Soliton dual comb in crystalline microresonators

We present a novel compact dual-comb source based on a monolithic optical crystalline MgF$_2$ multi-resonator stack. The coherent soliton combs generated in two microresonators of the stack with the repetition rate of 12.1 GHz and difference of 1.62 MHz provided after heterodyning a 300 MHz wide radio-frequency comb. Analogous system can be used for dual-comb spectroscopy, coherent LIDAR applications and massively parallel optical communications.Comment: 5 pages, 5 figure

A latent variable ranking model for content-based retrieval

34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012. ProceedingsSince their introduction, ranking SVM models [11] have become a powerful tool for training content-based retrieval systems. All we need for training a model are retrieval examples in the form of triplet constraints, i.e. examples specifying that relative to some query, a database item a should be ranked higher than database item b. These types of constraints could be obtained from feedback of users of the retrieval system. Most previous ranking models learn either a global combination of elementary similarity functions or a combination defined with respect to a single database item. Instead, we propose a “coarse to fine” ranking model where given a query we first compute a distribution over “coarse” classes and then use the linear combination that has been optimized for queries of that class. These coarse classes are hidden and need to be induced by the training algorithm. We propose a latent variable ranking model that induces both the latent classes and the weights of the linear combination for each class from ranking triplets. Our experiments over two large image datasets and a text retrieval dataset show the advantages of our model over learning a global combination as well as a combination for each test point (i.e. transductive setting). Furthermore, compared to the transductive approach our model has a clear computational advantages since it does not need to be retrained for each test query.Spanish Ministry of Science and Innovation (JCI-2009-04240)EU PASCAL2 Network of Excellence (FP7-ICT-216886

Theory of superfast fronts of impact ionization in semiconductor structures

We present an analytical theory for impact ionization fronts in reversely biased p^{+}-n-n^{+} structures. The front propagates into a depleted n base with a velocity that exceeds the saturated drift velocity. The front passage generates a dense electron-hole plasma and in this way switches the structure from low to high conductivity. For a planar front we determine the concentration of the generated plasma, the maximum electric field, the front width and the voltage over the n base as functions of front velocity and doping of the n base. Theory takes into account that drift velocities and impact ionization coefficients differ between electrons and holes, and it makes quantitative predictions for any semiconductor material possible.Comment: 18 pagers, 10 figure

Statistical Mechanics of Semi-Supervised Clustering in Sparse Graphs

We theoretically study semi-supervised clustering in sparse graphs in the presence of pairwise constraints on the cluster assignments of nodes. We focus on bi-cluster graphs, and study the impact of semi-supervision for varying constraint density and overlap between the clusters. Recent results for unsupervised clustering in sparse graphs indicate that there is a critical ratio of within-cluster and between-cluster connectivities below which clusters cannot be recovered with better than random accuracy. The goal of this paper is to examine the impact of pairwise constraints on the clustering accuracy. Our results suggests that the addition of constraints does not provide automatic improvement over the unsupervised case. When the density of the constraints is sufficiently small, their only impact is to shift the detection threshold while preserving the criticality. Conversely, if the density of (hard) constraints is above the percolation threshold, the criticality is suppressed and the detection threshold disappears.Comment: 8 pages, 4 figure

An experimental study of acoustic responses on the injection of supercritical CO2 into sandstones from the Otway Basin

Quantitative knowledge of the acoustic response of rock from an injection site on supercritical CO2 (scCO2) saturation is crucial for understanding the feasibility of time-lapse seismic monitoring of CO2 plume migration. A suite of shaley sandstones from the injection interval of the CRC-2 well, Otway Basin, Australia is tested to reveal the effects of supercritical CO2 injection on acoustic responses. CO2 is first injected into dry samples, flushed out with brine and then injected again into brine-saturated samples. Such a suite of experiments allows us to obtain acoustic velocities of the samples for a wide range of CO2/brine saturations from 0% to 100%. On injection of scCO2 into brine-saturated samples, the rocks exhibit a decrease of compressional velocities by about 7% with the increase of CO2 saturation from 0% to a maximum of about 50%. Anisotropy of the shaley sandstones from the Otway Basin must be taken into account as the difference in the velocities normal and parallel to bedding is comparable with the perturbation due to CO2 injection and the samples of different orientations exhibit transition from Gassmann-Hill to Gassmann-Wood bound at different scCO2 saturations. Changes of the dry samples before and after the CO2 injection (if any) are not traceable by acoustic methods