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Monte Carlo and Quasi-Monte Carlo Algorithms for the Barker-Ferry Equation with Low Complexity

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Numerical Methods and Applications (NMA 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2542))

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Abstract

In this paper we study the possibility to use the Sobol’ and Halton quasi-random number sequences (QRNs) in solving the Barker- Ferry (B-F) equation which accounts for the quantum character of the electron-phonon interaction in semiconductors. The quasi-Monte Carlo (QMC) solutions obtained by QRNs are compared with the Monte Carlo (MC) solutions in case when the scalable parallel random number generator (SPRNG) library is used for producing the pseudo-random number sequences (PRNs).

In order to solve the B-F equation by a MC method, a transition density with a new sampling approach is suggested in the Markov chain.

Supported by the Center of Excellence BIS-21 grant ICA1-2000-70016 and by the NSF of Bulgaria under grants MM-902/99 and I-1201/02.

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Gurov, T.V., Whitlock, P.A., Dimov, I.T. (2003). Monte Carlo and Quasi-Monte Carlo Algorithms for the Barker-Ferry Equation with Low Complexity. In: Dimov, I., Lirkov, I., Margenov, S., Zlatev, Z. (eds) Numerical Methods and Applications. NMA 2002. Lecture Notes in Computer Science, vol 2542. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36487-0_11

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  • DOI: https://doi.org/10.1007/3-540-36487-0_11

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  • Print ISBN: 978-3-540-00608-4

  • Online ISBN: 978-3-540-36487-0

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