Search results for "Data analysis."

showing 10 items of 377 documents

Gravitational-Wave Astronomy: Modelling, detection, and data analysis

2017

La detección directa de la primera señal de ondas gravitatorias, el 14 de Septiembre de 2015, puede considerarse uno de los mayores hitos científicos de todos los tiempos. No solo porque supone la confirmación de la última de las predicciones de la Teoría de la Relatividad General de Albert Einstein, sino porque anticipa una autentica revolución en el campo de las astrofísica, comparable a la producida con la invención del telescopio por Galileo Galilei en 1609. Este descubrimiento ha inaugurado un nuevo tipo de astronomía, la astronomía de ondas gravitatorias. Se abre así una nueva ventana al universo que permitirá el estudio de procesos físicos producidos en regiones no accesibles al espe…

ondas gravitatoriasastrofísicadata analysisUNESCO::ASTRONOMÍA Y ASTROFÍSICAastrofísica relativista:ASTRONOMÍA Y ASTROFÍSICA [UNESCO]gravitacion
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$\Lambda_c^{\pm}$ production in pp collisions with a new fragmentation function

2020

Physical review / D D 101(11), 114021 (2020). doi:10.1103/PhysRevD.101.114021

p p: scatteringLambda/c+: productiondata analysis methodPhysics::Instrumentation and Detectors14.40.NdBELLEannihilation [electron positron]electron positron: annihilationfragmentation [charm]530fragmentation functionquarkALICEfragmentationscattering [p p]ddc:530charm: fragmentationStrong InteractionsNuclear Experimentproduction [Lambda/c+]OPALCMSviolation [universality]High Energy Physics::PhenomenologytensionLHC-B12.39.StHigh Energy Physics - Phenomenology12.38.BxCERN LHC Coll[PHYS.HPHE]Physics [physics]/High Energy Physics - Phenomenology [hep-ph]High Energy Physics::Experimentuniversality: violation13.85.Ni
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Comparing proton momentum distributions in A = 2 and 3 nuclei via 2H 3H and 3He (e,e′p) measurements

2019

We report the first measurement of the $(e,e'p)$ reaction cross-section ratios for Helium-3 ($^3$He), Tritium ($^3$H), and Deuterium ($d$). The measurement covered a missing momentum range of $40 \le p_{miss} \le 550$ MeV$/c$, at large momentum transfer ($\langle Q^2 \rangle \approx 1.9$ (GeV$/c$)$^2$) and $x_B>1$, which minimized contributions from non quasi-elastic (QE) reaction mechanisms. The data is compared with plane-wave impulse approximation (PWIA) calculations using realistic spectral functions and momentum distributions. The measured and PWIA-calculated cross-section ratios for $^3$He$/d$ and $^3$H$/d$ extend to just above the typical nucleon Fermi-momentum ($k_F \approx 250$ …

production [pi]Nuclear and High Energy Physicsdata analysis methodPhotonNuclear TheoryNuclear TheoryinterferenceFOS: Physical sciencesElectronImpulse (physics)Inelastic scattering01 natural sciencesxperimental results | Jefferson Lab | electron p: scattering | parity: violation | inelastic scattering | structure function | interference | photon | Z0 | pi: production | spin: asymmetry | data analysis methodNuclear Theory (nucl-th)structure function0103 physical sciencesZ0Nuclear Experiment (nucl-ex)010306 general physicsNuclear ExperimentNuclear ExperimentPhysics010308 nuclear & particles physicsMomentum transferphotoninelastic scatteringscattering [electron p]Eikonal approximationNATURAL SCIENCES. Physics.lcsh:QC1-999PRIRODNE ZNANOSTI. Fizika.Deuteriumxperimental resultsHigh Energy Physics::Experimentviolation [parity]Atomic physicsNucleonasymmetry [spin]lcsh:PhysicsJefferson LabPhysics Letters B
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Deep-learning based reconstruction of the shower maximum X max using the water-Cherenkov detectors of the Pierre Auger Observatory

2021

The atmospheric depth of the air shower maximum $X_{\mathrm{max}}$ is an observable commonly used for the determination of the nuclear mass composition of ultra-high energy cosmic rays. Direct measurements of $X_{\mathrm{max}}$ are performed using observations of the longitudinal shower development with fluorescence telescopes. At the same time, several methods have been proposed for an indirect estimation of $X_{\mathrm{max}}$ from the characteristics of the shower particles registered with surface detector arrays. In this paper, we present a deep neural network (DNN) for the estimation of $X_{\mathrm{max}}$. The reconstruction relies on the signals induced by shower particles in the groun…

showers: energylongitudinal [showers]interaction: modelPhysics::Instrumentation and DetectorsAstronomyCalibration and fitting methods; Cluster finding; Data analysis; Large detector systems for particle and astroparticle physics; Particle identification methods; Pattern recognition01 natural sciencesHigh Energy Physics - ExperimentAugerHigh Energy Physics - Experiment (hep-ex)Particle identification methodscluster findingsurface [detector]ObservatoryLarge detector systemsInstrumentationMathematical PhysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)astro-ph.HEPhysicsPattern recognition cluster finding calibration and fitting methodsPhysicsSettore FIS/01 - Fisica Sperimentalemodel [interaction]DetectorAstrophysics::Instrumentation and Methods for AstrophysicsData analysicalibration and fitting methodsenergy [showers]AugerobservatoryPattern recognition cluster finding calibration and fitting methodastroparticle physicsAstrophysics - Instrumentation and Methods for AstrophysicsAstrophysics - High Energy Astrophysical Phenomenaatmosphere [showers]airneural networkAstrophysics::High Energy Astrophysical PhenomenaUHE [cosmic radiation]Data analysisFOS: Physical sciences610Cosmic raydetector: fluorescencePattern recognition0103 physical sciencesddc:530High Energy Physicsddc:610[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]cosmic radiation: UHEstructureparticle physicsnetwork: performance010306 general physicsInstrumentation and Methods for Astrophysics (astro-ph.IM)Ciencias ExactasCherenkov radiationfluorescence [detector]Pierre Auger ObservatoryCalibration and fitting methodsmass spectrum [nucleus]showers: atmospheredetector: surfacehep-ex010308 nuclear & particles physicsLarge detector systems for particle and astroparticle physicsCluster findingFísicaresolutioncalibrationComputational physicsperformance [network]Cherenkov counterAir showerLarge detector systems for particle and astroparticle physicExperimental High Energy PhysicsHigh Energy Physics::Experimentnucleus: mass spectrumshowers: longitudinalRAIOS CÓSMICOSEnergy (signal processing)astro-ph.IM
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Statistical inference for eye movement sequences using spatial and spatio-temporal point processes

2017

Eye tracking is a widely used method for recording eye movements, which are important indicators of ongoing cognitive processes during the viewing of a target stimulus. Despite the variety of applications, the analyses of eye movement data have been lacking of methods that could take both the spatial and temporal information into account. So far, most of the analyses are based on strongly aggregated measures, because eye movement data are considered to be complex due to their richness and large variation between and within the individuals. Therefore, the eye movement methodology needs new statistical tools in order to take full advantage of the data. This dissertation is among the first stud…

silmänliikkeetdatapisteprosessitspatio-temporal datamittausdata analysistilastomenetelmättrackingeye movementpoint processesstokastiset prosessit
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Detecting clusters in spatially correlated waveforms

2017

Seismic networks often record signals characterized by similar shapes that provide important information according to their geographic positions. We propose an approach to identify homogeneous clusters of seismic waves, combining analysis of waveforms with metadata and spectrogram information. In waveforms clustering, cross-correlation measures between signals may presents some limitations, so we refer to more recent contributes relating data-depth based clustering analysis. The mechanism for alignment is also an important topic of the analysis: warping (or aligning) procedures identify nuisance effects in phase variation, that, if ignored, may result in a possible loss of information and t…

spatial clusteringfast fourier transform.Seismic waveformfunctional data analysiSettore SECS-S/01 - StatisticaSeismic waveforms; spatial clustering; functional data analysis; fast fourier transform.
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An Examination of Tourist Arrivals Dynamics Using Short-Term Time Series Data: A Space—Time Cluster Approach

2013

The purpose of this study is to examine the development of Italian tourist areas ( circoscrizioni turistiche) through a cluster analysis of short time series. The technique is an adaptation of the functional data analysis approach developed by Abraham et al (2003), which combines spline interpolation with k-means clustering. The findings indicate the presence of two patterns (increasing and stable) averagely characterizing groups of territories. Moreover, tests of spatial contiguity suggest the presence of ‘space–time clusters’; that is, areas in the same ‘time cluster’ are also spatially contiguous. These findings appear to be more robust in particular for those series characterized by an…

spline interpolationjoin count testSeries (mathematics)Computer scienceSpace timeGeography Planning and Developmentk-means clusteringcluster analysis; short time series; spline interpolation; K-means; join count test; Italian tourist areasFunctional data analysisjel:C21jel:C22jel:C38jel:C14jel:L83K-meanshort time serieContiguity (probability theory)Tourism Leisure and Hospitality Managementcluster analysiItalian tourist areasEconometricsCluster (physics)Settore SECS-S/05 - Statistica SocialeSpline interpolationCluster analysisTourism Economics
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The ALHAMBRA survey: evolution of galaxy clustering since z∼1

2014

We study the clustering of galaxies as function of luminosity and redshift in the range $0.35 < z < 1.25$ using data from the Advanced Large Homogeneous Area Medium Band Redshift Astronomical (ALHAMBRA) survey. The ALHAMBRA data used in this work cover $2.38 \mathrm{deg}^2$ in 7 independent fields, after applying a detailed angular selection mask, with accurate photometric redshifts, $��_z \lesssim 0.014 (1+z)$, down to $I_{\rm AB} < 24$. Given the depth of the survey, we select samples in $B$-band luminosity down to $L^{\rm th} \simeq 0.16 L^{*}$ at $z = 0.9$. We measure the real-space clustering using the projected correlation function, accounting for photometric redshifts uncert…

statistical [Methods]Cosmology and Nongalactic Astrophysics (astro-ph.CO)FOS: Physical sciencesAstrophysicsAstrophysics::Cosmology and Extragalactic AstrophysicsCorrelation function (astronomy)01 natural sciencesPhysical cosmologyLuminosityLarge-scale structure of Universe.0103 physical sciencesRange (statistics)distances and redshifts [Galaxies]Sample variance10. No inequalitydata analysis [Methods]observations [Cosmology]010303 astronomy & astrophysicsAstrophysics::Galaxy AstrophysicsPhysics010308 nuclear & particles physicsAstronomyAstronomy and AstrophysicsGalaxyRedshiftSpace and Planetary ScienceHaloAstrophysics - Cosmology and Nongalactic Astrophysics
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THE ALHAMBRA SURVEY: EVOLUTION OF GALAXY SPECTRAL SEGREGATION

2016

arXiv:1601.03668v1

statistical [Methods]Cosmology and Nongalactic Astrophysics (astro-ph.CO)Large-scale structure of universeFOS: Physical sciencesAstrophysicsAstrophysics::Cosmology and Extragalactic Astrophysics01 natural sciencesMethods statisticalGalaxies: distances and redshiftsMethods: data analysis0103 physical sciencesdistances and redshifts [Galaxies]observations [Cosmology]data analysis [Methods]010303 astronomy & astrophysicsMethods: statisticalAstrophysics::Galaxy AstrophysicsComputingMilieux_MISCELLANEOUSPhysics[PHYS]Physics [physics]010308 nuclear & particles physicsCosmology: observationsFísicaAstronomy and AstrophysicsAstrophysics - Astrophysics of GalaxiesGalaxySpace and Planetary ScienceAstrophysics of Galaxies (astro-ph.GA)[PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]Astrophysics - Cosmology and Nongalactic Astrophysics
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Measuring galaxy segregation with the mark connection function

2010

(abridged) The clustering properties of galaxies belonging to different luminosity ranges or having different morphological types are different. These characteristics or `marks' permit to understand the galaxy catalogs that carry all this information as realizations of marked point processes. Many attempts have been presented to quantify the dependence of the clustering of galaxies on their inner properties. The present paper summarizes methods on spatial marked statistics used in cosmology to disentangle luminosity, colour or morphological segregation and introduces a new one in this context, the mark connection function. The methods used here are the partial correlation functions, includi…

statistical [Methods]Spatial correlationCosmology and Nongalactic Astrophysics (astro-ph.CO)Large-scale structure of UniversePopulationFOS: Physical sciencesContext (language use)AstrophysicsAstrophysics::Cosmology and Extragalactic AstrophysicsCorrelation function (astronomy)UNESCO::ASTRONOMÍA Y ASTROFÍSICAUNESCO::ASTRONOMÍA Y ASTROFÍSICA::Otras especialidades astronómicasdata analysis [Methods]educationCluster analysisPartial correlationPhysicseducation.field_of_studyAstronomy and AstrophysicsFunction (mathematics)GalaxyLarge-scale structure of Universe; Methods : data analysis; Methods : statisticalSpace and Planetary Science:ASTRONOMÍA Y ASTROFÍSICA [UNESCO]:ASTRONOMÍA Y ASTROFÍSICA::Otras especialidades astronómicas [UNESCO]Astrophysics - Cosmology and Nongalactic Astrophysics
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