A5073176948- Nonlinear Dynamics and Pattern Formation
- Advanced Thermodynamics and Statistical Mechanics
- Statistical Mechanics and Entropy
- Opinion Dynamics and Social Influence
- stochastic dynamics and bifurcation
- Theoretical and Computational Physics
- Complex Network Analysis Techniques
- Complex Systems and Time Series Analysis
- Neural dynamics and brain function
- Ecosystem dynamics and resilience
- Cold Atom Physics and Bose-Einstein Condensates
- Evolutionary Game Theory and Cooperation
- Gene Regulatory Network Analysis
- Neural Networks and Applications
- Neural Networks Stability and Synchronization
- Advanced Fluorescence Microscopy Techniques
- Mathematical and Theoretical Epidemiology and Ecology Models
- Evolution and Genetic Dynamics
- Particle Accelerators and Free-Electron Lasers
- Cellular Automata and Applications
- Diffusion and Search Dynamics
- Laser-Matter Interactions and Applications
- Spectroscopy and Quantum Chemical Studies
- Force Microscopy Techniques and Applications
- Quantum chaos and dynamical systems
University of Florence
2016-2025
Istituto Nazionale di Fisica Nucleare, Sezione di Firenze
2014-2023
Istituto Nazionale di Fisica Nucleare
2012-2023
Florence (Netherlands)
2020
Consorzio Interuniversitario per lo Sviluppo dei Sistemi a Grande Interfase
2009-2018
United States Nuclear Regulatory Commission
2016
Ricerca sul Sistema Energetico (Italy)
2006-2015
Centre National de la Recherche Scientifique
2010-2011
Laboratoire de Physique Théorique
2011
Institut de Recherche sur les Systèmes Atomiques et Moléculaires Complexes
2011
Charting an organs’ biological atlas requires us to spatially resolve the entire single-cell transcriptome, and relate such cellular features anatomical scale. Single-cell single-nucleus RNA-seq (sc/snRNA-seq) can profile cells comprehensively, but lose spatial information. Spatial transcriptomics allows for measurements, at lower resolution with limited sensitivity. Targeted in situ technologies solve both issues, are gene throughput. To overcome these limitations we present Tangram, a...
In the past 20 years network science has proven its strength in modeling many real-world interacting systems as generic agents, nodes, connected by pairwise edges. Nevertheless, relevant cases, interactions are not but involve larger sets of nodes at a time. These thus better described framework hypergraphs, whose hyperedges effectively account for multibody interactions. Here we propose and study class random walks defined on such higher-order structures grounded microscopic physical model...
The theory of patterns formation for a reaction-diffusion system defined on multiplex is developed by means perturbative approach. interlayer diffusion constants act as small parameter in the expansion and unperturbed state coincides with limiting setting where layers are decoupled. interaction between adjacent can seed instability homogeneous fixed point, yielding self-organized which instead impeded limit decoupled layers. Patterns individual also fade away due to cross-talking Analytical...
A stochastic version of the Brusselator model is proposed and studied via system size expansion. The mean-field equations are derived shown to yield organized Turing patterns within a specific parameters region. When determining condition for instability, we pay particular attention role cross-diffusive terms, often neglected in heuristic derivation reaction-diffusion schemes. Stochastic fluctuations give rise spatially ordered solutions, sharing same quantitative characteristic based...
Abstract Networks are a widely used and efficient paradigm to model real-world systems where basic units interact pairwise. Many body interactions often at play, cannot be modelled by resorting binary exchanges. In this work, we consider general class of dynamical anchored on hypergraphs. Hyperedges arbitrary size ideally encircle individual so as account for multiple, simultaneous interactions. These latter mediated combinatorial Laplacian, that is here introduced characterised. The...
A generic feature of systems with long-range interactions is the presence quasistationary states non-Gaussian single particle velocity distributions. For case Hamiltonian mean-field model, we demonstrate that a maximum entropy principle applied to associated Vlasov equation explains known features such for wide range initial conditions. We are able reproduce distribution functions an analytic expression which derived from theory no adjustable parameters. normal diffusion angles detected,...
Systems with long-range interactions display a short-time relaxation towards quasistationary states whose lifetime increases system size. With reference to the Hamiltonian mean field model, we here show that maximum entropy principle, based on Lynden-Bell's pioneering idea of "violent relaxation," predicts presence out-of-equilibrium phase transitions separating homogeneous (zero magnetization) or inhomogeneous (nonzero states. When varying initial condition within family "water bags"...
The process of pattern formation for a multispecies model anchored on time varying network is studied. A nonhomogeneous perturbation superposed to an homogeneous stable fixed point can be amplified following the Turing mechanism instability, solely instigated by dynamics. By properly tuning frequency imposed evolution, one make examined system behave as its averaged counterpart, over finite window. This key observation derive closed analytical prediction onset instability in dependent...
When the novel coronavirus disease SARS-CoV2 (COVID-19) was officially declared a pandemic by WHO in March 2020, scientific community had already braced up effort of making sense fast-growing wealth data gathered national authorities all over world. However, despite diversity theoretical approaches and comprehensiveness many widely established models, official figures that recount course outbreak still sketch largely elusive intimidating picture. Here we show unambiguously dynamics COVID-19...
Abstract We propose a one-parameter family of random walk processes on hypergraphs, where parameter biases the dynamics walker towards hyperedges low or high cardinality. show that for each value parameter, resulting process defines its own hypergraph projection weighted network. then explore differences between them by considering community structure associated to process. To do so, we adapt Markov stability framework hypergraphs and test it artificial real-world hypergraphs.
We propose an approach, based on statistical mechanics, to predict the saturated state of a single-pass, high-gain free-electron laser. In analogy with violent relaxation process in self-gravitating systems and Euler equation two-dimensional turbulence, initial laser can be described by mechanics associated Vlasov equation. The field intensity electron bunching parameter reach quasistationary value which is well fitted stationary if number electrons $N$ sufficiently large. Finite effects...
We here discuss the emergence of Quasi Stationary States (QSS), a universal feature systems with long-range interactions. With reference to Hamiltonian Mean Field (HMF) model, numerical simulations are performed based on both original $N$-body setting and continuum Vlasov model which is supposed hold in thermodynamic limit. A detailed comparison unambiguously demonstrates that Vlasov-wave system provides correct framework address study QSS. Further, analytical calculations Lynden-Bell's...
We investigate the dynamics of many-body long-range interacting systems, taking Hamiltonian mean-field model as a case study. show that regular trajectories, associated with invariant tori single-particle dynamics, prevail. The presence such provides dynamical interpretation emergence long-lasting out-of-equilibrium regimes observed generically in systems. This is alternative to previous statistical mechanics approach phenomena which was based on maximum entropy principle. Previously...
Light-sheet fluorescence microscopy (LSFM) enables real-time whole-brain functional imaging in zebrafish larvae. Conventional one-photon LSFM can however induce undesirable visual stimulation due to the use of visible excitation light. The two-photon (2P) excitation, employing near-infrared invisible light, provides unbiased investigation neuronal circuit dynamics. However, low efficiency 2P absorption process, speed this technique is typically limited by signal-to-noise-ratio. Here, we...
The effects of propaganda are analyzed in an opinion dynamics model which, under certain conditions, individuals adjust their as a result random binary encounters. aim this paper is to study what conditions changes the social system. Four different scenarios found, characterized by sensitivities propaganda. For each scenario maximum efficiency attained following given strategy that here outlined.
This review of the development and current status electron tomography deals mainly with mathematical algorithmic aspects. After a very brief description role in structural biology, we turn our attention to derivation forward operator. Starting from Schrödinger equation, electron–specimen interaction is modelled as diffraction problem picture completed by adding optical system transmission microscope. The first-order Born approximation enables one explicitly express intensity for any finite...
Chemical reactions involving diffusion of reactants and subsequent chemical fixation steps are generally termed "diffusion-influenced" (DI). Virtually all biochemical processes in living media can be counted among them, together with those occurring an ever-growing number emerging nano-technologies. The role the environment's geometry (obstacles, compartmentalization) distributed reactivity (competitive reactants, traps) is key modulating rate constants DI reactions, therefore a prime design...
Charting a biological atlas of an organ, such as the brain, requires us to spatially-resolve whole transcriptomes single cells, and relate cellular features histological anatomical scales. Single-cell single-nucleus RNA-Seq (sc/snRNA-seq) can map cells comprehensively 5,6 , but relating those their positions in context organ’s common coordinate framework remains major challenge barrier construction cell 7–10 . Conversely, Spatial Transcriptomics allows for in-situ measurements 11–13 at...
Nature is a blossoming of regular structures, signature self-organization the underlying microscopic interacting agents. Turing theory pattern formation one most studied mechanisms to address such phenomena and has been applied widespread gallery disciplines. himself used spatial discretization hosting support eventually deal with set ODEs. Such an idea contained seeds on discrete support, which fully acknowledged birth network science in early 2000s. This approach allows us tackle several...
The Wilson-Cowan model for metapopulation, a neural mass network model, treats different subcortical regions of the brain as connected nodes, with connections representing various types structural, functional, or effective neuronal connectivity between these regions. Each region comprises interacting populations excitatory and inhibitory cells, consistent standard model. In this article, we show how to incorporate stable attractors into such metapopulation model's dynamics. By doing so,...