Preparation and detection of d-wave superfluidity in two-dimensional optical superlattices

We propose a controlled method to create and detect d-wave superfluidity with ultracold fermionic atoms loaded in two-dimensional optical superlattices. Our scheme consists in preparing an array of nearest-neighbor coupled square plaquettes or ``superplaquettes'' and using them as building blocks to construct a d-wave superfluid state. We describe how to use the coherent dynamical evolution in such a system to experimentally probe the pairing mechanism. We also derive the zero temperature phase diagram of the fermions in a checkerboard lattice (many weakly coupled plaquettes) and show that by tuning the inter-plaquette tunneling spin-dependently or varying the filling factor one can drive the system into a d-wave superfluid phase or a Cooper pair density wave phase. We discuss the use of noise correlation measurements to experimentally probe these phases.Comment: 8 pages, 6 figure

Sympathetic cooling and collisional properties of a Rb-Cs mixture

We report on measurements of the collisional properties of a mixture of $^{133}$Cs and $^{87}$Rb atoms in a magnetic trap at $\mu\mathrm{K}$ temperatures. By selectively evaporating the Rb atoms using a radio-frequency field, we achieved sympathetic cooling of Cs down to a few $\mu\mathrm{K}$. The inter-species collisional cross-section was determined through rethermalization measurements, leading to an estimate of $a_s=595 a_0$ for the s-wave scattering length for Rb in the $|F=2, m_F=2>$ and Cs in the $|F=4, m_F=4>$ magnetic states. We briefly speculate on the prospects for reaching Bose-Einstein condensation of Cs inside a magnetic trap through sympathetic cooling

Data-Driven Stability Assessment of Multilayer Long Short-Term Memory Networks

Recurrent Neural Networks (RNNs) are increasingly being used for model identification, forecasting and control. When identifying physical models with unknown mathematical knowledge of the system, Nonlinear AutoRegressive models with eXogenous inputs (NARX) or Nonlinear AutoRegressive Moving-Average models with eXogenous inputs (NARMAX) methods are typically used. In the context of data-driven control, machine learning algorithms are proven to have comparable performances to advanced control techniques, but lack the properties of the traditional stability theory. This paper illustrates a method to prove a posteriori the stability of a generic neural network, showing its application to the state-of-the-art RNN architecture. The presented method relies on identifying the poles associated with the network designed starting from the input/output data. Providing a framework to guarantee the stability of any neural network architecture combined with the generalisability properties and applicability to different fields can significantly broaden their use in dynamic systems modelling and control

Preparing and probing atomic number states with an atom interferometer

We describe the controlled loading and measurement of number-squeezed states and Poisson states of atoms in individual sites of a double well optical lattice. These states are input to an atom interferometer that is realized by symmetrically splitting individual lattice sites into double wells, allowing atoms in individual sites to evolve independently. The two paths then interfere, creating a matter-wave double-slit diffraction pattern. The time evolution of the double-slit diffraction pattern is used to measure the number statistics of the input state. The flexibility of our double well lattice provides a means to detect the presence of empty lattice sites, an important and so far unmeasured factor in determining the purity of a Mott state

Asymmetric Landau-Zener tunneling in a periodic potential

Using a simple model for nonlinear Landau-Zener tunneling between two energy bands of a Bose-Einstein condensate in a periodic potential, we find that the tunneling rates for the two directions of tunneling are not the same. Tunneling from the ground state to the excited state is enhanced by the nonlinearity, whereas in the opposite direction it is suppressed. These findings are confirmed by numerical simulations of the condensate dynamics. Measuring the tunneling rates for a condensate of rubidium atoms in an optical lattice, we have found experimental evidence for this asymmetry.Comment: 5 pages, 3 figure

Simulation of the wave evolution and power capture of an oscillating wave surge converter

For oscillating wave surge converters (OWSC) the incident wave field is changed due to the movement of the flap structure. A key component influencing this motion response is the Power Take-Off (PTO) system used. This paper examines the relationship between incident waves and the perturbed fluid field near the flap using the Computational Fluid Dynamics method by using Reynolds Averaged Navier-Stokes (RANS) equations. Further, it investigates the influence of a PTO system in the energy extracted from regular waves. Whilst this wave evolution is not significant in the effective power captured by a unit device, it is of great importance when performing in arrays as neighbouring devices may influence each other