1,031 research outputs found
Soliton dual comb in crystalline microresonators
We present a novel compact dual-comb source based on a monolithic optical
crystalline MgF 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 âcoarse to fineâ ranking model where given a query we first compute a distribution over âcoarseâ 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
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