Classical Statistical Mechanics with Nested Sampling

Robert John Nicholas Baldock

ISBN 10: 3319667688 / ISBN 13: 9783319667683

Published by Springer, Springer Nov 2017, 2017

About this Item

This item is printed on demand - Print on Demand Titel. Neuware -Nominated as an outstanding PhD thesis by the University of Cambridge, UKSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 156 pp. Englisch.

Seller Inventory # 9783319667683

Bibliographic Details

• Title: Classical Statistical Mechanics with Nested Sampling
• Publisher: Springer, Springer Nov 2017
• Publication Date: 2017
• Language: English
• ISBN 10: 3319667688
• ISBN 13: 9783319667683
• Binding: Buch
• Condition: Neu
• Dimensions: 241W x 160H x 15D millimeters 241 millimeters width by 160 millimeters height by 15 millimeters depth
• Weight: 407 grams

About this title

Synopsis

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.

About the Author

Robert Baldock completed his doctoral studies in Physics at the University of Cambridge, UK, in the Theory of Condensed Matter Group in the Cavendish Laboratory (supervised by Dr Gábor Csányi and Prof Michael Payne FRS). He is currently a Postdoc at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland.