Search results for "Uncertainty estimate"

showing 3 items of 3 documents

Recent results on the meson and baryon spectrum from lattice QCD

2017

Recent lattice results on the meson and baryon spectrum with a focus on the determination of hadronic resonance masses and widths using a combined basis of single-hadron and hadron-hadron interpolating fields are reviewed. These mostly exploratory calculations differ from traditional lattice QCD spectrum calculations for states stable under QCD, where calculations with a full uncertainty estimate are already routinely performed. Progress and challenges in these calculations are highlighted.

Particle physicsMesonQC1-999High Energy Physics::LatticeLattice field theoryHadronNuclear TheoryFOS: Physical sciences01 natural sciencesUncertainty estimateHigh Energy Physics - LatticeHigh Energy Physics - Phenomenology (hep-ph)Lattice (order)0103 physical sciences010306 general physicsNuclear ExperimentPhysicsQuantum chromodynamics010308 nuclear & particles physicsPhysicsHigh Energy Physics::PhenomenologyHigh Energy Physics - Lattice (hep-lat)Lattice QCDBaryonHigh Energy Physics - PhenomenologyHigh Energy Physics::Experiment
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Gaussian processes retrieval of crop traits in Google Earth Engine based on Sentinel-2 top-of-atmosphere data.

2022

The unprecedented availability of optical satellite data in cloud-based computing platforms, such as Google Earth Engine (GEE), opens new possibilities to develop crop trait retrieval models from the local to the planetary scale. Hybrid retrieval models are of interest to run in these platforms as they combine the advantages of physically-based radiative transfer models (RTM) with the flexibility of machine learning regression algorithms. Previous research with GEE primarily relied on processing bottom-of-atmosphere (BOA) reflectance data, which requires atmospheric correction. In the present study, we implemented hybrid models directly into GEE for processing Sentinel-2 (S2) Level-1C (L1C)…

sentinel-2active learning (AL)Soil ScienceGeologyUNESCO::CIENCIAS TECNOLÓGICASUncertainty estimategaussian processes (GP)google earth engineBiophysical and biochemical crop traiteuclidean distance-based diversity (EBD)top-of-atmosphere reflectancehybrid retrieval methodsHybrid retrieval methoduncertainty estimatesbiophysical and biochemical crop traitsatmosphere radiative transfer modelComputers in Earth SciencesRemote sensing of environment
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EPPS16 - First nuclear PDFs to include LHC data

2017

We present results of our recent EPPS16 global analysis of NLO nuclear parton distribution functions (nPDFs). For the first time, dijet and heavy gauge boson production data from LHC proton-lead collisions have been included in a global fit. Especially, the CMS dijets play an important role in constraining the nuclear effects in gluon distributions. With the inclusion of also neutrino-nucleus deeply-inelastic scattering and pion-nucleus Drell-Yan data and a proper treatment of isospin-corrected data, we were able to free the flavor dependence of the valence and sea quark nuclear modifications for the first time. This gives us less biased, yet larger, flavor by flavor uncertainty estimates. …

Uncertainty estimates Uncertainty analysisHigh Energy Physics::LatticeLead collisionsNuclear TheoryHigh Energy Physics::PhenomenologyFOS: Physical sciencesNuclear parton distribution functions114 Physical sciencesHigh Energy Physics - ExperimentHigh Energy Physics - PhenomenologyHigh Energy Physics - Experiment (hep-ex)High Energy Physics - Phenomenology (hep-ph)Production dataHigh Energy Physics::ExperimentNuclear modificationNuclear ExperimentNuclear effectsBosonsDistribution functionsGlobal analysisInelastic scattering Deeply inelastic scatterings
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