Search results for "deviation"
showing 10 items of 367 documents
Prediction of chromatographic parameters for some anilines by molecular connectivity
1995
The possible relation existing between RF values obtained by thin-layer chromatography for a group of anilines with connectivity indices proposed by Kier and Hall has been studied. Using multivariable regression the corresponding connectivity functions, selected for their respective correlation coefficients, standard deviations, Snedecor's F and Student's t were obtained. Regression analysis of the connectivity functions gives a correct prediction of the experimental elution sequence for this group of substances on silica gel stationary phases and various mobile phases of different polarity. The corresponding random and stability studies of the different prediction models selected were carr…
Recovering Quantum Properties of Continuous-Variable States in the Presence of Measurement Errors.
2016
We present two results which combined enable one to reliably detect multimode, multipartite entanglement in the presence of measurement errors. The first result leads to a method to compute the best (approximated) physical covariance matrix given a measured non-physical one. The other result states that a widely used entanglement condition is a consequence of negativity of partial transposition. Our approach can quickly verify entanglement of experimentally obtained multipartite states, which is demonstrated on several realistic examples. Compared to existing detection schemes, ours is very simple and efficient. In particular, it does not require any complicated optimizations.
Using neural networks for (13)c NMR chemical shift prediction-comparison with traditional methods.
2002
Abstract Interpretation of 13 C chemical shifts is essential for structure elucidation of organic molecules by NMR. In this article, we present an improved neural network approach and compare its performance to that of commonly used approaches. Specifically, our recently proposed neural network ( J. Chem. Inf. Comput. Sci. 2000, 40, 1169–1176) is improved by introducing an extended hybrid numerical description of the carbon atom environment, resulting in a standard deviation (std. dev.) of 2.4 ppm for an independent test data set of ∼42,500 carbons. Thus, this neural network allows fast and accurate 13 C NMR chemical shift prediction without the necessity of access to molecule or fragment d…
Measurement of ϒ(1S) Elliptic Flow at Forward Rapidity in Pb-Pb Collisions at sNN=5.02 TeV
2019
The first measurement of the Υ(1S) elliptic flow coefficient (v2) is performed at forward rapidity (2.5 < y < 4) in Pb–Pb collisions at √sNN=5.02 TeV with the ALICE detector at the LHC. The results are obtained with the scalar product method and are reported as a function of transverse momentum (pT) up to 15 GeV/c in the 5%–60% centrality interval. The measured Υ(1S)v2 is consistent with 0 and with the small positive values predicted by transport models within uncertainties. The v2 coefficient in 2 < pT < 15 GeV/c is lower than that of inclusive J/ψ mesons in the same pT interval by 2.6 standard deviations. These results, combined with earlier suppression measurements, are in agreement with…
Witnessing nonclassicality through large deviations in quantum optics
2019
Non-classical correlations in quantum optics as resources for quantum computation are important in the quest for highly-specialized quantum devices. The standard way to investigate such effects relies on either the characterization of the inherent features of sources and circuits or the study of the output radiation of a given optical setup. The latter approach demands an extensive description of the output fields, but often overlooks the dynamics of the sources. Conversely, the former discards most of the information about the single trajectories, which are observed in experimental measurements. In this work we provide a natural link between the two frameworks by exploiting the thermodynam…
Lattice calculation of the hadronic leading order contribution to the muon g − 2
2019
The European physical journal / Web of Conferences Web of Conferences : proceedings proceedings 234, 01016 - (2020). doi:10.1051/epjconf/202023401016
Test of the MODIS Land Surface Temperature and Emissivity Separation Algorithm With Ground Measurements Over a Rice Paddy
2016
The Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) and emissivity separation (MODTES) algorithm is the basis of the MOD21 product, which provides 1-km LSTs and emissivities for bands 29 (8.55 μm), 31 (11 μm), and 32 (12 μm). The MODTES algorithm uses the TES method with the water vapor scaling (WVS) method for refined atmospheric correction. The performance of the MODTES algorithm was tested with a set of MODIS data concurrent with ground LST and emissivity measurements. The test site is a large area of homogeneous full-cover rice crops (graybody), with high atmospheric water vapor. The data included LSTs measured along transects with multiple calibrate…
Estimation of sea surface temperature from SEVIRI data: algorithm testing and comparison with AVHRR products
2006
Three surface temperature (ST) algorithms for Spinning Enhanced Visible and InfraRed Imager (SEVIRI) data are developed and tested. A general split window algorithm for ST estimation, a sea surface temperature (SST) algorithm and a nonlinear algorithm (NLSST) developed for SEVIRI data. The test was carried out by comparing SEVIRI data with two types of data: (a) in situ and (b) obtained with the NLSST algorithm applied to Advanced Very High Resolution Radiometer (AVHRR). The field campaign was carried out over sea using a thermal radiometer. The algorithms were applied to SEVIRI images in coincidence with the field campaign and the results show an rms error lower than 0.7 K. The comparison …
Analysis of random walks on a hexagonal lattice
2019
We consider a discrete-time random walk on the nodes of an unbounded hexagonal lattice. We determine the probability generating functions, the transition probabilities and the relevant moments. The convergence of the stochastic process to a 2-dimensional Brownian motion is also discussed. Furthermore, we obtain some results on its asymptotic behavior making use of large deviation theory. Finally, we investigate the first-passage-time problem of the random walk through a vertical straight-line. Under suitable symmetry assumptions we are able to determine the first-passage-time probabilities in a closed form, which deserve interest in applied fields.
Rotational CARS thermometry at high temperature (1800 K) and high pressure (0.1-1.55 MPa)
2007
International audience; Dual-broadband rotational CARS (DB-RCARS) thermometry has been investigated at high temperature and high pressure. Single-shot measurements were performed at 1800 K, in air and nitrogen at pressures up to 1.55 MPa and in oxygen at pressures up to 0.5 MPa. For all conditions, the resonant signal contribution to the spectra clearly dominated over the non-resonant one, implying the high potential for DB-RCARS for temperature and concentration measurements also at the high temperatures and pressures used in the present investigation. The relative standard deviation was generally similar to 2% for single-shot data at pressures from 0.5 to 1.55 MPa. At the investigated tem…