Response of YBCO/PCBO/YBCO ramp type Josephson junctions to near MM wave irradiation

A high Tc Josephson device for high frequency detection applications is being developed, consisting of an YBCO/PBCO/YBCO ramp type junction and a broad band log-periodic antenna. In this contribution we present the response of such a device to (near) mm wave irradiation. Shapiro steps have been observed up to very high voltage values - nearly 4 mV at 10 K, at the maximum of the radiation power. The modulation of the step amplitudes shows very good resemblence with the predictions from the Resistively Shunted Junction model

A mathematical model of the evaporation of a thin sessile liquid droplet : comparison between experiment and theory

A mathematical model for the quasi-steady diffusion-limited evaporation of a thin axisymmetric sessile droplet of liquid with a pinned contact line is formulated and solved. The model generalises the theoretical model proposed by Deegan et al. [Contact line deposits in an evaporating drop, Phys. Rev. E, 62 (2000) 756-765] to include the effect of evaporative cooling on the saturation concentration of vapour at the free surface of the droplet, and the dependence of the coefficient of diffusion of vapour in the atmosphere on the atmospheric pressure. The predictions of the model are in good qualitative, and in some cases also quantitative, agreement with recent experimental results. In particular, they capture the experimentally observed dependence of the total evaporation rate on the thermal conductivities of the liquid and the substrate, and on the atmospheric pressure

A Jackknife and Voting Classifier Approach to Feature Selection and Classification

With technological advances now allowing measurement of thousands of genes, proteins and metabolites, researchers are using this information to develop diagnostic and prognostic tests and discern the biological pathways underlying diseases. Often, an investigator’s objective is to develop a classification rule to predict group membership of unknown samples based on a small set of features and that could ultimately be used in a clinical setting. While common classification methods such as random forest and support vector machines are effective at separating groups, they do not directly translate into a clinically-applicable classification rule based on a small number of features.We present a simple feature selection and classification method for biomarker detection that is intuitively understandable and can be directly extended for application to a clinical setting. We first use a jackknife procedure to identify important features and then, for classification, we use voting classifiers which are simple and easy to implement. We compared our method to random forest and support vector machines using three benchmark cancer ‘omics datasets with different characteristics. We found our jackknife procedure and voting classifier to perform comparably to these two methods in terms of accuracy. Further, the jackknife procedure yielded stable feature sets. Voting classifiers in combination with a robust feature selection method such as our jackknife procedure offer an effective, simple and intuitive approach to feature selection and classification with a clear extension to clinical applications

Noise study of a high‐Tc Josephson junction under near‐millimeter‐wave irradiation

Noise studies of both the dc and ac Josephson effects have been performed on a high‐Tc ramp‐type Josephson junction irradiated at 176 GHz. Well‐established analytical results for noise in overdamped RSJs are used to model the measured I‐V characteristics, and their agreement is excellent. Noise‐rounded I‐V curves at the critical current and the first and second Shapiro steps under coherent 176 GHz radiation have been studied in detail at several temperatures and rf power levels. The noise temperatures inferred from these simulations are close to the physical temperatures. An increase of noise temperatures at high radiation power levels is a result of radiation heating, which could be due to a bolometric effect

Feedback cooling of a nanomechanical resonator

Cooled, low-loss nanomechanical resonators offer the prospect of directly observing the quantum dynamics of mesoscopic systems. However, the present state of the art requires cooling down to the milliKelvin regime in order to observe quantum effects. Here we present an active feedback strategy based on continuous observation of the resonator position for the purpose of obtaining these low temperatures. In addition, we apply this to an experimentally realizable configuration, where the position monitoring is carried out by a single-electron transistor. Our estimates indicate that with current technology this technique is likely to bring the required low temperatures within reach.Comment: 10 pages, RevTex4, 4 color eps figure

Improved perturbation theory in the vortex liquids state of type II superconductors

We develop an optimized perturbation theory for the Ginzburg - Landau description of thermal fluctuations effects in the vortex liquids. Unlike the high temperature expansion which is asymptotic, the optimized expansion is convergent. Radius of convergence on the lowest Landau level is $a_{T}=-3$ in 2D and $a_{T}=-5$ in 3D. It allows a systematic calculation of magnetization and specific heat contributions due to thermal fluctuations of vortices in strongly type II superconductors to a very high precision. The results are in good agreement with existing Monte Carlo simulations and experiments. Limitations of various nonperturbative and phenomenological approaches are noted. In particular we show that there is no exact intersection point of the magnetization curves both in 2D and 3D.Comment: 24 pages, 9 figure

Two-Dimensional Vortex Lattice Melting

We report on a Monte-Carlo study of two-dimensional Ginzburg-Landau superconductors in a magnetic field which finds clear evidence for a first-order phase transition characterized by broken translational symmetry of the superfluid density. A key aspect of our study is the introduction of a quantity proportional to the Fourier transform of the superfluid density which can be sampled efficiently in Landau gauge Monte-Carlo simulations and which satisfies a useful sum rule. We estimate the latent heat per vortex of the melting transition to be $\sim 0.38 k_B T_M$ where $T_M$ is the melting temperature.Comment: 10 pages (4 figures available on request), RevTex 3.0, IUCM93-00

Detecting the Most Distant (z>7) Objects with ALMA

Detecting and studying objects at the highest redshifts, out to the end of Cosmic Reionization at z>7, is clearly a key science goal of ALMA. ALMA will in principle be able to detect objects in this redshift range both from high-J (J>7) CO transitions and emission from ionized carbon, [CII], which is one of the main cooling lines of the ISM. ALMA will even be able to resolve this emission for individual targets, which will be one of the few ways to determine dynamical masses for systems in the Epoch of Reionization. We discuss some of the current problems regarding the detection and characterization of objects at high redshifts and how ALMA will eliminate most (but not all) of them.Comment: to appear in Astrophysics and Space Science, "Science with ALMA: a new era for Astrophysics", ed. R. Bachille

A comparison of statistical machine learning methods in heartbeat detection and classification

In health care, patients with heart problems require quick responsiveness in a clinical setting or in the operating theatre. Towards that end, automated classification of heartbeats is vital as some heartbeat irregularities are time consuming to detect. Therefore, analysis of electro-cardiogram (ECG) signals is an active area of research. The methods proposed in the literature depend on the structure of a heartbeat cycle. In this paper, we use interval and amplitude based features together with a few samples from the ECG signal as a feature vector. We studied a variety of classification algorithms focused especially on a type of arrhythmia known as the ventricular ectopic fibrillation (VEB). We compare the performance of the classifiers against algorithms proposed in the literature and make recommendations regarding features, sampling rate, and choice of the classifier to apply in a real-time clinical setting. The extensive study is based on the MIT-BIH arrhythmia database. Our main contribution is the evaluation of existing classifiers over a range sampling rates, recommendation of a detection methodology to employ in a practical setting, and extend the notion of a mixture of experts to a larger class of algorithms