Recent applications of the stochastic variational method.

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Description

The stochastic variational method has proved to be useful in various fields of physics, including atomic, molecular, solid state, nuclear and subnuclear physics. This paper only reviewed a small part of the applications. Other contributions to this volume will show its usefulness in studies related to the structure of the baryons. Its main application is in nuclear physics, which has not been covered here but the interested reader can find examples in the references. We would like to extend its applicability to larger systems and for more complicated interactions. Such developments are under way. This paper overviews the most recent ... continued below

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12 p.

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Varga, K. October 20, 1998.

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Description

The stochastic variational method has proved to be useful in various fields of physics, including atomic, molecular, solid state, nuclear and subnuclear physics. This paper only reviewed a small part of the applications. Other contributions to this volume will show its usefulness in studies related to the structure of the baryons. Its main application is in nuclear physics, which has not been covered here but the interested reader can find examples in the references. We would like to extend its applicability to larger systems and for more complicated interactions. Such developments are under way. This paper overviews the most recent developments and applications of the stochastic variational method for different physical systems.

Physical Description

12 p.

Notes

INIS; OSTI as DE00011051

Medium: P; Size: 12 pages

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  • 16th European Conference on Few-Body Problems in Physics, Institut des Sciences Nucleaires, Autrans (FR), 06/01/1998--06/06/1998

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  • Report No.: ANL/PHY/CP-97470
  • Grant Number: W-31109-ENG-38
  • Office of Scientific & Technical Information Report Number: 11051
  • Archival Resource Key: ark:/67531/metadc626576

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  • October 20, 1998

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  • June 16, 2015, 7:43 a.m.

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  • April 6, 2017, 8:08 p.m.

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Varga, K. Recent applications of the stochastic variational method., article, October 20, 1998; Illinois. (digital.library.unt.edu/ark:/67531/metadc626576/: accessed September 23, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.