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Monte Carlo Methods: A Hands-On Computational Introduction Utilizing Excel PDF

135 Pages·2021·5.112 MB·English
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ℝ Series ISSN: 1938-1743 C H O W D H U R Y Series Editor: Steven G. Krantz, Washington University in St. Louis Monte Carlo Methods MA Honanted sC-Oarnlo C Momepthutoadtisonal Introduction Utilizing Excel A Hands-On Sujaul Chowdhury, Shahjalal University of Science and Technology This book is intended for undergraduate students of Mathematics, Statistics, and Physics who know nothing about Monte Carlo Methods but wish to know how they work. All treatments M Computational have been done as much manually as is practicable. The treatments are deliberately manual to O N let the readers get the real feel of how Monte Carlo Methods work. T Definite integrals of a total of five functions F(x), namely Sin(x), Cos(x), ex, loge(x), E C and 1/(1+x2), have been evaluated using constant, linear, Gaussian, and exponential probability A R Introduction L density functions p(x). It is shown that results agree with known exact values better if p(x) is O proportional to F(x). Deviation from the proportionality results in worse agreement. M E Two separate chapters have been dedicated to Variational Quantum Monte Carlo T H method applied to ground state of simple harmonic oscillator and of Hydrogen atom. The book O D Utilizing Excel is intended to aid hands-on learning of Monte Carlo method. S Sujaul Chowdhury About SYNTHESIS TDhigisi tvaol lLumiber aisr ya porfi nEtendg ivneeresiroinng o fa an wd oCrko mthpaut taeprp eSacrise ninc eth. e SSyynntthheessiiss M books provide concise, original presentations of important research and O R development topics, published quickly, in digital and print formats. G A N & C L A Y store.morganclaypool.com P O O L Monte Carlo Methods A Hands-On Computational Introduction Utilizing Excel Synthesis Lectures on Mathematics and Statistics Editor StevenG.Krantz,WashingtonUniversity,St.Louis MonteCarloMethods:AHands-OnComputationalIntroductionUtilizingExcel SujaulChowdhury 2021 CrowdDynamicsbyKineticTheoryModeling:Complexity,Modeling,Simulations,and Safety BouchraAylaj,NicolaBellomo,LivioGibelli,andDamiánKnopoff 2020 ProbabilityandStatisticsforSTEM:ACourseinOneSemester E.N.BarronandJ.G.DelGreco 2020 AnIntroductiontoProofswithSetTheory DanielAshlockandColinLee 2020 DiscreteDistributionsinEngineeringandAppliedSciences RajanChattamvelliandRamalingamShanmugam 2020 AffineArithmeticBasedSolutionofUncertainStaticandDynamicProblems SnehashishChakravertyandSaudaminiRout 2020 TimeFractionalOrderBiologicalSystemswithUncertainParameters SnehashishChakraverty,RajaramaMohanJena,andSubratKumarJena 2020 FastStartAdvancedCalculus DanielAshlock 2019 iii FastStartIntegralCalculus DanielAshlock 2019 FastStartDifferentialCalculus DanielAshlock 2019 IntroductiontoStatisticsUsingR MustaphaAkinkunmi 2019 InverseObstacleScatteringwithNon-Over-DeterminedScatteringData AlexanderG.Ramm 2019 AnalyticalTechniquesforSolvingNonlinearPartialDifferentialEquations DanielJ.Arrigo 2019 AspectsofDifferentialGeometryIV EstebanCalviño-Louzao,EduardoGarcía-Río,PeterGilkey,JeongHyeongPark,andRamón Vázquez-Lorenzo 2019 SymmetryProblems.TheNavier–StokesProblem. AlexanderG.Ramm 2019 AnIntroductiontoPartialDifferentialEquations DanielJ.Arrigo 2017 NumericalIntegrationofSpaceFractionalPartialDifferentialEquations:Vol2– ApplicatonsfromClassicalIntegerPDEs YounesSalehiandWilliamE.Schiesser 2017 NumericalIntegrationofSpaceFractionalPartialDifferentialEquations:Vol1– IntroductiontoAlgorithmsandComputerCodinginR YounesSalehiandWilliamE.Schiesser 2017 AspectsofDifferentialGeometryIII EstebanCalviño-Louzao,EduardoGarcía-Río,PeterGilkey,JeongHyeongPark,andRamón Vázquez-Lorenzo 2017 iv TheFundamentalsofAnalysisforTalentedFreshmen PeterM.Luthy,GuidoL.Weiss,andStevenS.Xiao 2016 AspectsofDifferentialGeometryII PeterGilkey,JeongHyeongPark,RamónVázquez-Lorenzo 2015 AspectsofDifferentialGeometryI PeterGilkey,JeongHyeongPark,RamónVázquez-Lorenzo 2015 AnEasyPathtoConvexAnalysisandApplications BorisS.MordukhovichandNguyenMauNam 2013 ApplicationsofAffineandWeylGeometry EduardoGarcía-Río,PeterGilkey,StanaNikčević,andRamónVázquez-Lorenzo 2013 EssentialsofAppliedMathematicsforEngineersandScientists,SecondEdition RobertG.Watts 2012 ChaoticMaps:Dynamics,Fractals,andRapidFluctuations GoongChenandYuHuang 2011 MatricesinEngineeringProblems MarvinJ.Tobias 2011 TheIntegral:ACruxforAnalysis StevenG.Krantz 2011 StatisticsisEasy!SecondEdition DennisShashaandMandaWilson 2010 LecturesonFinancialMathematics:DiscreteAssetPricing GregAndersonandAlecN.Kercheval 2010 JordanCanonicalForm:TheoryandPractice StevenH.Weintraub 2009 v TheGeometryofWalkerManifolds MiguelBrozos-Vázquez,EduardoGarcía-Río,PeterGilkey,StanaNikčević,andRamón Vázquez-Lorenzo 2009 AnIntroductiontoMultivariableMathematics LeonSimon 2008 JordanCanonicalForm:ApplicationtoDifferentialEquations StevenH.Weintraub 2008 StatisticsisEasy! DennisShashaandMandaWilson 2008 AGyrovectorSpaceApproachtoHyperbolicGeometry AbrahamAlbertUngar 2008 Copyright©2021byMorgan&Claypool Allrightsreserved.Nopartofthispublicationmaybereproduced,storedinaretrievalsystem,ortransmittedin anyformorbyanymeans—electronic,mechanical,photocopy,recording,oranyotherexceptforbriefquotations inprintedreviews,withoutthepriorpermissionofthepublisher. MonteCarloMethods:AHands-OnComputationalIntroductionUtilizingExcel SujaulChowdhury www.morganclaypool.com ISBN:9781636390710 paperback ISBN:9781636390727 ebook ISBN:9781636390734 hardcover DOI10.2200/S01073ED1V01Y202101MAS037 APublicationintheMorgan&ClaypoolPublishersseries SYNTHESISLECTURESONMATHEMATICSANDSTATISTICS Lecture#37 SeriesEditor:StevenG.Krantz,WashingtonUniversity,St.Louis SeriesISSN Print1938-1743 Electronic1938-1751 Monte Carlo Methods A Hands-On Computational Introduction Utilizing Excel Sujaul Chowdhury ShahjalalUniversityofScienceandTechnology SYNTHESISLECTURESONMATHEMATICSANDSTATISTICS#37 M &C Morgan &cLaypool publishers ABSTRACT This book is intended for undergraduate students of Mathematics, Statistics, and Physics who know nothing about Monte Carlo Methods but wish to know how they work. All treatments have been done as much manually as is practicable. The treatments are deliberately manual to letthereadersgettherealfeelofhowMonteCarloMethodswork. DefiniteintegralsofatotaloffivefunctionsF.x/,namelySin.x/,Cos.x/,ex,log .x/,and e 1=.1 x2/, have been evaluated using constant, linear, Gaussian, and exponential probability C density functions p.x/. It is shown that results agree with known exact values better if p.x/ is proportionaltoF.x/.Deviationfromtheproportionalityresultsinworseagreement. ThisbookisonMonteCarloMethodswhicharenumericalmethodsforComputational Physics. These are parts of a syllabus for undergraduate students of Mathematics and Physics forthecoursetitled“ComputationalPhysics.” Needforthebook:Besidesthethreereferencedbooks,thisistheonlybookthatteaches how basic Monte Carlo methods work. This book is much more explicit and easier to follow than the three referenced books. The two chapters on the Variational Quantum Monte Carlo methodareadditionalcontributionsofthebook. Pedagogical features: After a thorough acquaintance with background knowledge in Chapter 1, five thoroughly worked out examples on how to carry out Monte Carlo integration is included in Chapter 2. Moreover, the book contains two chapters on the Variational Quan- tumMonteCarlomethodappliedtoasimpleharmonicoscillatorandahydrogenatom. The book is a good read; it is intended to make readers adept at using the method. The bookisintendedtoaidinhands-onlearningoftheMonteCarlomethods. KEYWORDS MonteCarlomethods,basicMonteCarlointegration,variationalquantumMonte Carlomethod,simpleharmonicoscillator,hydrogenatom

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