Mean field dynamics of superfluid-insulator phase transition in a gas of ultra cold atoms

A large scale dynamical simulation of the superfluid to Mott insulator transition in the gas of ultra cold atoms placed in an optical lattice is performed using the time dependent Gutzwiller mean field approach. This approximate treatment allows us to take into account most of the details of the recent experiment [Nature 415, 39 (2002)] where by changing the depth of the lattice potential an adiabatic transition from a superfluid to a Mott insulator state has been reported. Our simulations reveal a significant excitation of the system with a transition to insulator in restricted regions of the trap.Comment: final version, correct Fig.7 (the published version contains wrong fig.7 by mistake

Parametrization of local biholomorphisms of real analytic hypersurfaces

Let $M$ be a real analytic hypersurface in \bC^N which is finitely nondegenerate, a notion that can be viewed as a generalization of Levi nondegenerate, at $p_0\in M$. We show that if $M'$ is another such hypersurface and $p'_0\in M'$, then the set of germs at $p_0$ of biholomorphisms $H$ with $H(M)\subset M'$ and $H(p_0)=p'_0$, equipped with its natural topology, can be naturally embedded as a real analytic submanifold in the complex jet group of \bC^N of the appropriate order. We also show that this submanifold is defined by equations that can be explicitly computed from defining equations of $M$ and $M'$. Thus, $(M,p_0)$ and $(M',p'_0)$ are biholomorphically equivalent if and only if this (infinite) set of equations in the complex jet group has a solution. Another result obtained in this paper is that any invertible formal map $H$ that transforms $(M,p_0)$ to $(M',p'_0)$ is convergent. As a consequence, $(M,p_0)$ and $(M',p'_0)$ are biholomorphically equivalent if and only if they are formally equivalent

Downwash-Aware Trajectory Planning for Large Quadrotor Teams

We describe a method for formation-change trajectory planning for large quadrotor teams in obstacle-rich environments. Our method decomposes the planning problem into two stages: a discrete planner operating on a graph representation of the workspace, and a continuous refinement that converts the non-smooth graph plan into a set of C^k-continuous trajectories, locally optimizing an integral-squared-derivative cost. We account for the downwash effect, allowing safe flight in dense formations. We demonstrate the computational efficiency in simulation with up to 200 robots and the physical plausibility with an experiment with 32 nano-quadrotors. Our approach can compute safe and smooth trajectories for hundreds of quadrotors in dense environments with obstacles in a few minutes.Comment: 8 page