Results 41 to 50 of about 1,455,452 (353)
, 2013 The Euler-Maruyama scheme is known to diverge strongly and numerically weakly when applied to nonlinear stochastic differential equations (SDEs) with superlinearly growing and globally one-sided Lipschitz continuous drift coefficients.
Hutzenthaler, Martin +2 more
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Química Nova, 2008 The paper presents an introductory and general discussion on the quantum Monte Carlo methods, some fundamental algorithms, concepts and applicability. In order to introduce the quantum Monte Carlo method, preliminary concepts associated with Monte Carlo ...
Wagner Fernando Delfino Angelotti +3 more
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Comparation of nonuniform and uniform Monte - Carlo Searching
MATEC Web of Conferences, 2018 Nonuniform Monte-Carlo method is often used for optimization and solution of function mapping. This method has some disadvantages. New genetic algorithm, based on uniform Monte-Carlo is proposed by authors reduce disadvantage of nonuniform Monte- Carlo ...
Handrik Marián +3 more
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Optimization of ground and excited state wavefunctions and van der Waals clusters [PDF]
, 2000 A quantum Monte Carlo method is introduced to optimize excited state trial wavefunctions. The method is applied in a correlation function Monte Carlo calculation to compute ground and excited state energies of bosonic van der Waals clusters of upto seven
Andrei Mushinski +24 more
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Quasi-Monte Carlo simulation of Brownian sheet with application to option pricing
Statistical Theory and Related Fields, 2017 Monte Carlo and quasi-Monte Carlo methods are widely used in scientific studies. As quasi-Monte Carlo simulations have advantage over ordinary Monte Carlo methods, this paper proposes a new quasi-Monte Carlo method to simulate Brownian sheet via its ...
Xinyu Song, Yazhen Wang
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Transition Matrix Monte Carlo Method
, 1998 We analyze a new Monte Carlo method which uses transition matrix in the space of energy. This method gives an efficient reweighting technique. The associated artificial dynamics is a constrained random walk in energy, producing the result that ...
Wang, Jian-Sheng
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Self-Learning Determinantal Quantum Monte Carlo Method [PDF]
, 2016 Self-learning Monte Carlo method [arXiv:1610.03137, 1611.09364] is a powerful general-purpose numerical method recently introduced to simulate many-body systems. In this work, we implement this method in the framework of determinantal quantum Monte Carlo
Fu, Liang +4 more
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Efficient Least Squares Monte-Carlo Technique for PFE/EE Calculations [PDF]
arXiv, 2021 We describe a regression-based method, generally referred to as the Least Squares Monte Carlo (LSMC) method, to speed up exposure calculations of a portfolio. We assume that the portfolio contains several exotic derivatives that are priced using Monte-Carlo on each real world scenario and time step.
arxiv
An Efficient Anti-Optimization Approach for Uncertainty Analysis in Composite Laminates
Materials Research, 2021 This work presents an efficient approach to quantify uncertainties in composite laminates using the interval analysis, anti-optimization technique, and the α-cut procedure.
Pedro Bührer Santana +2 more
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Monte Carlo simulation method for Laughlin-like states in a disk geometry [PDF]
, 2003 We discuss an alternative accurate Monte Carlo method to calculate the ground-state energy and related quantities for Laughlin states of the fractional quantum Hall effect in a disk geometry.
C. Wexler +14 more
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