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Classical statistical mechanics with...
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Baldock, Robert John Nicholas.
Classical statistical mechanics with nested sampling
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Classical statistical mechanics with nested sampling/ by Robert John Nicholas Baldock.
Author:
Baldock, Robert John Nicholas.
Published:
Cham :Springer International Publishing : : 2017.,
Description:
xii, 144 p. :ill., digital ; : 24 cm.;
Contained By:
Springer eBooks
Subject:
Statistical mechanics. -
Online resource:
http://dx.doi.org/10.1007/978-3-319-66769-0
ISBN:
9783319667690
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
Standard No.: 10.1007/978-3-319-66769-0doiSubjects--Topical Terms:
676754
Statistical mechanics.
LC Class. No.: QC174.8
Dewey Class. No.: 530.132
Classical statistical mechanics with nested sampling
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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.
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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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Physics and Astronomy (Springer-11651)
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