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Book Chapter

Electron Paramagnetic Resonance, Optimization and Automatic Differentiation

  • Soulié E
  • Faure C
  • Berclaz T
  • et al.
Springer New York, (2002), 99-106
DOI: 10.1007/978-1-4613-0075-5_10
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Abstract

This chapter describes an optimization problem applied to electron paramagnetic resonance spectroscopy. Levenberg-Marquardt fails to converge using a divided differences Jacobian approximation in single precision, while it succeeds using Odyssee-generated forward mode Jacobian values. In double precision, the optimizer returns a smaller "minimum" objective function with AD compared to DD in 46% more CPU time.

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APA

Soulié, E. J., Faure, C., Berclaz, T., & Geoffroy, M. (2002). Electron Paramagnetic Resonance, Optimization and Automatic Differentiation. In Automatic Differentiation of Algorithms (pp. 99–106). Springer New York. https://doi.org/10.1007/978-1-4613-0075-5_10

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