Distillation of squeezing using an engineered pulsed parametric down-conversion source.

Hybrid quantum information processing combines the advantages of discrete and continues variable protocols by realizing protocols consisting of photon counting and homodyne measurements. However, the mode structure of pulsed sources and the properties of the detection schemes often require the use of optical filters in order to combine both detection methods in a common experiment. This limits the efficiency and the overall achievable squeezing of the experiment. In our work, we use photon subtraction to implement the distillation of pulsed squeezed states originating from a genuinely spatially and temporally single-mode parametric down-conversion source in non-linear waveguides. Due to the distillation, we witness an improvement of 0.17 dB from an initial squeezing value of -1.648 ± 0.002 dB, while achieving a purity of 0.58, and confirm the non-Gaussianity of the distilled state via the higher-order cumulants. With this, we demonstrate the source's suitability for scalable hybrid quantum network applications with pulsed quantum light.

Distribution of squeezed states through an atmospheric channel.

Continuous variable quantum states of light are used in quantum information protocols and quantum metrology and known to degrade with loss and added noise. We were able to show the distribution of bright polarization squeezed quantum states of light through an urban free-space channel of 1.6 km length. To measure the squeezed states in this extreme environment, we utilize polarization encoding and a postselection protocol that is taking into account classical side information stemming from the distribution of transmission values. The successful distribution of continuous variable squeezed states is accentuated by a quantum state tomography, allowing for determining the purity of the state.

Reverse Monte Carlo modeling of ion conducting network glasses: an evaluation based on molecular dynamics simulations.

We investigate the quality of structural models generated by the Reverse Monte Carlo (RMC) method in a typical application to glass systems. To this end we calculate diffraction data from a Li(2)O-SiO(2) molecular dynamics (MD) simulation and use it, in addition to minimal pair distances and coordination numbers of silicon (oxygen) to oxygen (silicon) ions, as input for RMC modeling. Then we compare partial radial distribution functions, coordination numbers, bond angles, and ring sizes predicted by the RMC models with those of the MD system. It is found that partial distribution functions and properties on small lengths scales, as distributions of coordination numbers and bond angles, are well reproduced by the RMC modeling. Properties in the medium-range order regime are, however, not well captured, as is demonstrated by comparison of ring size distributions. Due care therefore has to be exercised when extracting structural features from RMC models in this medium-range order regime. In particular we show that the occurrence of such features can be a mere consequence of the chosen starting configuration.

Mixed barrier model for the mixed glass former effect in ion conducting glasses.

Mixing two types of glass formers in ion conducting glasses can be exploited to lower conductivity activation energy and thereby increasing the ionic conductivity, a phenomenon known as the mixed glass former effect (MGFE). We develop a model for this MGFE, where activation barriers for individual ion jumps get lowered in inhomogeneous environments containing both types of network forming units. Fits of the model to experimental data allow one to estimate the strength of the barrier reduction, and they indicate a spatial clustering of the two types of network formers. The model predicts a time-temperature superposition of conductivity spectra onto a common master curve independent of the mixing ratio.