Coherent Collisions between Bose-Einstein Condensates

We study the non-degenerate parametric amplifier for matter waves, implemented by colliding two Bose-Einstein condensates. The coherence of the amplified waves is shown by observing high contrast interference with a reference wave and by reversing the amplification process. Since our experiments also place limits on all known sources of decoherence, we infer that relative number squeezing is most likely present between the amplified modes. Finally, we suggest that reversal of the amplification process may be used to detect relative number squeezing without requiring single-particle detection.Comment: 4.2 pages, 4 figures, please take postscript version for best quality of picture

Effective one-component description of two-component Bose-Einstein condensate dynamics

We investigate dynamics in two-component Bose-Einstein condensates in the context of coupled Gross-Pitaevskii equations and derive results for the evolution of the total density fluctuations. Using these results, we show how, in many cases of interest, the dynamics can be accurately described with an effective one-component Gross-Pitaevskii equation for one of the components, with the trap and interaction coefficients determined by the relative differences in the scattering lengths. We discuss the model in various regimes, where it predicts breathing excitations, and the formation of vector solitons. An effective nonlinear evolution is predicted for some cases of current experimental interest. We then apply the model to construct quasi-stationary states of two-component condensates.Comment: 8 pages, 4 figure

Enhanced heat flow in the hydrodynamic-collisionless regime

We study the heat conduction of a cold, thermal cloud in a highly asymmetric trap. The cloud is axially hydrodynamic, but due to the asymmetric trap radially collisionless. By locally heating the cloud we excite a thermal dipole mode and measure its oscillation frequency and damping rate. We find an unexpectedly large heat conduction compared to the homogeneous case. The enhanced heat conduction in this regime is partially caused by atoms with a high angular momentum spiraling in trajectories around the core of the cloud. Since atoms in these trajectories are almost collisionless they strongly contribute to the heat transfer. We observe a second, oscillating hydrodynamic mode, which we identify as a standing wave sound mode.Comment: Sumitted to Phys. Rev. Letters, 4 pages, 4 figure

Reaching the hydrodynamic regime in a Bose-Einstein condensate by suppression of avalanche

We report the realization of a Bose-Einstein condensate (BEC) in the hydrodynamic regime. The hydrodynamic regime is reached by evaporative cooling at a relative low density suppressing the effect of avalanches. With the suppression of avalanches a BEC containing 120.10^6 atoms is produced. The collisional opacity can be tuned from the collisionless regime to a collisional opacity of more than 3 by compressing the trap after condensation. In the collisional opaque regime a significant heating of the cloud at time scales shorter than half of the radial trap period is measured. This is direct proof that the BEC is hydrodynamic.Comment: Article submitted for Phys. Rev. Letters, 6 figure

Large atom number Bose-Einstein condensate of sodium

We describe the setup to create a large Bose-Einstein condensate containing more than 120x10^6 atoms. In the experiment a thermal beam is slowed by a Zeeman slower and captured in a dark-spot magneto-optical trap (MOT). A typical dark-spot MOT in our experiments contains 2.0x10^10 atoms with a temperature of 320 microK and a density of about 1.0x10^11 atoms/cm^3. The sample is spin polarized in a high magnetic field, before the atoms are loaded in the magnetic trap. Spin polarizing in a high magnetic field results in an increase in the transfer efficiency by a factor of 2 compared to experiments without spin polarizing. In the magnetic trap the cloud is cooled to degeneracy in 50 s by evaporative cooling. To suppress the 3-body losses at the end of the evaporation the magnetic trap is decompressed in the axial direction.Comment: 11 pages, 12 figures, submitted to Review Of Scientific Instrument

Training deep neural density estimators to identify mechanistic models of neural dynamics

Mechanistic modeling in neuroscience aims to explain observed phenomena in terms of underlying causes. However, determining which model parameters agree with complex and stochastic neural data presents a significant challenge. We address this challenge with a machine learning tool which uses deep neural density estimators-- trained using model simulations-- to carry out Bayesian inference and retrieve the full space of parameters compatible with raw data or selected data features. Our method is scalable in parameters and data features, and can rapidly analyze new data after initial training. We demonstrate the power and flexibility of our approach on receptive fields, ion channels, and Hodgkin-Huxley models. We also characterize the space of circuit configurations giving rise to rhythmic activity in the crustacean stomatogastric ganglion, and use these results to derive hypotheses for underlying compensation mechanisms. Our approach will help close the gap between data-driven and theory-driven models of neural dynamics