Lunedì 24 - Mercoledì 26 giugno 2013, Università di Parma

programma di mercoledì 26 giugno 2013
Alfredo Braunstein - Politecnico di Torino
Inverse problems in spread dynamics on networks image
We study some inverse problems arising in a class of stochastic spread dynamics which includes some well-known discrete time epidemic models on networks. In particular, we show how observations at a given time in the dynamics can be used efficiently to infer rich information about the past.
Mario Motta - Università degli Studi di Milano
Dynamical imaginary-time correlations from Auxiliary Fields Quantum Monte Carlo image
Quantum Monte Carlo (QMC) simulations of many body fermionic systems are considerably complicated by the well known sign problem [1]. Although very accurate approximation schemes have been developed for the calculation of static properties, like structure functions and energy, the possibility of extending such methodologies to the investigation of dynamical properties is still largely unexplored [2].
Recently, a number of innovative QMC methods have been conceived which map the imaginary time evolution into a random walk in the abstract manifold of Slater determinants. In such approaches the sign problem is not circumvented and still requires approximations, but emerges in a different - and hopefully easier to handle - way. We have focused on the phaseless auxiliary Fields QMC method (AFQMC), developed by Shiwei Zhang[3]. Generalizing the formal manipulations suggested by Assaad et al. [4], we propose a practical scheme to evaluate dynamic correlation functions in imaginary time, giving access to the study of excitations and response functions of interacting fermionic systems.
We have explored systematically the effects of the phaseless approximation, underlying the AFQMC technique and its dynamical generalization, via the study of exactly solvable simple models, comparing AFQMC predictions with exact solutions. We will present also results about a two-dimensional electron liquid, providing comparisons with other QMC techniques.

In collaboration with: D.E.Galli, S. Moroni and E.Vitali


[1] R.P. Feynman, A.R. Hibbs, Quantum Mechanics and Path Integrals, McGraw-Hill (1965)
[2] M. Nava, D. Galli, S. Moroni and E. Vitali: arXiv:1302.1799 (2013)
[3] S. Zhang: 'Quantum Monte Carlo Methods for Strongly Correlated Electron Systems', in Theoretical Methods for Strongly Correlated Electron Systems, Springer Verlag (2003)
[4] M. Feldbacher and F. F. Assaad: Phys. Rev. B 63, 073105 (2001)
10.40-11.30pausa caffè
Pasquale Calabrese - Università di Pisa
Replica Bethe ansatz solutions to KPZ equation image

The one-dimensional Kardar-Parisi-Zhang (KPZ) equation describes the scale-invariant stochastic motion of a line. I will report on the exact calculation of the height distribution at arbitrary time of the KPZ growth equation in one dimension with droplet and flat initial conditions obtained using the mapping to a directed polymer (DP) and the Bethe Ansatz for the replicated attractive boson model. The generating function of the moments of the DP partition sum is obtained as a Fredholm determinant/Pfaffian. The final result, valid for all times, exhibits convergence of the KPZ height distribution to the GOE/GUE Tracy Widom distributions at large time.

Based on:
P Calabrese and P. Le Doussal, Phys. Rev. Lett. 106, 250603 (2011); J. Stat. Mech. (2012) P06001; P Calabrese, P Le Doussal, and A Rosso, 2010 EPL 90 20002
Luca Dall'Asta - Politecnico di Torino
Optimal Immunization of Networks by Message-Passing image
Network immunization against failures and epidemic spreading can be written as a constrained optimization problem, in which the constraints are fixed-point equations for some local (node or edge) variables describing the stationary state of the dynamics. I will show how the cavity method, and message-passing techniques, can be used to study this problem and design efficient algorithms on large networks.
Asja Jelic - ISC-CNR Roma
Superfluid transport of information in turning flocks of starlings image

Turning flocks of starlings are a paradigm for a synchronized, rapid change of direction in moving animal groups. The efficiency of the information transport during such a collective change of state is the key factor to prevent cohesion loss and preserve robustness. However, the precise mechanism by which natural groups achieve such efficiency is currently not fully understood. I will present an experimental and theoretical study of starlings flocks undergoing collective turns in which we analyze how the turning decision spreads across the flock [1]. We find sound-like propagation with no damping of information. This is in contrast with standard theories of collective animal behavior based on alignment, which predict a much slower, diffusive spread of information. We propose a novel theory for propagation of orientation in flocks whose key ingredient is the existence of a conserved spin current generated by the gauge symmetry of the system. The theory falls in the same dynamical universality class of superfluid transport in liquid helium, naturally explaining the dissipationless propagating mode observed in turning flocks. Superfluidity also provides a quantitative prediction for the speed of propagation of the information, according to which transport must be swifter the stronger the group's orientational order. This is confirmed by the experimental data. The link between strong order and efficient decision-making required by superfluidity may be the adaptive drive for the high degree of behavioral polarization observed in many living groups.

[1] arXiv:1303.7097, arXiv:1305.1495

In collaboration with: Andrea Cavagna, Irene Giardina, Alessandro Attanasi, Lorenzo Del Castello, Tomas S. Grigera, Stefania Melillo, Leonardo Parisi, Oliver Pohl, Edward Shen, Massimiliano Viale
12.50-14.20pausa pranzo
Andrea Gabrielli - ISC-CNR Roma
Non-Markovian models of blocking in concurrent and countercurrent flows image
We investigate models in which blocking can interrupt a particulate flow process at any time [1]. Filtration, and flow in micro/nano-channels and traffic flow are examples of such processes. We first consider concurrent flow models where particles enter a channel randomly. If at any time two particles are simultaneously present in the channel, failure occurs. The key quantities are the survival probability and the distribution of the number of particles that pass before failure. We then consider a counterflow model with two opposing Poisson streams. There is no restriction on the number of particles passing in the same direction, but blockage occurs if, at any time, two opposing particles are simultaneously present in the passage.

[1] A. Gabrielli, J. Talbot and P. Viot, arXiv:1303.4918 , in publication on Phys. Rev. Lett.
Daniele Tantari - Università di Roma "La Sapienza"
Retrieving an infinite number of patterns in a spin glass model of the immune system image
I will introduce a statistical mechanic model of a network able to exhibit multitasking capabilities. In addition to their relevance in artificial intelligence, these models are increasingly important in immunology, where stored patterns represent strategies to fight pathogens and nodes represent lymphocyte clones. They allow us to understand the crucial ability of the immune system to respond simultaneously to multiple distinct antigen invasions.
Pierangelo Lombardo - SISSA Trieste
Fixation time in a subdivided population with balancing selection image
We describe a population of individuals carrying one of the two possible variants of a gene (alleles). The population is subdivided into groups (demes) living on a fully connected graph, and individuals are allowed to migrate from one deme to another. While the stochastic dynamics (genetic drift) of each deme tends to fix one allele and make it present in all individuals of the deme, a deterministic force favours rare alleles (balancing selection). We investigate the influence of population subdivision on the mean time required by the population to fix one of the two alleles: this fixation time shows an unexpected behaviour as a function of the migration rate, which we rationalized within our approach.
Guido Boffetta - Università degli Studi di Torino
Causalità e reversibilità in turbolenza image