Dissertations / Theses on the topic 'Monte Carlo'
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Janzon, Krister. "Monte Carlo Path Simulation and the Multilevel Monte Carlo Method." Thesis, Umeå universitet, Institutionen för fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-151975.
Full textJun, Seong-Hwan. "Entangled Monte Carlo." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/44953.
Full textDickinson, Andrew Samuel. "On the analysis of Monte Carlo and quasi-Monte Carlo methods." Thesis, University of Oxford, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409715.
Full textGöncü, Ahmet. "Monte Carlo and quasi-Monte Carlo methods in pricing financial derivatives." Tallahassee, Florida : Florida State University, 2009. http://etd.lib.fsu.edu/theses/available/etd-06232009-140439/.
Full textAdvisor: Giray Ökten, Florida State University, College of Arts and Sciences, Dept. of Mathematics. Title and description from dissertation home page (viewed on Oct. 5, 2009). Document formatted into pages; contains x, 105 pages. Includes bibliographical references.
Berezovska, Ganna [Verfasser], and Alexander [Akademischer Betreuer] Blumen. "Monte Carlo study of semiflexible polymers = Monte Carlo Studie von semiflexiblen Polymeren." Freiburg : Universität, 2011. http://d-nb.info/1125885467/34.
Full textDrumond, Lorenzo. "Il Metodo Monte Carlo." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20698/.
Full textChin, Mary Pik Wai. "Monte Carlo portal dosimetry." Thesis, Cardiff University, 2005. http://orca.cf.ac.uk/54085/.
Full textMcNeil-Watson, Graham. "Phase switch Monte Carlo." Thesis, University of Bath, 2007. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.486842.
Full textBakra, Eleni. "Aspects of population Markov chain Monte Carlo and reversible jump Markov chain Monte Carlo." Thesis, University of Glasgow, 2009. http://theses.gla.ac.uk/1247/.
Full textBryskhe, Henrik. "Optimization of Monte Carlo simulations." Thesis, Uppsala University, Department of Information Technology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-121843.
Full textThis thesis considers several different techniques for optimizing Monte Carlo simulations. The Monte Carlo system used is Penelope but most of the techniques are applicable to other systems. The two mayor techniques are the usage of the graphics card to do geometry calculations, and raytracing. Using graphics card provides a very efficient way to do fast ray and triangle intersections. Raytracing provides an approximation of Monte Carlo simulation but is much faster to perform. A program was also written in order to have a platform for Monte Carlo simulations where the different techniques were implemented and tested. The program also provides an overview of the simulation setup, were the user can easily verify that everything has been setup correctly. The thesis also covers an attempt to rewrite Penelope from FORTAN to C. The new version is significantly faster and can be used on more systems. A distribution package was also added to the new Penelope version. Since Monte Carlo simulations are easily distributed, running this type of simulations on ten computers yields ten times the speedup. Combining the different techniques in the platform provides an easy to use and at the same time efficient way of performing Monte Carlo simulations.
Zeineh, Rami. "Adaptive threshold Monte Carlo localization." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ61962.pdf.
Full textHolenstein, Roman. "Particle Markov chain Monte Carlo." Thesis, University of British Columbia, 2009. http://hdl.handle.net/2429/7319.
Full textByrd, Jonathan Michael Robert. "Parallel Markov Chain Monte Carlo." Thesis, University of Warwick, 2010. http://wrap.warwick.ac.uk/3634/.
Full textLewis, R. D. "Monte Carlo modelling for radiotherapy." Thesis, Swansea University, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.637892.
Full textTaft, Keith. "Monte Carlo methods for radiosity." Thesis, University of Liverpool, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272796.
Full textWhiteley, Nicholas Paul. "Advances in Monte Carlo filtering." Thesis, University of Cambridge, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611476.
Full textBadinski, Alexander Nikolai. "Forces in quantum Monte Carlo." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.612494.
Full textStrathmann, Heiko. "Kernel methods for Monte Carlo." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10040707/.
Full textSilva, Ivair Ramos. "Otimalidade de Testes Monte Carlo." Universidade Federal de Minas Gerais, 2011. http://hdl.handle.net/1843/ICED-8H2HFS.
Full textLin, Xichen. "Monte Carlo Simulation and Integration." Scholarship @ Claremont, 2018. https://scholarship.claremont.edu/cmc_theses/2009.
Full textTuffin, Bruno. "Simulation acceleree par les methodes de monte carlo et quasi-monte carlo : theorie et applications." Rennes 1, 1997. http://www.theses.fr/1997REN10181.
Full textHoffmann, Jochen. "Monte-Carlo- und Pfad-Integral-Monte-Carlo-Simulationen zu Strukturen und Phasenübergängen in Nano-Porenkondensaten." [S.l. : s.n.], 2002. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB9910270.
Full textWaldeckerová, Naďa. "Option pricing using Monte Carlo methods." Master's thesis, Vysoká škola ekonomická v Praze, 2015. http://www.nusl.cz/ntk/nusl-206936.
Full textOunaissi, Daoud. "Méthodes quasi-Monte Carlo et Monte Carlo : application aux calculs des estimateurs Lasso et Lasso bayésien." Thesis, Lille 1, 2016. http://www.theses.fr/2016LIL10043/document.
Full textThe thesis contains 6 chapters. The first chapter contains an introduction to linear regression, the Lasso and the Bayesian Lasso problems. Chapter 2 recalls the convex optimization algorithms and presents the Fista algorithm for calculating the Lasso estimator. The properties of the convergence of this algorithm is also given in this chapter using the entropy estimator and Pitman-Yor estimator. Chapter 3 is devoted to comparison of Monte Carlo and quasi-Monte Carlo methods in numerical calculations of Bayesian Lasso. It comes out of this comparison that the Hammersely points give the best results. Chapter 4 gives a geometric interpretation of the partition function of the Bayesian lasso expressed as a function of the incomplete Gamma function. This allowed us to give a convergence criterion for the Metropolis Hastings algorithm. Chapter 5 presents the Bayesian estimator as the law limit a multivariate stochastic differential equation. This allowed us to calculate the Bayesian Lasso using numerical schemes semi-implicit and explicit Euler and methods of Monte Carlo, Monte Carlo multilevel (MLMC) and Metropolis Hastings algorithm. Comparing the calculation costs shows the couple (semi-implicit Euler scheme, MLMC) wins against the other couples (scheme method). Finally in chapter 6 we found the Lasso convergence rate of the Bayesian Lasso when the signal / noise ratio is constant and when the noise tends to 0. This allowed us to provide a new criteria for the convergence of the Metropolis algorithm Hastings
Mandreoli, Lorenzo. "Density based Kinetic Monte Carlo Methods." [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=975329111.
Full textBrangian, Claudio. "Monte Carlo simulations of Potts glasses." [S.l.] : [s.n.], 2002. http://ArchiMeD.uni-mainz.de/pub/2002/0115/diss.pdf.
Full textRadev, Rossen. "Monte Carlo Group - Atomic Physics Department." Phd thesis, Monte Carlo Group, Atomic Physics Department, University of Sofia, 1997. http://cluster.phys.uni-sofia.bg:8080/.
Full textSebastian, Shalin. "Empirical evaluation of Monte Carlo sampling /." Available to subscribers only, 2005. http://proquest.umi.com/pqdweb?did=1075709431&sid=9&Fmt=2&clientId=1509&RQT=309&VName=PQD.
Full textSchyberg, Oskar. "Monte Carlo Study of Reinsurance Contracts." Licentiate thesis, Mälardalens högskola, Akademin för utbildning, kultur och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-18374.
Full textHine, Nicholas. "New applications of quantum Monte Carlo." Thesis, Imperial College London, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.446023.
Full textZhang, Kai. "Monte Carlo methods in derivative modelling." Thesis, University of Warwick, 2011. http://wrap.warwick.ac.uk/35689/.
Full textMaggio, Emilio. "Monte Carlo methods for visual tracking." Thesis, Queen Mary, University of London, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.497791.
Full textLee, Ming Ripman, and 李明. "Monte Carlo simulation for confined electrolytes." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B31240513.
Full textPhillips, Richard J. "Monte Carlo generation of Cerenkov radiation." Thesis, Monterey, California. Naval Postgraduate School, 1989. http://hdl.handle.net/10945/26090.
Full textAnderson, Jeppe Rosenkrantz. "Monte Carlo studies of BFKL physics." Thesis, Durham University, 2002. http://etheses.dur.ac.uk/4118/.
Full textCrosby, Richard S. "Monte Carlo methods for lattice fields." Thesis, Massachusetts Institute of Technology, 1989. http://hdl.handle.net/1721.1/77699.
Full textWang, Junxiong. "Option Pricing Using Monte Carlo Methods." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/331.
Full textLu, Mengliu. "Option Pricing Using Monte Carlo Methods." Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-theses/380.
Full textSwetnam, Adam D. "Monte Carlo simulation of lattice polymers." Thesis, University of Warwick, 2011. http://wrap.warwick.ac.uk/49196/.
Full textClark, Michael A. "The rational hybrid Monte Carlo algorithm." Thesis, University of Edinburgh, 2005. http://hdl.handle.net/1842/13416.
Full textXia, Yuan. "Multilevel Monte Carlo for jump processes." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:7bc8e98a-0216-4551-a1f3-1b318e514ee8.
Full textPoole, Thomas. "Calculating derivatives within quantum Monte Carlo." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/29359.
Full textZhang, Yichuan. "Scalable geometric Markov chain Monte Carlo." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/20978.
Full textDesplat, Jean-Christophe. "Monte Carlo simulations of amphiphilic systems." Thesis, Sheffield Hallam University, 1996. http://shura.shu.ac.uk/19557/.
Full textFang, Youhan. "Efficient Markov Chain Monte Carlo Methods." Thesis, Purdue University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10809188.
Full textGenerating random samples from a prescribed distribution is one of the most important and challenging problems in machine learning, Bayesian statistics, and the simulation of materials. Markov Chain Monte Carlo (MCMC) methods are usually the required tool for this task, if the desired distribution is known only up to a multiplicative constant. Samples produced by an MCMC method are real values in N-dimensional space, called the configuration space. The distribution of such samples converges to the target distribution in the limit. However, existing MCMC methods still face many challenges that are not well resolved. Difficulties for sampling by using MCMC methods include, but not exclusively, dealing with high dimensional and multimodal problems, high computation cost due to extremely large datasets in Bayesian machine learning models, and lack of reliable indicators for detecting convergence and measuring the accuracy of sampling. This dissertation focuses on new theory and methodology for efficient MCMC methods that aim to overcome the aforementioned difficulties.
One contribution of this dissertation is generalizations of hybrid Monte Carlo (HMC). An HMC method combines a discretized dynamical system in an extended space, called the state space, and an acceptance test based on the Metropolis criterion. The discretized dynamical system used in HMC is volume preserving—meaning that in the state space, the absolute Jacobian of a map from one point on the trajectory to another is 1. Volume preservation is, however, not necessary for the general purpose of sampling. A general theory allowing the use of non-volume preserving dynamics for proposing MCMC moves is proposed. Examples including isokinetic dynamics and variable mass Hamiltonian dynamics with an explicit integrator, are all designed with fewer restrictions based on the general theory. Experiments show improvement in efficiency for sampling high dimensional multimodal problems. A second contribution is stochastic gradient samplers with reduced bias. An in-depth analysis of the noise introduced by the stochastic gradient is provided. Two methods to reduce the bias in the distribution of samples are proposed. One is to correct the dynamics by using an estimated noise based on subsampled data, and the other is to introduce additional variables and corresponding dynamics to adaptively reduce the bias. Extensive experiments show that both methods outperform existing methods. A third contribution is quasi-reliable estimates of effective sample size. Proposed is a more reliable indicator—the longest integrated autocorrelation time over all functions in the state space—for detecting the convergence and measuring the accuracy of MCMC methods. The superiority of the new indicator is supported by experiments on both synthetic and real problems.
Minor contributions include a general framework of changing variables, and a numerical integrator for the Hamiltonian dynamics with fourth order accuracy. The idea of changing variables is to transform the potential energy function as a function of the original variable to a function of the new variable, such that undesired properties can be removed. Two examples are provided and preliminary experimental results are obtained for supporting this idea. The fourth order integrator is constructed by combining the idea of the simplified Takahashi-Imada method and a two-stage Hessian-based integrator. The proposed method, called two-stage simplified Takahashi-Imada method, shows outstanding performance over existing methods in high-dimensional sampling problems.
Jaeckel, Alain. "Simulations Monte Carlo de chaînes confinées." Montpellier 2, 1997. http://www.theses.fr/1997MON20206.
Full textMari, Martine. "L'opéra de Monte-Carlo : (1892-1951)." Nice, 1986. http://www.theses.fr/1986NICE2036.
Full textJohnson, Lindsay Marie. "Diffusion Monte Carlo studies of CH5+." The Ohio State University, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=osu1413365241.
Full textKłos, J. S., and J. U. Sommer. "Dendrimer solutions: a Monte Carlo study." Royal Society of Chemistry, 2016. https://tud.qucosa.de/id/qucosa%3A36416.
Full textCornebise, Julien. "Méthodes de Monte Carlo séquentielles adaptatives." Paris 6, 2009. http://www.theses.fr/2009PA066152.
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