Search results for " Statistical"

showing 10 items of 1649 documents

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

2021

The Pierre Auger Observatory, at present the largest cosmic-ray observatory ever built, is instrumented with a ground array of 1600 water-Cherenkov detectors, known as the Surface Detector (SD). The SD samples the secondary particle content (mostly photons, electrons, positrons and muons) of extensive air showers initiated by cosmic rays with energies ranging from $10^{17}~$eV up to more than $10^{20}~$eV. Measuring the independent contribution of the muon component to the total registered signal is crucial to enhance the capability of the Observatory to estimate the mass of the cosmic rays on an event-by-event basis. However, with the current design of the SD, it is difficult to straightfo…

PhotonPhysics::Instrumentation and DetectorsAstronomyElectron01 natural sciencesHigh Energy Physics - ExperimentAugerHigh Energy Physics - Experiment (hep-ex)mass [cosmic radiation]surface [detector]Observatory[PHYS.HEXP]Physics [physics]/High Energy Physics - Experiment [hep-ex]photon: cosmic radiationInstrumentationMathematical PhysicsPhysicsAGASAPhysicsSettore FIS/01 - Fisica SperimentaleDetectorcosmic radiation [photon]Astrophysics::Instrumentation and Methods for AstrophysicsMonte Carlo [numerical calculations]electromagnetic [showers]Augerobservatorycosmic radiation [electron]Analysis and statistical methodsnumerical calculations: Monte CarloAnalysis and statistical methodperformancepositron: cosmic radiationatmosphere [showers]Cherenkov detectordata analysis methodAnalysis and statistical methods; Calibration and fitting methods; Cherenkov detectors; Cluster finding; Large detector systems for particle and astroparticle physics; Pattern recognitionCherenkov counter: waterairneural networkAstrophysics::High Energy Astrophysical Phenomena610FOS: Physical sciencesCosmic raycosmic radiation [positron]cosmic radiation: massCalibration and fitting methodNuclear physicsstatistical analysisPattern recognition0103 physical sciencesshowers: electromagneticddc:530ddc:610High Energy Physics010306 general physicsZenithPierre Auger ObservatoryCalibration and fitting methodscosmic radiation [muon]Muonshowers: atmosphere010308 nuclear & particles physicsdetector: surfacehep-exLarge detector systems for particle and astroparticle physicswater [Cherenkov counter]Cherenkov detectorsCluster findingelectron: cosmic radiationRecurrent neural networkmuon: cosmic radiationLarge detector systems for particle and astroparticle physicExperimental High Energy PhysicsHigh Energy Physics::ExperimentRAIOS CÓSMICOSexperimental results
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The FiR 1 photon beam model adjustment according to in-air spectrum measurements with the Mg(Ar) ionization chamber.

2014

Abstract The mixed neutron–photon beam of FiR 1 reactor is used for boron–neutron capture therapy (BNCT) in Finland. A beam model has been defined for patient treatment planning and dosimetric calculations. The neutron beam model has been validated with an activation foil measurements. The photon beam model has not been thoroughly validated against measurements, due to the fact that the beam photon dose rate is low, at most only 2% of the total weighted patient dose at FiR 1. However, improvement of the photon dose detection accuracy is worthwhile, since the beam photon dose is of concern in the beam dosimetry. In this study, we have performed ionization chamber measurements with multiple b…

PhotonQuantitative Biology::Tissues and OrgansPhysics::Medical PhysicsMonte Carlo methodAnalytical chemistryBoron Neutron Capture TherapySensitivity and SpecificityOpticsNuclear ReactorsDosimetryPenelopeIonization ChamberDosimetryComputer SimulationPhoton beamRadiometryMonte CarloPhysicsPhotonsRadiationModels Statisticalbusiness.industryAirRadiotherapy Planning Computer-AssistedReproducibility of ResultsEquipment DesignNeutron radiationEquipment Failure AnalysisIonization chamberBNCTPhysics::Accelerator PhysicsComputer-Aided DesignDose ratebusinessMCNP5Beam (structure)Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
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Subpicosecond transient signal spectroscopy of Prodan in dimethylformamide solution.

2008

We report a pump-probe experiment revealing the temporal evolution of subpicosecond evolution of Prodan's excited-state absorption in dimethylformamide. Also, we present calculation of the first spectral moment of this spectral band and estimation of different relaxation components on the subpicosecond time scale.

PhotonsModels StatisticalTime FactorsChemistryPhotochemistryGeneral NeuroscienceLasersRelaxation (NMR)Analytical chemistryDimethylformamideSpectral bandsEquipment DesignMolecular physicsGeneral Biochemistry Genetics and Molecular BiologyAbsorptionchemistry.chemical_compoundKineticsSpectrometry FluorescenceHistory and Philosophy of Science2-NaphthylamineDimethylformamideSpectroscopyAbsorption (electromagnetic radiation)Transient signalFluorescent DyesAnnals of the New York Academy of Sciences
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Ab initioquality neural-network potential for sodium

2010

An interatomic potential for high-pressure high-temperature (HPHT) crystalline and liquid phases of sodium is created using a neural-network (NN) representation of the ab initio potential energy surface. It is demonstrated that the NN potential provides an ab initio quality description of multiple properties of liquid sodium and bcc, fcc, cI16 crystal phases in the P-T region up to 120 GPa and 1200 K. The unique combination of computational efficiency of the NN potential and its ability to reproduce quantitatively experimental properties of sodium in the wide P-T range enables molecular dynamics simulations of physicochemical processes in HPHT sodium of unprecedented quality.

Physicochemical ProcessesCondensed Matter - Materials ScienceMaterials scienceStatistical Mechanics (cond-mat.stat-mech)Artificial neural networkSodiumAb initioMaterials Science (cond-mat.mtrl-sci)FOS: Physical sciencesThermodynamicschemistry.chemical_elementInteratomic potentialCondensed Matter PhysicsElectronic Optical and Magnetic MaterialsCrystalQuality (physics)chemistryCondensed Matter - Statistical MechanicsPhysical Review B
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Dynamics of fintech terms in news and blogs and specialization of companies of the fintech industry

2020

We perform a large scale analysis of a list of fintech terms in (i) news and blogs in English language and (ii) professional descriptions of companies operating in many countries. The occurrence and co-occurrence of fintech terms and locutions shows a progressive evolution of the list of fintech terms in a compact and coherent set of terms used worldwide to describe fintech business activities. By using methods of complex networks that are specifically designed to deal with heterogeneous systems, our analysis of a large set of professional descriptions of companies shows that companies having fintech terms in their description present over-expressions of specific attributes of country, muni…

Physics - Physics and SocietyApplied MathematicsEconomic sectorFintech Statistically validated networksGeneral Physics and AstronomyFOS: Physical sciencesStatistical and Nonlinear PhysicsEnglish languagePhysics and Society (physics.soc-ph)Complex networkBusiness activities01 natural sciencesSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)010305 fluids & plasmasSet (abstract data type)FOS: Economics and businessDynamics (music)0103 physical sciencesSpecialization (functional)Business010306 general physicsGeneral Finance (q-fin.GN)Quantitative Finance - General FinanceMathematical PhysicsIndustrial organization
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A tool for filtering information in complex systems

2005

We introduce a technique to filter out complex data-sets by extracting a subgraph of representative links. Such a filtering can be tuned up to any desired level by controlling the genus of the resulting graph. We show that this technique is especially suitable for correlation based graphs giving filtered graphs which preserve the hierarchical organization of the minimum spanning tree but containing a larger amount of information in their internal structure. In particular in the case of planar filtered graphs (genus equal to 0) triangular loops and 4 element cliques are formed. The application of this filtering procedure to 100 stocks in the USA equity markets shows that such loops and cliqu…

Physics - Physics and SocietyComputer scienceComplex systemFOS: Physical sciencesPhysics and Society (physics.soc-ph)Minimum spanning treecomputer.software_genrePlanarHierarchical organizationINTERNETCondensed Matter - Statistical MechanicsComplex data typeMultidisciplinarySmall-world networkStatistical Mechanics (cond-mat.stat-mech)SMALL-WORLD NETWORKSFilter (signal processing)Disordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksComplex networkWEBDYNAMIC ASSET TREESPhysical SciencesGRAPHData miningAlgorithmcomputerMathematicsofComputing_DISCRETEMATHEMATICS
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Cluster analysis for portfolio optimization

2005

We consider the problem of the statistical uncertainty of the correlation matrix in the optimization of a financial portfolio. We show that the use of clustering algorithms can improve the reliability of the portfolio in terms of the ratio between predicted and realized risk. Bootstrap analysis indicates that this improvement is obtained in a wide range of the parameters N (number of assets) and T (investment horizon). The predicted and realized risk level and the relative portfolio composition of the selected portfolio for a given value of the portfolio return are also investigated for each considered filtering method.

Physics - Physics and SocietyEconomics and EconometricsControl and OptimizationMathematics::Optimization and ControlFOS: Physical sciencesStatistics::Other StatisticsPhysics and Society (physics.soc-ph)random matrix theoryportfolio optimizationcorrelation matriceRate of return on a portfolioFOS: Economics and businessComputer Science::Computational Engineering Finance and ScienceEconometricsEconomicsCluster analysisModern portfolio theoryStatistical Finance (q-fin.ST)Covariance matrixApplied MathematicsQuantitative Finance - Statistical FinanceCondensed Matter - Other Condensed MatterPortfolioPortfolio optimizationVolatility (finance)clustering methodRandom matrixOther Condensed Matter (cond-mat.other)
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There's more to volatility than volume

2006

It is widely believed that fluctuations in transaction volume, as reflected in the number of transactions and to a lesser extent their size, are the main cause of clustered volatility. Under this view bursts of rapid or slow price diffusion reflect bursts of frequent or less frequent trading, which cause both clustered volatility and heavy tails in price returns. We investigate this hypothesis using tick by tick data from the New York and London Stock Exchanges and show that only a small fraction of volatility fluctuations are explained in this manner. Clustered volatility is still very strong even if price changes are recorded on intervals in which the total transaction volume or number of…

Physics - Physics and SocietyEconomicsvolatilityFOS: Physical sciencessubordinated processesPhysics and Society (physics.soc-ph)FOS: Economics and businessStock exchangeddc:330EconometricsEconomicsVolatility Modelling; Transaction Frequency; Trading Volume; Market StructurevolumeStatistical Finance (q-fin.ST)Financial marketVolume (computing)WirtschaftQuantitative Finance - Statistical FinancePolitical EconomyVolkswirtschaftslehrefinancial marketVolatility (finance)Constant (mathematics)General Economics Econometrics and FinanceDatabase transactionFinance
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Scaling and data collapse for the mean exit time of asset prices

2005

We study theoretical and empirical aspects of the mean exit time of financial time series. The theoretical modeling is done within the framework of continuous time random walk. We empirically verify that the mean exit time follows a quadratic scaling law and it has associated a pre-factor which is specific to the analyzed stock. We perform a series of statistical tests to determine which kind of correlation are responsible for this specificity. The main contribution is associated with the autocorrelation property of stock returns. We introduce and solve analytically both a two-state and a three-state Markov chain models. The analytical results obtained with the two-state Markov chain model …

Physics - Physics and SocietyFísica matemàticaFOS: Physical sciencesMarkov processPhysics and Society (physics.soc-ph)FOS: Economics and businessFINANCEsymbols.namesakeFRACTIONAL CALCULUSQuadratic equationEconometricsNonlinear systemsApplied mathematicsDISTRIBUTIONSTime seriesScalingBrownian motionMathematicsStatistical hypothesis testingRANDOM-WALKSStatistical Finance (q-fin.ST)Series (mathematics)Markov chainStochastic processSistemes no linealsPhysicsAutocorrelationQuantitative Finance - Statistical FinanceFísicaFLUCTUATIONSMathematical physicssymbolsContinuous-time random walk
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Evolution of correlation structure of industrial indices of U.S. equity markets

2013

We investigate the dynamics of correlations present between pairs of industry indices of US stocks traded in US markets by studying correlation based networks and spectral properties of the correlation matrix. The study is performed by using 49 industry index time series computed by K. French and E. Fama during the time period from July 1969 to December 2011 that is spanning more than 40 years. We show that the correlation between industry indices presents both a fast and a slow dynamics. The slow dynamics has a time scale longer than five years showing that a different degree of diversification of the investment is possible in different periods of time. On top to this slow dynamics, we als…

Physics - Physics and SocietyIndex (economics)Scale (ratio)Operations researchSettore SECS-P/05Diversification (finance)FOS: Physical sciencesPhysics and Society (physics.soc-ph)01 natural sciences010305 fluids & plasmasFOS: Economics and businessCorrelationRandom matrix theoryMINIMUM SPANNING-TREES0103 physical sciencesEconometricsPCA Random matrix theory010306 general physicsCORRELATION-BASED NETWORKSMathematicsPCAStatistical Finance (q-fin.ST)Settore SECS-S/03CROSS-CORRELATIONSCovariance matrixSpectral propertiesSettore SECS-S/06Equity (finance)Quantitative Finance - Statistical FinanceFINANCIAL-MARKETSSubprime crisisInvestment (macroeconomics)Degree (music)Settore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)DYNAMIC ASSET TREESMATRICES
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