Cosimo Lupo

Cosimo Lupo
INFN - Istituto Nazionale di Fisica Nucleare | INFN · Rome I

PhD in Theoretical Physics
PostDoc researcher at INFN-Roma1

About

18
Publications
1,207
Reads
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61
Citations
Citations since 2016
18 Research Items
61 Citations
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Introduction
I'm currently working as a PostDoc at the "Laboratoire de Physique de l'Ecole Normale Supérieure" (LPENS) in Paris, in the research group of Aleksandra Walczak and Thierry Mora. My main focus is on the statistical description on the evolution of B-cells in the human immune system, especially when in presence of chronic infections. Previously, I've been a PostDoc at the Department of Physics, Sapienza University of Rome, in the research group lead by Giorgio Parisi, with a research project on the low-temperature physics of strongly disordered systems with continuous degrees of freedom.
Additional affiliations
February 2018 - January 2021
Ecole Normale Supérieure de Paris
Position
  • PostDoc Position
October 2017 - December 2017
Sapienza University of Rome
Position
  • Laboratory Assistant
Description
  • Laboratory of Computational Physics
October 2017 - December 2017
Sapienza University of Rome
Position
  • Professor (Assistant)
Description
  • Tutoring Course on Basic Mathematical skills
Education
November 2013 - February 2017
Sapienza University of Rome
Field of study
  • Theoretical Physics
October 2011 - September 2013
Sapienza University of Rome
Field of study
  • Physics
October 2008 - October 2011
Sapienza University of Rome
Field of study
  • Physics

Publications

Publications (18)
Preprint
Full-text available
Sleep is known to play a central role in learning and cognition, yet the mechanisms underlying its role in stabilizing learning and improving energetic management are still to be clarified. It is characterized by patterns of cortical activity alternating between the stages of slow wave sleep (NREM) and rapid eye movement sleep (REM). In this work,...
Preprint
Full-text available
The brain can efficiently learn a wide range of tasks, motivating the search for biologically inspired learning rules for improving current artificial intelligence technology. Most biological models are composed of point neurons, and cannot achieve the state-of-the-art performances in machine learning. Recent works have proposed that segregation of...
Conference Paper
Full-text available
The brain can learn to solve a wide range of tasks with high temporal and energetic efficiency. However, most biological models are composed of simple single-compartment neurons and cannot achieve the state-of-the-art performances of artificial intelligence. We propose a multi-compartment model of pyramidal neuron, in which bursts and dendritic inp...
Preprint
HIV-1 broadly neutralizing antibodies (bNAbs) are able to suppress viremia and prevent infection. Their induction by vaccination is therefore a major goal. However, in contrast to antibodies that neutralize other pathogens, HIV-1-specific bNAbs frequently carry uncommon molecular characteristics that might prevent their induction. Here, we performe...
Article
Full-text available
Affinity maturation is crucial for improving the binding affinity of antibodies to antigens. This process is mainly driven by point substitutions caused by somatic hypermutations of the immunoglobulin gene. It also includes deletions and insertions of genomic material known as indels. While the landscape of point substitutions has been extensively...
Preprint
Full-text available
The brain can learn to solve a wide range of tasks with high temporal and energetic efficiency. However, most biological models are composed of simple single compartment neurons and cannot achieve the state-of-art performances of artificial intelligence. We propose a multi-compartment model of pyramidal neuron, in which bursts and dendritic input s...
Preprint
Full-text available
Affinity maturation is crucial for improving the binding affinity of antibodies to antigens. This process is mainly driven by point substitutions caused by somatic hypermutations of the immunoglobulin gene. It also includes deletions and insertions of genomic material known as indels. While the landscape of point substitutions has been extensively...
Poster
Full-text available
The ferromagnetic XY model on sparse random graphs in a randomly oriented field is analyzed via the belief propagation algorithm. At variance with the fully connected case and with the random field Ising model on the same topology, we find strong evidence of a tiny region with replica symmetry breaking (RSB) in the limit of very low temperatures. T...
Preprint
Full-text available
The ferromagnetic XY model on sparse random graphs in a randomly oriented field is analyzed via the belief propagation algorithm. At variance with the fully connected case and with the random field Ising model on the same topology, we find strong evidences of a tiny region with Replica Symmetry Breaking (RSB) in the limit of very low temperatures....
Article
Full-text available
Vector spin glasses are known to show two different kinds of phase transitions in presence of an external field: the so-called de Almeida-Thouless and Gabay-Toulouse lines. While the former has been studied to some extent on several topologies (fully connected, random graphs, finite-dimensional lattices, chains with long-range interactions), the la...
Presentation
Full-text available
Coauthors: Giorgio Parisi, Federico Ricci-Tersenghi
Presentation
Full-text available
Coauthors: Giorgio Parisi, Federico Ricci-Tersenghi
Presentation
Full-text available
Coauthors: Giorgio Parisi, Federico Ricci-Tersenghi
Article
Full-text available
Numerical simulations of spin glass models with continuous variables set the problem of a reliable but efficient discretization of such variables. In particular, the main question is how fast physical observables computed in the discretized model converge toward the ones of the continuous model when the number of states of the discretized model inc...
Thesis
Full-text available
This thesis focuses on the XY model, that is the simplest continuous spin model, used for describing numerous physical systems, from random lasers to superconductors, from synchronization problems to superfluids. It is studied for different sources of quenched disorder: random couplings, random fields, or both them. The belief propagation algorithm...
Poster
Full-text available
A reliable description of the behaviour of spin glasses in a magnetic field represents a crucial milestone in the seek of a full comprehension of disordered systems. Today we know (almost) everything about the Ising model in a field (eg RFIM), but what about vector spin glasses? Known results about them regards fully connected topologies. When a un...

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Projects

Project (1)
Project
Vector spin glass models have been scarcely studied, mostly on fully connected topologies, which provide some unphysical predictions. We focus instead on diluted topologies, which yield more reliable results. By exploiting belief-propagation, we find that the XY model (the simplest vector model) is by far more unstable toward replica symmetry breaking (RSB), due to the combined effect of the graph sparsity and the spin continuous nature. Several interesting consequences arise, among which the appearance of RSB in the random field XY model and the recovering of the frequency density of vibrations in glasses in the zero–temperature limit.