rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Classical Statistical Mechanics with Nested Sampling
  name:
    name part: Baldock, Robert John Nicholas.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2017
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XII, 144 p. 30 illus., 25 illus. in color. online resource.
  abstract: 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.
  table of contents: 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.
  note: by Robert John Nicholas Baldock.
  subject:
    topic: Physics
  subject:
    topic: System theory
  subject:
    topic: Phase transitions (Statistical physics)
  subject:
    topic: Physics
  subject:
    topic: Complex Systems
  subject:
    topic: Phase Transitions and Multiphase Systems
  subject:
    topic: Numerical and Computational Physics, Simulation
  subject:
    topic: Statistical Physics and Dynamical Systems
  classification: QC174.7-175.36
  classification: 621
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Theses, Recognizing Outstanding Ph.D. Research
  identifier: 9783319667690
  identifier: http://dx.doi.org/10.1007/978-3-319-66769-0
  record info:
    record creation date: 171117
    record change date: 20171117192532.0
    record identifier: 978-3-319-66769-0