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Bansal, Monika; Bansal, Sunil; Kumar, Ramandeep – Physics Education, 2021
Simulation of physics phenomena is an indispensable part of experimental studies. Undergraduate and postgraduate physics students are often introduced to the simulation of various phenomena as one of the most important pedagogical tools. In this document, we demonstrate the simulations of the two-body decay of a particle and equilibrium states in…
Descriptors: Physics, Simulation, College Science, Mechanics (Physics)
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Singh, Satya Pal – European Journal of Physics Education, 2014
This paper presents a brief review of Ising's work done in 1925 for one dimensional spin chain with periodic boundary condition. Ising observed that no phase transition occurred at finite temperature in one dimension. He erroneously generalized his views in higher dimensions but that was not true. In 1941 Kramer and Wannier obtained…
Descriptors: Physics, Scientific Principles, Magnets, Motion
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Guastella, Ivan; Fazio, Claudio; Sperandeo-Mineo, Rosa Maria – European Journal of Physics, 2012
A procedure modelling ideal classical and quantum gases is discussed. The proposed approach is mainly based on the idea that modelling and algorithm analysis can provide a deeper understanding of particularly complex physical systems. Appropriate representations and physical models able to mimic possible pseudo-mechanisms of functioning and having…
Descriptors: Predictive Validity, Quantum Mechanics, Science Education, Science Instruction
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Morio, Jerome; Pastel, Rudy; Le Gland, Francois – European Journal of Physics, 2010
Monte Carlo simulations are a classical tool to analyse physical systems. When unlikely events are to be simulated, the importance sampling technique is often used instead of Monte Carlo. Importance sampling has some drawbacks when the problem dimensionality is high or when the optimal importance sampling density is complex to obtain. In this…
Descriptors: Science Instruction, Physics, Simulation, Sampling
Gergely, John Robert – ProQuest LLC, 2009
Obtaining an accurate microscopic description of water structure and dynamics is of great interest to molecular biology researchers and in the physics and quantum chemistry simulation communities. This dissertation describes efforts to apply quantum Monte Carlo methods to this problem with the goal of making progress toward a fully "ab initio"…
Descriptors: Monte Carlo Methods, Physics, Molecular Biology, Water
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Capizzo, M. C.; Sperandeo-Mineo, R. M.; Zarcone, M. – European Journal of Physics, 2008
We present a pedagogic approach aimed at modelling electric conduction in semiconductors in order to describe and explain some macroscopic properties, such as the characteristic behaviour of resistance as a function of temperature. A simple model of the band structure is adopted for the generation of electron-hole pairs as well as for the carrier…
Descriptors: Teaching Methods, Science Instruction, Laboratory Equipment, Science Experiments
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Peralta, Luis; Farinha, Ana Catarina; Rego, Florbela – European Journal of Physics, 2008
X-ray fluorescence is a non-destructive technique that allows elemental composition analysis. In this paper we describe a prescription to obtain the elemental composition of homogeneous coins, like 50 cent Euro coins, and how to get the quantitative proportions of each element with the help of Monte Carlo simulation. Undergraduate students can…
Descriptors: Undergraduate Students, Monte Carlo Methods, Chemistry, Science Laboratories
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Lee, Wei; Mulliss, Christopher L.; Chu, Hung-Chih – Chinese Journal of Physics, 2000
Investigates the commonly suggested rounding rule for addition and subtraction including its derivation from a basic assumption. Uses Monte-Carlo simulations to show that this rule predicts the minimum number of significant digits needed to preserve precision 100% of the time. (Author/KHR)
Descriptors: Addition, Higher Education, Monte Carlo Methods, Physics
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Mulliss, Christopher L.; Lee, Wei – Chinese Journal of Physics, 1998
Investigates the standard rounding rule for multiplication and division including its derivation from a basic assumption. Uses Monte-Carlo simulations to show that this rule predicts the minimum number of significant digits needed to preserve precision only 46.4% of the time and leads to a loss in precision 53.5% of time. Suggests an alternative…
Descriptors: Division, Higher Education, Monte Carlo Methods, Multiplication