9.4010.20  Alfredo Braunstein  Politecnico di Torino
Inverse problems in spread dynamics on networks
We study some inverse problems arising in a class of stochastic spread dynamics which
includes some wellknown 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.

10.2010.40  Mario Motta  Università degli Studi di Milano
Dynamical imaginarytime correlations from Auxiliary Fields Quantum Monte Carlo
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 twodimensional electron liquid, providing comparisons with other QMC techniques. In collaboration with: D.E.Galli, S. Moroni and E.Vitali REFERENCES: [1] R.P. Feynman, A.R. Hibbs, Quantum Mechanics and Path Integrals, McGrawHill (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) 
10.4011.30  pausa caffè 
11.3012.10  Pasquale Calabrese  Università di Pisa
Replica Bethe ansatz solutions to KPZ equation The onedimensional KardarParisiZhang (KPZ) equation describes the scaleinvariant 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 
12.1012.30  Luca Dall'Asta  Politecnico di Torino
Optimal Immunization of Networks by MessagePassing
Network immunization against failures and epidemic spreading can
be written as a constrained optimization problem, in which the constraints
are fixedpoint equations for some local (node or edge) variables
describing the stationary state of the dynamics. I will show how the
cavity method, and messagepassing techniques, can be used to study this problem
and design efficient algorithms on large networks.

12.3012.50  Asja Jelic  ISCCNR Roma
Superfluid transport of information in turning flocks of starlings 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 soundlike 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 decisionmaking 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:1305.1495In collaboration with: Andrea Cavagna, Irene Giardina, Alessandro Attanasi, Lorenzo Del Castello, Tomas S. Grigera, Stefania Melillo, Leonardo Parisi, Oliver Pohl, Edward Shen, Massimiliano Viale 
12.5014.20  pausa pranzo 
14.2015.00  Andrea Gabrielli  ISCCNR Roma
NonMarkovian models of blocking in concurrent and countercurrent flows
We investigate models in which blocking can interrupt a particulate flow
process at any time [1]. Filtration, and flow in micro/nanochannels 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. 
15.0015.20  Daniele Tantari  Università di Roma "La Sapienza"
Retrieving an infinite number of patterns in a spin glass model of the immune system
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.

15.2015.40  Pierangelo Lombardo  SISSA Trieste
Fixation time in a subdivided population with balancing selection
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.

15.4016.20  Guido Boffetta  Università degli Studi di Torino
Causalità e reversibilità in turbolenza
tba
