome of the former. Motivated by this, we design a parsimonious game-theoretic behavioral--epidemic model, in which an interplay of realistic factors shapes the co-evolution of individual decision-making and epidemics on a network. Although such a co-evolution is deeply intertwined in the real-world, existing models schematize population behavior as instantaneously reactive, thus being unable to capture human behavior in the long term. Our model offers a unified framework to model and predict complex emergent phenomena, including successful collective responses, periodic oscillations, and resurgent epidemic outbreaks. The framework also allows to assess the effectiveness of different policy interventions on ensuring a collective response that successfully eradicates the outbreak. Two case studies, inspired by real-world diseases, are presented to illustrate the potentialities of the proposed model.

q-bio.PE↗

arXiv2021

High-resolution agent-based modeling of COVID-19 spreading in a small town

Amid the ongoing COVID-19 pandemic, public health authorities and the general population are striving to achieve a balance between safety and normalcy. Ever changing conditions call for the development of theory and simulation tools to finely describe multiple strata of society while supporting the evaluation of "what-if" scenarios. Particularly important is to assess the effectiveness of potential testing approaches and vaccination strategies. Here, an agent-based modeling platform is proposed to simulate the spreading of COVID-19 in small towns and cities, with a single-individual resolution. The platform is validated on real data from New Rochelle, NY -- one of the first outbreaks registered in the United States. Supported by expert knowledge and informed by reported data, the model incorporates detailed elements of the spreading within a statistically realistic population. Along with pertinent functionality such as testing, treatment, and vaccination options, the model accounts for the burden of other illnesses with symptoms similar to COVID-19. Unique to the model is the possibility to explore different testing approaches -- in hospitals or drive-through facilities -- and vaccination strategies that could prioritize vulnerable groups. Decision making by public authorities could benefit from the model, for its fine-grain resolution, open-source nature, and wide range of features.

q-bio.PE↗

arXiv2020

Modelling and predicting the effect of social distancing and travel restrictions on COVID-19 spreading

To date, the only effective means to respond to the spreading of COVID-19 pandemic are non-pharmaceutical interventions (NPIs), which entail policies to reduce social activity and mobility restrictions. Quantifying their effect is difficult, but it is key to reduce their social and economical consequences. Here, we introduce a meta-population model based on temporal networks, calibrated on the COVID-19 outbreak data in Italy and apt to evaluate the outcomes of these two types of NPIs. Our approach combines the advantages of granular spatial modelling of meta-population models with the ability to realistically describe social contacts via activity-driven networks. We provide a valuable framework to assess the viability of different NPIs, varying with respect to their timing and severity. Results suggest that the effects of mobility restrictions largely depend on the possibility to implement timely NPIs in the early phases of the outbreak, whereas activity reduction policies should be prioritised afterwards.

physics.soc-ph↗

arXiv2018

Distributed Estimation of State and Parameters in Multi-Agent Cooperative Load Manipulation

We present two distributed methods for the estimation of the kinematic parameters, the dynamic parameters, and the kinematic state of an unknown planar body manipulated by a decentralized multi-agent system. The proposed approaches rely on the rigid body kinematics and dynamics, on nonlinear observation theory, and on consensus algorithms. The only three requirements are that each agent can exert a 2D wrench on the load, it can measure the velocity of its contact point, and that the communication graph is connected. Both theoretical nonlinear observability analysis and convergence proofs are provided. The first method assumes constant parameters while the second one can deal with time-varying parameters and can be applied in parallel to any task-oriented control law. For the cases in which a control law is not provided, we propose a distributed and safe control strategy satisfying the observability condition. The effectiveness and robustness of the estimation strategy is showcased by means of realistic MonteCarlo simulations.

cs.RO↗

arXiv2017

Epidemic spreading in modular time-varying networks

We investigate the effects of modular and temporal connectivity patterns on epidemic spreading. To this end, we introduce and analytically characterise a model of time-varying networks with tunable modularity. Within this framework, we study the epidemic size of Susceptible-Infected-Recovered, SIR, models and the epidemic threshold of Susceptible-Infected-Susceptible, SIS, models. Interestingly, we find that while the presence of tightly connected clusters inhibit SIR processes, it speeds up SIS diseases. In this case, we observe that heterogeneous temporal connectivity patterns and modular structures induce a reduction of the threshold with respect to time-varying networks without communities. We confirm the theoretical results by means of extensive numerical simulations both on synthetic graphs as well as on a real modular and temporal network.

physics.soc-ph↗

arXiv2017

The HPS electromagnetic calorimeter

The Heavy Photon Search experiment (HPS) is searching for a new gauge boson, the so-called "heavy photon." Through its kinetic mixing with the Standard Model photon, this particle could decay into an electron-positron pair. It would then be detectable as a narrow peak in the invariant mass spectrum of such pairs, or, depending on its lifetime, by a decay downstream of the production target. The HPS experiment is installed in Hall-B of Jefferson Lab. This article presents the design and performance of one of the two detectors of the experiment, the electromagnetic calorimeter, during the runs performed in 2015-2016. The calorimeter's main purpose is to provide a fast trigger and reduce the copious background from electromagnetic processes through matching with a tracking detector. The detector is a homogeneous calorimeter, made of 442 lead-tungstate (PbWO4) scintillating crystals, each read out by an avalanche photodiode coupled to a custom trans-impedance amplifier.

physics.ins-det↗

arXiv2015

Design and realization of a facility for the characterization of Silicon Avalanche PhotoDiodes

We present the design, construction, and performance of a facility for the characterization of Silicon Avalanche Photodiodes in the operating temperature range between -2 $^\circ$C and 25 $^\circ$C. The system can simultaneously measure up to 24 photo-detectors, in a completely automatic way, within one day of operations. The measured data for each sensor are: the internal gain as a function of the bias voltage and temperature, the gain variation with respect to the bias voltage, and the dark current as a function of the gain. The systematic uncertainties have been evaluated during the commissioning of the system to be of the order of 1%. This paper describes in detail the facility design and layout, and the procedure employed to characterize the sensors. The results obtained from the measurement of the 380 Avalanche Photodiodes of the CLAS12-Forward Tagger calorimeter detector are then reported, as the first example of the massive usage of the facility.

physics.ins-det↗

arXiv2013

Motility fractionation of bacteria by centrifugation

Centrifugation is a widespread laboratory technique used to separate mixtures into fractions characterized by a specific size, weight or density. We demonstrate that centrifugation can be also used to separate swimming cells having different motility. To do this we study self-propelled bacteria under the influence of an external centrifugal field. Using dynamic image correlation spectroscopy we measure the spatially resolved motility of bacteria after centrifugation. A significant gradient in swimming-speeds is observed for increasing centrifugal speeds. Our results can be reproduced by a model that treats bacteria as "hot" colloidal particles having a diffusion coefficient that depends on the swimming speed.

cond-mat.soft↗

arXiv2001

An Automatic Validation System for Interferometry Density Measurements in the ENEA-FTU Tokamak Based on Soft- Computing

In this paper, an automatic sensor validation strategy for the measurements of plasma line density in the ENEA-FTU tokamak is presented. Density measurements are performed by a 5-channel DCN interferometer. The approach proposed is based on the design of a neural model of the observed system., i.e. a model able to emulate the behavior of a fault-free sensor and of a two-stage fuzzy system able to detect the occurence of a fault by using a set of suitable indicators. The fault diagnosis and classification is also accomplished. The validation strategy has been implemented and embedded in an interactive software tool installed at FTU. Statistics concerning the rate of fault detection agree with the rate of uncertainty usually achieved in the post-pulse manual validation.

physics.ins-det↗