Experimental Quantum Teleportation with a 3-Bell-state Analyzer

We present a Bell-state analyzer for time-bin qubits allowing the detection of three out of four Bell-states with linear optics, two detectors and no auxiliary photons. The theoretical success rate of this scheme is 50%. A teleportation experiment was performed to demonstrate its functionality. We also present a teleportation experiment with a Fidelity larger than the cloning limit of F=5/6.Comment: 11 pages, 14 figure

The smallest refrigerators can reach maximal efficiency

We investigate whether size imposes a fundamental constraint on the efficiency of small thermal machines. We analyse in detail a model of a small self-contained refrigerator consisting of three qubits. We show analytically that this system can reach the Carnot efficiency, thus demonstrating that there exists no complementarity between size and efficiency.Comment: 9 pages, 1 figure. v2: published versio

Bivariate galaxy luminosity functions in the Sloan Digital Sky Survey

Bivariate luminosity functions (LFs) are computed for galaxies in the New York Value-Added Galaxy Catalogue, based on the Sloan Digital Sky Survey Data Release 4. The galaxy properties investigated are the morphological type, inverse concentration index, Sérsic index, absolute effective surface brightness (SB), reference frame colours, absolute radius, eClass spectral type, stellar mass and galaxy environment. The morphological sample is flux limited to galaxies with r < 15.9 and consists of 37 047 classifications to an rms accuracy of ± half a class in the sequence E, S0, Sa, Sb, Sc, Sd, Im. These were assigned by an artificial neural network, based on a training set of 645 eyeball classifications. The other samples use r < 17.77 with a median redshift of z∼ 0.08, and a limiting redshift of z < 0.15 to minimize the effects of evolution. Other cuts, for example in axis ratio, are made to minimize biases. A wealth of detail is seen, with clear variations between the LFs according to absolute magnitude and the second parameter. They are consistent with an early-type, bright, concentrated, red population and a late-type, faint, less concentrated, blue, star-forming population. This bimodality suggests two major underlying physical processes, which in agreement with previous authors we hypothesize to be merger and accretion, associated with the properties of bulges and discs, respectively. The bivariate luminosity–SB distribution is fit with the Chołoniewski function (a Schechter function in absolute magnitude and Gaussian in SB). The fit is found to be poor, as might be expected if there are two underlying processes

Galaxy types in the Sloan Digital Sky Survey using supervised artificial neural networks

Supervised artificial neural networks are used to predict useful properties of galaxies in the Sloan Digital Sky Survey, in this instance morphological classifications, spectral types and redshifts. By giving the trained networks unseen data, it is found that correlations between predicted and actual properties are around 0.9 with rms errors of order ten per cent. Thus, given a representative training set, these properties may be reliably estimated for galaxies in the survey for which there are no spectra and without human intervention