Plasma Waves in Anisotropic Superconducting Films Below and Above the Plasma Frequency

We consider wave propagation inside an anisotropic superconducting film sandwiched between two semi-infinite non-conducting bounding dieletric media such that along the c-axis, perpendicular to the surfaces, there is a plasma frequency $\omega_p$ below the superconducting gap. Propagation is assumed to be parallel to the surfaces in the dielectric medium, where amplitudes decay exponentially.Below $\omega_p$, the amplitude also evanesces inside the film, and we retrieve the experimentally measured lower dispersion relation branch, $\omega \propto \sqrt{\beta}$, and the recently proposed higher frequency branch, $\omega \propto 1/\sqrt{\beta}$.Above $\omega_p$, propagation is of the guided wave type, i.e., a dispersive plane wave confined inside the film that reflects into the dielectric interfaces,and the modes are approximately described by $\omega \approx \omega_p \sqrt{ 1+ (\beta/\beta_0)^2}$, where $\beta_0$ is discussed here.Comment: 26 pages,4 figures.Submitte

Electrical noise properties in aging materials

The electric thermal noise has been measured in two aging materials, a colloidal suspension (Laponite) and a polymer (polycarbonate), presenting very slow relaxation towards equilibrium. The measurements have been performed during the transition from a fluid-like to a solid-like state for the gel and after a quench for the polymer. For both materials we have observed that the electric noise is characterized by a strong intermittency, which induces a large violation of the Fluctuation Dissipation Theorem (FDT) during the aging time, and may persist for several hours at low frequency. The statistics of these intermittent signals and their dependance on the quench speed for the polymer or on sample concentration for the gel are studied. The results are in a qualitative agreement with recent models of aging, that predict an intermittent dynamics.Comment: SPIE Proceeding Journa

Machine Learning Classification of SDSS Transient Survey Images

We show that multiple machine learning algorithms can match human performance in classifying transient imaging data from the Sloan Digital Sky Survey (SDSS) supernova survey into real objects and artefacts. This is a first step in any transient science pipeline and is currently still done by humans, but future surveys such as the Large Synoptic Survey Telescope (LSST) will necessitate fully machine-enabled solutions. Using features trained from eigenimage analysis (principal component analysis, PCA) of single-epoch g, r and i-difference images, we can reach a completeness (recall) of 96 per cent, while only incorrectly classifying at most 18 per cent of artefacts as real objects, corresponding to a precision (purity) of 84 per cent. In general, random forests performed best, followed by the k-nearest neighbour and the SkyNet artificial neural net algorithms, compared to other methods such as na\"ive Bayes and kernel support vector machine. Our results show that PCA-based machine learning can match human success levels and can naturally be extended by including multiple epochs of data, transient colours and host galaxy information which should allow for significant further improvements, especially at low signal-to-noise.Comment: 14 pages, 8 figures. In this version extremely minor adjustments to the paper were made - e.g. Figure 5 is now easier to view in greyscal

Effect of the boundary condition on the vortex patterns in mesoscopic three-dimensional superconductors - disk and sphere

The vortex state of mesoscopic three-dimensional superconductors is determined using a minimization procedure of the Ginzburg-Landau free energy. We obtain the vortex pattern for a mesoscopic superconducting sphere and find that vortex lines are naturally bent and are closest to each other at the equatorial plane. For a superconducting disk with finite height, and under an applied magnetic field perpendicular to its major surface, we find that our method gives results consistent with previous calculations. The matching fields, the magnetization and $H_{c3}$, are obtained for models that differ according to their boundary properties. A change of the Ginzburg-Landau parameters near the surface can substantially enhance $H_{c3}$ as shown here.Comment: 7 pages, 4 figures (low resolution

On the collapse pressure of armored bubbles and drops

International audienceDrops and bubbles wrapped in dense monolayers of hydrophobic particles are known to sustain a significant decrease of their internal pressure. Through dedicated experiments we investigate the collapse behavior of such armored water drops as a function of the particle-to-drop size ratio in the range 0.02-0.2. We show that this parameter controls the behavior of the armor during the deflation: at small size ratios the drop shrinkage proceeds through the soft crumpling of the monolayer, at intermediate ratios the drop becomes faceted, and for the largest studied ratios the armor behaves like a granular arch. The results show that each of the three morphological regimes is characterized by an increasing magnitude of the collapse pressure. This increase is qualitatively modeled thanks to a mechanism involving out-of-plane deformations and particle disentanglement in the armor

Observation of transition from escape dynamics to underdamped phase diffusion in a Josephson junction

We have investigated the dynamics of underdamped Josephson junctions. In addition to the usual crossover between macroscopic quantum tunnelling and thermally activated (TA) behaviour we observe in our samples with relatively small Josephson coupling E_J, for the first time, the transition from TA behaviour to underdamped phase diffusion. Above the crossover temperature the threshold for switching into the finite voltage state becomes extremely sharp. We propose a (T,E_J) phase-diagram with various regimes and show that for a proper description of it dissipation and level quantization in a metastable well are crucial.Comment: 4 pages, 3 figure

Superconducting Qubits Coupled to Nanoelectromechanical Resonators: An Architecture for Solid-State Quantum Information Processing

We describe the design for a scalable, solid-state quantum-information-processing architecture based on the integration of GHz-frequency nanomechanical resonators with Josephson tunnel junctions, which has the potential for demonstrating a variety of single- and multi-qubit operations critical to quantum computation. The computational qubits are eigenstates of large-area, current-biased Josephson junctions, manipulated and measured using strobed external circuitry. Two or more of these phase qubits are capacitively coupled to a high-quality-factor piezoelectric nanoelectromechanical disk resonator, which forms the backbone of our architecture, and which enables coherent coupling of the qubits. The integrated system is analogous to one or more few-level atoms (the Josephson junction qubits) in an electromagnetic cavity (the nanomechanical resonator). However, unlike existing approaches using atoms in electromagnetic cavities, here we can individually tune the level spacing of the ``atoms'' and control their ``electromagnetic'' interaction strength. We show theoretically that quantum states prepared in a Josephson junction can be passed to the nanomechanical resonator and stored there, and then can be passed back to the original junction or transferred to another with high fidelity. The resonator can also be used to produce maximally entangled Bell states between a pair of Josephson junctions. Many such junction-resonator complexes can assembled in a hub-and-spoke layout, resulting in a large-scale quantum circuit. Our proposed architecture combines desirable features of both solid-state and cavity quantum electrodynamics approaches, and could make quantum information processing possible in a scalable, solid-state environment.Comment: 20 pages, 14 separate low-resolution jpeg figure