Production of non-local quartets and phase-sensitive entanglement in a superconducting beam splitter

Three BCS superconductors S_a, S_b, and S and two short normal regions N_a and N_b in a three-terminal S_aN_aSN_bS_b set-up provide a source of non-local quartets spatially separated as two correlated pairs in S_a and S_b, if the distance between the interfaces N_aS and SN_b is comparable to the coherence length in S. Low-temperature dc-transport of non-local quartets from S to S_a and S_b can occur in equilibrium, and also if S_a and S_b are biased at opposite voltages. At higher temperatures, thermal excitations result in correlated current fluctuations which depend on the superconducting phases phi_a and phi_b in S_a and S_b. Phase-sensitive entanglement is obtained at zero temperature if N_a and N_b are replaced by discrete levels.Comment: 4 pages, 2 figures; technical details attached in ancillary file http://arxiv.org/src/1102.2355v4/anc/EPAPS_Freyn_2011.pdf; higher versions: minor corrections, cleanup and corrected reference

Accelerating exhaustive pairwise metagenomic comparisons

In this manuscript, we present an optimized and parallel version of our previous work IMSAME, an exhaustive gapped aligner for the pairwise and accurate comparison of metagenomes. Parallelization strategies are applied to take advantage of modern multiprocessor architectures. In addition, sequential optimizations in CPU time and memory consumption are provided. These algorithmic and computational enhancements enable IMSAME to calculate near optimal alignments which are used to directly assess similarity between metagenomes without requiring reference databases. We show that the overall efficiency of the parallel implementation is superior to 80% while retaining scalability as the number of parallel cores used increases. Moreover, we also show thats equential optimizations yield up to 8x speedup for scenarios with larger data.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

STUDY OF CORROSION AND WEAR OF SURGICAL INSTRUMENTS DURING STERILIZATION

Oral Communication presented at the ";Forum des Jeunes Chercheurs";, Brest (France) 2011

NIKEL: Electronics and data acquisition for kilopixels kinetic inductance camera

A prototype of digital frequency multiplexing electronics allowing the real time monitoring of microwave kinetic inductance detector (MKIDs) arrays for mm-wave astronomy has been developed. Thanks to the frequency multiplexing, it can monitor simultaneously 400 pixels over a 500 MHz bandwidth and requires only two coaxial cables for instrumenting such a large array. The chosen solution and the performances achieved are presented in this paper.Comment: 21 pages, 14 figure

Asymptotically maximal families of hypersurfaces in toric varieties

A real algebraic variety is maximal (with respect to the Smith-Thom inequality) if the sum of the Betti numbers (with $\mathbb{Z}_2$ coefficients) of the real part of the variety is equal to the sum of Betti numbers of its complex part. We prove that there exist polytopes that are not Newton polytopes of any maximal hypersurface in the corresponding toric variety. On the other hand we show that for any polytope $\Delta$ there are families of hypersurfaces with the Newton polytopes $(\lambda\Delta)_{\lambda \in \mathbb{N}}$ that are asymptotically maximal when $\lambda$ tends to infinity. We also show that these results generalize to complete intersections.Comment: 18 pages, 1 figur

Lumped element kinetic inductance detectors maturity for space-borne instruments in the range between 80 and 180 GHz

This work intends to give the state-of-the-art of our knowledge of the performance of LEKIDs at millimetre wavelengths (from 80 to 180~GHz). We evaluate their optical sensitivity under typical background conditions and their interaction with ionising particles. Two LEKID arrays, originally designed for ground-based applications and composed of a few hundred pixels each, operate at a central frequency of 100, and 150~GHz ($\Delta \nu / \nu$ about 0.3). Their sensitivities have been characterised in the laboratory using a dedicated closed-circle 100~mK dilution cryostat and a sky simulator, allowing for the reproduction of realistic, space-like observation conditions. The impact of cosmic rays has been evaluated by exposing the LEKID arrays to alpha particles ($^{241}$Am) and X sources ($^{109}$Cd) with a readout sampling frequency similar to the ones used for Planck HFI (about 200~Hz), and also with a high resolution sampling level (up to 2~MHz) in order to better characterise and interpret the observed glitches. In parallel, we have developed an analytical model to rescale the results to what would be observed by such a LEKID array at the second Lagrangian point.Comment: 7 pages, 2 tables, 13 figure

Niobium Silicon alloys for Kinetic Inductance Detectors

We are studying the properties of Niobium Silicon amorphous alloys as a candidate material for the fabrication of highly sensitive Kinetic Inductance Detectors (KID), optimized for very low optical loads. As in the case of other composite materials, the NbSi properties can be changed by varying the relative amounts of its components. Using a NbSi film with T_c around 1 K we have been able to obtain the first NbSi resonators, observe an optical response and acquire a spectrum in the band 50 to 300 GHz. The data taken show that this material has very high kinetic inductance and normal state surface resistivity. These properties are ideal for the development of KID. More measurements are planned to further characterize the NbSi alloy and fully investigate its potential.Comment: Accepted for publication on Journal of Low Temperature Physics. Proceedings of the LTD15 conference (Caltech 2013

Identifying Solar Flare Precursors Using Time Series of SDO/HMI Images and SHARP Parameters

We present several methods towards construction of precursors, which show great promise towards early predictions, of solar flare events in this paper. A data pre-processing pipeline is built to extract useful data from multiple sources, Geostationary Operational Environmental Satellites (GOES) and Solar Dynamics Observatory (SDO)/Helioseismic and Magnetic Imager (HMI), to prepare inputs for machine learning algorithms. Two classification models are presented: classification of flares from quiet times for active regions and classification of strong versus weak flare events. We adopt deep learning algorithms to capture both the spatial and temporal information from HMI magnetogram data. Effective feature extraction and feature selection with raw magnetogram data using deep learning and statistical algorithms enable us to train classification models to achieve almost as good performance as using active region parameters provided in HMI/Space-Weather HMI-Active Region Patch (SHARP) data files. Case studies show a significant increase in the prediction score around 20 hours before strong solar flare events