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Classical statistical mechanics with...

Baldock, Robert John Nicholas.

Classical statistical mechanics with nested sampling

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Classical statistical mechanics with nested samplingby Robert John Nicholas Baldock.
作者:	Baldock, Robert John Nicholas.
出版者:	Cham :Springer International Publishing :2017.
面頁冊數:	xii, 144 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Statistical mechanics.
電子資源:	http://dx.doi.org/10.1007/978-3-319-66769-0
ISBN:	9783319667690$q(electronic bk.)

Classical statistical mechanics with nested sampling
Baldock, Robert John Nicholas.

Classical statistical mechanics with nested sampling[electronic resource] /by Robert John Nicholas Baldock. - Cham :Springer International Publishing :2017. - xii, 144 p. :ill., digital ;24 cm. - Springer theses, recognizing outstanding Ph.D. research,2190-5053. - Springer theses, recognizing outstanding Ph.D. research..

Introduction -- A Primer in Probability -- Phase Space Probability Distributions for Various External Conditions -- Relating Probability Density Functions to the Behaviour of Systems -- The Strategy of Nested Sampling -- Nested Sampling for Materials -- Equations of State -- Parallelising Nested Sampling -- Hamiltonian Monte Carlo for the Canonical Distribution -- Hamiltonian Monte Carlo for Nested Sampling -- Conclusion of Thesis and Further Work.

This thesis develops a nested sampling algorithm into a black box tool for directly calculating the partition function, and thus the complete phase diagram of a material, from the interatomic potential energy function. It represents a significant step forward in our ability to accurately describe the finite temperature properties of materials. In principle, the macroscopic phases of matter are related to the microscopic interactions of atoms by statistical mechanics and the partition function. In practice, direct calculation of the partition function has proved infeasible for realistic models of atomic interactions, even with modern atomistic simulation methods. The thesis also shows how the output of nested sampling calculations can be processed to calculate the complete PVT (pressure-volume-temperature) equation of state for a material, and applies the nested sampling algorithm to calculate the pressure-temperature phase diagrams of aluminium and a model binary alloy.

ISBN: 9783319667690$q(electronic bk.)

Standard No.: 10.1007/978-3-319-66769-0doiSubjects--Topical Terms:

191064
Statistical mechanics.

LC Class. No.: QC174.8

Dewey Class. No.: 530.132

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490 1 $a Springer theses, recognizing outstanding Ph.D. research, $x 2190-5053
505 0 $a Introduction -- A Primer in Probability -- Phase Space Probability Distributions for Various External Conditions -- Relating Probability Density Functions to the Behaviour of Systems -- The Strategy of Nested Sampling -- Nested Sampling for Materials -- Equations of State -- Parallelising Nested Sampling -- Hamiltonian Monte Carlo for the Canonical Distribution -- Hamiltonian Monte Carlo for Nested Sampling -- Conclusion of Thesis and Further Work.
520 $a This thesis develops a nested sampling algorithm into a black box tool for directly calculating the partition function, and thus the complete phase diagram of a material, from the interatomic potential energy function. It represents a significant step forward in our ability to accurately describe the finite temperature properties of materials. In principle, the macroscopic phases of matter are related to the microscopic interactions of atoms by statistical mechanics and the partition function. In practice, direct calculation of the partition function has proved infeasible for realistic models of atomic interactions, even with modern atomistic simulation methods. The thesis also shows how the output of nested sampling calculations can be processed to calculate the complete PVT (pressure-volume-temperature) equation of state for a material, and applies the nested sampling algorithm to calculate the pressure-temperature phase diagrams of aluminium and a model binary alloy.
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