Classical Statistical Mechanics with Nested Sampling

Nominated as an outstanding PhD thesis by the University of Cambridge, UK Enables the calculation of partition functions as explicit functions of temperature for realistic models of materials directly from atomic interactions Allows the determination of complete phase diagrams and pressurevolumetemperature equations of state Illustrates the efficiency of the algorithm which paves the way for the automated calculation of phase diagrams

Nominated as an outstanding PhD thesis by the University of Cambridge, UK Enables the calculation of partition functions as explicit functions of temperature for realistic models of materials directly from atomic interactions Allows the determination of complete phase diagrams and pressurevolumetemperature equations of state Illustrates the efficiency of the algorithm which paves the way for the automated calculation of phase diagrams Includes supplementary material: sn.pub/extras

Auteur
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.

Contenu
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.