Interpretation of the unpolarized azimuthal asymmetries in SIDIS

The measurement of azimuthal modulations in hadron leptoproduction on unpolarized nucleons allows to get information on the intrinsic transverse momentum $\langle k_T^2 \rangle$ of quarks in a nucleon through both the Cahn effect and the Boer-Mulders function. We have compared the azimuthal asymmetries in the cross section of $160\, \rm{GeV}/c$ muons scattered off an unpolarised deuteron target as measured by COMPASS with a Monte Carlo program, based on the ${}^3P_0$ model of quark anti-quark pair production at string breaking, which accounts for the Cahn effect. Large differences have been observed between data and Monte Carlo, in particular at large values of the fraction of the longitudinal momentum of the fragmenting quark carried by the produced hadron. We found out that most of these differences are due to pions from exclusive vector mesons contaminating the SIDIS sample, which also exhibit large azimuthal modulations. Using the measurements of the exclusive reaction $\mu N\rightarrow \mu' \, \rho\, N$ we had done in 2006, we can reproduce reasonably well the observed differences. Subtracting the contribution of hadrons produced in the decay of exclusive vector mesons from the SIDIS unpolarised azimuthal asymmetries is therefore a prerequisite condition for extracting $\langle k_T^2 \rangle$ and the Boer-Mulders function.Comment: to be published in the 23rd International Spin Physics Symposium (SPIN2018) proceedings, 11 pages, 7 figure

Binary interaction algorithms for the simulation of flocking and swarming dynamics

Microscopic models of flocking and swarming takes in account large numbers of interacting individ- uals. Numerical resolution of large flocks implies huge computational costs. Typically for $N$ interacting individuals we have a cost of $O(N^2)$. We tackle the problem numerically by considering approximated binary interaction dynamics described by kinetic equations and simulating such equations by suitable stochastic methods. This approach permits to compute approximate solutions as functions of a small scaling parameter $\varepsilon$ at a reduced complexity of O(N) operations. Several numerical results show the efficiency of the algorithms proposed

Linear multistep methods for optimal control problems and applications to hyperbolic relaxation systems

We are interested in high-order linear multistep schemes for time discretization of adjoint equations arising within optimal control problems. First we consider optimal control problems for ordinary differential equations and show loss of accuracy for Adams-Moulton and Adams-Bashford methods, whereas BDF methods preserve high--order accuracy. Subsequently we extend these results to semi--lagrangian discretizations of hyperbolic relaxation systems. Computational results illustrate theoretical findings

Implicit-Explicit multistep methods for hyperbolic systems with multiscale relaxation

We consider the development of high order space and time numerical methods based on Implicit-Explicit (IMEX) multistep time integrators for hyperbolic systems with relaxation. More specifically, we consider hyperbolic balance laws in which the convection and the source term may have very different time and space scales. As a consequence the nature of the asymptotic limit changes completely, passing from a hyperbolic to a parabolic system. From the computational point of view, standard numerical methods designed for the fluid-dynamic scaling of hyperbolic systems with relaxation present several drawbacks and typically lose efficiency in describing the parabolic limit regime. In this work, in the context of Implicit-Explicit linear multistep methods we construct high order space-time discretizations which are able to handle all the different scales and to capture the correct asymptotic behavior, independently from its nature, without time step restrictions imposed by the fast scales. Several numerical examples confirm the theoretical analysis

Invisible control of self-organizing agents leaving unknown environments

In this paper we are concerned with multiscale modeling, control, and simulation of self-organizing agents leaving an unknown area under limited visibility, with special emphasis on crowds. We first introduce a new microscopic model characterized by an exploration phase and an evacuation phase. The main ingredients of the model are an alignment term, accounting for the herding effect typical of uncertain behavior, and a random walk, accounting for the need to explore the environment under limited visibility. We consider both metrical and topological interactions. Moreover, a few special agents, the leaders, not recognized as such by the crowd, are "hidden" in the crowd with a special controlled dynamics. Next, relying on a Boltzmann approach, we derive a mesoscopic model for a continuum density of followers, coupled with a microscopic description for the leaders' dynamics. Finally, optimal control of the crowd is studied. It is assumed that leaders exploit the herding effect in order to steer the crowd towards the exits and reduce clogging. Locally-optimal behavior of leaders is computed. Numerical simulations show the efficiency of the optimization methods in both microscopic and mesoscopic settings. We also perform a real experiment with people to study the feasibility of the proposed bottom-up crowd control technique.Comment: in SIAM J. Appl. Math, 201