3,839 research outputs found
Common pulse retrieval algorithm: a fast and universal method to retrieve ultrashort pulses
We present a common pulse retrieval algorithm (COPRA) that can be used for a
broad category of ultrashort laser pulse measurement schemes including
frequency-resolved optical gating (FROG), interferometric FROG, dispersion
scan, time domain ptychography, and pulse shaper assisted techniques such as
multiphoton intrapulse interference phase scan (MIIPS). We demonstrate its
properties in comprehensive numerical tests and show that it is fast, reliable
and accurate in the presence of Gaussian noise. For FROG it outperforms
retrieval algorithms based on generalized projections and ptychography.
Furthermore, we discuss the pulse retrieval problem as a nonlinear
least-squares problem and demonstrate the importance of obtaining a
least-squares solution for noisy data. These results improve and extend the
possibilities of numerical pulse retrieval. COPRA is faster and provides more
accurate results in comparison to existing retrieval algorithms. Furthermore,
it enables full pulse retrieval from measurements for which no retrieval
algorithm was known before, e.g., MIIPS measurements
EU accession and Poland's external trade policy
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On statistical approaches to generate Level 3 products from satellite remote sensing retrievals
Satellite remote sensing of trace gases such as carbon dioxide (CO) has
increased our ability to observe and understand Earth's climate. However, these
remote sensing data, specifically~Level 2 retrievals, tend to be irregular in
space and time, and hence, spatio-temporal prediction is required to infer
values at any location and time point. Such inferences are not only required to
answer important questions about our climate, but they are also needed for
validating the satellite instrument, since Level 2 retrievals are generally not
co-located with ground-based remote sensing instruments. Here, we discuss
statistical approaches to construct Level 3 products from Level 2 retrievals,
placing particular emphasis on the strengths and potential pitfalls when using
statistical prediction in this context. Following this discussion, we use a
spatio-temporal statistical modelling framework known as fixed rank kriging
(FRK) to obtain global predictions and prediction standard errors of
column-averaged carbon dioxide based on Version 7r and Version 8r retrievals
from the Orbiting Carbon Observatory-2 (OCO-2) satellite. The FRK predictions
allow us to validate statistically the Level 2 retrievals globally even though
the data are at locations and at time points that do not coincide with
validation data. Importantly, the validation takes into account the prediction
uncertainty, which is dependent both on the temporally-varying density of
observations around the ground-based measurement sites and on the
spatio-temporal high-frequency components of the trace gas field that are not
explicitly modelled. Here, for validation of remotely-sensed CO data, we
use observations from the Total Carbon Column Observing Network. We demonstrate
that the resulting FRK product based on Version 8r compares better with TCCON
data than that based on Version 7r.Comment: 28 pages, 10 figures, 4 table
The Belgian repository of fundamental atomic data and stellar spectra (BRASS). I. Cross-matching atomic databases of astrophysical interest
Fundamental atomic parameters, such as oscillator strengths, play a key role
in modelling and understanding the chemical composition of stars in the
universe. Despite the significant work underway to produce these parameters for
many astrophysically important ions, uncertainties in these parameters remain
large and can propagate throughout the entire field of astronomy. The Belgian
repository of fundamental atomic data and stellar spectra (BRASS) aims to
provide the largest systematic and homogeneous quality assessment of atomic
data to date in terms of wavelength, atomic and stellar parameter coverage. To
prepare for it, we first compiled multiple literature occurrences of many
individual atomic transitions, from several atomic databases of astrophysical
interest, and assessed their agreement. Several atomic repositories were
searched and their data retrieved and formatted in a consistent manner. Data
entries from all repositories were cross-matched against our initial BRASS
atomic line list to find multiple occurrences of the same transition. Where
possible we used a non-parametric cross-match depending only on electronic
configurations and total angular momentum values. We also checked for duplicate
entries of the same physical transition, within each retrieved repository,
using the non-parametric cross-match. We report the cross-matched transitions
for each repository and compare their fundamental atomic parameters. We find
differences in log(gf) values of up to 2 dex or more. We also find and report
that ~2% of our line list and Vienna Atomic Line Database retrievals are
composed of duplicate transitions. Finally we provide a number of examples of
atomic spectral lines with different log(gf) values, and discuss the impact of
these uncertain log(gf) values on quantitative spectroscopy. All cross-matched
atomic data and duplicate transitions are available to download at
brass.sdf.org.Comment: 18 pages, 12 figures, 9 tables. Accepted for publication in A&
Manipulating cues in involuntary autobiographical memory: verbal cues are more effective than pictorial cues
In two experiments, pictorial cues were compared with their verbal labels to assess their effectiveness in eliciting involuntary autobiographical memories. Cues were relatively complex in Experiment 1 (e.g., relaxing on a beach) and simple objects in Experiment 2 (e.g., a ball). In both experiments, participants went through a vigilance task in which they were presented with frequent nontarget and rare target visual stimuli. Pictures or their corresponding verbal labels were also displayed on both target and nontarget stimuli, but participants were told that these were irrelevant to the task. They were asked to interrupt the vigilance task whenever they became aware of task-unrelated mental contents and to report them. In both experiments, more involuntary memories were elicited in the verbal cue condition, rather than in the pictorial cue condition. This result is discussed in relation to previous work that highlighted the greater effectiveness of verbal cues in memory tasks
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Encoding Sequential Information in Vector Space Models of Semantics: Comparing Holographic Reduced Representation and Random Permutation
Encoding information about the order in which words typically appear has been shown to improve the performance of high-dimensional semantic space models. This requires an encoding operation capable of binding together vectors in an order-sensitive way, and efficient enough to scale to large text corpora. Although both circular convolution and random permutations have been enlisted for this purpose in semantic models, these operations have never been systematically compared. In Experiment 1 we compare their storage capacity and probability of correct retrieval; in Experiments 2 and 3 we compare their performance on semantic tasks when integrated into existing models. We conclude that random permutations are a scalable alternative to circular convolution with several desirable properties
Multiple Retrieval Models and Regression Models for Prior Art Search
This paper presents the system called PATATRAS (PATent and Article Tracking,
Retrieval and AnalysiS) realized for the IP track of CLEF 2009. Our approach
presents three main characteristics: 1. The usage of multiple retrieval models
(KL, Okapi) and term index definitions (lemma, phrase, concept) for the three
languages considered in the present track (English, French, German) producing
ten different sets of ranked results. 2. The merging of the different results
based on multiple regression models using an additional validation set created
from the patent collection. 3. The exploitation of patent metadata and of the
citation structures for creating restricted initial working sets of patents and
for producing a final re-ranking regression model. As we exploit specific
metadata of the patent documents and the citation relations only at the
creation of initial working sets and during the final post ranking step, our
architecture remains generic and easy to extend
Peer to Peer Information Retrieval: An Overview
Peer-to-peer technology is widely used for file sharing. In the past decade a number of prototype peer-to-peer information retrieval systems have been developed. Unfortunately, none of these have seen widespread real- world adoption and thus, in contrast with file sharing, information retrieval is still dominated by centralised solutions. In this paper we provide an overview of the key challenges for peer-to-peer information retrieval and the work done so far. We want to stimulate and inspire further research to overcome these challenges. This will open the door to the development and large-scale deployment of real-world peer-to-peer information retrieval systems that rival existing centralised client-server solutions in terms of scalability, performance, user satisfaction and freedom
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